E&EG Journal Volume XXX, Number 4

Environmental & Engineering Geoscience NOVEMBER 2024

VOLUME XXX, NUMBER 4

THE JOINT PUBLICATION OF THE ASSOCIATION OF ENVIRONMENTAL AND ENGINEERING GEOLOGISTS AND THE GEOLOGICAL SOCIETY OF AMERICA SERVING PROFESSIONALS IN ENGINEERING GEOLOGY, ENVIRONMENTAL GEOLOGY, AND HYDROGEOLOGY

Environmental & Engineering Geoscience Volume 30, Number 4, November 2024 Table of Contents 173

Quarries as a Source of Nitrate Pollution in Karst Aquifers: Case Study, the Edwards Aquifer, Texas James David Doyle

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Determining Groundwater Table in Slopes With Horizontal Drains and Design Framework for Length and Spacing Mihira Lakruwan, Akiyoshi Kamura, and Motoki Kazama

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Using the Total Apparent Spacing Approach to Optimize Foundation Drain Orientations William M. Roman and John N. Berezniak

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Development of a 3D Geologic Model Used in the Seismic Hazard and Liquefaction Hazard Analysis of Madison County, Tennessee Valarie Joyner Harrison, Hamed Tohidi, Roy Van Arsdale, Chris Cramer, and David Arellano

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Using Landslides to Locate the Epicenter for the Historic 1882 Earthquake in Colorado Justin Marchlewicz and Paul Santi Book Review

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Introduction to Waste Management: A Textbook Thomas Oommen

Quarries as a Source of Nitrate Pollution in Karst Aquifers: Case Study, the Edwards Aquifer, Texas JAMES DAVID DOYLE* 200 Cedar Park, Canyon Lake, TX 78132

Key Terms: Edwards Aquifer, Nitrate, Aggregate, Quarries, Karstic Aquifer ABSTRACT The San Antonio segment of the karstic Edwards Aquifer provides an example of the impact of aggregate quarries on nitrate loads in karst aquifers. Previous published reports have not evaluated aggregate quarries as a possible cause of nitrate concentrations in the Edwards Aquifer above normal background levels and instead attribute nitrate to recent urban development directly over the aquifer’s recharge zone. Quarries are known to be sources of nitrate pollution of groundwater resulting from use of ammonium nitrate fuel–oil (ANFO) mixtures as explosives in mining operations.

Ammonium nitrate is highly soluble and leaches readily into the formation being mined. Large quantities are used, up to 30 percent of which is not consumed by blasting, thus constituting a potential groundwater pollutant. Groundwater data from the Texas Water Development Board and stream data from the Texas Commission on Environmental Quality show that urbanization cannot explain the geographic distribution and historical changes of nitrate in the aquifer.

The geographic distribution of numerous limestone quarries fits with the data, and nitrate concentrations in the Edwards Aquifer have risen since ANFO use as an explosive began on a large scale, which indicates quarries are a major contributor of nitrate to the aquifer. Water-quality measurements of nitrate in the Edwards Aquifer mostly remain at a level safe for humans. However, some freshwater aquatic organisms are harmed by prolonged exposure to lower nitrate levels. Recent nitrate measurements show that most measurements have reached a level that might be harmful to some groundwater species.

INTRODUCTION Texas leads all American states in the production of crushed stone. The Texas Hill Country is located in the southeastern corner of the karstic Edwards Plateau and is a major production area for limestone aggregate (Kyle *Corresponding author email: bangeo1@hotmail.com

and Elliot, 2019). State-wide, limestone aggregate production has increased steadily over the years. For example, from 2010 to 2018, annual crushed limestone production in Texas increased from 104 million to 161 million metric tons (National Minerals Information Center, 2021). Air, water, and noise pollution from quarries has become an increasing concern, particularly where quarries are concentrated along the Interstate Highway 35 corridor (Figure 1; Chasnof, 2021). Prior studies of nitrate concentration in the Edwards Aquifer known to the author have not considered quarries as a potential source. The purpose of this study is to use public data to assess whether quarries are significant contributors of nitrate pollution to the San Antonio segment of the Edwards Aquifer as representative of karst aquifers in general.

Background Edwards Aquifer hydrological zones comprise a contributing (or drainage) zone that delivers surface water to a recharge zone where the Edwards Limestone is at the surface, and a portion of the water flowing from the contributing zone passes into the subsurface via fractures and karst features. In a relatively narrow transition zone, younger strata are at the surface, but water can reach the Edwards Aquifer through faults and fractures.

The Edwards Aquifer is underlain by the Trinity Aquifer, which also extends north of the Edwards Aquifer recharge zone where the Trinity group is at the surface (Sharp and Green, 2022). The Edwards Trinity Aquifer occurs in the northwestern part of the study area (Figure 1). Aside from streams that cross from the contributing zone to the recharge zone, the Edwards Aquifer is sourced from rainfall runoff on the recharge zone, from cross-formation flow with the Trinity Aquifer where the Edwards and Trinity aquifers are juxtaposed by faults in the Balcones Fault Zone, and from the Edwards Trinity Plateau Aquifer in Uvalde County (Lindgren et al., 2004). In the artesian zone, the Edwards Limestone is overlain by younger impermeable formations (Schindel, 2019; TCEQ, 2019). Quarries are mostly sited on the recharge zone, whereas the contributing zone has a few small quarries. Near the town of Uvalde, quarries appear to be targeting local Edwards Limestone outcrops south of the recharge zone (Figures 1–3).

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Figure 1. Quarry locations shown with reference to major aquifers (TWDB, n.d.a) and zones of the Edwards Aquifer. Locations of Edwards Aquifer zones are from TCEQ (2019) and EAA (2014).

The aggregate industry mostly uses ammonium nitrate fuel–oil (ANFO) mixtures as explosives. ANFO mixtures vary somewhat but typically are a stoichiometric composition of 94.5 percent ammonium nitrate and 5.5 percent fuel oil. Ammonium nitrate is a salt that disassociates in water to NH4þ and NO3 and dissolves readily (Brochu, 2010). Nitrification converts ammonium to nitrate nitrogen (American Waterworks Association and Economic and Engineering Services, Inc., 2002). Loss of ANFO by leaching to the formation being mined is variable and influenced by several factors, including specifications of the explosive, nature of the site being mined, design of boreholes and explosive patterns, and length of time between loading boreholes and detonation (Brochu, 2010). Even slight amounts of water in boreholes can dissolve enough ANFO to prevent detonation (Konya and Konya, 2019). Aside from being leached from boreholes, about 28–30 percent of ANFO that is used is not consumed in blasting (Alberts, 2016). Consequently, nitrate pollution of groundwater from mining is a recognized problem in some parts of the world (Golder Associates, 2014; Alberts, 2016).

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Some states, e.g., New Hampshire and Vermont, regulate the mining process to minimize the potential for groundwater contamination and require groundwater monitoring during the life of a quarry (Kernan, 2010; Agency of Natural Resources, 2014). The Texas Commission on Environmental Quality (TCEQ) requires a Water Pollution Abatement Plan (WPAP) for construction on the recharge zone and has established best management practices (BMPs) for quarries to meet waterquality standards for the Edwards Aquifer that are not applicable to other aquifers (Barrett, 2005; Barrett and Eck, 2012). The BMPs address handling of sensitive karst features, prevention of spills, and creation of berms to isolate the site. However, the manner of conducting blasting operations is not addressed, and monitoring of wells is not required.

To avoid directly introducing contaminants to the Edwards Aquifer, one of the BMPs recommended by the TCEQ is to maintain the base of quarry operations at least 7.6 m (25 ft) above the aquifer level expected for comparatively wet years, defined as having 110 cm (45 in.) or more of rainfall. The height above the aquifer is based on an estimated depth of induced fractures

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Quarries as a Source of Nitrate Pollution in Karst Aquifers

Figure 2. Quarry locations are shown with reference to outcrops of stratigraphic units correlative to the Edwards and Trinity groups. Surface geology is from the USGS (2022). Recharge and transition zone outlines are from TCEQ (2019).

beneath shot holes. A wet-year aquifer elevation estimate for the quarry site must be based on a water elevation measurement from an on-site well or close offset well. The recorded water elevation in the on-site well must be adjusted using a well in the same county with historical water table elevation data and by determining the difference between the water elevations on the

observation date in the on-site well and the wet-year elevation in the reference well (Barrett and Eck, 2012).

According to the Texas Aggregates and Concrete Association (TACA), washing of aggregate is a routine activity (TACA, 2020), and the fines are accumulated in settling ponds. Ponds may use a liner, but due to the scale of water handling, operators may create ponds by

Figure 3. Generalized cross-section illustrating the zones of the Edwards Aquifer. Modified with permission from EAA (2020).

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sealing voids and fractures on the pond floor and permeable beds on the walls lining the pond. Some water loss to the formation is expected (Barrett and Eck, 2012).

The Texas Water Development Board (TWDB) maintains a groundwater database (GWDB) that includes water-quality measurements from well samples (TWDB, n.d.b) that are predominantly reported in milligrams per liter as “nitrate as NO3” but may be reported as “nitrate as N.” The ratio of the two measures (TWDB, n.d.c) used for conversion is as follows: nitrate as NO3 ¼ nitrate as N 3 4:427 In this paper, nitrate refers to nitrate as NO3.

Background nitrate levels are typically 4.4 mg/L (1.0 mg/L nitrate as N) for aquifers in general (Dubrovsky et al., 2010) and for the Edwards Aquifer in particular (Department of the Interior, Fish and Wildlife Service, 2012). The U.S. Environmental Protection Agency (EPA) set the maximum contaminant level (MCL) for nitrate in public water supplies at 40 mg/L (10 mg/L nitrate as N) for human consumption (EPA, 2017). Above the MCL, risks are primarily to infants, who may develop methemoglobinemia (blue baby syndrome), which can be fatal. In addition, for pregnant women, drinking water where nitrate levels are above the MCL has been linked to low birth weights (Swistock, 2022). Some freshwater aquatic species have nitrate tolerances lower than the MCL. In Texas, the ecological screening benchmark for nitrate adopted by the TCEQ for protecting freshwater life is 13 mg/L (TCEQ, 2022b). Others have concluded that a maximum nitrate level from 8 mg/L (Monson, 2022) to 9 mg/L (Carmago et al., 2005) would be an appropriate limit for protecting sensitive freshwater species.

Previous Investigations Bush et al. (2000) reviewed water-quality data for South-Central Texas for the period from 1996 to 1998.

Although they noted that nitrate levels in the Edwards Aquifer were elevated relative to those of most other aquifers, including the underlying Trinity Aquifer, they thought it was relatively unaffected by human activity.

Regarding surface water, they found that nitrate concentrations were highest close to wastewater treatment plants, which are mostly over the artesian zone of the Edwards Aquifer, where the aquifer is confined above by impermeable strata (Figure 3). Although the contributing and recharge zones had begun to experience population growth, they described those areas as mostly rangeland and did not go into detail about what may have caused the aquifer’s elevated nitrate level.

Reedy and Scanlon (2017) reviewed nitrate concentrations in all aquifers in Texas with a focus on understanding nitrate hotspots exceeding the MCL. Nitrate 176

sources were considered to be either natural (atmospheric deposition, nitrogen fixation by legumes, nitrification of organic material, and geological sources) or anthropogenic (fertilizers, animal feeding stations, septic tanks, and sewage systems). They reviewed public water supply systems (PWSs) and water-quality samples from wells. For the Edwards and Trinity aquifers, nitrate was found to be generally below the MCL. However, regarding percentages of samples above the MCL for nitrate, the Edwards Trinity Aquifer was among the four highest aquifers they analyzed, with the highest values falling in the northern part of the aquifer.

Musgrove et al. (2016) evaluated nitrate levels in the Barton Springs and San Antonio segments of the Edwards Aquifer, which are separated by a potentiometric divide. They used samples taken in 2011 and 2012 from streams and from wells in the San Antonio segment in Bexar County and considered historical data from Comal Springs. Comal Springs data consisted of seven samples from the 1930s and 1940s, one sample in 1974, and 27 samples from 2000 to 2012. Although they noted a doubling of nitrate values between the 1940s and 2000, the data to tell whether the change was gradual or abrupt were lacking. The authors stated that agricultural land uses are minor in central Texas and indicated that these could not account for elevated nitrate levels in the Edwards Aquifer. They also indicated that stream samples cannot account for elevated nitrate values in the Edwards Aquifer. Instead, they postulated that urbanization since 2000 over the recharge zone in northern San Antonio contributes high levels of nitrogen species to the aquifer and that organic nitrogen undergoes nitrification in the aquifer.

Sullivan and Gao (2016) addressed nitrate concentrations in surface waters in the drainage basins of Cibolo Creek and Dry Comal Creek, which are mostly in Bexar, Comal, and Kendall counties. The study area includes both portions of the contributing zone, where the Glen Rose Formation of the Trinity group is at the surface, and the recharge zone, where the Edwards group is at the surface. A Soil and Water Assessment Tool (SWAT) model was developed for surface waters in the drainage basins.

Sullivan and Gao (2016) considered nitrate inputs from agriculture, urbanization, wildlife, and atmospheric deposition. The study assumed the same background nitrate concentration for both Edwards and Trinity aquifers based on a median value of 8.19 mg/L (1.85 mg/L nitrate as N) reported for the Edwards Aquifer by Musgrove et al.

(2010) for 1996–2006. Nitrate measurements in the Glen Rose portion of the Trinity Aquifer were not directly considered. From the calibrated model, the authors concluded that the two most important nitrate inputs were from atmospheric deposition followed by livestock.

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Quarries as a Source of Nitrate Pollution in Karst Aquifers

Sullivan et al. (2019) used a finite difference groundwater model (MODFLOW) to address nitrate concentrations in the Edwards Aquifer for 2001–2010. For the study area of Sullivan and Gao (2016), nitrate recharge values for the Edwards Aquifer were based on the SWAT model results. Elsewhere, they were set to average values for the Edwards Aquifer. Crossflow from the Trinity Aquifer was modeled as 9.34 mg/L (2.11 mg/L nitrate as N) based on an average value derived from TWDB data. The authors deemed the study successful in predicting nitrate levels within 1,000 m of the recharge zone.

RESEARCH METHODS Quarry locations (Figure 1) were compiled from several sources (TCEQ GIS Team, 2020; Texas Hearst Data Visualization Team, 2021). In addition, quarries were outlined from satellite view. Using open-source geographic information system software, an area was computed for each.

Well data in the GWDB include aquifer codes that were mostly determined by TWDB geologists (TWDB, n.d.c). The aquifer codes were the basis for selecting data from the GWDB. Nitrate measurements, for parameter code 71851, “Nitrate Nitrogen, Dissolved, Calculated (mg/L as NO3),” were obtained from the GWDB for the Edwards Aquifer. In addition, measurements for parameter code 618, “Nitrate Nitrogen, Dissolved (mg/L as N),” were converted to nitrate as NO3. These were reviewed for geographic variation and historical changes.

Nitrate measurements from the Trinity and Edwards Trinity aquifers were also evaluated to assess their potential for contributing nitrate to the Edwards Aquifer via crossflow.

Some water-quality analyses prior to 1940 may not be reliable (Welder and Reeves, 1964), so all aquifers measurements prior to 1940 were excluded from this study. Also excluded were sample measurements designated in the TWDB database with a reliability code of 14, “reliability unknown or not recorded.”

Water-quality analyses including measurements of dissolved organic nitrogen were obtained from the GWDB. For Edwards Aquifer samples, total nitrogen was determined from dissolved organic nitrogen, nitrate, nitrite, and ammonia. Sample measurements recorded as milligrams per liter as N were converted to milligrams per liter as NO3. Dissolved oxygen measurements were obtained from the GWDB as available.

Nitrate measurements for parameter code 620, “Nitrate Nitrogen, Total (mg/L as N),” from surface water-quality data were obtained from the TCEQ (TCEQ, 2022a, 2024) and converted to nitrate as NO3. For surface water-quality data with measurements of dissolved organic nitrogen, total nitrogen was calculated and converted to milligrams

per liter as NO3. Dissolved oxygen measurements were obtained from the TCEQ database as available.

The Edwards Aquifer Authority (EAA) records water-quality measurements from well and surface locations. In response to a request for all nitrate measurements collected, the EAA provided a file of measurements taken from December 2004 to July 2023, which included both surface and groundwater data.

Some EAA data are in the GWDB. The EAA uses a unique nomenclature for sample sites that is not crossreferenced to the state well nomenclature (EAA Open Records Center, 2024, personal communication). Due to the difficulty of determining the overlap between EAA and GWDB sources, the EAA data were evaluated separately.

Agricultural activities associated with farming and livestock may be a source of nitrate contamination of groundwater (Reedy and Scanlon, 2017). Cropland harvested and cattle-and-calves inventory tabulated in agricultural censuses since 1950 were reviewed as indicators of farming activity (U.S. Department of Agriculture, 2024). Agricultural census data are reported by county.

To help determine whether agricultural activity has played a significant role in explaining nitrate levels in the Edwards Aquifer, distribution of farm land based on data from the Multi-Resolution Land Characteristics Consortium (MRLC) was examined (MRLC, 2019). Locations of concentrated animal-feeding operations (CAFOs) relative to the recharge zone were also determined (Carnegie Corporation and University of Iowa, 2017).

Musgrove et al. (2016) concluded that urbanization over the recharge zone is the primary factor behind elevated nitrate levels in the Edwards Aquifer. As part of assessing that, population change by county was determined by the U.S. Census Bureau. That data, together with land use maps, allow comparison of the location and timing of population change to the location and timing of rising nitrate values.

Specific limestone aggregate production data for individual quarries or the Hill Country as a whole are not available. An exception is a single mention of one day’s use of explosives at the Servtex Plant in Garden Ridge, Texas (Chasnof, 2021). For the Servtex example, explosive usage per unit volume mined was calculated for comparison to typical industry usage.

To evaluate whether mining contributes significant amounts of nitrate to the Edwards Aquifer, industry information on typical explosive use and unexploded residuals is applied to an example of a quarried area on the recharge zone. The calculation is based on the rock volume removed from an 8.09 3 105 m2 (200 acre) portion of the Cemex Balcones New Braunfels Quarry in Comal County. The volume is derived from elevation contours digitized from georeferenced U.S. Geological

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RESULTS

Figure 4. For part of the Cemex quarry, contours were digitized from USGS topographic maps for the New Braunfels, West Texas, quadrangle from (A) 1958 and (B) 2022. Contours are labeled in feet above mean sea level.

Survey (USGS) topographic maps of the New Braunfels, West Texas, quadrangle made in 1958 (prior to quarrying) and 2022 (USGS, n.d.), as shown in Figure 4. Digital elevation models (DEMs) were made from both topographic maps and used to calculate the volume of rock removed.

A total of 80 quarries were identified. Of these, 16 are on the contributing zone, and the remaining 64 fall along the recharge and transition zones (Figure 1). Of the 16 quarries on the contributing zone, 10 are 4.05 3 104 m2 (10.0 acres) or less, and the largest is 4.38 3 105 m2 (108 acres). Area measurements of contributing zone quarries totaled 1.74 3 106 m2 (429 acres). The 64 quarries falling along the recharge zone ranged upward to 6.7 3 106 m2 (1,730 acres), and the median value was 2.28 3 105 m2 (56.3 acres). Area measurements of recharge zone quarries totaled 4.02 3 107 m2 (9,920 acres).

Historically, mining engineers used a “powder factor” to estimate the amount of explosive per unit volume.

The powder factor for a medium-hard rock type would be 0.4–0.5 kg/m3 (Dyno Nobel, 2010). For comparison, the Servtex Plant in a single day used 5,900 kg (13,000 lbs) of explosives to remove 2 3 107 kg (20,000 tons) of rock (Chasnof, 2021). If the typical value of unexploded residual (28 percent) is applied, that suggests that for one day, 1,700 kg (3,640 lbs) of unexploded ANFO would be available to leach into the aquifer. Material that is too fine-grained to be commercial may constitute 20–30 percent of the volume mined, as indicated in a WPAP for the Martin Marietta Materials New Braunfels Quarry (Forster, 2010). If 25 percent of a mined volume is left behind, the explosive usage at the Servtex Plant translates to a powder factor of 0.6–0.5 kg/m3 for a limestone porosity range of 15–25 percent (Table 1).

Soil thickness is negligible in the area of the 8.09 3 105 m2 (200 acre) portion of the Cemex Balcones New Braunfels Quarry (Pelletier et al., 2016). The rock volume removed, calculated by subtracting the 2022 DEM from the 1958 DEM, is 1.99 3 107 m3 (7.03 3 108 ft3).

Applying a powder factor of 0.45 kg/m3 and a value of 28 percent for unexploded residual would result in 2.5 3 106 kg (5.5 3 106 lbs) of ANFO, or 2.4 3 106 kg (5.3 3 106 lbs) of ammonium nitrate, left behind (Table 2). Since nitrate from ANFO can be introduced directly to groundwater and ammonium is subject to nitrification (Musgrove et al., 2016), the potential amount of nitrate after nitrification totals 3.7 3 106 kg (8.2 3 106 lbs).

U.S. Census Bureau data show a contrast in population growth between Bexar County, along with Comal

Table 1. Explosive use (powder factor) estimate for the Servtex plant in Garden Ridge, Texas.* Porosity (%)

Density† (kg/m3)

Limestone daily* (kg)

Limestone volume (m3)

Rock volume‡ (m3)

Explosive daily* (kg)

Powder factor (kg/m3)

15 25

2,304 2,033

2 3 107 2 3 1107

8,000 9,000

10,000 12,000

5,897 5,897

0.6 0.5

* Based on Chasnof (2021). † Using limestone matrix density ¼ 2.710 gm/cc (Asquith and Gibson, 1982). ‡ Using 25 percent volume of non-commercial fines (Forster, 2010).

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Quarries as a Source of Nitrate Pollution in Karst Aquifers Table 2. Potential nitrate residual from quarrying 8.09 3 105 m2 (200 acres) in Comal County.

Rock volume* (m3)

ANFO† (kg)

Residual ANFO‡ (kg)

Ammonium nitrate§ (kg)

Nitrate (kg)

Nitrification of NH4 (kg)

Total (kg)

1.99 3 107

9.0 3 106

2.5 3 106

2.4 3 106

1.8 3 106

1.8 3 106

3.7 3 106

* Based on 1958 and 2022 USGS topographic maps for the New Braunfels, West Texas, quadrangle (USGS, n.d.). † Using 0.45 kg/m3 (Dyno Nobel, 2010). ‡ Using 28 percent not consumed in blasting (Alberts, 2016). § Using 94.5 percent of ANFO by weight (Brochu, 2010).

and Hays counties, and Medina and Uvalde counties to the west. Bexar County’s population increased from 1,185,394 in 1990 to 2,009,322 in 2020, which is 20 percent more than its increase in the previous 40 years. From 1990 to 2020, Comal County’s population increased from 51,832 to 161,482, whereas the Hays County population increased from 56,225 to 241,066. For the same time period, the population in Medina and Uvalde counties increased from 27,312 to 50,739 and 23,340 to 24,564, respectively.

The recharge zone occurs in Bexar, Comal, Hays, Medina, and Uvalde counties. Since Medina and Uvalde counties are upgradient in the flow direction of the Edwards Aquifer compared to the more populous counties to the east (Figure 5), nitrate measurements made since 1990 from wells in the Edwards and Trinity aquifers were divided into east and west areas (Figure 6A and B).

Background nitrate concentrations are expected to be 4.4 mg/L or less (Dubrovsky et al., 2010), so nitrate values were placed in separate categories to emphasize changes in the low end. Measurements in the fourth category (5–8 mg/L) and above indicate nitrate concentrations above background. The three highest categories mark the range in which nitrate values are harmful to some freshwater aquatic animals (8–13 mg/L), in excess of the TCEQ benchmark for freshwater organisms (13–40 mg/L), and of concern for human consumption (.40 mg/L). Nitrate measurements from the EAA for the period from December 2004 to September 2023 are shown for comparison (Figure 6C and D).

Exact dates of operation of the quarries are not available, so the maximum nitrate value recorded for each well from 1990 to the present was determined. For the Edwards, Trinity, and Edwards Trinity aquifers, Figure 7

Figure 5. Generalized flow pattern within the Edwards Aquifer. Modified with permission from EAA (2019).

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Figure 6. For each well, nitrate measurements since 1990 are grouped into one of seven categories for GWDB measurements for the Edwards and Trinity aquifers. Bar charts show the percentage of each category for (A) the eastern area for the Edwards Aquifer (1,289 samples from Bexar, Comal, Guadalupe, and Hays counties) and Trinity Aquifer (742 samples from Bexar, Blanco, Comal, Kendall, and Hays counties) and (B) the western area for the Edwards Aquifer (532 samples from Medina and Uvalde counties) and Trinity Aquifer (318 samples from Bandera, Kerr, Medina, Real, and Uvalde counties). Also shown are the categories corresponding in the east to the Edwards Aquifer average (7.6 mg/L) and median (7.6 mg/L) and the Trinity Aquifer average (4.5 mg/L) and median (1.0 mg/L) and in the west to the Edwards Aquifer average (8.7 mg/L) and median (8.0 mg/L) and the Trinity Aquifer average (1.9 mg/L) and median (0.13 mg/L). For comparison, nitrate data since 2004 provided by the EAA were grouped into seven categories. The percentage of each category is shown for (C) the eastern area and (D) the western area.

displays the category of each well’s maximum value in map view.

For the Edwards and Trinity aquifers on the contributing zones, observations in the two categories above 13 mg/L nitrate comprise a small percentage of the total (Figure 6). Figure 8 shows categories in map view for wells with maximum nitrate values above 13 mg/L. A cluster of wells north of the contributing zone near the Trinity Aquifer’s border with the Edwards Trinity Aquifer (Figure 1) have values above 13 mg/L (Figure 8).

For the two areas, Figure 9 illustrates changes by decade in nitrate concentration within the Edwards Aquifer by showing the changing percentages of the various categories defined in Figure 6. The median measured nitrate value for the Edwards Aquifer is also shown for each decade.

Nitrate measurements are available for stream samples beginning in 1970 (TCEQ, 2022a, 2024). Figure 10A and B compare nitrate measurements from surface water since 1990 to Edwards Aquifer groundwater samples since 1990 separately for east and west areas.

In addition, total nitrogen from stream samples is compared to total nitrogen from groundwater samples separately for east and west areas for the same period in Figure 10C and D. 180

Agricultural activities associated with farming and livestock may be a source of nitrate contamination of groundwater (Reedy and Scanlon, 2017). Cropland harvested, as tabulated in agricultural censuses since 1950, is used as an indicator of farming activity. Census data are reported by county (Figure 11). Location of cropland and CAFOs relative to the recharge zone is important for understanding whether they have played a significant role in explaining nitrate elevations in the Edwards Aquifer (Figure 12).

For the entire area of the Edwards Trinity Aquifer, 6,473 nitrate measurements made since 1940 were obtained from the GWDB. From nitrate measurements taken since 1990, the maximum value was determined for each of 1,117 wells and assigned to one of the seven categories (Figure 13A). For counties in or close to the study area, the percentage of each nitrate category was determined from 758 measurements in 420 wells (Figure 13B). In addition, the change in median nitrate values was determined for each decade for those counties (Figure 13C).

DISCUSSION The Servtex Plant (Chasnof, 2021) provided the lone example from the study area of usage of ANFO per

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Quarries as a Source of Nitrate Pollution in Karst Aquifers

Figure 7. Category corresponding to the maximum value of nitrate for each well in the GWDB data since 1990 for the Trinity, Edwards, and Edwards Trinity aquifers is shown in map view. The MCL falls in the nitrate category (.40 mg/L), and the category (8–13 mg/L) is the level at which some freshwater organisms may be harmed.

mined rock volume and was found to be consistent with usage typical for industry (Table 1).

Applying typical industry values for ANFO usage and unexploded residual of ANFO to the volume of rock removed from the 8.09 3 105 m2 (200 acre) portion of the Cemex Balcones New Braunfels Quarry (Figure 4; Table 2) illustrates the large volumes of nitrate that quarry operations may contribute to the aquifer. Quarry area is not a direct indicator of volume mined, because volume of a particular mine depends on topography and quarry base elevation, but the total area mined along the recharge zone is 50 times the area of the Cemex example, which can be used to illustrate the order of magnitude of potential nitrate contamination from quarrying over time.

In contrast, the 16 small contributing-zone quarries, scattered across a larger area, would have a relatively minor impact on nitrate concentration in groundwater.

BMPs for quarries from the TCEQ stipulate that karst features deemed likely to be connected to the aquifer

and capable of allowing rapid inflow of water be sealed or isolated using buffers until they can be mined (Barrett and Eck, 2012). Examples cited of sensitive karst features include solution-enlarged fractures, caves, and sinkholes. Together with requiring a minimum elevation for the base of a quarry at 7.6 m (25 ft) above the wetweather elevation of the underlying aquifer, the BMPs are intended to prevent pollutants from reaching the aquifer. However, they are unlikely to be successful. Surface water crossing the recharge zone flows into the Edwards Aquifer primarily through karst features, many of which are not readily apparent (Schindel, 2019). Johnson et al.

(2010) demonstrated through a dye trace study that water delivered to a surface site with no recognizable karst features could be detected in monitoring wells.

If correctly implemented, stopping a quarrying operation 7.6 m (25 ft) above the estimated groundwater level may shield the aquifer from directly introducing pollutants to the aquifer through fractures induced by blasting.

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Figure 8. Wells for which the maximum value of nitrate concentration observed since 1990 are in the top two categories (above TCEQ’s ecological screening benchmark of 13 mg/L) are shown in map view.

However, fractures induced during quarrying would likely enhance the passage of pollutants to the natural fracture system within the quarry. In addition, the quarrying operation may increase the likelihood of nitrate reaching the aquifer by reducing the distance of the surface to the underlying aquifer.

Aggregate washing is a routine practice, and process water is directed to settling ponds within a quarry (TACA, 2020). Ponds are monitored for at least 6 months to ensure the rate of water loss to the aquifer does not exceed an allowed amount (Barrett and Eck, 2012). Since the highly soluble ANFO residue would likely be dissolved in the washing process, any such water loss is another means for nitrate to reach the underlying aquifer.

For most of the contributing zone, the Glen Rose Formation of the Trinity group is at the surface (Figures 1 and 2), and recharge is mostly from infiltration of precipitation (Jones, 2011). Streams crossing the contributing zone have both gaining and losing reaches. In particular, where the 182

upper Glen Rose is at the surface, stream loss to the underlying aquifer may be rapid (Green et al., 2011). Using water-quality measurements submitted since 1990 to the TWDB, Figure 6 compares the level of nitrate for the Edwards and Trinity aquifers. Trinity Aquifer measurements are distinctly lower than those of the Edwards Aquifer for both the eastern counties, which have had rapid population growth since 1990, and those in the western part of the study area, which have not. The data collected by the EAA show the same contrast. Where cross-fault exchange between the Trinity and the Edwards aquifers is occurring, it is most likely with the Glen Rose Formation (Johnson et al., 2010; Schindel, 2019). Measurements from the GWDB from wells in both areas taken since 1990 that were recorded as Glen Rose have low nitrate values relative to the Edwards Aquifer (Figure 14). The map view of the maximum recorded nitrate values since 1990 further illustrates the contrast between the Trinity and the Edwards aquifers (Figure 7). Together, Figures 6, 7, and 14 show that crossflow from the Trinity Aquifer to the Edwards

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Figure 9. For the Edwards Aquifer, changes by decade in the median value and relative proportions of nitrate categories for (A) the eastern area (Bexar, Comal, Guadalupe, and Hays counties) and (B) the western area (Medina and Uvalde counties).

Aquifer cannot account for the level of nitrate in the Edwards Aquifer.

The map view in Figure 7 is useful principally in illustrating the overall contrast in nitrate levels for the two aquifers. Sufficient information is lacking to interpret individual measurements. That would require knowledge of the nature and timing of a potential source of nitrate nearby, in addition to the timing of the water sample. Based on studies that measure rapid changes in aquifer parameters following recharge events, maximum recorded values in karst aquifers are often well below actual maximums due to the high anisotropy of karst aquifers. This makes the actual maximum difficult to record even by standard periodic monitoring (George Veni, 2022, personal communication). Even monthly or

quarterly sampling of monitoring wells is unlikely to adequately represent the contaminant charge (Worthington, 2011). Nitrate values in Figure 7 are not from monitoring wells but instead are for all wells in the TWDB database.

For the Edwards Aquifer, 46 percent have only one measurement and 71 percent have three or fewer measurements. For the Trinity Aquifer, those values are 59 and 91 percent, respectively. Only 12 Edwards Aquifer wells had as many as 20 samples, and in each case, the samples were taken once a year. For the Trinity Aquifer, the most observations in a single well totaled 12.

For the Edwards Aquifer, observations in the two categories above 13 mg/L nitrate comprise only a small percentage of the total (Figure 6B and D). High values are clustered near the quarries, and all but two are within 10 km of a quarry (Figure 8). Although individual measurements may be high or low depending on the timing of the potential source and sample and the position, clustering of high values reflects proximity to source for wells situated favorably within the fracture system.

Nitrate measurements taken over the contributing and recharge zones in streams are low relative to the Edwards Aquifer (Figure 10). BMPs for quarries dictate that berms and other measures be used to isolate quarries from both storm water inflow and water outflow (Barrett, 2005), with the result that quarries are not likely to directly contribute nitrate to streams via runoff. As shown in Figure 7, no wastewater outfalls are located over the recharge zone, but some are present on the contributing zone including three that are classified as major (EPA, 2023). Wastewater outfalls and other aspects of increasing population on the contributing zone cause the elevation of stream nitrate levels relative to the Trinity Aquifer (Figures 6, 10, and 14) and likely the slight elevation of nitrate in the east compared to the west Glen Rose portions of the aquifer (Figure 14). However, nitrate levels in streams are lower than in the Edwards Aquifer, and comparison of total-nitrogen measurements between stream samples and Edwards Aquifer samples shows a similar pattern to nitrate. Even if nitrification of organic material takes place in the Edwards Aquifer, the total-nitrogen measurements indicate that surface water crossing the recharge zone cannot account for nitrate levels in the Edwards Aquifer, as previously determined

by Musgrove et al. (2016).

Assessing sources that potentially deliver nitrate to the Edwards Aquifer requires comparison for each geographic distribution of the potential source to elevated nitrate measurements in the aquifer and determination that a potential source is increasing coincident with the timing of any rise of nitrate concentration in the aquifer.

Agricultural activities are an anthropogenic source that has the potential to contaminate groundwater (Reedy and Scanlon, 2017). In the study area, farmland and

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Figure 10. For the entire study area, nitrate categories were determined for stream sample measurements since 1990. Comparisons are made between (A) 1,289 Edwards Aquifer well samples in the east area and 4,647 stream samples in the Guadalupe and San Antonio river basins and (B) 532 Edwards Aquifer well samples in the west area and 196 stream samples in the Nueces River basin. For well and stream samples with dissolved organic nitrogen measurements, nitrogen as NO3 was calculated and categorized. Stream and well samples are compared for (C) 285 Edwards Aquifer well samples in the east area and 4,647 stream samples in the Guadalupe and San Antonio river basins and (D) 128 Edwards Aquifer well samples in the west area and 434 Nueces River basin stream samples.

CAFOs over the contributing and recharge zones are limited compared to the artesian zone of the Edwards Aquifer, where the aquifer is shielded above by impermeable formations (Figure 12). With the exception of an increase in Uvalde County between 1969 and 1982, agricultural activity as measured by the amount of cropland harvested was relatively constant or declining for all counties during the period when nitrate levels were rising in the Edwards Aquifer (Figures 9 and 11). For the study area, the totals for cattle and calves were fairly constant from the 1950 to 1992 censuses but declined by 48 percent from 1992 to 2022. Together, Figures 11 and

Figure 11. Census data on cropland harvested, reported by county, as a measure of agricultural trends.

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12 confirm the opinions of previous authors that agriculture is unlikely to be the cause of rising nitrate levels.

Using the SWAT model, Sullivan and Gao (2016) concluded that atmospheric deposition of nitrate was the most important input of nitrate to water charging the Edwards Aquifer. One measure of success of the SWAT model was that the calibrated shallow aquifer nitrate concentration was consistent with that reported for the Edwards Aquifer by Musgrove et al. (2010). The contrast in observed values between the Edwards and the Trinity aquifers (Figures 6 and 7) was not addressed.

The MODFLOW model (Sullivan et al., 2019) used average nitrate concentrations from TWDB data for areas beyond the SWAT model study for both the Edwards and the Trinity aquifers. In particular, nitrate in the crossflow from the Trinity Aquifer was modeled as 9.34 mg/L (2.11 mg/L nitrate as N). An average is strongly influenced by extreme values and is not representative of nitrate in the Trinity Aquifer (Figures 6B and 14). Neither study addressed elevation of background levels of nitrate in the Edwards Aquifer compared to the relatively undisturbed levels measured in the 1940s and 1950s (Figure 9).

Both regional distribution and timing of atmospheric nitrogen deposition indicate it is not the principal cause of elevated nitrate levels in the Edwards Aquifer.

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Figure 12. 2019 distribution of cultivated crops and hay or pasture (MRLC, 2019).

Reactive nitrogen oxide (NOx) is largely produced by anthropogenic activity and in the United States has declined since 1980. The sharpest decline has been since 1995 as a result of the 1990 Clean Air Act Amendments.

Atmospheric ammonia deposition has been essentially flat in the United States since 1990 (National Atmospheric Deposition Program, 2016). National maps of atmospheric deposition of ammonium, nitrate, and total nitrogen from 1986 to 2016 show no consistent trend (National Atmospheric Deposition Program, 2020) that could be related to the rise in nitrate levels in the Edwards Aquifer for the same period (Figure 9). The largest sources of NOx are motor vehicles and power generation. Consequently, deposition of NO3 is highest in urban areas (National Atmospheric Deposition Program, 2016). The effect is illustrated for this study area by a nitrate–N map for 2012, which shows a 50 percent decline in atmospheric nitrate deposition from Bexar County to Uvalde County (Reedy and Scanlon, 2017, their Figure 16). Consequently, atmospheric deposition does not explain the similarity of Edwards Aquifer nitrate measurements in the east and west parts of the study area (Figure 6).

As noted by Reedy and Scanlon (2017), the Edwards Trinity Aquifer (Figure 1) has elevated nitrate levels, which are highest in the north largely due to agricultural activity. Assignment of GWDB measurements to nitrate categories illustrate this (Figure 13A) in showing a north-to-south decline in measured nitrate. However, counties immediately north of the study area have

observed nitrate levels since 1990 that are comparable to those in the Edwards Aquifer (Figure 13B). This raises the possibility that the Edwards Trinity Aquifer is contributing nitrate to the Edwards Aquifer. Across most of the study area, any nitrate from the Edwards Trinity Aquifer would have to reach the Edwards Aquifer via spring flow contributions to contributing zone streams or by crossflow into the Trinity Aquifer. Neither stream measurements nor Trinity Aquifer measurements support a significant nitrate contribution in those areas. In western Uvalde County, samples designated as Edwards Trinity have elevated nitrate levels close to the Edwards Aquifer where crossflow occurs. However, one indication that crossflow from the west from the Edwards Trinity Aquifer is not the primary source of nitrate in the Edwards Aquifer is that Edwards Aquifer nitrate concentrations are fairly constant across the study area (Figures 6 and 7). A western source would show westto-east dilution. In addition, Lindgren et al. (2004) concluded inflow to the Edwards Aquifer, including both the northern and the northwestern boundaries, was only 6.5 percent of total recharge. Furthermore, the timing of nitrate concentrations in the Edwards Trinity Aquifer differs from that of the Edwards Aquifer in that it rose from the 1940s to 1990s but declined afterward.

Musgrove et al. (2016) primarily used data from Bexar County, together with data from Comal Springs, to attribute elevated nitrate levels in the San Antonio segment of the Edwards Aquifer to anthropogenic sources in urbanized areas of the recharge zone. The two

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Figure 13. For Edwards Trinity Aquifer samples from the GWDB, the categories corresponding to nitrate measurements were determined. (A) For each well, the category corresponding to the maximum nitrate measurement is displayed in map view. (B) The percentage of categories for 420 wells in counties in or close to the study area (Bandera. Blanco, Crockett, Edwards, Gillespie, Hays, Kerr, Kimble, Kinney, Real, Sutton, and Val Verde) was determined for samples taken starting in 1990. (C) The median value of nitrate was determined by decade for wells in the counties in or close to the study area.

areas distinguished on the basis of population change can be used to test whether urbanization is sufficient on its own to explain the nitrate observations. Medina and Uvalde counties have relatively small populations and low population growth. Development over the recharge zone there remains low (Figure 15). With respect to flow in the Edwards Aquifer, Medina and Uvalde counties are upgradient of the urbanization associated with the increase in population of Bexar, Comal, and Hays counties since 1990 (Figure 5). Rather than low nitrate values in the Edwards Aquifer in Medina and Uvalde counties, nitrate measurements are elevated (Figures 6 and 7).

Opsahl et al. (2018) evaluated water quality in the Edwards Aquifer using rainfall data, surface water samples, groundwater data from six wells in Bexar County, and a single well in Medina County. Isotopic samples 186

analyzed by Opsahl et al. (2018) and Musgrove et al.

(2016) found both natural and anthropogenic sources for nitrate, and both studies indicate that higher values of delta nitrogen-15 of nitrate (d15N-nitrate) mark greater input of human or pet waste. The samples from the Medina County well had the lowest measured d15N-nitrate, which the authors considered to be natural. However, the isotopic signature of soil nitrogen and ammonium from ammonium nitrate overlap (Opsahl et al., 2018). Both studies considered lower dissolved oxygen in groundwater versus surface water to be an indication of nitrification taking place in the Edwards Aquifer, and Musgrove et al. (2016) interpreted it as evidence of urbanization on the recharge zone. The GWDB had 68 measurements of dissolved oxygen from 1994 to 2022 from wells in Bexar, Comal, and Hays counties, with a median value of 5.9 mg/L. For 14,085 stream samples from the Guadalupe and San

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Figure 14. Nitrate measurements since 1990 are grouped into one of seven categories for GWDB samples from the Glen Rose Formation of the Trinity Aquifer. Bar charts show the percentage of each category for the eastern area for 401 samples and the western area for 198 samples. Also shown are the categories corresponding in the east to the sample average (4.7 mg/L) and median (1.3 mg/L) and in the west to the sample average (2.4 mg/L) and median (0.38 mg/L).

Antonio river basins over the contributing and recharge zones, the median value for dissolved oxygen is 8 mg/L (TCEQ, 2024). The drop in dissolved oxygen from surface samples to groundwater samples in the eastern area is consistent with the previous studies. However, the median value for 48 well samples from the Edwards Aquifer from 1996 to 2022 in Medina and Uvalde counties is 6 mg/L, and for 808 stream samples from the Nueces River basin over the contributing and recharge zones, the median value for dissolved oxygen is 8.6 mg/L. Combined with lower total nitrogen in stream than in groundwater samples across the study area (Figure 10C and D), the consistent drop in dissolved oxygen may be an indicator of nitrification of ammonium from ANFO. If elevated nitrate levels in the Edwards Aquifer are the result of urbanization over the recharge zone, one would expect rising nitrate levels to coincide in time with increased development of that area. Land use maps confirm the observation by Bush et al. (2000) that development over the recharge and transition zones was mostly after 1992 (Figure 15). For the San Antonio segment of the Edwards Aquifer, Musgrove et al. (2016) did not use historical data of water-quality measurements other than reports from Comal Springs from the 1930s and 1940s. Based on TWDB well data, median Edwards Aquifer nitrate levels in the 1940s and 1950s were near background levels (Figure 9). By the 1960s, nitrate levels were distinctly elevated. For the San Antonio segment of the Edwards Aquifer, the plots by decade show that elevation of nitrate levels preceded intensive development over the recharge zone, so an additional explanation is required.

Dates of operation for all quarries identified on Figure 1 are not available. Quarries are known to have been present in the area from the late nineteenth

century, e.g., Cameron (1994) and Haas (1995). A 2010 WPAP application (Forster, 2010) noted that there had been significant quarry operations on the Edwards recharge zone for more than 80 years. The rise in nitrate concentration in the Edwards Aquifer (Figure 9) coincides with the entry of ANFO on a large scale in the commercial explosive market in the mid-1950s, and ANFO dominated the market by the 1960s (Moreira, 2012).

Elevated nitrate values are found well into the artesian zone of the Edwards Aquifer (Figure 7). Long-distance transport from sources along the recharge zone is consistent with nitrate being nearly inert in groundwater (Starks and Champion, 2001). Tracer tests document that solution features allow rapid passage of water in karstic aquifers (Johnson et al., 2010). In a study of samples from a PWS well field in Bexar County located approximately 10 km southeast of the recharge zone, Jagucki et al. (2011) showed that water is relatively young (,1–41 years), and well mixed over the 150-m (500 ft) producing interval. From modeling, they concluded that as a result of rapid transport of water through karst features, more than 40 percent of produced water is less than 2 years old. Contaminants introduced into the recharge zone would be detectable in the PWS wells within a year and reach 90 percent of the introduced contaminant level in 10 years. Reduction of a contaminant source would be detectable in one to several years. Nitrate in the Edwards Aquifer has shown at least a 60-year rise in concentration (Figure 9), which indicates an increasing amount of nitrate contamination relative to the potential for dilution by recharge. Jagucki et al. (2011) note some variability in the proportion of old water in regional wells that they relate to travel times and that would imply saturation of any contaminants would not be uniform in the Edwards Aquifer.

Making an order-of-magnitude estimate of residual nitrate that may have resulted from mining all mapped quarries requires estimating the acreage mined since the mid-1950s and using that to scale up the potential nitrate residual from quarrying 8.09 3 105 m2 (200 acres) in Comal County (Table 2). In general, limestone aggregate production roughly increases with the increase in Texas’s population (Kyle and Elliot, 2019).

The increase in population from 1955 through 2022 is 88 percent of the increase since 1930 (Macrotrends, 2024). That percentage leads to an estimate of the quarry area mined since 1955 of 3.5 3 107 m2 (8,700 acres) and a nitrate residual estimate of 1.7 3 108 kg, or an average of 2.4 3 106 kg annually over 67 years.

Median annual recharge to the Edwards Aquifer is estimated to be 6.8 3 108 m3 from 1934 through 2021 (EAA, 2021). Relative to median annual recharge, the

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Figure 15. Urban development in the study area in (A) 1992 (Sohl et al., 2018) and (B) 2019 (MRLC, 2019).

average potential annual nitrate contribution to the aquifer is on the order of 3.6 mg/L. Flow in the Edwards Aquifer is dominated by conduits with comparatively little contribution from the larger matrix volume (Hauwert, 2011). Lindgren et al.

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(2004) cite an estimate of water-filled pore space for the San Antonio segment of the Edwards Aquifer of 2.13 3 1011 m3 (1.73 3 107 acre ft). For karstic aquifers like the Edwards Aquifer, conduit volume as a percentage of total porosity is estimated to be as much as 1 percent

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(Taylor and Greene, 2008). Relative to that estimate of conduit volume, the potential annual nitrate residual is on the order of 1.1 mg/L. The timing of nitrate increase in the east and west areas (Figure 9) resulting from the introduction of ANFO to aggregate operations would be expected to be similar. However, nitrate concentrations observed in the west are higher than might be expected compared to eastern counties based on the number and size of quarries (Figures 1 and 6), particularly in Uvalde County.

Quarries in Uvalde County are clustered in a relatively small area and are separated from the remainder of the San Antonio segment by a flow restriction, the Knippa Gap (Figure 1), which was originally defined from a steepening of potentiometric contours in the eastern part of that county (Lindgren et al., 2004). Those authors describe the flow pattern in central Uvalde County as complex and poorly defined. Clark et al. (2013) determined that the Knippa Gap reflects a change in orientation of relay ramps from southwest dipping in Medina County to northeast dipping in Uvalde County. The Edwards Aquifer likely has a different dilution history in Uvalde County compared to areas to the east, which may influence the observed nitrate levels. In addition, the elevated nitrate levels in groundwater of the Edwards Trinity Plateau Aquifer in northwestern Uvalde County may contribute nitrate to the Edwards Aquifer by crossflow.

Four San Antonio Water System well fields produce water exclusively from the Edwards Aquifer: Castle Hills, Geronimo, Mountain Laurel, and Texas Research Park. For these well fields, nitrate measurements made in 2022 ranged from 5.39 to 9.86 mg/L (SAWS, 2023).

These values correspond to groups in Figures 6 and 7, which show elevation of nitrate levels. For well waterquality analyses from the TWDB database, nitrate values above the MCL remain rare for 2020 through 2022, but 74 percent of TWDB nitrate measurements were 8 mg/L or greater, which is the category harmful to some freshwater aquatic organisms.

CONCLUSIONS Measurements of nitrate in the Edwards Aquifer are elevated relative to what might be expected from unpolluted sources and have clearly increased over time to a point where they potentially threaten aquatic organisms within the Edwards Aquifer karst environment. Neither surface water from the contributing zone nor cross-fault flow from the Trinity Aquifer account for elevated nitrate measurements in the Edwards Aquifer. In addition, it is clear from both geographic and temporal perspectives that neither urban development over the recharge zone nor atmospheric deposition of nitrogen account for the observed nitrate levels in the Edwards Aquifer.

Use of ANFO in quarrying operations has not been previously published as a source of nitrate pollution in the Edwards Aquifer. The high solubility of ANFO, the large volumes of ANFO used in quarry operations, and the high percentage of explosive residuals, together with the fact that quarry operations are a known source of nitrate pollution of groundwater elsewhere, make it clear that aggregate quarries are large contributors of nitrate to the aquifer. Quarry distribution aligns well with the geographic distribution of elevated nitrate concentrations in the Edwards Aquifer. That, together with the coincidence in time of increasing nitrate levels with the large-scale introduction of ANFO to aggregate mining, indicates that quarries are a significant, if not the main, source of nitrate pollution in the aquifer and make the Edwards Aquifer a useful example of the impact of aggregate mining on karstic aquifers.

ACKNOWLEDGMENTS George Veni provided extensive input to the content and organization of this paper. Doug Wierman and Brian Smith provided helpful reviews.

REFERENCES Agency of Natural Resources, 2014, Best Management Practices for Blasting Activities to Avoid Environmental Contamination: State of Vermont, Department of Environmental Conservation, Waste Management Prevention Division, 3 p.

ALBERTS, N., 2016, Tackling nitrate contamination of water in mines: Mining News Digest, August 11, Electronic document, available at https://www.mining.com/web/tackling-nitrate-contamination-ofwater-in-mines/ American Waterworks Association and Economic and Engineering Services, Inc., 2002, Nitrification: U.S. Environmental Protection Agency, Office of Ground Water and Drinking Water Distribution System Issue Paper, 17 p.

ASQUITH, G. AND GIBSON, C., 1982, Basic Well Log Analysis for Geologists: American Association of Petroleum Geologists, Tulsa, OK, 216 p.

BARRETT, M. E., 2005, Complying with the Edwards Aquifer Rules Technical Guidance on Best Management Practices: Texas Commission on Environmental Quality, 415 p.

BARRETT, M. E. AND ECK, B. J., 2012, Best Management Practices for Quarry Operations Complying with the Edwards Aquifer Rules: Texas Commission on Environmental Quality RG-350, 26 p.

BROCHU, S., 2010, Assessment of ANFO on the Environment, Technical Investigation 09-01: DRDC Valcartier TM 2009-195; Defence R&D Canada, Valcartier, Canada, 38 p.

BUSH, P. W.; ARDIS, A. F.; FAHLQUIST, L.; GING, P. B.; HORNIG, C. E.; AND LANNING-RUSH, J., 2000, Water Quality in South-Central Texas, 1996–98: U.S. Geological Survey Circular 1212, 34 p.

CAMERON, M. B., 1994, Beckman, TX: Handbook of Texas Online: Electronic document, available at https://www.tshaonline.org/handbook/ entries/beckman-tx CARMAGO, J.; ALONSO, A.; AND SALAMANCA, A., 2005, Nitrate toxicity to aquatic animals: A review with new data for freshwater invertebrates: Chemosphere, Vol. 58, pp. 1255–1267. https:// doi.org/10.1016/j.chemosphere.2004.10.044

Environmental & Engineering Geoscience, Vol. XXX, No. 4, November 2024, pp. 173–191

189

Doyle Carnegie Corporation and University of Iowa, 2017, CAFOs in the US: Electronic document, available at https://cafomaps.org/bystate/tx.html CHASNOF, B., 2021, From Garden Ridge to New Braunfels, “Quarry Row” has residents demanding stricter regulation: San Antonio Express News, October 6, Electronic document, available at https:// www.expressnews.com/news/investigations/article/quarry-row-rockmining-16510615.php CLARK, A. K.; PEDRAZA, D. E.; AND MORRIS, R. R., 2013, Geologic framework, structure, and hydrogeologic characteristics of the Knippa Gap area in eastern Uvalde and western Medina Counties, Texas: U.S. Geological Survey Scientific Investigations Report 2013-5149, 35 p.

Department of the Interior, Fish and Wildlife Service, 2012, Endangered and Threatened Wildlife and Plants; Endangered Status for Four Central Texas Salamanders and Designation of Critical Habitat: National Archives and Records Administration Federal Register, Vol. 77, No. 163, August 22, Part II, 88 p.

DUBROVSKY, N. M.; BUROW, K. R.; CLARK, G. M.; GRONBERG, J. M.; HAMILTON, P. A.; HITT, K. J.; MUELLER, D. K.; MUNN, M. D.; NOLAN, B. T.; PUCKETT, L. J.; RUPERT, M. G.; SHORT, T. M.; SPAHR, N. E.; SPRAGUE, L. A.; AND WILBER, W. G., 2010, The Quality of Our Nation’s Water—Nutrients in the Nation’s Streams and Groundwater, 1992–2004: U.S. Department of the Interior, U.S. Geological Survey Circular 1350, 174 p.

Dyno Nobel, 2010, Blasting and Explosives Quick Reference Guide: Dyno Nobel Asia Pacific Pty Limited, 32 p., Electronic document, available at https://www.lrl.mn.gov/docs/2015/other/ 150681/PFEISref_1/Dyno%20Nobel%202010.pdf EAA (Edwards Aquifer Authority), 2014, Shapefiles, available at https://www.edwardsaquifer.org/science-maps/maps/shapefiles/ EAA, 2019, General Aquifer Flowpath: Electronic document, available at https://www.edwardsaquifer.org/wp-content/uploads/ 2019/04/generalaquiferflowpath.pdf EAA, 2020, What Is the Aquifer: Electronic document, available at https://www.edwardsaquifer.org/wp-content/uploads/2020/07/Whatis-the-Aquifer.pdf EAA, 2021, 2021 Groundwater Recharge: Electronic document, available at https://www.edwardsaquifer.org/science-maps/researchscientific-reports/hydrologic-data-reports/ EAA Open Records Center, 2024, personal communication, EAA, 900 E. Quincy, San Antonio, TX 78215.

EPA (U.S. Environmental Protection Agency), 2017, Ground Water and Drinking Water National Primary Drinking Water Regulations: Electronic document, available at https://www.epa.gov/ground-waterand-drinking-water/national-primary-drinking-water-regulations EPA, 2023, Status of Nutrient Requirements for NPDES-Permitted Facilities: National Pollutant Discharge Elimination System (NPDES): Electronic document, available at https://www.epa.gov/npdes/statusnutrient-requirements-npdes-permitted-facilities FORSTER, C. P., 2010, Recharge and Transition Zone Exception Request Form, Martin Marietta New Braunfels Quarry Operations Modification: Electronic document, available at. https://www.cceo.org/ environmental/documents/WPAP/Martin_Marietta_Materials_New_ Braunfels_Quarry.pdf Golder Associates, 2014, Amulsar gold project: Estimate of nitrate and ammonia concentrations in mine water as a product of blasting, technical memorandum: Electronic document, available at https:// www.lydianarmenia.am/resources/mainFiles/pdf/2864656c847d598 7d1653486d6fdd291.pdf GREEN, R. T.; BERTETTI, F. P.; AND CANDELARIO, M. O., 2011, Edwards Aquifer—Upper Glen Rose aquifer hydraulic interaction. In Gary, M. O.; Gary, R. H.; and Hunt, B. B. (Editors), Interconnection of the Trinity (Glen Rose) and Edwards Aquifers along the Balcones Fault Zone and Related Topics: Proceedings of the Karst

190

Conservation Initiative Meeting: Austin, TX, pp. 30–35, available at https://www.edwardsaquifer.org/wp-content/uploads/2021/ 04/2011-Interconnection-of-the-Trinity-Glen-Rose-and-EdwardsAquifers-along-the-Balcones-Fault-Zone-and-Related-Topics-KarstConservation-Initiative.pdf HAAS, O., 1995, Ogden, TX (Comal County): Handbook of Texas Online, Electronic document, available at https://tshaonline.org/ handbook/entries/ogden-tx-comal-county HAUWERT, N. M., 2011, Could much of Edwards Aquifer “matrix storage” actually be Trinity Aquifer contributions from the Blanco River? In Gary, M. O.; Gary, R. H.; and Hunt, B. B. (Editors), Interconnection of the Trinity (Glen Rose) and Edwards Aquifers along the Balcones Fault Zone and Related Topics: Proceedings of the Karst Conservation Initiative Meeting: Austin, TX, pp. 15–24, available at https://www.edwardsaquifer.org/wp-content/uploads/ 2021/04/2011-Interconnection-of-the-Trinity-Glen-Rose-andEdwards-Aquifers-along-the-Balcones-Fault-Zone-and-Related-TopicsKarst-Conservation-Initiative.pdf JAGUCKI, M. L.; MUSGROVE, M.; LINDGREN, R. J.; FAHLQUIST, L.; AND EBERTS, S. M., 2011, Assessing the Vulnerability of Public-Supply Wells to Contamination: Edwards Aquifer Near San Antonio, Texas: U.S. Department of the Interior, U.S. Geological Survey Fact Sheet 2011-3142, 6 p. https://doi.org/10.3133/fs20113142 JOHNSON, S.; SCHINDEL, G.; AND VENI, G., 2010, Tracing Groundwater Flowpaths in the Edwards Recharge Zone, Panther Springs Creek Basin, Northern Bexar County, Texas: Edwards Aquifer Authority Report No. 10-01, 112 p.

JONES, I. C., 2011, Interaction between the Hill Country portion of the Trinity and Edwards Aquifers: Model results. In Gary, M. O.; Gary, R. H.; and Hunt, B. B. (Editors), Interconnection of the Trinity (Glen Rose) and Edwards Aquifers along the Balcones Fault Zone and Related Topics: Proceedings of the Karst Conservation Initiative Meeting: Austin, TX, pp. 36–37, available at https://www.edwardsaquifer. org/wp-content/uploads/2021/04/2011-Interconnection-of-the-TrinityGlen-Rose-and-Edwards-Aquifers-along-the-Balcones-Fault-Zone-andRelated-Topics-Karst-Conservation-Initiative.pdf KERNAN, B., 2010, Rock Blasting and Water Quality Measures That Can Be Taken To Protect Water Quality and Mitigate Impacts: DES Drinking Water Source Protection Program, New Hampshire Department of Environmental Services, 3 p.

KONYA, A. AND KONYA, C., 2019, Blasting mechanics revisited: Characteristics of explosives: Pit and Quarry, March 20, Electronic document, available at https://www.pitandquarry.com/ blasting-mechanics-revisited-characteristics-of-explosives/ KYLE, J. R. AND ELLIOTT, B., 2019, Past, present, and future of Texas industrial minerals: Mining, Metallurgy & Exploration, Vol. 36, pp. 475–486. https://doi.org/10.1007/s42461-019-0050-1 LINDGREN, R. J.; DUTTON, A. R.; HOVORKA, S. D.; WORTHINGTON, S. R. H.; AND PAINTER, S., 2004, Conceptualization and simulation of the Edwards Aquifer, San Antonio Region, Texas: U.S. Department of the Interior, U.S. Geological Survey Scientific Investigations Report 2004-5277, 143 p. https://doi.org/10.3133/ sir20045277 Macrotrends, 2024, Texas population 1900–2023: Electronic document, available at https://www.macrotrends.net/global-metrics/states/texas/ population MONSON, P., 2022, Aquatic Life Water Quality Standards Draft Technical Support Document for Nitrate: Minnesota Pollution Control Agency, 21 p., Electronic document, available at https://www.pca. state.mn.us/sites/default/files/wq-s6-13.pdf MOREIRA, G., 2012, History of explosives and initiation devices: Sand & Stone: Official Publication of the CMPA, Electronic document, available at https://sandandstone.cmpavic.asn.au/history-ofexplosives-and-initiation-devices/

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Quarries as a Source of Nitrate Pollution in Karst Aquifers MRLC (Multi-Resolution Land Characteristics Consortium), 2019, Data Services Page: Electronic document, available at https:// www.mrlc.gov/data-services-page MUSGROVE, M.; FAHLQUIST, L.; HOUSTON, N. A.; LINDGREN, R. J.; AND GING, P. B., 2010, Geochemical evolution processes and waterquality observations based on results of the National Water-Quality Assessment Program in the San Antonio segment of the Edwards aquifer, 1996–2006: U.S. Geological Survey Scientific Investigations Report 2010-5129, 93 p.

MUSGROVE, M.; OPSAHL, S. P.; MAHLER, B. J.; HERRINGTON, C.; SAMPLE, T. L.; AND BANTA, J. R., 2016, Source, variability, and transformation of nitrate in a regional karst aquifer: Edwards aquifer, central Texas: Science Total Environment, Vol. 568, pp. 457–469. http:// dx.doi.org/10.1016/j.scitotenv.2016.05.201 National Atmospheric Deposition Program, 2016, Nitrogen From the Atmosphere: Electronic document, available at https://nadp.slh. wisc.edu/wp-content/uploads/2021/05/nitrogenAtmos.pdf National Atmospheric Deposition Program, 2020, Animated Maps: Electronic document, available at https://nadp.slh.wisc.edu/mapsdata/animated-maps/ National Minerals Information Center, 2021, USGS Aggregates Time Series Data by State, Type, and End Use: Electronic document, available at https://www.usgs.gov/media/files/usgsaggregates-time-series-data-state-type-and-end-use OPSAHL, S. P.; MUSGROVE, M.; MAHLER, B. J.; AND LAMBERT, R. B., 2018, Water-quality Observations of the San Antonio Segment of the Edwards Aquifer, Texas, with an Emphasis on Processes Influencing Nutrient and Pesticide Geochemistry and Factors Affecting Aquifer Vulnerability, 2010–16: U.S. Geological Survey Scientific Investigations Report 2018-5060, 67 p. https://doi.org/10.3133/sir20185060 PELLETIER, J. D.; BROXTON, P. D.; HAZENBERG, P.; ZENG, X.; TROCH, P. A.; NIU, G.; WILLIAMS, Z. C.; BRUNKE, M. A. AND GOCHIS, D., 2016, Global 1-km Gridded Thickness of Soil, Regolith, and Sedimentary Deposit Layers: Oak Ridge National Laboratory, Distributed Active Archive Center for Biogeochemical Dynamics, Oak Ridge, TN. https://doi.org/10.3334/ORNLDAAC/1304 REEDY, R. C. AND SCANLON, B. R., 2017, Evaluation of Groundwater Nitrate Contamination in Public Water Systems and Major and Minor Aquifers in Texas: Final Contract Report prepared for Texas Commission on Environmental Quality, 64 p.

SAWS (San Antonio Water System), 2023, Water Quality 2023 Report: Electronic document, available at https://www.saws.org/ your-water/water-quality/water-quality-report/ SCHINDE, G. M., 2019, Genesis of the Edwards (Balcones Fault Zone) Aquifer. In Sharp, J. M., JR., Green, R. T. and Schindel, G. M. (Editors), The Edwards Aquifer: The Past, Present, and Future of a Vital Water Resource: Geological Society of America Memoir 215, pp. 9–18. https://doi.org/10.1130/2019.1215(02) SHARP, J. M. AND GREEN, R. T., 2022, The Edwards Aquifer: The Groundwater Project, Guelph, Ontario, Canada, Electronic document, available at https://doi.org/10.21083/978-1-77470-029-7 SOHL, T. L.; SAYLER, K. L.; BOUCHARD, M. A.; REKER, R. R.; FREISZ, A. M.; BENNETT, S. L.; SLEETER, B. M.; SLEETER, R. R.; WILSON, T.; SOULARD, C.; KNUPPE, M.; AND VAN HOFWEGEN, T., 2018, Conterminous United States Land Cover Projections—1992 to 2100: U.S. Geological Survey data release, https://doi.org/10.5066/P95AK9HP STARKS, R. AND CHAMPION, K. M., 2001, The hydrology and water quality of select springs in the Southwest Florida Water Management District: Electronic document, available at https:// digitalcommons.usf.edu/kip_data/90 SULLIVAN, T. P. AND GAO, Y, 2016, Assessment of nitrogen inputs and yields in the Cibolo and Dry Comal Creek watersheds using the SWAT model, Texas, USA 1996–2010: Environmental Earth Sciences, Vol. 75, No. 9, 20 p. https://doi.org/10.1007/s12665-016-5546-0

SULLIVAN, T. P.; GAO, Y.; AND REIMANN, T., 2019, Nitrate transport in a karst aquifer: Numerical model development and source evaluation: Journal of Hydrology, Vol. 573, June, pp. 432–448. https:// doi.org/10.1016/j.jhydrol.2019.03.078 SWISTOCK, B., 2022, Nitrates in Drinking Water: Electronic document, available at https://extension.psu.edu/nitrates-in-drinking-water TACA (Texas Aggregates and Concrete Association), 2020, How do Texas quarry operators manage precious water resources as they deliver the materials Texas needs to grow and thrive? TACA, January, 2 p., Electronic document, available at https://www.txtaca.org/water-management TAYLOR, C. J. AND GREENE, E. A., 2008, Hydrogeologic characterization and methods used in the investigation of karst hydrology: In Rosenberry, D. O. and LaBaugh, J. W. (Editors), Field Techniques for Estimating Water Fluxes between Surface Water and Ground Water: U.S. Geological Survey Techniques and Methods 4-D2, pp.

71–114, https://pubs.usgs.gov/tm/04d02/ TCEQ (Texas Commission on Environmental Quality), 2019, Edwards Aquifer, available at https://gis-tceq.opendata.arcgis.com/maps/TCEQ:: edwards-aquifer/about TCEQ, 2022a, Surface Water Quality Viewer, available at https:// www.tceq.texas.gov/gis/segments-viewer TCEQ, 2022b, TCEQ Ecological Screening Benchmarks.xlsx: Electronic document, available at https://www.tceq.texas.gov/remediation/eco TCEQ, 2024, The Texas Clean Rivers Program: Electronic document, available at https://www80.tceq.texas.gov/SwqmisWeb/public/crpweb. faces TCEQ GIS Team, 2020, Edwards Aquifer Land Use/Cover: Electronic document, available at https://gis-tceq.opendata.arcgis.com/datasets/ TCEQ::edwards-aquifer-land-use-land-cover/explore?location¼ 29.593896%2C-98.544918%2C13.88&showTable¼true Texas Hearst Data Visualization Team, 2021, Do You Live Near a Quarry? San Antonio Express News, October 6, Electronic document, available at https://www.expressnews.com/projects/2021/texas-quarrymap/ TWDB (Texas Water Development Board), n.d.a, GIS Data: Electronic document, available at https://www.twdb.texas.gov/mapping/gisdata. asp TWDB, n.d.b, Groundwater Database (GWDB) Reports and Downloads: Electronic document, available at https://www. twdb.texas.gov/groundwater/data/gwdbrpt.asp TWDB, n.d.c, Explanation of the Groundwater Database (GWDB): Electronic document, available at https://www.twdb.texas.gov/ groundwater/faq/faqgwdb.asp U.S. Department of Agriculture, 2024, Census of Agriculture: Electronic document, available at https://www.nass.usda.gov/AgCensus/ USGS (U.S. Geological Survey), 2022, Texas Geologic Map Data: Electronic document, available at https://mrdata.usgs.gov/geology/ state/state.php?state¼TX USGS, n.d., TNM Download (v2.0): Electronic document, available at https://apps.nationalmap.gov/downloader/#/? z¼4&y¼37.99999999999999&x¼-95&basemap¼usgs_topo& datasets¼&layerIds¼ VENI, G., 2022, personal communication, George Veni and Associates, 507 E. Chapman Road, Carlsbad, NM 88220.

WELDER, F. A. AND REEVES, R. D., 1964, Geology and Ground-Water Resources of Uvalde County, Texas: Geological Survey WaterSupply Paper 1584, 49 p. https://doi.org/10.3133/wsp1584 WORTHINGTON, S. R. H., 2011, Management of carbonate aquifers. In van Beynen, P. (Editor), Karst Management: Springer, Dordrecht, Netherlands. 233–261. https://doi.org/10.1007/978-94-007-12072_11

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Determining Groundwater Table in Slopes With Horizontal Drains and Design Framework for Length and Spacing MIHIRA LAKRUWAN*, AKIYOSHI KAMURA, AND MOTOKI KAZAMA Department of Civil and Environmental Engineering, Tohoku University, 6-6-06, Aoba Aramaki, Aoba-ku, Sendai, Miyagi, Japan 980-8579

Design of Horizontal Drains in Landslide Mitigation Projects

2005). Today, they are widely used as an effective technique for drainage management in a variety of geotechnical applications, including slope and embankment stability improvement (Nonveiller, 1981; Lau and Kenney, 1984; Martin et al., 1995; Cai et al., 1998; Forrester, 2001; Rahardjo et al., 2003, 2011; Tsao et al., 2005; Ghiassian and Ghareh, 2008; Shrestha et al., 2008; and Hinds et al., 2021), drainage management behind soil nailing and retaining walls (Chen and Chen, 2013; Geotechnical Engineering Office, 2017; Lakruwan and Kulathilaka, 2020, 2021), enhancement of the liquefaction resistance of soil (Fasano et al., 2019, 2021), and acceleration of consolidation (Feng et al., 2020). This study focused on evaluating the effectiveness of HDs in enhancing slope stability.

The effectiveness of HDs in enhancing slope stability is primarily based on several design parameters such as location, spacing, length, and drain type (Rahardjo et al., 2011; Lakruwan et al., 2021; and Abed et al., 2024). Rahardjo et al. (2003) showed that installation of HDs at the bottom of a slope was more effective than installation of HDs at higher elevations, thus confirming the results of Lau and Kenney (1984) and Martin et al. (1995). Additionally, some studies have tried to identify a maximum limit for the length of HDs (Royster, 1980; Lau and Kenney, 1984; Cai et al., 1998; and Cook et al., 2008), and several attempts have been made to develop design charts (Kenny et al., 1977; Stani c, 1984), but they are generally only valid for the specific slope conditions (Resnick and Znidar ci c, 1990).

Additionally, the general guidelines provided by Cook et al.

(2012) for HD spacing based on the soil type vary significantly depending on the soil and recharge conditions.

Previous studies have proven that the design of HDs is highly site-specific and that providing generalized guides is not feasible. Hence, instead of a generalized guide, a novel method that is applicable to a wide range of slope conditions is proposed in this study to uniquely analyze the effects of the length and spacing of HDs on the pore water force reduction on a slip surface and, subsequently, the stability enhancement of a slope.

Horizontal drains (HDs) were initially introduced for groundwater management in agricultural land (Stuyt et al.,

Groundwater Table Profile between Parallel and Long HDs

*Corresponding author email: samarasekara.okandapala.arachchige.don. m.b8@tohoku.ac.jp

Among the several theoretical methods developed to obtain the groundwater table (GWT) profile between

Key Terms: Slope Stabilization, Landslides, Drainage, Horizontal Drains, Water Table Profile, Pore Water Pressure, Slip Surface ABSTRACT Horizontal drains (HDs) are commonly implemented in slope stabilization to reduce the pore water pressure (PWP); however, they also cause complex three-dimensional (3D) variations in the groundwater table (GWT), which require intricate 3D flow models. To address this challenge, we propose a novel semi-empirical method based on a series of numerical simulations validated through numerical and field studies to determine the GWT of a slope with HDs. Subsequently, the proposed method was extended to calculate the average PWP (U) acting on a predefined slip surface via linear integration.

The decrease of U (DU) resulting from HDs can be used to evaluate the performance of HDs. To create design charts that consider the impact of length and spacing of HDs on DU for a specific slope, we developed a Pythonbased computer program. Two case studies were conducted, which showed that DU increases with longer HDs and shorter spacing. The results also indicated that extending the HDs beyond a particular length does not significantly affect DU; it is highly sensitive to the spacing in short HDs and not sensitive in long HDs. Furthermore, we found that the total length of HDs required to achieve a target DU is less in wide spacings than in short spacings. In conclusion, long HDs with wide spacings are more effective and economical. Owing to the unique nature of each slope stability problem, this study offers a practical tool for analyzing the effectiveness of HDs instead of providing a general guide.

INTRODUCTION

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HDs in agricultural lands (Hooghoudt, 1940; Ernst, 1954; and Kirkham, 1958), the Hooghoudt (1940) equation, which is based on Darcy’s law and the Dupuit-Forchheimer theory of horizontal flow, is widely used. Luthin (1966) presented the work of Hooghoudt (1940), which was originally presented in the Netherlands, as: rffiffiffiffi S R hm ¼ (1) de : 2 ks Here, hm denotes the maximum GWT height at the mid-point between the parallel and infinitely long HDs (m), S represents the drain spacing (m), R corresponds to the constant or steady-state recharge from the ground surface (or infiltration) (m/s), ks denotes the saturated hydraulic conductivity of the soil (m/s), and de reflects the equivalent depth to the impermeable layer (m), which accounts for the radial flow in the vicinity of the pipe that does not satisfy the Dupuit-Forchheimer assumption. Greg et al. (2013) presented the following relationships for determining de: de ¼

1 þ DS

de ¼

D

D # 0:31; S

(2)

D ; for > 0:31; S 1:15

(3)

2:55ln

S

2:55ln rSd

D rd

C

; for

where D is the depth of the impermeable layer (m), rd is the pipe radius (m), and 2 D D C ¼ 3:55 1:6 þ 2 : (4) S S Although a few studies (Greg et al., 2013; Conte and Troncone, 2018) have used the Hooghoudt (1940) method for slope stability applications, its applicability to slopes is limited because the assumption of semi-infinitely long and parallel HDs is invalid for most slope stabilization applications. Although the Hooghoudt (1940) method assumes a uniform variation in the GWT profile along the HDs, the limited lengths result in nonuniform GWT variations along the HDs on slopes, leading to a complex distribution of the GWT profile in three-dimensional (3D) space.

Crenshaw and Santi (2004) were the first researchers to address this issue and proposed an empirical method for determining the 3D variation in the GWT along short HDs. However, the requirement of a GWT height of approximately 20 ft (6 m) behind the drain field and the inability to predict the GWT profile beyond the HD field are drawbacks of Crenshaw and Santi’s (2004) method.

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Pore Water Pressure on a Slip Surface The accumulation of pore water pressure (PWP) on the slip surface can be identified as the major triggering factor for rain-induced slope failures. Several studies have evaluated slope stability based on the pore water force on the slip surface (U) (Tsao et al., 2005; Conte and Troncone, 2012, 2018).

Novel Method to Obtain GWT Profile and Design Procedure for HDs Currently available analytical and empirical methods do not adequately address the effect of 3D variation in the GWT in short HDs on slopes. Additionally, two-dimensional (2D) flow simulation models neglect the 3D effect of the GWT profile, potentially resulting in a inadequate design (Lakruwan et al., 2022; Abed et al., 2024). Consequently, to accurately capture the comprehensive effect of the 3D variation of the GWT, complex 3D flow simulation models are necessary. However, setting up an accurate 3D model to represent an actual slope is challenging, and the time and computational power required to iterate such complex models to obtain the optimal design parameters for HDs significantly increase the complexity of the process.

In contrast, this study proposes a novel semi-empirical method for predicting the steady-state GWT profile of HDs with limited lengths based on a series of numerical simulations. This method was validated through a series of numerical cases and field studies. The proposed method has fewer limitations, requires minimal computational power, can be conveniently implemented, and not only can predict the GWT profile in the HD field, but also the slope behind the HD. Furthermore, we extend the proposed GWT prediction method to obtain the U and reduction of U (DU) by HDs. We then describe the procedure for developing a design chart to select the optimal length and spacing of the HDs for a given slope. To demonstrate the effectiveness of our proposed method and design procedure, we performed two case studies, and we provide several guidelines for selecting the optimal length and spacing of HDs. The proposed GWT prediction method and design procedure allow designers to efficiently perform HD design while considering the 3D nature of the problem.

OBJECTIVES The objectives of this study are summarized as follows: 1. To develop a novel semi-empirical method to predict the GWT profile of a slope with HDs based on the observation of numerical simulations and to validate

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Figure 1. Methodology for the study.

the proposed method through a comprehensive series of numerical case studies and a rigorous field study, ensuring the reliability and applicability of the proposed method; 2. To establish an average GWT profile that adequately captures 3D variations, which may be utilized in 2D numerical simulations, providing a more accurate and efficient approach for analyzing slope stability; 3. To quantify the U and DU values in the presence of a slip surface by integrating across the average GWT, and to thoroughly analyze the effect of the HD length and spacing on DU, highlighting the significance of selecting suitable values to achieve effective and economical design; and 4. To produce a design chart for specific slope conditions, enabling designers to confidently select optimal HD lengths and spacing based on the design requirements, and to provide insights and recommendations for the selection of HD lengths and spacing to achieve an optimal design.

The structure of this article (Figure 1) is summarized as follows: 1. Proposed Method: The novel semi-empirical method developed to determine or predict the GWT on a slope

with HDs based on a series of 3D finite element (FE) analyses conducted on slope I is presented and shown in Figure 2. The average GWT obtained from the results is subsequently used to calculate the U and DU. 2. Validation: The proposed method for predicting GWT, U, and DU is comprehensively validated through a numerical case study on slopes I and II in Figure 2 and a field study.

3. Results and Discussion: The effect of the HD length and spacing on the DU (and factor of safety [FS] enhancement, DFS) value is rigorously evaluated using slopes I and II in Figure 2.

PROPOSED METHOD Novel Semi-Empirical Method to Predict GWT Profile Model Setup and Boundary Conditions Series of FE steady-state flow analyses were performed on a 30-m-wide (in the Y direction) section of slope I using PLAXIS 3D (CONNECT Edition V20) (PLAXIS, 2020). Ten-node tetrahedral elements were used for FE discretization. The 3D FE model of slope I is shown in Figure 3. Table 1 presents the details of the

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Figure 2. Slope profiles used in the study: (a) slope I, and (b) slope II.

numerical model analysis, and the parameters are shown in Figures 3 and 4.

Establishing the upstream hydraulic boundary in slopes is challenging due to its complex behavior influenced by hydrological conditions outside the slope domain. Following previous studies (Das et al., 2022; Lernia et al., 2022), a constant-head Dirichlet boundary with a total head of Hi (D þ hi, where hi is the height of the GWT at the boundary relative to the HD level) was used. Although this upstream

head exhibits seasonal variation (Lernia et al., 2022), using the high head value of the rainy season is a conservative approach in steady-state analysis. The constraints for the location of the upstream boundary are outlined in the section on “Constraints of the Proposed Method.” A Neumann boundary condition was assumed at the top surface to simulate the infiltration during rain. Although infiltration has temporal variability, we used the average value of the peak rainfall as a constant recharge (R) to provide a conservative

Figure 3. The 30-m-wide 3D FE model of slope I used to develop the proposed semi-empirical method to obtain the GWT profile (S ¼ 5 m).

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Defining Zones in the GWT Profile

Table 1. Details of the FE models used to develop empirical relationships (with parameters as illustrated in Figures 3 and 4).

We observed three distinct regions of groundwater flow on slopes with HDs, which were characterized by flow direction (Figure 5). In the region behind the HDs, the X-directional component of the groundwater flow (qx) dominates the Y-directional component (qy), resulting in a 2D flow in the XZ plane. Conversely, when HDs were present, qy became dominant over qx, leading to 2D flow in the YZ plane. The transition from the XZ plane to the YZ plane occurred through a narrow region at the end of the HDs. Because clear distinctions between the three regions could not be established based solely on groundwater flow, we examined the GWT profile at the mid-section between the HDs (on the XZ plane).

The gradual increase in the GWT in the HD field was idealized into two linear profiles with different gradients

Details of PLAXIS Models D (m) B (m) 10 20

50 90 50

L (m)

hi (m) S (m)

n

15, 20, 25, 30, 35 2, 5, 8 10, 5 0, 0.05, 0.1, 0.2 20, 30, 40, 50, 60, 70 10 5 0, 0.1 15, 20, 25, 30, 35 5 5 0, 0.1

estimate in steady-state conditions. This recharge represents the infiltration after surface runoff. Additionally, a 0.1 m cutoff value was used to prevent excessive ponding on the surface. Line drains with zero water pressure were employed as the HDs, neglecting the effect of entrance head loss and pressure head inside fully flowing pipes.

Table 2. Summary of validation, showing MAE and R2 values between the GWTs from 3D FE models and proposed method.

Total Length (Zones 1, 2, and 3) Figure 10 (a) n ¼ 0.1 /S ¼ 2.5 m /hi ¼ 22 m L ¼ 10 m L ¼ 20 m L ¼ 30 m L ¼ 40 m L ¼ 50 m n ¼ 0.1 /S ¼ 5 m /hi ¼ 22 m L ¼ 10 m L ¼ 20 m L ¼ 30 m L ¼ 40 m L ¼ 50 m n ¼ 0.1 /S ¼ 10 m /hi ¼ 22 m L ¼ 10 m L ¼ 20 m L ¼ 30 m L ¼ 40 m L ¼ 50 m Figure 10 (b) S ¼ 10 m /L ¼ 30 m /hi ¼ 12 m n ¼ 0.05 n ¼ 0.1 n ¼ 0.3 Figure 10 (c) n ¼ 0.17 /S ¼ 10 m /L ¼ 30 m hi ¼ 17 m hi ¼ 12 m hi ¼ 7 m hi ¼ 2 m Figure 10 (d) n ¼ 0.1 /S ¼ 5 m /L ¼ 30 m /hi ¼ 22 m h ¼ 2.5° h ¼ 5° h ¼ 10°

On HD (Zones 1 and 2)

MAE (m)

R

2

0.215 0.156 0.192 0.238 0.313

On Zone 3

MAE (m)

R

2

MAE (m)

R2

0.998 0.999 0.999 0.999 0.998

0.305 0.197 0.238 0.295 0.381

0.786 0.869 0.810 0.739 0.638

0.195 0.140 0.159 0.175 0.188

0.997 0.999 0.998 0.998 0.998

0.193 0.214 0.269 0.326 0.405

0.998 0.998 0.998 0.997 0.996

0.363 0.343 0.386 0.453 0.536

0.789 0.823 0.814 0.802 0.792

0.156 0.160 0.187 0.183 0.165

0.998 0.998 0.997 0.997 0.998

0.210 0.302 0.361 0.412 0.479

0.998 0.996 0.996 0.995 0.993

0.502 0.507 0.509 0.543 0.621

0.814 0.814 0.844 0.858 0.874

0.148 0.217 0.258 0.264 0.220

0.998 0.995 0.993 0.992 0.994

0.180 0.200 0.687

0.997 0.996 0.972

0.277 0.296 0.447

0.901 0.913 0.894

0.112 0.132 0.855

0.997 0.995 0.607

0.258 0.178 0.172 0.158

0.997 0.997 0.993 0.951

0.413 0.312 0.252 0.240

0.837 0.835 0.831 0.640

0.150 0.085 0.115 0.100

0.998 0.998 0.992 0.917

0.339 0.289 0.498

0.996 0.997 0.994

0.597 0.504 0.498

0.729 0.886 0.941

0.159 0.138 0.498

0.999 0.999 0.981

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Figure 4. Typical groundwater table profile of a slope at the mid-section between HDs.

to simplify the proposed method. Zone 1 corresponds to the region with flow in the YZ plane and exhibits a gradual increase in GWT with a small gradient. Zone 2 was located near the drain end, where a sudden increase in the GWT occurred, corresponding to the transition region. The length of this region is approximately equal to the drain spacing (S) and has a steeper gradient than that of zone 1. Finally, zone 3 represents the curved GWT profile behind the HD field, where the flow is in the XZ plane.

In summary, we defined three distinct zones in the GWT profile based on our observations of flow direction and changes in the GWT gradient along the profile. These zones are labeled as zones 1, 2, and 3, as illustrated in Figure 4.

Establishing the GWT Profile When the saturated hydraulic conductivity of the soil was isotropic and homogeneous, we distinguished the GWT of the slope into two parts as formed as a result of hi and the relative recharge intensity (n) from the top surface (or infiltration) (Figure 4). n¼

Recharge from the top ðRÞ ðm=sÞ : Hydraulic conductivity of the soil ðks Þ ðm=sÞ

(5)

The heights of the GWT between zones 1 and 2 and between zones 2 and 3 are denoted as hc and he (m), respectively. Then, hc and he are divided into two parts obtained from hi and n, such that

Figure 5. The X and Y directional flow velocities (qx and qy, respectively) of slope I in the section at the quarter point between HDs (S ¼ 10 m, L ¼ 25 m).

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Figure 6. Empirical relationships for: (a) he0, (b) hc0, (c) her, and (d) hcr.

hc ¼ hc0 þ hcr ;

(6)

he ¼ he0 þ her ;

(7)

and

where hc0 (m) and hcr (m) denote the components of hc caused by hi and n, respectively; and he0 (m) and her (m) denote the components of he caused by hi and n, respectively. Based on the numerical model analysis results, we derived the following empirical linear relationships for he0, hc0, her, and hcr, as shown in Figure 6: he0 hi pffiffiffi ¼ 2:103 þ 0:034; B L S

(8)

hc0 hi pffiffiffi ¼ 0:930 þ 0:019; B LþS S

(9)

her pffiffiffi ¼ 0:090ðB LÞ 0:072; hm n

(10)

hcr pffiffiffi ¼ 0:032ðB L þ S Þ þ 0:368; hm n

(11)

and

where L is the length of the HD in the X direction (m), B is the length of hi at the upstream boundary of the slope from the HD starting point, and hm indicates the maximum GWT height obtained using the Hooghoudt (1940) method (Eq. 1) for parallel and infinitely long drains, where hi is the measured height of the GWT, located sufficiently away from the HD field.

The GWT profile in the mid-section between HDs can be predicted as follows.

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hc Zw ¼ X þ D; L S

Correction for Inclined HDs (12)

where Zw is the GWT profile (m), and D denotes the depth to the impermeable layer (m).

• Zone 2:

Zw ¼

he hc ðX L þ SÞ þ hc þ D; S

(13)

HDs are typically inclined to facilitate gravity drainage, resulting in a higher GWT profile than horizontally installed HDs. Therefore, we introduced a correction to the proposed method to account for the inclinations of the HDs. The correction involves adjusting the values of hc and he. First, the value of hi is corrected with reference to the elevations of the HD at the boundary of zones 1 and 2 and the drain end as follows (Figure 4):

and • Zone 3: Zone 3 may be characterized by two different methods, in local coordinates and global coordinates.

Local Coordinates (xz Space)—Figure 5 shows that the groundwater flow in zone 3 mainly occurs in the X direction, allowing the use of the Dupuit-Forchheimer assumption for horizontal flow. Using Darcy’s law and the Dupuit-Forchheimer assumption, the discharge (q, in m 2/s) per unit slope width across a section at point P, as shown in Figure 4, can be obtained as: Dz q ¼ ks z : (14) Dx The increment of the water flow, Dq, is equal to the recharge from the top: Dq ¼ DxR:

(15)

By integration and applying boundary conditions, q ¼ qi þ ðB L xÞR;

(16)

where qi is the water flow from behind the slope (m2/s).

Substituting Eq. 16 into Eq. 14, we obtain

qi þ ðB L xÞn dx ¼ zdz: ks

(17)

By integration and applying boundary conditions,

Hi2 He2 2 2 z ¼ He þ (18) þ ðB LÞn x nx2 ; B L where He ¼ he þ D (m), and Hi is the constant head at the upstream boundary of the model hi þ D (m).

Global Coordinates (XZ Space)—The z is converted to Zw in global coordinate system by replacing x with (X L)

2

200

(20)

hieh ¼ hi LtanðhÞ;

(21)

where h is the inclination angle of the HDs to the horizontal, and hich (m) and hieh (m) are the corrected hi values for calculating hc0 and he0, respectively. The values of L and S are measured in the horizontal direction. Note that the values of hcr and her remain unchanged because they are solely based on the recharge from the top.

Finally, the corrected hc and he values can be obtained as:

and

hc ¼ hc0 þ hcr þ ð L S ÞtanðhÞ;

(22)

he ¼ he0 þ her þ LtanðhÞ:

(23)

In this GWT prediction method, zones 1 and 2 provide empirical solutions, whereas zone 3 represents a theoretical GWT profile with an empirical boundary (he).

The accuracy of the proposed method for predicting the GWT at the mid-section between the HDs was validated through a comprehensive series of numerical case studies using the 3D FE model of slope II and a field study.

Average GWT Profile for Slopes with HDs The GWT profile variation between the HDs on the YZ plane for slope I having HDs with 10 m spacing and 30 m length is shown in Figure 7. The GWT profile between the drains conformed to the half-elliptical pattern proposed by Hooghoudt (1940) along the length of the drains. However, a uniform GWT profile was observed behind the HD field.

Hence, the average value of the GWT profile along the length of the HDs (zones 1 and 2), denoted as (Zw(avg)), as shown in Figure 8, can be used to characterize the GWT profile for further calculations of U, DU, and factor of safety (FS) enhancement (DFS), as well as incorporation into 2D numerical simulations (see Supplemental Material Appendix A).

PWP on Slip Surface

Hi2 He2 2 2 Zw ¼ H e þ þ ð B LÞ n ð X LÞ B L nð X LÞ :

and

hich ¼ hi ð L S ÞtanðhÞ;

(19)

The objective of HDs is to enhance the slope stability by reducing the PWP acting on the slip surface. Once Zw(avg) (m) is determined from the proposed method, the average

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Figure 7. Groundwater table profile between HDs on the YZ plane at different locations on the X axis (L ¼ 30 m, S ¼ 10 m, hi ¼ 6 m, and n ¼ 0.1 in slope I).

pore water force (U [kN/m]) acting on the unit width of a predefined slip surface (Zs [m]) can be calculated via linear integration between Zw(avg) and Zs (Figure 9). Following the method of slices, the slip surface is divided into a finite number of slices with linear bottoms. The pore water force on a slice (ui [kN/m]) can be obtained as 8 xi þDx > ð > > > < ZwðavgÞ Zs ðqw gÞdxðsecai Þ; For Zw > Zs ; ui ¼ > > > > : xi 0; For Zw # Zs (24) where qw is the density of water (kg/m3), g is the gravitational acceleration (m/s2), and ai is the angle of the bottom of the slice relative to the horizontal line. Then, the total average PWP on the slip is (kN/m2): U ¼

n X

½ui :

(25)

i¼1

Next, the reduction of average PWP on the slip surface (DU [kN/m2]) can be obtained as:

DU ¼ U0 U;

(26)

where U0 is the initial average PWP on the slip surface.

Constraints of the Proposed Method The constraints of the proposed GWT prediction method and concomitant design chart are as follows: • The slope is assumed to consist of isotropic and homogeneous soil.

• A horizontal impermeable layer is present at the bottom of the slope.

• A known groundwater level exists sufficiently away from the slope that can be used as the upstream constant head boundary. It is recommended to locate this boundary at least 15 m away from the HD field, which is the minimum distance considered in this study.

• An equivalent constant recharge rate must be defined for infiltration.

• There is a uniform distribution of water level in the Y direction. In the case of a non-uniform distribution, particularly hi, it is recommended to divide the slope into sections with uniform water level and apply the method to each section separately.

Figure 8. Average GWT profile between HDs in zones 1 and 2 for calculating U, DU, and DFS. These values were used in 2D analyses.

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Figure 9. Average GWT (Zw(avg)), slip surface (Zs), and calculation of FS of a slope by method of slices. m P

Design Procedure The proposed method involves multiple rigorous iterative calculation steps to determine the optimal length and spacing of HDs. To overcome the time-consuming nature of the design process, a Python-based (Python 3.6.2; Rossum and Drake, 2009) computer program was developed to automate the calculations. The step-by-step design procedure for HDs, based on the framework proposed in this study, is outlined in Figure B1 (Supplemental Material Appendix B).

VALIDATION OF THE PROPOSED METHOD This section presents the verification of the proposed GWT prediction method using a series of numerical case studies and a field study. Also, the accuracy of the calculation method for U and DU is discussed.

Validation of the Proposed GWT Prediction Method through Numerical Case Studies The proposed GWT prediction method was comprehensively verified under a wide range of conditions within the aforementioned limitations. Verification was performed on slope II, considering variations in the HD length, spacing, and installation angle, rainfall conditions, and initial GWT. The predicted GWT profile obtained using the proposed method was compared with the GWT profile at the mid-section of the 3D FE model. To prevent water ponding, a correction was introduced to the proposed method, particularly for the toe region. In addition to a visual comparison, a quantitative evaluation was conducted using the mean absolute error (MAE) between the predicted and 3D FE model GWTs. The MAE was calculated as follows: 202

MAE ¼

i¼1

ZwðPredictÞ Zwð3D FE ModelÞ m

;

(27)

where Zw(Predict) is the GWT profile predicted using the proposed method, Zw(3D FE Model) is the GWT at the midpoint between the HDs obtained from the 3D FE model, and m is the number of data points. Comparisons of the GWT profiles were made at 5 m intervals in the X direction. The MAE values were calculated for the entire length of the slope and separately for the HD field (zones 1 and 2) and behind the HDs (zone 3). The MAE values are summarized in Table 2.

Figure 10A shows a comparison of the predicted and 3D FE model GWT profiles for horizontally installed HDs with different lengths and spacings. The small MAE values indicate good agreement between the GWT profiles. Generally, zones 1 and 2 showed less agreement between the GWT profiles than zone 3, which can be attributed to the empirical linear idealization of the GWT in zones 1 and 2.

In contrast, the theoretical prediction of the GWT profile with an empirical boundary in zone 3 resulted in lower MAE values. Furthermore, the agreement between the GWT profiles deteriorated with an increase in the spacing and length of the HDs. When the HD length increased, the distance to the upstream boundary of the slope (distance to hi) decreased, leading to poor predictions. Therefore, it is crucial to establish the hi at a sufficient distance away from the expected length of the HDs to ensure accurate results.

Figure 10B compares the predicted and 3D FE model GWT profiles for horizontally installed HDs at different rainfall intensities (n). Higher rainfall intensities resulted in a lower agreement between the GWT profiles, and a slight overestimation in zone 2 was also observed. The lower conformity indicated by the lower R2 value (Figure 11) for the

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Figure 10. Validation of the proposed GWT prediction method by 3D FE model for: (a) different lengths and spacings (n ¼ 0.1) (slope II); (b) different rainfall intensities (S ¼ 5 m) (slope II); (c) different hi values (n ¼ 0.17) (slope II); and (d) inclined HDs (S ¼ 5 m and n ¼ 0.1) (slope II).

prediction of hcr can be identified as the reason for this behavior. However, it did not significantly affect the accuracy of the GWT prediction. Figure 10c and d confirms the accuracy of the proposed method in predicting the GWT under different initial GWT conditions and HD angles, respectively.

Figure 11 compares the hc and he values predicted by the proposed method with the values obtained from the 3D FE models. The low MAE and high R2 values suggest that the proposed method provides a good prediction of hc and hc.

Validation of Proposed GWT Prediction Method by Field Study The Ginigathhena landslide, located at bridge no. 48/2 at the Avissawella-Hatton-Nuwaraeliya Road in Sri Lanka, was selected for field validation of the proposed method. The details of the landslides were documented

by Lakruwan (2019) and Lakruwan and Kulathilaka (2020, 2021). The landslide mass consisted of thick colluvium and a residual soil layer underlain by highly

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Figure 11. Comparison of predicted (a) hc and (b) he values to the values obtained from the 3D FE model.

crystalline metamorphic rock. The initial slope failure occurred on June 22, 2014, followed by excavation at the toe for road widening and propagation to the upper slope during the rainy season. The landslide was mitigated by improvements in drainage and soil nailing.

The average homogeneous and isotropic hydraulic conductivity of the soil overburden was found to be 8 3 10 6 m/s, and the bedrock was considered to be impermeable (Lakruwan, 2019). The water levels of the two observation wells, W1 and W2, located 1.7 m and 42.38 m away from HD field, respectively, were monitored after the 20-m-long HDs with 5 m spacing were installed (Figure 12). Because the horizontal impermeable bottom layer only existed in that section, only the top slope section

demarcated by the dotted line rectangle in Figure 12 was considered for the validation of the proposed method. Two cases were selected for validation: Case 1, no rainfall from February 27 to March 21, 2018, and Case 2, 450 mm cumulative rainfall from May 18 to 23, 2018 (n ¼ 0.11). Since the water level of W2 was rather constant with time, it was selected as the Hi (B ¼ 62.38 m and Hi ¼ 15.00 m [Case 1]/15.58 m [Case 2]). The observed and predicted water levels of W1 in Case 1 (zero elevation at the top of the impermeable layer) were 2.67 and 2.77 m, respectively. The observed and predicted water levels of W1 in Case 2 were 3.61 and 4.06 m, respectively.

Therefore, despite a slight overestimation, the proposed method can accurately predict the water level.

Figure 12. Field validation of the proposed GWT prediction method for the Ginigathhena landslide.

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Figure 13. Validation of the proposed method to obtain (a) U and (b) DU (n ¼ 0.1) (slope I).

Validation of the Proposed Method for Obtaining U and DU

several conclusions on selecting appropriate lengths and spacing for HDs.

Slope I was used for the validation of the proposed method for obtaining U and DU. The average U (kN/m) from the 3D FE model was obtained by integrating the PWP values of the 51 stress points located on the FE mesh of the slip surface (Figure B2 in Supplemental Material Appendix B). Three point-rows were located, one on a section on the HD and one each on sections at the mid- and quarter-points between the HDs. Each row consisted of 19 points at 2.5 m spacings in the X direction.

The good agreement between the U values obtained from the 3D FE models and the proposed method (Eq. 24 and Eq. 25) for slope I (hi ¼ 6 m and n ¼ 0.1), as shown in Figure 13a, confirms its validity. Also, the plots of DU in Figure 13b confirm the accuracy of the proposed method in calculating DU. This comprehensive validation confirmed the accuracy of the proposed GWT prediction method for slopes with HDs under a wide range of conditions subjected to the aforementioned limitations. Moreover, it validates the prediction of U and DU in the presence of predefined slip surface. Therefore, the proposed method can be used as an efficient tool for designing HDs while overcoming the difficulties of complex 3D numerical simulations.

Effect of HD on PWP and Effective Stress on Slip Surface

RESULTS AND DISCUSSION This section presents examples of applications of the proposed method for the design of HDs and provides

A 3D FE stress-deformation analysis was performed on slope I using the strength reduction method to obtain the PWP on the slip surface and FS. Figure 14 shows the PWP distribution on the slip surface obtained from the 3D FE model of slope I with a drain spacing of 10 m. The PWP decreased with HD length, and no further reduction occurred beyond normalized drain length (L/Ls, where Ls is the length to the slip surface) of 2.0. The effective stress increased, as shown in Figure 15, while complying with the decrease in PWP, which eventually resulted in similar behavior in the FS enhancement.

Figures 13 provides further insights into the effects of the HD length. In Figure 13, both U and DU achieve uniform values for long HDs, and a further increase in the drain length becomes insignificant, which confirms the results of Cai et al. (1998), Cook et al. (2008), Lau and Kenney (1984), and Royster (1980). This phenomenon is explained in Figure B3 (Supplemental Material Appendix B). In short HDs, the failure wedge extends into all three zones of the GWT, and U becomes highly sensitive to the length of the HDs because the high GWT in zone 3 gradually moves away from the failure wedge. With an increase in HD length, zones 3 and 2 gradually move away from the failure wedge, eventually limiting the failure

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Figure 14. PWP distribution on the slip surface for different L values obtained from the 3D FE model analysis (S ¼ 10 m, Ls ¼ 10 m, D ¼ 10 m, B ¼ 50 m, hi ¼ 5 m, and n ¼ 0.1).

wedge to zone 1. In zone 1, U shows negligible sensitivity to drain length increments because the gradient of the GWT is very small.

Effect of n on U Figure 16 illustrates the effect of n, ranging from 0.01 to 0.2, on U for different drain lengths and spacing. The U values at n ¼ 0.01 and n ¼ 0.2 are denoted as U0.01 and U0.2, respectively. High GWTs in widely spaced HDs are highly sensitive to surface recharge, making n significantly affect U at large S values. This effect reduces as the GWT lowers in closely spaced HDs. Furthermore, the impact of n on U is significant in short HDs and decreases with increasing drain length, due to the shift in the slip surface location from zone 3 to zone 1, as discussed in the previous section.

206

Producing Design Charts A design chart can be used to efficiently select the length and spacing of HDs to achieve the desired DU or DFS values for a particular slope failure. The procedure for calculating DFS is outlined in Supplemental Material Appendix C. Given the heterogeneity of the failures, the design charts by Kenny et al. (1977) and Stani c (1984) were developed for unique slope conditions. Therefore, instead of producing generalized charts, we propose creating unique design charts for a given slope to select the drain length and spacing. The limitations on the chart used are outlined in the section “Constraints of the Proposed Method.”

Figure 17 shows the design charts, and variation in DU and DFS with drain spacing for different L/Ls, produced for slopes I and II. The non-compatibility of the design charts for slopes I and II shows that they are unique for a

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Figure 15. Distribution of the effective stress on the slip surface for different L values obtained from the 3D FE model analysis (S ¼ 10 m, Ls ¼ 10 m, D ¼ 10 m, B ¼ 50 m, hi ¼ 5 m, and n ¼ 0.1).

given slope, and a generalized design chart cannot be adopted.

A reduction in the sensitivity of the drain length for long HDs is also reflected in the design charts, where the design

charts indicate that the effect of drain spacing is more significant in short HDs, whereas it is not significant in long HDs. In long HDs (i.e., when the failure wedge is located in zone 1), increasing the spacing causes only a slight

Figure 16. Effect of n on U for different drain lengths in slope I (S ¼ 5 m, Ls ¼ 10 m, D ¼ 10 m, B ¼ 50 m, and hi ¼ 6 m).

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Figure 17. Design chart for the selection of drain spacing and lengths for: (a) slope I and (b) slope II.

increase in the GWT profile inside the failure wedge.

Therefore, only a small increment in U is observed when increasing the spacing in long HDs, which is also shown

by Abed et al. (2024).

A target value of DFS or DU can be achieved with a smaller HD length per unit slope width when large drain spacings are used (Figure 18). For example, to achieve DU of 9.9 kN/m2 (DFS 0.6) in slope I, 5.3 and 1.7 m pipe lengths per meter width of slope are required when the spacing is 1.0 and 5.0 m, respectively. Therefore, the use

of a larger drain spacing is more economical. However, two main issues arise with a wide drain spacing. One issue is the risk of non-functioning HDs for various reasons, such as clogging of the filter screen, mineral precipitation, and root growth inside the pipe (Martin et al., 1995; Lee, 2013). In the case of a non-functioning drain pipe, the drain spacing will be doubled, and DFS will be reduced to 0.54 and 0.35 for the initial drain spacing of 1.0 and 5.0 m, respectively. Therefore, a small spacing is more conservative in such situations. This issue can be eliminated using

Figure 18. Total HD length per slope width (m/m) to achieve target DU for: (a) slope I and (b) slope II.

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long HDs because the effect of spacing is not significant.

The next issue associated with widely spaced HDs is the requirement for a pipe with a higher discharge capacity.

Therefore, a trade-off exists between the pipe flow capacity and total pipe length, and the flow capacity of the drain pipe should also be considered in the selection of drain spacing.

CONCLUSIONS The following conclusions have been drawn from this study.

1. A novel semi-empirical method that can be used to obtain the GWT profile of a slope with HDs subjected to constant recharge from the surface is proposed in this study, along with a design framework for HD length and spacing. The accuracy of the proposed method was comprehensively validated through a series of numerical case studies for a wide range of conceivable conditions and monitoring data of an actual slope.

2. The proposed method was extended to determine the PWP force on a predefined slip surface via linear integration between Zw(avg) and Zs, which was subsequently verified through a numerical case study. The Zw(avg) can be used in 2D numerical models to replicate the 3D effects of the GWT. 3. A Python-based computer program was developed to automate multiple rigorous iterative calculation steps for determining the optimal length and spacing of the HDs. A unique design chart was produced for a specific slope using the developed computer program.

4. Design charts of slopes I and II were used to evaluate the effects of length and spacing of the HDs on the PWP reduction and FS increment of a slope. The HDs must only be extended to a length equal to the drain spacing beyond the slip surface. The length and spacing of the HDs required to achieve the target FS increase can be obtained from the design chart produced for a particular slope condition. Although lengthening the HDs is more effective than reducing the drain spacing, the risk of drain blockage and discharge capacity of the drain pipe must be considered when selecting the drain spacing.

SUPPLEMENTAL MATERIAL Supplemental Material associated with this article can be found online at https://www.aegweb.org/e-eg-supplements.

ACKNOWLEDGMENTS This research was supported by the Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (KAKENHI) grant (no. JP24K00974).

REFERENCES ABED, M.; PEETHAMBARAN, B.; AND LESHCHINSKY, B., 2024, Evaluating transient drawdown and slope stabilization from horizontal drain installation: Computers and Geotechnics, Vol. 167, p. 106044. https://doi.org/10.1016/j.compgeo.2023.106044 CAI, F.; UGAI, K.; WAKAI, A.; AND LI, Q., 1998, Effects of horizontal drains on slope stability under rainfall by three-dimensional finite element analysis: Computers and Geotechnics, Vol. 23, No. 4, pp.

255–275. https://doi.org/10.1016/S0266-352X(98)00021-4 CHEN, C. N. AND CHEN, H. Y., 2013, Distributions of pore water pressure surround a horizontal drain pipe on a retaining wall under steady state condition: Journal of Mechanics, Vol. 29, No. 2, pp.

263–272. https://doi.org/10.1017/jmech.2012.132 CONTE, E. AND TRONCONE, A., 2012, Stability analysis of infinite clayey slopes subjected to pore pressure changes: Géotechnique, Vol. 62, No. 1, pp. 87–91. https://doi.org/10.1680/geot.10.T.002 CONTE, E. AND TRONCONE, A., 2018, A performance-based method for the design of drainage trenches used to stabilize slopes: Engineering Geology, Vol. 239, pp. 158–166. https://doi.org/10.1016/j. enggeo.2018.03.017 COOK, D. I.; SANTI, P. M.; AND HIGGINS, J. D., 2008, Horizontal landslide drain design: State of the art and suggested improvements: Environmental and Engineering Geoscience, Vol. 14, No. 4, pp.

241–250. http://dx.doi.org/10.2113/gseegeosci.14.4.241 COOK, D. I.; SANTI, P. M.; AND HIGGINS, J. D., 2012, Prediction of piezometric surfaces and drain spacing for horizontal drain design: Landslides, Vol. 9, No. 4, pp. 547–556. https://doi.org/10.1007/ s10346-012-0337-5 CRENSHAW, B. A. AND SANTI, P. M., 2004, Water table profiles in the vicinity of horizontal drains: Environmental and Engineering Geoscience, Vol. 10, No. 3, pp. 191–201. https://doi.org/10.2113/10.3.191 DAS, T.; RAO, V. D.; AND CHOUDHURY, D., 2022, Numerical investigation of the stability of landslide-affected slopes in Kerala, India, under extreme rainfall event: Natural Hazards, Vol. 114, No. 1, pp. 751–785. https://doi.org/10.1007/s11069-022-05411-x ERNST, L., 1954, Het berekenen van stationaries groundwater storming walked in verticals flak afgebeeld kunen worden (The Computation of Steady State Groundwater Flows, Which Can Be Projected in the Vertical Plane): Institute of The Netherlands Organization for Applied Scientific Research, Groningen, Netherlands.

FASANO, G.; DE SARNO, D.; BILOTTA, E.; AND FLORA, A., 2019, Design of horizontal drains for the mitigation of liquefaction risk: Soils and Foundations, Vol. 59, No. 5, pp. 1537–1551. https://doi.org/ 10.1016/j.sandf.2019.07.004 FASANO, G.; NAPPA, V.; OZCEBE, A. G.; AND BILOTTA, E., 2021, Numerical modelling of the effect of horizontal drains in centrifuge tests on soil structure interaction in liquefiable soils: Bulletin of Earthquake Engineering, Vol. 19, pp. 3895–3931. https://doi.org/10.1007/s10518-02101084-2 FENG, J.; PENGPENG, N.; ZHENG, C.; GUOXIONG, M.; AND MEIJUAN, X., 2020, Positioning design of horizontal drain in sandwiched clay-drain systems for land reclamation: Computers and Geotechnics, Vol. 127, p. 103777. https://doi.org/10.1016/j.compgeo.2020.103777 FORRESTER, K., 2001, Subsurface Drainage for Slope Stabilization: ASCE Press, Reston, VA, 208 p. https://doi.org/10.1061/9780784400166 Geotechnical Engineering Office, 2017, Geoguide 7—Guide to Soil Nail Design and Construction: Civil Engineering and Development Department, The Government of the Hong Kong Special Administrative Region, Hong Kong, 97 p.

GHIASSIAN, H. AND GHAREH, S., 2008, Stability of sandy slopes under seepage conditions: Landslides, Vol. 5, No. 4, pp. 397–406. https:// doi.org/10.1007/s10346-008-0132-5 GREG, M. P.; ROSEMARY, W. C.; DONALD, M. R.; RISHI, P.; BALASINGAM, M.; SUTHARSAN, T.; TOM, B.; STEVE, L.; AND KIM, A. W., 2013,

Environmental & Engineering Geoscience, Vol. XXX, No. 4, November 2024, pp. 193–210

209

Lakruwan, Kamura, and Kazama Design Guidelines for Horizontal Drains Used for Slope Stabilization: Washington State Department of Transportation, Olympia, WA, 377 p.

HINDS, E. S.; LU, N.; MIRUS, B. B.; GODT, J. W.; AND WAYLLACE, A., 2021, Evaluation of techniques for mitigating snowmelt infiltration-induced landsliding in a highway embankment: Engineering Geology, Vol. 291, p. 106240. https://doi.org/10.1016/j.enggeo.2021.106240 HOOGHOUDT, S., 1940, Bijdrage tot de kennis van enige natuurkundige grootheden van der grond: Verslag bouwk Onderzoek, Vol. 46, No. 14 B, pp. 515–707.

KENNY, T. C.; CHOI, W. S.; AND PAZIN, M., 1977, Design of horizontal drains for soil slopes: Journal of the Geotechnical Engineering Division (ASCE), Vol. 103, No. 11, pp. 1311–1323. https://doi. org/10.1061/AJGEB6.0000522 KIRKHAM, D., 1958, Seepage of steady rainfall through soil into drains: Transactions American Geophysical Union, Vol. 39, No. 5, pp.

892–908. https://doi.org/10.1029/TR039i005p00892 LAKRUWAN, S. O. A. D. M., 2019, Enhancement of the Stability at the Site of an Ancient Landslide in a Road Cutting with Drainage and Reinforcement—Case History at Ginigathhena: M.Sc. dissertation, Department of Civil Engineering, University of Moratuwa, Moratuwa, Sri Lanka, 126 p.

LAKRUWAN, M.; KAMURA, A.; AND KAZAMA, M., 2022, Effect of 3D water table profile of horizontal drains on slope stability and idealization of 3D-FEM flow modeling to 2D-FEM flow modeling. In Feng, H. Y.; Ling, L. Y.; Siong, W. K.; Lee, L. M.; Hon, L. K.; Hung, L. S.; and Han, L. M. (Editors), 2nd International Conference on Civil and Environmental Engineering (ICCEE2022), E3S Web of Conferences, 347: EDP Sciences, Castanet-Tolosan, France, p.

03002. http://doi.org/10.1051/e3sconf/202234703002 LAKRUWAN, M. AND KULATHILAKA, S. A. S., 2020, Economizing soil nailing design by drainage improvement—Case history at Ginigathhena.

In Vilímek, V.; Wang, F.; Strom, A.; Sassa, K.; Bobrowsky, P. T.; and Takara, K. (Editors), Understanding and Reducing Landslide Disaster Risk, Vol. 5: Springer, Cham, Switzerland, pp. 331–339. http:// doi.org/10.1007/978-3-030-60319-9_37 LAKRUWAN, M. AND KULATHILAKA, S. A. S., 2021, Evaluation of the performance of landslide mitigation measures at Ginigathhena.

In Ranathunga, A.; Karunawardena, A.; Kulathilaka, A.; Kurukulasuriya, C.; Sampath, K. H. S. M.; Nasvi, M. C.M.; De Silva, N.; Nasvi, M.; Alagiyawanna, N.; Priyankara, N. H.; Rathnaweera, P.; Thilakasiri, S.; Navaratnarajah, S. K.; and Nawagamuwa, U. (Editors), International Conference on Geotechnical Engineering ICGE Colombo 2020: Sri Lankan Geotechnical Society, Colombo, Sri Lanka, pp. 459–464.

LAKRUWAN, M.; OIKAWA, H.; KAMURA, A.; AND KAZAMA, M., 2021, Experimental evaluation of effect of perforation arrangement on performance of horizontal drains in landslide mitigation: Landslides, Vol. 18, No. 11, pp. 3707–3714. http://doi.org/10.1007/ s10346-021-01724-3 LAU, K. C. AND KENNEY, T. C., 1984, Horizontal drains to stabilize clay slopes: Canadian Geotechnical Journal, Vol. 21, No. 2, pp. 241–249. https://doi.org/10.1139/t84-027

210

LEE, T. S., 2013, Horizontal drains—State of practice the past seven decades in the US. In Meehan, C.; Pradel, D.; Pando, M.A.; and Labuz, J. F. (Editors), Geo-Congress 2013: Stability and Performance of Slopes and Embankments III. ASCE, New York, pp.

1759–1773. https://doi.org/10.1061/9780784412787.176 LERNIA, A. D.; COTECCHIA, F.; ELIA, G.; TAGARELLI, V.; SANTALOIA, F.; AND PALLADINO, G., 2022, Assessing the influence of the hydraulic boundary conditions on clay slope stability: The Fontana Monte case study: Engineering Geology, Vol. 297, p. 106509. https://doi. org/10.1016/j.enggeo.2021.106509 LUTHIN, J. N., 1966, Drainage Engineering: John Wiley & Sons, Inc., New York, 250 p.

MARTIN, R.; SIU, K.; AND PREMCHITT, J., 1995, Performance of Horizontal Drains in Hong Kong: Hong Kong: Geotechnical Engineering Office (GEO) Report No. 42, The Government of the Hong Kong Special Administrative Region, Hong Kong, 108 p.

NONVEILLER, E., 1981, Efficiency of horizontal drains on slope stability. In Proceedings of the 10th International Conference on Soil Mechanics and Foundation Engineering, 15–19 June, Stockholm, Sweden: A.A. Balkema, Rotterdam, Netherlands, pp. 495–499.

PLAXIS, 2020, PLAXIS 3D Reference Manual CONNECT Edition V20: Bentley, Exton, PA. RAHARDJO, H.; HRITZUK, J. J.; LEONG, E. C.; AND REZAUR, R. B., 2003, Effectiveness of horizontal drains for slope stability: Engineering Geology, Vol. 69, No. 3–4, pp. 295–308. https://doi.org/10.1016/ S0013-7952(02)00288-0 RAHARDJO, H.; SANTOSO, V. A.; LEONG, E. C.; NG, Y. S.; AND HUA, C. J., 2011, Performance of horizontal drains in residual soil slopes: Soils and Foundations, Vol. 51, No. 3, pp. 437–447. https://doi.org/ 10.3208/sandf.51.437 RESNICK, G. S. AND ZNIDARČIĆ, D., 1990, Centrifugal modeling of drains for slope stabilization: Journal of Geotechnical Engineering, Vol. 116, No. 11, pp. 1607–1624. https://doi.org/10.1061/(ASCE)07339410(1990)116:11(1607) ROSSUM, V. G. AND DRAKE, F. L., 2009, Python 3 Reference Manual: CreateSpace, Scotts Valley, CA. ROYSTER, D. L., 1980, Horizontal drains and horizontal drilling: An overview: Transportation Research Record, Vol. 783, pp. 16–20.

SHRESTHA, H. K.; YATABE, R.; AND BHANDARY, N. P., 2008, Groundwater flow modeling for effective implementation of landslide stability enhancement measures: Landslides, Vol. 5, No. 3, pp. 281–290. https://doi.org/10.1007/s10346-008-0121-8 STANIĆ, B., 1984, Influence of drainage trenches on slope stability: Journal of Geotechnical Engineering, Vol. 110, No. 11, pp. 1624–1636. https://doi.org/10.1061/(ASCE)0733-9410(1984)110:11(1624) STUYT, L. C. P. M.; DIERICKX, W.; AND BELTRAN, J. M., 2005, Materials for Subsurface Land Drainage Systems: Food and Agricultural Organization of the United Nations, Rome, Italy, 183 p.

TSAO, T. M.; WANG, M. K.; CHEN, M. C.; TAKEUCHI, Y.; MATSUURA, S.; AND OCHIAI, H., 2005, A case study of the pore water pressure fluctuation on the slip surface using horizontal borehole works on drainage well: Engineering Geology, Vol. 78, pp. 105–118. https://doi. org/10.1016/j.enggeo.2004.11.002

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Using the Total Apparent Spacing Approach to Optimize Foundation Drain Orientations WILLIAM M. ROMAN1* Chief Geologist, Gannett Fleming, Inc., Camp Hill PA

JOHN N. BEREZNIAK2 2277 Sagamore Drive, State College, PA 16803

Key Terms: Concrete Dams, Foundation Drains, Discontinuities, Optimum Drilling Direction, Uplift, Design ABSTRACT Design of foundation drain holes in bedrock where fractures control the permeability may be optimized based on the discontinuity pattern, specifically the spacing and orientation of the predominant discontinuity sets. When suitable representative outcrops are available, either naturally or by means of excavation, joint spacing and orientation can be measured directly by traditional methods using a measuring tape and compass or pocket transit or newer methods using computer software to measure virtual joint surfaces within a digital terrain model developed from digital photogrammetry or light detection and ranging (LiDAR) surveys. When suitable outcrops are not available, joint spacing and orientation can be measured using oriented core drilling techniques or downhole imaging tools (e.g., optical and acoustic sondes) that provide digital images of the borehole wall. With an understanding of the bedrock jointing pattern obtained from one or more of the above methods, the total apparent spacing (TAS) approach can be used to optimize the orientation of drain holes. The TAS approach employs the vector dot product formula to minimize the total apparent spacing between discontinuities and maximize the number of discontinuities intercepted by the drain hole. The TAS approach was used to optimize the orientation of foundation drain holes during rehabilitation of the Gilboa Dam in Schoharie County, NY. The TAS approach has other applications, e.g., optimizing the orientation of exploratory core holes to collect discontinuity data or the orientation of grout holes for foundation grouting.

1

Retired; present address: 1080 State Park Rd, Newport, PA 17074 Previously at: U.S. Army Corps of Engineers Headquarters, Washington, DC, Senior Civil Engineer (retired) *Corresponding author email: bill.roman.bretz@gmail.com 2

INTRODUCTION Uplift pressure is critical to both the sliding and overturning stability of concrete dams founded directly on rock.

The uplift pressure beneath such a dam is a function of the hydraulic gradient, which is assumed to vary linearly from headwater at the heel of the dam to zero or tailwater at the toe of the dam (Figure 1a), assuming a homogeneous and isotropic condition where hydraulic conductivity does not change significantly over the dam site, which is not often the case in the real world. In the case where hydraulic conductivity does change, the relationship between uplift pressure and headwater and tailwater pressure is non-linear.

Studies done by Grenoble et al. (1995) showed that rising reservoir levels can differentially deform discontinuities in the foundation and cause the hydraulic conductivity to increase at the heel of the dam and decrease at the toe (tapered joint). A non-linear response may produce an uplift pressure distribution that is greater than the conventional linear assumption for uplift (Ebeling and Pace, 1996a). Non-linear responses of uplift pressures to reservoir level have been analytically modeled (Ebeling and Pace, 1996b) and physically observed in several dams (Stone and Webster Engineering Corporation, 1992). The expansion and contraction of downstream faces due to seasonal ambient temperature changes may cause greater changes in uplift pressure than changes in headwater levels (Stone and Webster Engineering Corporation, 1992).

Installation of drains beneath the dam can alter the hydraulic gradient and help to reduce the uplift pressure (Figure 1b). Drains are considered to be the most reliable and cost-effective way of reducing foundation uplift pressures, especially for structures founded on rock (USACE, 2005). The effectiveness of the drainage system depends on the depth, size, and spacing of the drains; the character of the foundation; and the facility with which the drains can be maintained.

The hydraulic conductivity of a jointed rock mass is commonly controlled by its secondary permeability, so in many civil engineering applications, bedrock discontinuities dominate the drain design procedures. Assuming other discontinuity characteristics such as aperture, length, and filling are relatively uniform, foundation drain holes drilled at the

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Figure 1. Schematics showing theoretical uplift distribution beneath a concrete dam (A) having no drains and (B) with foundation drains. Modified from U.S. Army Corps of Engineers (2005, Figure C-4).

optimum orientation and inclination with respect to the orientation and spacing of the predominant discontinuities should relieve uplift pressure most efficiently. However, it should be noted that the severity of uplift pressure may be independent of discontinuity orientation (Grenoble and Amadei, 1990) as discontinuity aperture and filling may control uplift pressures more than discontinuity orientation (Murphy et al., 2002).

When other discontinuity parameters are not relatively uniform and result in an anisotropic distribution of foundation hydrostatic pressures, optimization of drain hole orientations based solely on the orientation and spacing of the predominant discontinuities is not appropriate.

Anisotropic hydrostatic pressures may occur in foundations where multiple episodes of structural deformation due to plate convergence or rifting have produced discontinuity sets having significantly varying discontinuity parameters.

Variations in stress regimes may affect discontinuity aperture and length, and preferential flow of fluids during structural deformation may result in precipitation of minerals that completely fill certain discontinuity sets. Drilling foundation drain holes at the optimum orientation and inclination with respect to the orientation and spacing of the predominant discontinuities is appropriate only when discontinuity parameters are relatively uniform, a case more likely to exist within bedrock foundations that have experienced only minor structural deformation. Site reconnaissance and subsurface investigation should seek to identify and characterize those discontinuities that affect the hydraulic pressures in the foundation, which could include less prevalent discontinuities and, in some cases, even one single discontinuity.

Several authors have addressed aspects of drain hole design. Cook et al. (2007) discussed the state of the art and presented suggestions for improvement in the design 212

of landslide horizontal drains. Two approaches for optimizing borehole orientation have been presented in Environmental & Engineering Geoscience. Zhou and Maerz (2002) developed an approach to find the optimum drilling direction for maximizing a borehole’s interception of discontinuity sets. The basic concept involves finding a drilling direction that minimizes the linear sampling bias index (LSBI), which is a function of the relative angle between the orientation of the borehole and the mean orientation of the poles of each of the discontinuity sets. The optimum drilling direction is the direction along which the LSBI is minimized. Haneberg (2009) observed that while the LSBI minimization approach produces correct results, it suffers from multiple shortcomings that inhibit its utility. Haneberg (2009) presented an approach that builds upon the approach taken by Zhou and Maerz (2002) by incorporating changes to make it potentially more useful and geometrically meaningful. Haneberg (2009) described this approach to optimize a borehole’s orientation by minimizing the linear sampling angular deviation and provided examples produced using a series of functions written for the computer program Mathematica (Haneberg, 2004).

This paper describes how the total apparent spacing (TAS) approach optimizes drain hole orientation using a minimization process based on discontinuity spacing and orientation. The TAS approach seeks to minimize the total apparent spacing of discontinuities along the drain hole and to maximize the number of discontinuities encountered by the drain hole. Beyond the foundation drain hole orientation example provided herein, use of the TAS approach to strategically orient a drill hole so as to intersect the maximum number of discontinuities along the drill hole for a given drilling length may be useful for other purposes within

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the realms of geotechnical exploration, rock engineering, and foundation treatment.

BEDROCK JOINTING Origins and Patterns Fractures occur in response to stresses that exceed the strength of the rock to resist the resulting force. Fractureproducing stresses may be tensile, compressive, shear, or a combination of stress types. Stresses may vary in strength and orientation over time and space, so fractures may occur in multiple sets having varying orientations and characteristics within a region. Once formed, fractures can be modified as a result of tectonic and thermal stress and strain, changes in fluid pressure, and physical, chemical, and biological processes such as erosion and valley stress relief, dissolution or precipitation of minerals, and degradation by roots (NASEM, 2020).

Planar bedrock discontinuities, which may not necessarily be flat, often occur in sets of discontinuities having semi-parallel orientations or falling within a range of similar orientations. Horizontal to gently dipping sedimentary rocks with limited tectonic stresses often feature two nearly orthogonal joint sets that are both roughly perpendicular to a set of bedding joints developed along bedding planes. One joint set is composed of “strike joints,” which generally strike in about the same direction as bedding strike, while the other set is composed of “dip joints,” which generally strike roughly parallel to the bedding dip direction. Additional discontinuity sets are often present in sedimentary rocks subjected to higher tectonic or other external stresses. A similar blocky jointing pattern may occur in igneous rocks having flow banding. “Flat-lying joints” are approximately horizontal and strike parallel to the flow lines indicated by the preferred orientation of the long axes of the rock crystals. A second joint set is composed of “Q joints” or “cross joints” that strike nearly perpendicular to the flow lines. A third set is composed of “S joints” or “longitudinal joints” that dip steeply and strike parallel to the flow lines (Krynine and Judd, 1957). In igneous rock masses lacking flow banding, local and regional stress and strain distributions tend to define the fracture pattern. “Tensile joints” form generally parallel to the maximum stress trajectory, and “shear joints” form at an angle of roughly 20 to 35 degrees to the maximum stress trajectory (NASEM, 2020).

Survey Methods The pattern of discontinuities within a rock mass, specifically the typical orientation and spacing of discontinuities, must be determined in order to use the TAS approach. The orientation of relatively planar discontinuities can be expressed by an azimuth (either strike or dip direction) and

a dip angle. Discontinuity spacing and orientation data can be collected using one or more of several available survey methods. Properly conducted surveys can furnish data with a high probability of accurately representing the typical orientation and spacing of the discontinuities within a rock mass.

When suitable representative outcrops are available, either naturally or by means of excavation, discontinuity spacing and orientation can be measured directly by traditional methods (e.g., linear scan line or window sampling) using one or more tools such as a measuring tape and a compass, pocket transit, smart phone, or tablet. Corrections for observation bias have been developed for scan-line sampling (Terzaghi, 1965) and for borehole sampling, which may be considered as a subsurface scan line (Mauldon and Mauldon, 1997). Observational bias may be removed by orienting scan lines perpendicular to one another and by recording the trace length, orientation, and point of intersection of every discontinuity along the scan lines (La Pointe and Hudson, 1985). For window sampling, the window should be as large as possible to minimize sampling bias. Ideally, at least two windows of similar size should be established on adjacent rock exposures having different (preferably orthogonal) orientations (Priest, 1993). Window sampling reduces the observation bias due to the discontinuity orientation and length associated with scan-line sampling; however, bias may remain as a result of curtailment of the discontinuities due to outcrop cover.

Newer methods use computer software to measure virtual discontinuity surfaces within a digital terrain model of the rock outcrop developed by means of digital photogrammetry or light detection and ranging (LiDAR) surveys (Haneberg et al., 2006; Tonon and Kottenstette, 2007; Haneberg, 2008; Kemeny and Turner, 2008; Kottenstette and Shaffner, 2008; Shaffner et al., 2009; Kemeny et al., 2011; and Watts, 2011). Using both digital photogrammetry and LiDAR imaging may be useful in some circumstances (Otoo et al., 2011). Although useful for measuring locations and orientations of discontinuities, photogrammetry may not provide critical geological information that can be gleaned only by human examination of the discontinuities (Gates and Haneberg, 2012; Battulwar et al., 2021). Traditional field characterization and input from experienced professionals may enhance the reliability of laser scanning (Farny, 2017).

When suitable outcrops are not available, discontinuity spacing and orientation can be measured using oriented core drilling techniques or downhole imaging tools (e.g., optical and acoustic sondes) that provide digital images of the borehole wall. Provided borehole instability does not preclude the use and retrieval of the imaging sonde, borehole imaging serves as a powerful tool for measuring fracture orientations and spacings, better characterizing zones of broken core, and unraveling the mysteries of core losses.

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The survey methods used should provide an understanding of the variability in orientations and dip angles of the discontinuities. This understanding is very important in ultimately selecting the typical discontinuity orientation and dip angle. Larger variability in the data will make the selection of the typical discontinuity parameters even more important. Moreover, discontinuity data should be collected as close to the site as possible. Discontinuity data from an off-site location should be compared to available information from the site to determine its applicability.

THEORY Assumptions The TAS approach for identifying the optimum foundation drain hole orientation is based on the following general assumptions: 1. Jointing is the primary pathway of water flow and pressure through the rock mass forming the dam foundation.

2. Surveys are properly conducted and accurately represent the typical discontinuity spacing and orientation of the predominant discontinuity sets within the dam foundation.

3. The spacing between individual discontinuities within a set is generally uniform throughout the dam foundation; consequently, the average discontinuity spacing of each set can be used.

4. The orientations of discontinuities within a set are generally uniform throughout the dam foundation; consequently, the average discontinuity orientation of each set can be used.

5. The discontinuity sets are persistent throughout the dam foundation.

6. A drain hole direction trending parallel to the plane representing the average orientation of a discontinuity set has an infinite apparent spacing and is excluded as an optimum foundation drain hole direction.

7. The discontinuity sets are relatively uniform in aperture, length, and filling. The TAS approach may be modified by adding weighting factors when this is not the case.

If discontinuity spacing, orientation, and persistence are significantly non-uniform, then consideration should be given to subdividing the foundation into regions or areas of similar discontinuity properties and performing separate evaluations.

Concept For a drain hole to drain water most effectively from a jointed rock mass, the drain hole must be oriented so that it intercepts the discontinuity network most frequently; i.e., the highest number of discontinuities is intercepted per unit length of drill hole. Since the discontinuity network 214

consists of a certain number of predominant discontinuity sets, a drain hole will intercept each predominant discontinuity set of the discontinuity network at a certain average distance along the length of the drain hole. Optimizing the drain hole orientation thus requires a minimization of the average distances between joint sets intercepted by the drain hole. The dot product formula provides a means to accomplish this minimization.

The designated predominant discontinuity sets should be those that significantly contribute to pressure in the foundation of the structure. When the characterization of foundation conditions determines that multiple discontinuity sets contribute to pressure in the foundation, but that their contributions vary significantly, consideration should be given to assigning weighting factors to the predominant discontinuity sets or to subdividing the foundation into regions or areas of similar discontinuity properties and performing separate evaluations.

Formulas Although discussed in terms of “joints” and “joint sets,” the formulas below are applicable to the broader category of structural breaks encompassed by the terms “discontinuity” and “discontinuity sets.”

The dot product (or scalar product) of two threedimensional Cartesian vectors *

*

a ¼ ðax ; ay ; az Þ and b ¼ ðbx ; by ; bz Þ is defined as: *

*

a b ¼ ax bx þ ay by þ az bz :

(1)

It can be proven (Stewart, 2003, p. 844) that Eq. 1 is equivalent to *

*

*

*

a b ¼ ja jjb jcosh ¼ abcosh; *

(2)

*

where ja j a and jb j b denote the magnitudes of vectors *

*

*

*

a and b , and h is the angle between a and b . * Let n be the normal vector (pole) of a plane P that represents the average joint orientation in a joint set. Let the * * magnitude of n (denoted jn j n) represent the orthogonal * (true) average spacing of the joints within the set. Let r be an arbitrary vector representing the proposed drain hole orientation starting at the origin and connecting the * origin to an arbitrary point on plane P. The magnitude of r * (denoted jr j r) represents the apparent average spacing of the joints within the set along the drain hole (Figure 2). * Let r 0 be a vector within plane P connecting the tip * * * of n with the tip of r as shown in Figure 2. Vector r 0 is * * thus equal to the difference of r and n :

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*

^ r n ¼ ðrr^ Þ ðnnÞ ^ ¼ rnr^ n:

(7)

Setting the two solved equalities for the dot product * * of r and n equal to each other yields: ^ ¼ n2 : rnr^ n

(8)

Because the dot product of two vectors is a scalar, Eq. ^ 8 can be divided by nr^ n: ^ Þ: r ¼ n=ðr^ n

Figure 2. Schematic drawing illustrating the vector representing the * pole to the joint set (n ), the vector representing the proposed drain * ! hole orientation ( r ), and the vector connecting them (r 0 ) within the plane representing the average joint orientation (P). *

*

*

r 0 ¼ r n;

(3)

*

*

*

or, equivalently, r is equal to the sum of n and r 0 : *

*

*

r ¼ n þ r 0:

(4)

! * * Replacing a and b with r 0 and n in Eq. 2 shows that * * the dot product of these vectors is zero since r 0 ? n , and therefore the included angle is a right angle: *

*

*

*

*

r 0 n ¼ jr 0 jjn jcosh ¼ r0 ncos90 ¼ 0: *

(5)

*

Taking the dot product of r and n and substituting in the equalities of Eq. 3 and Eq. 4, using the distributive property * * of the dot product, and knowing that r 0 n ¼ 0, yields: *

*

*

*

*

*

*

*

*

*

*

¼ n2 þ r 0 n *

¼ n2 þ 0 ¼ n2 :

(10)

^ 1 and r^ into Eq. Substituting the product of vectors n 9 and defining this quantity as d1 yields: d1 r ¼ n1 =ðsinu1 cosh1 sinu cosh þ sinu1 sinh1 sinu sinh þ cosu1 cosuÞ:

(11)

Hence, d1 is the apparent joint spacing for Joint Set 1 when drilling with azimuth h and plunge u.

Equation 11 approximates the apparent spacing of discontinuities belonging to Joint Set 1 along a theoretical drain hole. Similar equations can be written to solve for the apparent spacing of other recognized joint sets along a theoretical drain hole. The total apparent spacing approach minimizes the sum of the apparent spacings of all selected joint sets along a theoretical drain hole, which is given by: k X

ni =sinui coshi sinu cosh

þ sinui sinhi sinu sinh þ cosui cosu;

*

¼ n n þ ðr n Þ n *

^ 1 r^ ¼ sinu1 cosh1 sinu cosh n þ sinu1 sinh1 sinu sinh þ cosu1 cosu:

i¼1

¼ ðn þ ðr n ÞÞ n *

^ 1 represent the average pole to Joint Set 1 and r^ Let n represent the proposed drain hole orientation. In spher^ 1 ¼ ð1; h1 ; u1 Þ ical coordinates, the unit vectors are n and r^ ¼ ð1; h; uÞ. Converting to Cartesian coordi^ 1 ¼ ðsinu1 cosh1 ; sinu1 sinh1 ; cosu1 Þ nates produces n and r^ ¼ ðsinucosh; sinusinh; cosuÞ. ^ 1 and Using Eq. 1 to take the dot product of vectors n r^ yields:

*

r n ¼ ðn þ r 0 Þ n

(9)

(6)

Using the conventional unit vector notation of * * ^ ¼ a=jaj ¼ a=a, the dot product of r and n can also a be written as:

(12)

where k ¼ number of selected joint sets, ni ¼ true joint spacing of the ith joint set, ui ¼ joint dip angle of the ith joint set, hi ¼ joint dip direction of the ith joint set, u ¼ drain hole inclination, and h ¼ drain hole azimuth.

It should be noted that the angular measurements in Eq. 12 reference spherical coordinates as used in

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mathematics, so h and hi refer to the angular measurement from the x axis in a counterclockwise direction within the X-Y plane (with east ¼ 0 degrees), and u and ui refer to the angular measurement from the z axis (with zero degrees representing vertically upward and 180 degrees representing vertically downward). If joint dip direction and drain hole azimuth are measured in compass bearings (0 to 360 degrees with north ¼ 0 degrees), then the compass bearing should be subtracted from 90 degrees to convert to h and hi . If joint dip angle and drain hole inclination are measured from the horizontal plane (with 90 degrees representing vertically upward and 90 degrees representing vertically downward), then the angle should be subtracted from 90 degrees to convert to u and ui .

Application Equation 12 provides a formula to minimize the sum of the apparent spacings of all selected joint sets along a theoretical drain hole, which is the purpose of the TAS approach. Application of the TAS approach will typically involve the following activities: 1. Perform the research and site investigations needed to characterize the discontinuities within the rock mass forming the dam foundation and to group the discontinuities into sets.

2. Identify the discontinuities or sets of discontinuities that significantly influence uplift.

3. Assess the TAS approach assumptions to determine whether the TAS approach is applicable.

4. If the variation in the parameters of the selected discontinuity sets indicates the TAS approach is not applicable, then consider subdividing the foundation into zones for separate evaluations and/or assigning weighting factors to the selected discontinuity sets.

5. Determine the best-fit orientations of the selected discontinuity sets.

6. Determine the range of favorable drain hole orientations.

7. For each possible favorable drain hole orientation, use Eq. 11 to calculate the apparent spacing of each joint set and sum the apparent joint spacings along the drain hole per Eq. 12. A computer spreadsheet will facilitate these calculations.

8. Use the calculated results to identify the optimum drain hole orientation.

The level of effort devoted to applying the TAS approach should be commensurate with the relative importance of the drain design in the overall dam design or stability analysis.

For example, if reduction in uplift pressure by foundation drains is not being factored into the stability analysis (a conservative approach), then a less rigorous application of the TAS approach may be warranted. Rehabilitation of Gilboa Dam provides an example of the application of the TAS approach.

216

Figure 3. Topographic map showing location of Gilboa Dam in Schoharie County, NY.

GILBOA DAM EXAMPLE During the rehabilitation of Gilboa Dam in New York State, the TAS approach was used to optimize drain hole orientation.

Gilboa Dam Gilboa Dam is located in the Catskill Mountains in southern Schoharie County, NY (Figure 3). The dam is situated approximately 125 mi (200 km) north-northwest of Manhattan and 37 mi (60 km) southwest of Albany, NY. Gilboa Dam impounds Schoharie Reservoir, which is operated by the New York City Department of Environmental Protection, and which is a key component of the city’s water supply system. Schoharie Reservoir has a normal storage volume of approximately 20.8 billion gallons (7.88 3 107 m3) and covers 1,159 acres (469 hectares) at normal pool. The reservoir has a watershed area of approximately 314 mi2 (813 km2).

The eastern portion of Gilboa Dam consists of a 160-fthigh (48.8 m), 1,324-ft-long (404 m) concrete spillway founded on rock and having a crest elevation of 1,130 ft (344.4 m). Due to the presence of a deep, pre-glacial channel

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Figure 4. Aerial view of Gilboa Dam showing the concrete spillway (CS), earth embankment (EE), and downstream retaining wall (RW).

Figure 5. Sandstone beds undercut by less resistant beds on east side of Schoharie Creek gorge downstream of Gilboa Dam.

in the bedrock, the western portion of Gilboa Dam consists of a 180-ft-high (54.9 m), 700-ft-long (213 m) earth embankment with a crest elevation of 1,150 ft (351.5 m). A retaining wall extends downstream from the junction of the concrete spillway and earth embankment (Figure 4).

Construction of Gilboa Dam began in 1919 and was completed in 1927. A major rehabilitation of Gilboa Dam began in 2006 and was completed in 2014. The rehabilitation included installation of 80 post-tensioned rock anchors in the spillway, placement of 57,000 yd3 (43,580 m3) of concrete buttress on the downstream side of the concrete dam, a new reinforced concrete lining in the spillway channel and plunge pool, installation of a new 9-ft-diameter (2.7 m) low-level outlet, and addition of a gallery with foundation drains. In 2015, the project was named the Association of State Dam Safety Officials National Dam Rehabilitation Project of the Year.

fossil forest (Stein et al., 2012). The area was glaciated, and Glacial Lake Grand Gorge and Glacial Lake Schoharie occupied the Schoharie Valley during the Wisconsinan stage (Rich, 1935; Titus, 2003).

Core borings at Gilboa Dam penetrated a sandstonedominated portion of the Moscow Formation. Bridge and Willis (1994, pp. 1441–1443) described the Gilboa Dam section as two 35-m-thick sandstone-dominated sequences separated by a 5-mr-thick mudstone-rich interval with sediments of the two sandstone bodies showing mainly wave and tidal current influence lower down and offshore-directed current influence higher up, which reflects deposition in water becoming increasingly shallow and closer to land.

In addition to sandstone, dam rehabilitation core borings encountered minor beds of calcareous siltstone, shale, and mudstone, some of which are visible in outcrops below the dam (Figures 5, 6, and 7). Analyses of several finer-grained marker beds using the three-point method indicated the overall bedrock strike is N80°W, and the overall dip is 1.5 degrees to the south-southwest.

Site Geology Bedrock in the vicinity of Gilboa Dam is part of the Catskill clastic wedge and consists generally of thick sandstone beds and thinner beds of siltstone, shale, and mudstone, which are locally mapped as the Moscow Formation of the Hamilton Group (Fisher et al., 1961). The sediments forming these Middle Devonian rocks appear to have been deposited within a migrating, deltaic shore zone between marine sediments to the west and non-marine (fluvial) sediments to the east (Bridge and Willis, 1994; Bridge and Jarvis, 1998; and Bridge, 2000). Gilboa is the site of one of the world’s oldest fossil forests, and during the original construction of Gilboa Dam, tree stump fossils were sent to several museums (Bartholomew and Brett, 2003; Hernick, 2003). Excavation of a former quarry downstream of the dam during the dam rehabilitation provided an opportunity for researchers to observe and map a portion of the

Jointing Characterization Scan-Line Survey Rock outcrops along Schoharie Creek below Gilboa Dam were examined as part of the reconnaissance effort for the dam rehabilitation. During a detailed line survey consisting of five traverses, the orientations of 45 discontinuities were measured, and notes were taken on their properties (e.g., length, continuity, roughness, infilling, thickness, waviness, and moisture). Discontinuity orientation data are summarized in Tables 1, 2, and 3. Little variation was observed in discontinuity properties, as might be expected in relatively flat-lying beds having only minor deformation due to plate convergence during the Alleghenian orogeny,

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Roman and Berezniak Table 1. Joint Set 1 measurements.* Traverse ID A

B

C

D Figure 6. Steeply dipping, solutioned joints in a calcareous bed on the east side of Schoharie Creek gorge.

E

so discontinuity sets were not weighted, and the dam site was not subdivided into zones during the foundation drain design process.

Joint Orientation Most measured discontinuity surfaces were vertical, and all but one had a dip of 75 degrees or more. The great circles and poles corresponding to the 44 steeply dipping measurements are plotted in a stereonet in Figure 8. Rocscience Dips software was used to determine the global best-fit orientations of the three identified joint sets, which

Trend (°) 225 225 205 190 190 185 200 190 190 190 190 190 190 190 167 167 167 153 153 153 153 153 197 197 197 197

Joint

Distance (ft) No. 5 9 19 22 28 35 5 20 20 25 33 41 51 3 6 10 18 5 12 19 23 26 8 17 31 36

1 2 5 6 8 9 11 15 16 18 19 20 21 24 25 27 28 30 32 34 35 36 38 41 43 45

Mean Median Best-fit plane Best-fit pole (plunge/trend)

Strike Direction (°) 052 069 042 045 050 047 050 036 045 050 047 017 042 032 024 032 030 049 047 036 043 037 046 054 045 055 043 045 043 —

Dip Dip Angle (°) Direction (°) 90 90 90 90 90 90 86 88 90 90 87 90 75 90 90 90 90 90 90 90 90 86 90 88 90 90 89 90 89 1

— — — — — — 140 306 — — 137 — 312 — — — — — — — — 307 — 324 — — — — 313 133

*Trends and directions are expressed in compass coordinates.

5 ft ¼ 1.5 m.

expressed in terms of strike and dip are N43°E/89°NW, N75°W/88°NE, and N5°W/89°SW. The three joint sets were observed on both the east and west sides of the Schoharie Creek gorge below the dam (Figures 9 and 10). The three identified joint sets appear to be of regional significance, as they bear similarities to joint systems depicted in the Gilboa and Schoharie 15-minute quadrangles (Isachsen and McKendree, 1977a) and to brittle structures delineated in the Gilboa 15-minute quadrangle (Isachsen and McKendree, 1977b). The northerly strike of the third joint set is parallel to the overall trend of Schoharie Creek through the gorge containing the Schoharie Reservoir and Gilboa Blenheim Reservoir, a power supply reservoir located downstream of Gilboa Dam. Joint Spacing

Figure 7. Fossil mud cracks on a boulder within Schoharie Creek gorge.

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Measurements taken during the detailed line survey provided an apparent spacing of joints along each traverse.

The true spacing between joints can be calculated by rewriting Eq. 11 as follows:

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Trend (°)

Distance (ft) No.

200 190 190 190 190 190 190 167 153 153 153 197 197 197

C D E

Joint

0 16 16 17 22 47 0 8 2 11 15 10 16 35

10 12 13 14 17 22 23 26 29 31 33 39 40 44

Mean Median Best-fit plane Best-fit pole (plunge/trend)

Strike Direction (°)

Dip Dip Angle (°) Direction (°)

297 290 279 283 275 291 286 286 283 285 284 282 287 287 285 286 285 —

90 85 87 83 84 87 84 86 90 84 82 85 88 90 86 86 88 2

— 020 009 013 185 201 016 016 — 015 014 192 017 — — — 015 195

*Trends and directions are expressed in compass coordinates.

5 ft ¼ 1.5 m.

nn ¼ dn ðsinun coshn sinu cosh þ sinun sinhn sinu sinh þ cosun cosuÞ;

(13)

wherenn ¼ the true joint spacing of joint set n, dn ¼ the apparent joint spacing of joint set n, un ¼ the plunge of the pole to joint set n, hn ¼ the trend of the pole to joint set n, u ¼ the plunge of the traverse, and h ¼ the trend of the traverse.

Figure 8. Stereonet plot of the planes and poles corresponding to the joint measurements and the best-fit orientation for each set.

lengths of each traverse segment. Next, the average true joint spacing was calculated, and then a weighted average was calculated for each joint set based on the lengths of the traverses. The weighted calculated average true joint spacing for Joint Sets 1, 2, and 3 was 3.7 ft (1.1 m), 9.4 ft (2.9 m), and 6.8 ft (2.1 m), respectively.

Drain Hole Design

First, an average apparent joint spacing was calculated for each joint set for each traverse having at least two measurements for the joint set (Table 4). The traverse trend was determined from field measurement with a Brunton compass. In cases where the traverse trend was not constant, a weighted average trend was calculated based on the

Orientation Based on the principal component and average joint spacing of each joint set, the derived equations were used to calculate the apparent spacing between joints of each set

Table 3. Joint Set 3 measurements.* Traverse ID A E

Trend (°) 205 190 197 197

Joint

Distance (ft) No. 16 25 4 27

4 7 37 42

Mean Median Best-fit plane Best-fit pole (plunge/trend)

Strike Direction (°) 350 352 360 359 355 356 355 —

Dip Dip Angle (°) Direction (°) 90 90 87 90 89 90 89 1

— — 270 — 265 266 265 85

*Trends and directions are expressed in compass coordinates.

5 ft ¼ 1.5 m.

Figure 9. Joint Sets 1, 2, and 3 on the east side of Schoharie Creek gorge.

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Figure 10. Joint Sets 1, 2, and 3 on the west side of Schoharie Creek gorge.

for drain holes trending in an upstream direction and plunging from 45 to 70 degrees from horizontal. An Excel spreadsheet was used to perform the calculations in 1-degree increments of azimuth and plunge, so 4,706 possible drain hole orientations were evaluated. A partial plot of the results indicates that the shallowest plunge (45 degrees) is the most favorable of the hole inclinations considered (Figure 11).

The most favorable azimuths are clustered around 142, 249, 71, and 203 degrees, in that order. Holes having these azimuths and plunging 45 degrees are ranked 1st, 15th, 77th, and 203rd when the results are sorted by total apparent spacing, i.e., the combined apparent spacing of each joint set within the proposed drain hole. The calculations indicate a drain hole trending 142 degrees has the optimum total apparent joint spacing and will intercept joints belonging to Joint Sets 1, 2, and 3 every 5.2 ft (1.6 m), 20.9 ft (6.4 m), and 17.1 ft (5.2 m), respectively, on average (Figure 12).

As part of a peer review of the proposed foundation drain design, including the favorable drain orientations identified using the TAS approach, an alternate analysis was performed using the LSBI approach of Zhou and Maerz (2002). Using the LSBI approach, the most favorable drain hole azimuths were found to be clustered around 140, 74, 251, and 199 degrees, in that order (Figure 13). Table 5 provides a comparison of the results for favorable drain hole azimuths using the two approaches.

To optimize borehole inclination, the LSBI approach calculates the LSBI based on the angle between the borehole inclination and the average dips of the joint sets projected onto a vertical east-west plane (0 to 180 degrees).

Drain holes inclined 45 to 90 degrees fall in the range of inclinations from 45 to 135 degrees. Similar to the TAS approach, the LSBI approach indicates that shallower inclinations are more favorable (Figure 14), which intuitively makes sense given the near-vertical average orientations of the three joint sets. Both the TAS and LSBI approaches are thought to be computationally similar in the application of the respective approach and produce comparable results.

The TAS approach uses a formula that factors in both borehole azimuth and inclination to calculate the total apparent spacing along the borehole, while the LSBI approach calculates a separate LSBI for the borehole azimuth and for the borehole inclination.

Drain Hole Length For a given drain hole orientation, drain hole length influences the reduction of the uplift pressures the most, followed by drain hole spacing and drain hole diameter, in that order (da Silva, 2005). Drain hole length has a large influence on the values of the uplift pressures up to approximately half the value of the upstream reservoir depth. From this point onwards, the influence of the drain hole length decreases up to a value equal to the reservoir

Table 4. Summary of calculated average joint spacing.* Best-Fit Pole Joint Set

hn Trend (°)

un Plunge (°)

1

317

91

2

255

92

3

5

91

Traverse

ID

h Trend (°)

u Plunge (°)

Length (ft)

Number of Joints

dn Average Apparent Spacing (ft)

nn Average True Spacing (ft)

Weighted Average True Spacing (ft)

A B C D E B C D E A E

247.5 258.0 279.9 297.0 253.0 257.0 268.6 297.0 253.0 260.0 253.0

90 90 90 90 90 90 90 90 90 90 90

30 46 15 21 28 47 8 13 25 9 23

6 7 4 5 4 6 2 3 3 2 2

6.0 7.7 5.0 5.3 9.3 9.4 8.0 6.5 12.5 9.0 23.0

2.1 4.0 4.0 5.0 4.1 9.4 7.8 4.8 12.5 2.3 8.6

3.7

*Trends and plunges are expressed in spherical coordinates. 5 ft ¼ 1.5 m.

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9.4

6.8

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Figure 11. Plot of total apparent spacing of Joint Sets 1, 2, and 3 for drain holes trending from 071 to 251 degrees and inclined from 45 to 70 degrees.

depth. After that, its influence is very small (da Silva, 2005).

Current design standards suggest that foundation drains should be installed to a vertical depth of two-thirds to threequarters of the depth of the existing grout curtain (USACE, 1995). The depth of the foundation drains should never exceed the depth of the grout curtain (ASCE and USCOLD, 1967). Geologic setting, engineering parameters, and operational and performance objectives also need to be considered in evaluating the design depth of the drain holes.

At Gilboa Dam, the final drain hole design consisted of two rows (A and B) of drain holes. Row A drain holes were drilled S38°E at an angle of 45 degrees from vertical and 27 ft (8.2 m) into rock. Row B drain holes were drilled vertically 10 ft (3 m) into rock. Given the calculated apparent joint spacings, each angled Row A drain hole would be expected to intercept at least five, and possibly six, joints belonging to Joint Set 1 and at least one, and possibly two, joints belonging to Joint Sets 2 and 3 (Figure 12). The vertical Row B drain holes would be expected to intercept mainly bedding joints dipping 1.5 degrees to the south-southwest.

Drain Hole Spacing The drain hole spacing will be controlled by the apparent spacing of joint sets along the drain hole, which has already been determined, and the apparent spacing of joint sets along the gallery where the drain holes are to

be drilled. In order to avoid gaps between drain holes, the drain hole spacing should not exceed the apparent joint spacing along the gallery of each joint set multiplied by the number of joints belonging to the joint set theoretically penetrated by the drain hole.

The apparent joint spacing of each joint set along the gallery (dn) can be calculated by modifying Eq. 11 to consider the azimuth and plunge of the gallery instead of the azimuth and plunge of the drain hole: dn ¼ nn =ðsinun coshn sinu cosh þ sinun sinhn sinu sinh þ cosun cosuÞ;

(14)

where nn ¼ true joint spacing of joint set n, un ¼ joint dip angle of joint set n, hn ¼ joint dip direction of joint set n, u ¼ gallery inclination, and h ¼ gallery azimuth.

The number of joints theoretically penetrated by each drain hole (Nj) is given by: Nj ¼ L=dn ;

(15)

where L ¼ length of the drain hole, and dn ¼ apparent spacing of joint set n along the drain hole.

Thus, the maximum spacing of drain holes along the gallery (Dmax) for a particular joint set is given by:

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calculations assuming a drain hole length of 27 ft. For Joint Sets 1, 2, and 3, the maximum drain hole spacings are 38.5, 22.9, and 11.0 ft, respectively. Joint Set 3 controls the maximum drain hole spacing since the strike of Joint Set 3 has the smallest angular deviation from the drain hole orientation.

Drain spacing must account for deterioration of foundation drains over time due to clogging, incrustation, mineralization, etc., as well as consideration of non-linear uplift distribution.

Major hydraulic structures must be designed with both resiliency and redundancy, and a reliable and robust foundation drainage system is one of the most important aspects of maintaining a stable dam. A drain spacing of 10 ft (3 m) was selected for the Row A drain holes. The above calculation does not apply to Row B drain holes since they were drilled vertically. A spacing of 10 ft (3.0 m) was also selected for the Row B drain holes.

Drain Hole Construction Nominal 3-in.-diameter (7.6 cm) drain holes were typically drilled with percussive rotary methods using water flush at a spacing of 10 ft (3 m) (Figure 15). Where exploratory holes were required, NQ wireline double-tube rock coring was specified. At each drilling location, one hole was drilled S38° E at an angle of 45 degrees from vertical and 27 ft (8.2 m) into rock, and a second hole was drilled vertically 10 ft (3 m) into rock. In total, 248 drain holes were drilled at 124 drilling locations. The drain holes were drilled prior to the creation of the dam gallery during construction of the downstream concrete buttress (Figures 16 and 17).

Uplift was considered in the design of the site structures at Gilboa Dam. The spillway, spillway channel, plunge pool concrete panels, and retaining/training walls were designed assuming full uplift. Uplift of the concrete slabs in the spillway channel and plunge pool was addressed using passive anchor bars grouted into bedrock. Although the gallery foundation drains in the spillway and the underdrain system within the spillway channel and plunge pool were included in the design, the drains were not accounted for as an uplift reduction method since the gallery and spillway channel were designed to be below tailwater elevation during flood conditions.

SUMMARY Figure 12. Schematic plan views along drain hole path showing calculated average apparent spacing of discontinuities of (a) Joint Set 1, (b) Joint Set 2, and (c) Joint Set 3.

Dmax ¼ dn 3 Nj :

(16)

At Gilboa, the gallery trends approximately 253 degrees and plunges about 3 degrees from horizontal. Table 6 provides a summary of the maximum drain hole spacing 222

Fractures develop in a rock mass in response to stresses that exceed the strength of the rock to resist the resulting forces. Discontinuities typically exhibit preferred orientations and often occur as sets, with each set consisting of regular joints sub-parallel to each other. In each set, discontinuities usually have the same general orientation and exhibit relatively common physical characteristics. Rock masses may contain multiple discontinuity sets, and three to four sets are typical of many rock masses.

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Figure 13. Plot of LSBI for Joint Sets 1, 2, and 3 for drain holes with azimuths from 071 to 251 degrees.

Uplift is one of the primary loads that affect the stability of a concrete dam founded on rock. The hydraulic conductivity of a jointed rock mass is commonly controlled by its secondary permeability, and in most civil engineering applications involving rock foundations, the secondary permeability controls the drain design procedures. Drains are used to reduce dangerous uplift pressure beneath hydraulic structures and must be correctly placed in three-dimensional space to intersect hydraulically significant discontinuities that are capable of fracture flow.

Numerous methods, such as scan-line outcrop surveys and core hole imaging, can be used to systematically collect the data required to characterize the jointing pattern of a rock mass. Properly conducted surveys can provide data on the orientation, spacing, and physical condition of the discontinuity sets within a rock foundation or rock slope.

These data can provide the a priori knowledge about the Table 5. Nodes of optimum drain hole azimuths.* TAS Approach Azimuth 142 249 71 203

LSBI Approach

TAS (ft)

Azimuth

LSBI

43.2 44.0 45.9 48.8

140 251 74 199

4.49 4.95 4.90 5.92

LSBI ¼ linear sampling bias index; TAS ¼ total apparent spacing. *Drain holes trending downstream not considered. 5 ft ¼ 1.5 m.

discontinuity structure of the rock foundation that is needed to effectively utilize the analytical approaches described herein. The TAS approach can be used to define an optimum drilling direction, that is, the correct orientation and inclination along which a borehole can be drilled to intersect as many discontinuities as possible for a given drilling length.

This analytical tool has a direct application in the design of systematic drains installed in a jointed rock foundation.

LIMITATIONS Primary and secondary permeability may overlap in some rock foundations. In these circumstances, rock foundations may exhibit primary permeability that is generally similar to secondary permeability. The approaches presented herein do not explicitly consider the effect of primary permeability on seepage and, hence, cannot be used to properly design a foundation drainage system that is significantly affected by primary permeability. Flow nets, or other analytical or numerical methods, are required to design a foundation drainage system largely influenced by primary permeability.

The formula used in the TAS approach will provide an infinite total apparent spacing in certain scenarios.

For example, using the formula to optimize a scenario including a discontinuity set oriented exactly parallel to the proposed drain hole will have a solution of infinity, since the drain hole will theoretically never intercept a discontinuity set oriented exactly parallel to the drain hole. In this

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Figure 14. Plot of LSBI for Joint Sets 1, 2, and 3 for drain holes with inclinations from 45 to 135 degrees.

case, if the proposed drain hole orientation is deemed to be necessary for some reason, then a preferable solution might be to optimize the orientation of one set of drain holes based on the non-parallel discontinuity sets and add a second set of drain holes having an orientation optimized to intercept the parallel discontinuity set.

Likewise, when multiple sets of discontinuities exist and influence uplift, optimizing the drain hole orientation based on an analysis factoring in all the discontinuity sets may result in a compromise solution that may be less effective than a design incorporating a variety of drain hole orientations, each optimized to target a single set or group of discontinuity sets, e.g., one drain hole orientation optimized to intersect near-vertical discontinuity sets and one drain hole orientation optimized to intersect near-horizontal bedding joints.

Regardless of the resulting optimized drilling orientation developed by the TAS or alternate methods, the actual optimum orientation results may be limited by factors outside

the numerical analysis. The physical characteristics of the site and the limitations of equipment and access must be taken into account prior to designating an orientation for boreholes in a drilling work plan, scope of work, or contract. The analysis may indicate that drain holes having a shallow plunge from horizontal are most favorable, but the mechanics of executing such an orientation may preclude the feasibility of drilling a drain hole having that orientation. The access and logistics of a site may also preclude using equipment that might otherwise be able to achieve the optimized orientation. Under these conditions, alternative scenarios must be considered to determine the best practical solution during the analysis and design phase, rather than after equipment and personnel have been mobilized.

Drilling tolerance and the potential for deviation should also be considered when putting the results of these methods into a specific application. At greater inclinations from vertical, the borehole is more likely to deviate from the desired orientation, all other factors being equal.

Table 6. Summary of calculated maximum drain hole spacing.

Joint Set

dn Apparent Joint Spacing Along the Gallery (ft)

L Drain Hole Length (ft)

dn Apparent Joint Spacing Along the Drain Hole (ft)

Nj Number of Joints Intercepted by the Drain Hole

Dmax Maximum Drain Hole Spacing (ft)

7.4 17.7 7.0

27.0 27.0 27.0

5.2 20.9 17.1

5.2 1.3 1.6

38.5 22.9 11.0

1 2 3 5 ft ¼ 1.5 m.

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Figure 15. Drilling 3-in.-diameter (7.6 cm) drain hole at the downstream toe of the dam.

Figure 17. Completed foundation drain within the new dam gallery.

Despite a rigorously executed site investigation program, considerable geologic uncertainties may still exist. Any site investigation program must be thoroughly evaluated for sampling bias and other deficiencies. Site investigation deficiencies and inadequacies must be thoroughly considered when finalizing any foundation drain design.

Conclusions based upon limited sampling data may introduce significant epistemic uncertainty into the geotechnical design process. This uncertainty should be fully recognized and considered, and sound engineering principles and judgement are still required when applying the analytical approaches described herein.

can intersect as many discontinuities as possible for a given drilling length. Given a priori knowledge of the jointing pattern within a rock foundation, this approach provides a means to rationally design the optimal orientation, depth, and spacing of rock foundation drains. Drains properly installed at the optimal orientation, depth, and spacing will more effectively and efficiently diminish the hydraulic pressure beneath a concrete dam founded directly on jointed rock. When properly applied, the TAS approach can supersede the long-standing rules-of-thumb that have historically been used to design the spacing, depth, and orientation of foundation drains.

The TAS approach has numerous geotechnical exploration and rock engineering applications. Specific applications include the orientation of drill holes used for: geotechnical site investigations, permeation grouting, permeation grouting verification, pressure (packer) testing, installation of geotechnical instrumentation, groundwater sampling and production wells, rock slope investigation and design, installation of rock support anchors, and collection of rock core samples for engineering property testing, etc. The TAS approach may be applied strategically to intercept as many discontinuities as possible or to focus on intercepting those discontinuities of greatest significance, or those that pose the greatest risks due to structural or seepage concerns.

CONCLUSIONS The TAS approach can be used to define an optimum drilling direction, that is, the direction along which a borehole

ACKNOWLEDGMENTS

Figure 16. Construction of dam gallery (near center of photo) during construction of a stepped concrete buttress on the downstream face of the existing dam during dam and spillway rehabilitation.

The authors thank Dr. Abdul Shakoor, former co-editor of Environmental and Engineering Geoscience, for his invitation to submit this manuscript to the journal after a presentation on the TAS approach at an Association of Environmental and Engineering Geologists Annual Meeting.

The authors also thank the New York City Department of Environmental Protection for permission to use the Gilboa Dam rehabilitation project as a worked example; Jake Roman for his kind assistance on the mathematical aspects of the manuscript; and the peer reviewers for their many

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insightful comments and thoughtful suggestions for improving the manuscript.

REFERENCES ASCE (AMERICAN SOCIETY OF CIVIL ENGINEERS) AND USCOLD (UNITED STATES COMMITTEE ON LARGE DAMS), 1967, Joint ASCE-USCOLD Committee on current United States practice in the design and construction of: Arch dams, embankment dams, and concrete gravity dams: American Society of Civil Engineers, New York, 131 p.

BARTHOLOMEW, A. J. AND BRETT, C. E., 2003, The Middle Devonian (Givetian) Gilboa forest: Sequence stratigraphic determination of the world’s oldest fossil forest deposit, Schoharie County, New York State: Geological Society of America Abstracts with Programs, Vol. 35, No. 3, p. 83.

BATTULWAR, R.; ZARE-NAGHADEHI, M.; EMAMI, E.; AND SATTARVAND, J., 2021, A state-of-the-art review of automated extraction of rock mass discontinuity characteristics using three-dimensional surface models: Journal of Rock Mechanics and Geotechnical Engineering, Vol. 13, No. 4, pp. 920–936.

BRIDGE, J. S., 2000, The geometry, flow patterns and sedimentary processes of Devonian rivers and coasts, New York and Pennsylvania, USA. In Friend, P. F. and Williams, B. P. J. (Editors), New perspectives on the Old Red Sandstone: Special Publication 180, Geological Society, London, U.K., pp. 85–108.

BRIDGE, J. S. AND JARVIS, S., 1998, Devonian fluvial to shallow marine strata, Schoharie Valley, New York. In Naslund, H. R. (Editor), Field Trip Guide for the 70th Annual Meeting of the New York State Geological Association: New York State Geological Association, Binghamton, NY, pp. 43–69.

BRIDGE, J. S. AND WILLIS, B. J., 1994, Marine transgressions and regressions recorded in Middle Devonian shore-zone deposits of the Catskill clastic wedge: Geological Society of America Bulletin, Vol. 106, No. 11, pp. 1440–1458.

COOK, D. I.; SANTI, P. M.; AND HIGGINS, J. D., 2007, Horizontal landslide drain design: State of the art and suggested improvements: Environmental & Engineering Geoscience, Vol. 14, No. 4, pp. 241–250.

DA SILVA, J. F., 2005, Influence of the geometry of the drainage system and of the foundation anisotropy on the uplift pressures under concrete dams: Infogeo 2005—5th Brazilian Symposium on Applications of Computational Mechanics in Geotechnical Engineering, Belo Horizonte, Brazil, pp. 165–174.

EBELING, R. M. AND PACE, M. E., 1996a, Uplift pressure resulting from flow along tapered rock joints: REMR Bulletin, Vol. 13, No. 1, pp. 1–4.

EBELING, R. M. AND PACE, M. E., 1996b, Variation in uplift pressures with changes in loadings along a single rock joint below a gravity dam: REMR Bulletin, Vol. 13, No. 1, pp. 5–8.

FARNY, N. J., 2017, Comparing rock discontinuity measurements using geological compass, smartphone application, and laser scanning methods: Environmental & Engineering Geoscience, Vol. 23, No. 2, pp. 97–112.

FISHER, D. W.; BROUGHTON, J. G.; ISACHSEN, Y. W.; RICKARD, L. V.; AND OFFIELD, T. W. (Compilers and Editors), 1961, Geologic map of New York, Hudson-Mohawk sheet: New York State Museum and Science Service Map and Chart Series 5, scale 1:250,000.

GATES, W. C. B. AND HANEBERG, W. C., 2012, Comparison of standard structural mapping results to 3-D photogrammetric model results: Boundary Transformer Banks rockfall mitigation project, Metaline Falls, Washington. In Bobet, A.; Ewy, R.; Gadde, M.; Labuz, J.; Pyrak-Nolte, L.; Tutuncu, A.; and Westman, E. (Editors), 46th U. S. Rock Mechanics/ Geomechanics Symposium Proceedings, Vol. 2: American Rock Mechanics Association, Alexandria, VA, pp. 1489–1493.

GRENOBLE, B. A. AND AMADEI, B., 1990, Evaluation of uplift pressure for concrete gravity dams founded on jointed rock: analytical

226

results. In Proceedings of the 10th USCOLD Meeting and Lecture Series, New Orleans, LA, U.S. Committee on Large Dams, Denver, CO, pp. 1–20.

GRENOBLE, B. A.; HARRIS, C. W.; MEISENHEIMER, J. K.; AND MORRIS, D. I., 1995, Influence of rock joint deformations on uplift pressure in concrete gravity dam foundations: Field measurements and interpretation. In Myer, L. R. and Cook, N. G. (Editors), Fractured and jointed rock masses, Proceedings of the Conference on Fractured and Jointed Rock Masses, Lake Tahoe, CA, 3–5 June 1992: A. A. Balkema, Rotterdam, Brookfield, pp. 535–542.

HANEBERG, W. C., 2004, Computational geosciences with Mathematica: Springer-Verlag, Berlin, Germany, 381 p.

HANEBERG, W. C., 2008, Using close range terrestrial digital photogrammetry for 3-D rock slope modeling and discontinuity mapping in the United States: Bulletin of Engineering Geology and the Environment, Vol. 67, No. 4, pp. 457–469.

HANEBERG, W. C., 2009, Technical Note—Improved optimization and visualization of drilling directions for rock mass discontinuity characterization: Environmental & Engineering Geoscience, Vol. 15, No. 2, pp. 107–113.

HANEBERG, W. C.; NORRISH, N. I.; AND FINDLEY, D. P., 2006, Digital outcrop characterization for 3-D structural mapping and rock slope design along Interstate 90 near Snoqualmie Pass, Washington: 57th Annual Highway Geology Symposium Proceedings, Breckenridge, CO, pp.

146–160.

HERNICK, L. V., 2003, The Gilboa Fossils: New York State Museum Circular 65, New York State Education Department, Albany, NY. ISACHSEN, Y. W. AND MCKENDREE, W. G. (Compilers), 1977a, Generalized map of recorded joint systems in New York: New York State Museum Map and Chart Series No. 31F, scale 1:1,000,000.

ISACHSEN, Y. W. AND MCKENDREE, W. G., 1977b, Preliminary brittle structures map of New York—Hudson-Mohawk sheet: New York State Museum Map and Chart Series No. 31B, scale 1:250,000.

KEMENY, J.; BATEMAN, V.; DIMITROPLOS, C. G.; FOLTZ, B.; HADJIN, D.; MCCLELLAND, M.; COMBS, J.; ORTIZ, T.; PELHAM, K.; PRIZNAR, N.; TURNER, K.; AND WEBSTER, B., 2011, Transportation pooled fund project of highway geotechnical applications of ground-based LIDAR: 62nd Highway Geology Symposium Proceedings, Lexington, KY, pp.

195–211.

KEMENY, J. AND TURNER, K., 2008, Ground-based LiDAR rock slope mapping and assessment: Federal Highway Administration Report No. FHWA-CFL/TD-08-006.

KOTTENSTETTE, J. T. AND SHAFFNER, P. T., 2008, Photogrammetric mapping and geological characterization of foundation blocks in the right abutment of East Canyon Dam. In 42nd U.S. Rock Mechanics Symposium and 2nd US-Canada Rock Mechanics Symposium 2008, Vol. 3: American Rock Mechanics Association, Alexandria, VA, pp.

1463–1478.

KRYNINE, D. P. AND JUDD, W. R., 1957, Principles of engineering geology and geotechnics: McGraw-Hill Book Company, Inc., New York, 730 p.

LA POINTE, P. R. AND HUDSON, J. A., 1985, Characterization and interpretation of rock mass joint patterns: Special Paper 199, Geological Society of America, Boulder, CO, 37 p.

MAULDON, M. AND MAULDON, J. G., 1997, Fracture sampling on a cylinder: From scanlines to boreholes and tunnels: Rock Mechanics and Rock Engineering, Vol. 30, No. 3, pp. 129–144.

MURPHY, W. L.; EBELING, R. M.; AND ANDERSEN, J. M., 2002, Assessment of geology as it pertains to modeling uplift in jointed rock: A basis for inclusion of uncertainty in flow models: U.S. Army Corps of Engineers, Engineer Research and Development Center Report ERDC TR-02-2.

[NASEM] NATIONAL ACADEMIES OF SCIENCES, ENGINEERING, AND MEDICINE, 2020, Characterization, modeling, monitoring, and remediation of

Environmental & Engineering Geoscience, Vol. XXX, No. 4, November 2024, pp. 211–227

Approach to Optimize Foundation Drain Orientations fractured rock: The National Academies Press, Washington, D.C. https://doi.org/10.17226/21742 OTOO, J. N.; MAERZ, N. H.; DUAN, Y.; AND XIAOLING, L., 2011, LiDAR and optical imaging for 3-D fracture orientations: NSF Engineering Research and Innovation Conference Proceedings, Atlanta, GA, 8 p.

PRIEST, S. P., 1993, Discontinuity analysis for rock engineering: Chapman & Hall, London, U.K., 473 p.

RICH, J. L., 1935, Glacial geology of the Catskills: New York State Museum Bulletin 299.

SHAFFNER, P.; HEISLER, R.; KROSLEY, L.; KOTTENSTETTE, J.; AND WRIGHT, J., 2009, Characterization of dam foundation blocks using digital photogrammetric mapping and borehole geophysical logging to create comprehensive 3D foundation models. In Managing our water retention systems, 29th Annual USSD Conference, Nashville, TN: U.S. Society on Dams, Aurora, CO, pp. 473–505.

STEIN, W. E.; BERRY, C. M.; HERNICK, L. V.; AND MANNOLINI, F., 2012, Surprisingly complex community discovered in the mid-Devonian fossil forest at Gilboa: Nature, Vol. 483, No. 7387, pp. 78–81.

STEWART, J., 2003, Multivariable calculus, 5th ed.: Brooks/Cole— Thomson Learning, Belmont, CA, 1204 p.

STONE AND WEBSTER ENGINEERING CORPORATION, 1992, Uplift pressures, shear strengths, and tensile strengths for stability analysis of concrete gravity dams, Volume 1: Electric Power Research Institute Technical Report TR-100345s, 304 p.

TERZAGHI, R. D., 1965, Sources of error in joint surveys: Géotechnique, Vol. 15, No. 3, pp. 287–304.

TITUS, R., 2003, The Catskills in the ice age, revised ed.: Purple Mountain Press, Jamestown, PA, 127 p.

TONON, F. AND KOTTENSTETTE, J. T. (Editors), 2007, Laser and photogrammetric methods for rock face characterization: Report on a workshop held June 17–18, 2006 in Golden, CO, in Conjunction with GoldenRocks 2006—The 41st U.S. Rock Mechanics Symposium, Colorado School of Mines, June 17–21, 2006: American Rock Mechanics Association, Alexandria, VA, 120 p.

USACE (U.S. ARMY CORPS OF ENGINEERS), 1995, Planning and design of navigation dams: U.S. Army Corps of Engineers Engineer Manual EM 1110-2-2607, 117 p.

USACE (U.S. ARMY CORPS OF ENGINEERS), 2005, Stability analysis of concrete structures, Appendix C, uplift: U.S. Army Corps of Engineers Engineer Manual EM 1110-2-2100, pp. C-1–C-4.

WATTS, C. F., 2011, LiDAR and 3D photogrammetry for evaluating geologic structure in rock slope stability analyses: 25th Central Pennsylvania Geotechnical Conference Proceedings, Hershey, PA: American Society of Civil Engineers, Central PA Section, pp. 58–71.

ZHOU, W. AND MAERZ, N. H., 2002, Identifying the optimum drilling direction for characterization of discontinuous rock: Environmental & Engineering Geoscience, Vol. 13, No. 4, pp. 295–307.

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Development of a 3D Geologic Model Used in the Seismic Hazard and Liquefaction Hazard Analysis of Madison County, Tennessee VALARIE JOYNER HARRISON* Department of Earth Sciences, University of Memphis, 109 Johnson Hall, Memphis, TN 38152-3430 and Tennessee Department of Environment and Conservation, Memphis Environmental Field Office, 8383 Wolf Lake Drive, Bartlett, TN 38133-4119

HAMED TOHIDI Department of Civil Engineering, University of Memphis, 104 Engineering Science Building, Memphis, TN 38152 and MIGIZI Group, Inc., 201 160th Street South, Suite 401, Seattle, WA, 98448

ROY VAN ARSDALE Department of Earth Sciences, University of Memphis, 109 Johnson Hall, Memphis, TN 38152-3430 and Department of Environmental Science, Rhodes College, 2000 North Pkwy, Memphis, TN 38112

CHRIS CRAMER Center for Earthquake Research and Information, University of Memphis, 3890 Central Avenue, Memphis, TN 38152-3050

DAVID ARELLANO Department of Civil Engineering, University of Memphis, 104 Engineering Science Building, Memphis, TN 38152

Key Terms: 3D Geologic Modeling, Madison County, Tennessee, New Madrid Seismic Zone, Mississippi Embayment, Quaternary, Tertiary, Paleogene, Cretaceous ABSTRACT Madison County of western Tennessee is approximately 100 km southeast of the New Madrid seismic zone and, thus, is subject to potentially dangerous seismic shaking and liquefaction events. Holocene floodplain alluvium and associated Pliocene/Pleistocene terraces of the Forked Deer and Hatchie Rivers cover a large part of Madison County. Underlying these unconsolidated sediments are approximately ∼650 m of poorly consolidated Paleogene and Cretaceous terrestrial and marine sediments, which are underlain by Paleozoic limestone bedrock. Uniform regional geology used in the 2014 United States Geological Survey seismic hazard maps assumes a homogenous seismic velocity structure above bedrock. Three-dimensional geologic mapping of the ∼700 m of Quaternary, *Corresponding author email: Valarie.harrison@tn.gov

Neogene, Paleogene, and Cretaceous sediments conducted in this study provides a more detailed velocity structure, resulting in a more accurate and detailed map of the expected ground motions in Madison County during future earthquakes. In addition, the surface geologic map reveals regions that are susceptible to liquefaction. This paper discusses the methods used to construct the surface geology map, subsurface structure contour maps, isopach maps, and 3D geologic model used in the seismic hazard and liquefaction hazard analyses of Madison County, Tennessee, and summaries of the results of these analyses are presented.

INTRODUCTION Located approximately 100 km southeast of the New Madrid seismic zone, Madison County, Tennessee, and its primary city of Jackson (population 68,114) (Figure 1) may be affected by both earthquake ground shaking and liquefaction in the event of future large New Madrid earthquakes (Chiu et al., 1992; Cox et al., 2001, 2006, 2013; Tuttle et al., 2002, 2019; Cramer, 2006; Csontos

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Figure 1. (A) Location of Madison County, Tennessee. (B) Geologically mapped 7.5-minute quadrangles of Madison County. The Mercer, Spring Creek, and Cedar Grove quadrangles are highlighted in yellow and have not been geologically mapped and published. The basemap is a 1-m DEM of Madison County with the black to white color ramp showing elevations from low (93 m) to high (204 m), respectively.

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and Van Arsdale, 2008; Cramer and Boyd, 2014; Cramer et al., 2018a, 2023). The 2014 regional United States Geological Survey (USGS) probabilistic seismic ground motion maps predict peak ground acceleration (PGA) from 0.2 to 0.7 g, where g is gravitational acceleration, for Madison County (Figure 9A) in the event of future M 7.3–7.7 New Madrid seismic zone earthquakes. However, USGS seismic ground motion maps are based on uniform standard geology and do not include the effects of near-surface geology (Petersen et al., 2014), which can be significant in the event of a large proximal earthquake (Cramer et al., 2023). In this paper, we detail the process of constructing the surface geologic map, structure contour and isopach maps, and the 3D geologic model of Madison County that was used in the seismologic hazard modeling that is detailed in Cramer et al.

(2023). This research documents near-surface geology and produces a more accurate and detailed seismic hazard analysis as well as liquefaction hazard analysis. This study also illustrates the usefulness of continued 3D geologic and seismologic mapping peripheral to the New Madrid seismic zone, which includes large portions of western Tennessee, western Kentucky (Zhu et al., 2021), southwestern Illinois, southeastern Missouri, and northeastern Arkansas.

General Geology of Madison County Madison County consists of lowland floodplains of the South Fork and Middle Fork of the Forked Deer rivers, Hatchie River, Hatchie River tributaries, terraces of these rivers, and areas of Paleogene and Late Cretaceous strata (Figure 2) (Brown, 1968a, b; Parks, 1968a, b, c, d, e, f, g; Saucier, 1987; Jewel, 2006; Antonacci and Hoyal, 2011, 2012a, b, 2014). A thin deposit of Pleistocene loess overlies the terraces and both Paleogene and Cretaceous sediments. Beneath the floodplain and terrace deposits in most of Madison County are Eocene (»34 Ma) sediments that overlie older Paleogene, Late Cretaceous, and Paleozoic strata (Figure 2 and Table 1).

No faults have been mapped in Madison County, and the county is seismically inactive (Figure 2A).

Approximately 3.6 Ma (Odum et al., 2020), the ancestral Mississippi River system flowed through the central United States and deposited floodplain sediments now discontinuously preserved as a high-level terrace called the Upland Complex (Van Arsdale et al., 2007; Cox et al., 2014; Cupples and Van Arsdale, 2014; Lumsden et al., 2016). Remnants of the 3.6 Ma terrace have been mapped in Obion, Dyer, Lauderdale, Tipton, and Shelby counties in western Tennessee (Figure 1A) (Van Arsdale et al., 2007). Remnants of terraces have also been mapped in Madison County (Saucier, 1987). Incision through the Upland Complex throughout the lower Mississippi/Ohio River system began in the early

Figure 2. (A) 7.5-minute quadrangles of Madison County mapped by Antonacci and Hoyal (2011; 2012a, b; 2014), Brown (1968a, b), Jewel (2006), and Parks (1968a, b, c, d, e, f, g). Quadrangles labeled in Figure 1. Line A-A’ in Jackson North quadrangle indicates location of cross section in B. (B) West–east geologic cross section of the Jackson North 7.5-minute geologic quadrangle map with 4X vertical scale (modified from Jewel, 2006). (C) Geologic column of Jackson North 7.5-minute geologic quadrangle map (modified from Jewel, 2006).

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Period

Group and Formation

Symbol

Quaternary Tertiary (?) and Quat.

Tertiary

Alluvium Fluvial Deposits Wilcox Group Porters Creek Clay Clayton Fm.

Cretaceous

Owl Creek Fm. McNairy Sand Demopolis Fm. Coffee Sand

Paleozoics

Undifferentiated Limestone

Qal QTf Tw Tp Tcl Ko Km Kd Kc Pal

Pleistocene with growth of continental ice sheets and resultant lower sea levels (Saucier, 1994; Van Arsdale et al., 2007). During the Pleistocene, the Humboldt, Hatchie, and Finley terraces formed along the Obion, Forked Deer, and Hatchie rivers (Saucier, 1987; Rodbell, 1996) and up to four loess layers were deposited in western Tennessee (Markewich et al., 1998). In Dyer County (Figure 1A), Rodbell (1996) identified Peoria loess (,20 ka) and underlying Roxanna silt (.65 ka loess) on top of Humboldt and Hatchie River terrace alluvium (Reichenbacher et al., 2022). The researchers believe that the ancestral Mississippi/Ohio river system and its tributaries entrenched .65 ka in western Tennessee because the Humboldt terrace alluvium is overlain by the .65 ka loess based on the Dyer and Lauderdale counties’ geologic histories. Subsequently, the Mississippi/Ohio river system and its tributaries further entrenched to form the Hatchie (also .65 ka) and then Finley (»22 ka) terrace levels (Harrison, 2022). The final entrenchment of the Mississippi and its tributary rivers in western Tennessee occurred within the last 22,000 years, resulting in most of the modern floodplain alluvium being ,12 ka.

METHODS The surface geology of Madison County—except for the Mercer, Cedar Grove, and Spring Creek 7.5-minute topographic quadrangles—has been mapped at a scale of 1:24,000 (Figure 2A) (Brown, 1968a, b; Parks, 1968a, b, c, d, e, f, g; Jewel, 2006; Antonacci and Hoyal, 2011, 2012a, b, 2014). For this geologic and earthquake hazard investigation, Madison County was divided into three surface geologic units: Holocene river floodplain alluvium, Pliocene and/or Pleistocene river terrace alluvium, and semi-consolidated sediments of Paleogene and Cretaceous age. Bedrock beneath Madison County is 232

Paleozoic limestone and dolomite (Figure 2 and Table 1) (Jewel, 2006). To complete the surface geology of Madison County, the Mercer, Cedar Grove, and Spring Creek 7.5-minute quadrangles (Figure 1B) were interpreted by using 1-m lidar digital elevation models (DEM) and projecting the surface geology of adjacent 7.5-minute published geologic quadrangle maps (Figure 2A). Most of the Mercer quadrangle in Madison County was mapped

by Saucier (1987) as Hatchie River terrace, and Saucier’s map forms the basis for our mapping of this quadrangle.

The remaining area within the Mercer Quadrangle was mapped by extending alluvium from streams in the surrounding quadrangles through the Hatchie River terrace.

To complete the mapping of Madison County, the Spring Creek and Cedar Grove quadrangles were subdivided into 27 polygons. The polygons adjacent to the published surface geology were split into the three classifications of Holocene floodplain alluvium, Pliocene/Pleistocene terrace alluvium, and Paleogene and Cretaceous sediments based on surface elevation. These polygons were then reclassified until the pattern at the perimeter of the DEM matched the pattern of the known adjacent published surface geology (Figure 2A). This process was repeated for each polygon.

The resulting rasters were merged into a mosaic to represent the interpreted surface geology of the three quadrangles and merged with the geology classification of Table 1 to produce a simplified surface geologic map of Madison County (Figure 3).

Subsurface lithologic boring logs were acquired from petroleum exploration wells, Tennessee Department of Environmental Control, and the State of Tennessee Department of Environment and Conservation Division of Geology. These borings contain lithologic descriptions of the Neogene, Paleogene, Cretaceous, and Paleozoic strata that reach a depth of »410 m below the Jackson North geologic quadrangle near the middle of Madison County (Figures 1B and 2B).

The subsurface geology of Madison County is illustrated in the cross-section that accompanies the 7.5minute Jackson North Geologic Quadrangle map (Figure 2B) (Jewel, 2006). The basal portion of the Paleocene Clayton Formation is difficult to differentiate from the top of the underlying Cretaceous sediment (the Owl Creek Formation) in some published quadrangles (e.g., Figure 2B) as they are both described as consisting of glauconitic clay and sand. Therefore, these units are combined in those maps based on their similar lithologies. Because the lithologies are indistinguishable, they are expected to have the same seismic velocities. Within this study, the term “top of Cretaceous” is used even where a thin section of Paleocene Clayton is present, and thus, the uncertainty of the top of the Cretaceous strata is considered in the final ground-shaking hazard maps. The elevations of the tops of the Wilcox Group, Porters Creek Clay, and

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Figure 3. Simplified geologic map of Madison County for this seismic ground motion and liquefaction investigation. Liquefaction probability curves in Figure 9A and B were calculated for the floodplain strata (Holocene floodplain alluvium) and non-floodplain strata (Pliocene/Pleistocene terrace alluvium, Paleogene strata, and Cretaceous strata). Earthquake liquefaction potential is high for the Holocene floodplain areas of Madison County.

Cretaceous were determined by surface contact elevations from published 7.5-minute geologic quadrangle maps in Madison and adjacent counties (Figure 2A) and from well data. All top of Paleozoic elevation picks in Madison County are from well data.

Structure contour maps were made showing the elevations of the tops of the Claiborne Group, Cretaceous strata, and the top of the Paleozoic strata (Table 1).

These maps were made using the Natural Neighbor contouring algorithm. Planar trend surfaces of the tops of the Wilcox Group and Porters Creek Clay were also made. The planar trend surfaces were used to extrapolate the tops of the Wilcox Group and Porters Creek Clay under most of Madison County. Control for the top of the Cretaceous was obtained from outcrop data in eastern Madison County and adjacent counties and from petroleum exploration wells. The top of Paleozoic structure contour map was constructed from oil well exploration data. Strikes and dips of the mapped units were determined from first order trend maps of the units’ elevation data.

Near-surface geologic unit thicknesses are necessary for a comprehensive evaluation of local ground motion and liquefaction potential (Cramer et al., 2023). Therefore, isopach maps were constructed of the Lowland Holocene

alluvium, Pliocene/Pleistocene terrace alluvium, Claiborne Group, Wilcox Group, Porters Creek Clay, and Cretaceous sections. Lowland Quaternary alluvium thicknesses were locally determined from published 7.5-minute geologic quadrangle maps that had cross-sections across river floodplains. In addition, road bridge crossings of the middle and south forks of the Forked Deer River in Madison County were visited, and the height from the bridge deck to the bottom of the deepest part of the river flowing beneath the bridge was measured by dropping a weighted measuring tape to the riverbed. Immediately adjacent to the bridge crossings, 1-m lidar DEM data were used to make topographic profiles across the floodplain. Bridge deck elevation, floodplain surface elevation derived from the 1-m lidar data, and the height of the bridge deck to the bottom of the channel were used to estimate the floodplain thickness at the bridge crossings as follows: The bridge deck height above channel bottom minus bridge deck height above floodplain equals channel depth, which equals approximate floodplain alluvium thickness.

The calculated elevations of the base of the floodplains were used to approximate planar trend surfaces of the base of the alluvium beneath the south and central Forked Deer River floodplains. An isopach map of the south and central Forked Deer River floodplains was made by subtracting the elevations of the floodplain base planar trend surface from the floodplain surface elevations. The isopach map of the Pliocene/Pleistocene terrace alluvium was determined by subtracting the elevations of the base of the terrace alluvium from the ground surface elevations; thus, the thin surface loess was included in this thickness. The Claiborne Group isopach map was derived by subtracting the elevation of the top of the Wilcox Formation from the surface elevation where the Claiborne is exposed and from the elevation of the top of the Claiborne where it’s covered by Holocene flood plain alluvium or Pliocene/Pleistocene terrace alluvium. Isopach maps of the Wilcox Group, Porters Creek Clay, and Cretaceous section were made by subtracting the elevations from the basal structure contour map from the overlying structure contour map of each mapping unit (e.g., Porters Creek Clay top elevation – Cretaceous top elevation ¼ thickness of Porters Creek Clay). For data used in this study, see Appendix A. The surface geology of Madison County, structure contour maps, and isopach maps were compiled into a 3D model and animation of the geology of Madison County (Appendix B). S-wave velocities were determined for the mapped surface and subsurface geologic units, and in conjunction with the units’ respective thicknesses, a vertical seismic velocity profile was calculated for every 0.5 km2 of Madison County and a 10-km surrounding area. A detailed discussion of the seismic methodology is presented in Cramer et al. (2023).

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Geotechnical Engineering Analysis Geotechnical analysis of Madison County was conducted to develop liquefaction probability curves (LPCs) based on geotechnical soil borings, groundwater levels (GWL), and seismic ground motion estimates.

The LPCs were developed using the three-step procedure utilized by Rix and Romero-Hudock (2006), Cramer et al. (2018a, b; 2019; 2020a, b; 2021; 2022; 2023) and summarized in Tohidi et al. (2021). However, an overview of each step, including specific modifications incorporated for Madison County, is provided as follows.

Step 1 involves calculating the factor of safety against liquefaction at each 0.6-m depth increment to a depth of 20 m of each soil boring using the simplified procedure of Seed and Idriss (1971) and the Youd and Idriss (2001) relationship for determining the cyclic resistance ratio based on standard penetration test (SPT) data. A total of 233 soil boring logs were collected from various organizations. However, only 69 of these soil boring logs met the following screening criteria for liquefaction analysis: (1) Borings must be at least 20 m (66 ft) deep, (2) borings must include N-values and Unified Soil Classification System (USCS) soil classifications to a depth of 15 m (50 ft), and (3) the boring locations must have latitude and longitude coordinates.

After summarizing the boring logs for N-values, USCS soil classification, and fines content using a depth increment of 0.6 m to a total depth of 20 m, the GWL at each boring location was estimated from the GWL contour map of Schrader (2008) and corroborated with data from 23 wells provided by the Jackson Energy Authority (JEA), which indicated a stable water level over a 15year period (from 2006 to 2020). The measurements from these 15 years indicate that the change in water level is minor. Additionally, JEA has not encountered any sudden rise in water levels near rivers. The JEA GWLs are in general agreement with the levels indicated by the contour map of Schrader (2008). Therefore, the Schrader GWL contour map was utilized to obtain the GWL at each soil-boring location to perform liquefaction analysis.

Step 2 consists of calculating the liquefaction potential index (LPI) at each soil-boring location based on the Iwasaki et al. (1978, 1982) method. Tohidi (2022) provides an overview of the LPI method as well as the equations used to obtain LPI. LPI values are determined at each soil-boring location for PGA values of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 1.0 g and earthquake magnitudes (Mw) of 5, 5.5, 6, 6.5, 7, 7.5, and 8. Thus, LPI values are determined for each of 70 possible combinations of PGA and Mw, i.e., 70 earthquake scenarios.

Step 3 consists of developing an LPC for the probability of exceeding a target LPI value of 5 and 15 for each primary 234

surficial geologic unit. However, due to the very limited number of soil borings available in some near-surface geologic units, surface geology was separated into floodplain alluvium and non-floodplain strata as mapped in Figure 3.

The non-floodplain strata consist of river terrace alluvium and Tertiary-Cretaceous strata. However, for non-floodplain strata, all borings are within the terrace alluvium, and there are no borings within the Tertiary-Cretaceous strata. The Tertiary-Cretaceous strata have the highest elevation; consequently, they have the lowest GWL and the lowest probability of liquefaction. In summary, LPCs were developed based on SPT data of 25 soil borings within the floodplain alluvium and 44 soil borings from the terrace alluvium.

LPCs determined for this study are based on the probability of exceeding an LPI value of five, which is moderate liquefaction potential based on the results of Iwasaki et al. (1978, 1982) and Toprak and Holzer (2003). The probability of exceeding an LPI of five is based on the number of soil borings with LPI exceeding five (cumulative frequency distribution). An example of computing the probability of LPI . 5 is given in Tohidi et al. (2021) and Tohidi (2022). Similarly, LPCs are also developed based on the probability of exceeding an LPI value of 15, which is “severe” liquefaction potential.

RESULTS Surface Geologic Map The surface geology of Madison County (Figure 2A) was geologically differentiated into three mapping units for seismic and liquefaction hazard analyses (Figure 3): Holocene river floodplain alluvium, Pliocene/Pleistocene river terrace alluvium, and semiconsolidated sediments of Paleogene and Cretaceous age. The Figure 2B cross-section from the Jackson North 7.5-minute geologic quadrangle is representative of the geology that underlies most of Madison County.

Structure Contour Maps The top of the Paleogene and Cretaceous strata are exposed in easternmost Madison County. Over much of the county, 1–25 m of Pliocene/Pleistocene terrace alluvium and 1–9 m of Holocene river alluvium overlie Paleogene and Cretaceous strata (Figure 3).

Structure contour maps were made from surface data of the contact tops of the Claiborne Group, Wilcox Group, Porters Creek Clay, and Cretaceous strata mapped in the published 7.5-minute geologic quadrangle maps of Figure 2 (Figure 4A through F) (Brown, 1968a, b; Parks, 1968a, b, c, d, e, f, g; Jewel, 2006; Antonacci and Hoyal,

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Figure 4. (A) Surface outcrop data (blue dots) used to make structure contour map in “B” of the top of the Claiborne Group with blue lines showing published quadrangle cross-section lines. Planar trend surface structure contour maps of the Wilcox Group (C), the Porters Creek Clay (D), Cretaceous strata (E), and the Paleozoic strata (F) with stratigraphic contact and borehole data points used to constrain the tops of these units.

Elevation is in meters with respect to sea level.

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2011, 2012a, b, 2014) and from drill hole data. Planar trend surfaces were fit to the elevations of the tops of the Wilcox Group and Porters Creek Clay to make planar trend surface structure contour maps (Figure 4C and D). Fitting planes to these formation tops is justified because no faults or folds have been mapped in Madison County (Figure 2A).

Strike and dip of the geologic formations were determined from the contour lines in their planar trend surfaces (Figure 4C and D). These unit tops slope westerly at less than 1°: The Wilcox Group is N28°E, 0.21° NW, and Porters Creek Clay is N27°E, 0.27° NW. The strikes and dips of the tops of the Cretaceous (N28°E, 0.48°NW) and Paleozoic (N21°E, 0.44° NW) in Madison County were determined from the contour lines on their structure contour maps (Figure 4E and F). The structural analysis in this study shows that, in Madison County, the entire stratigraphic section from the top of the Paleogene to the top of the Paleozoic dips westerly at ,1°.

Isopach Maps Holocene river floodplain alluvium thickness measurements along the Forked Deer rivers and Hatchie River tributaries range from 1 to 9 m (Figures 5 and 6A). The floodplain alluvium thickness in this study, as determined from the bridge measurements (Figures 5 and 6A), is an estimate because floodplain alluvium could underlie the channel base or the channel base could be incised into Paleogene strata. Based on available borehole data and lithologic descriptions in the available quadrangles, the floodplain in this study is interpreted to contain a surface silt and clay overbank layer, which overlies point bar sand that may contain gravel.

Pliocene/Pleistocene terrace alluvium thickness is variable with values ranging from 1 to 25 m (Figure 6B). In general, terrace alluvium is thickest along drainage divides and thins towards modern streams. The Pliocene/ Pleistocene river terraces are topographically higher than the Holocene floodplains and consist of surface silt and clay that overlies sand and gravel (Figure 2C). A thin layer of Pleistocene loess overlies the river terrace alluvium. There are at least two terrace levels apparent in 1-m lidar DEM data, but the different terrace levels are not herein differentiated.

Paleogene and Cretaceous strata are at ground surface in easternmost Madison County and underlie western Madison County (Figures 2 and 4 and Table 1). In some areas, the Paleogene strata are covered with a thin veneer of Pleistocene loess. The Claiborne Group thickens northwesterly (Figure 6C), but thickness is irregular because its upper surface has been eroded to various elevations by the entrenchment of Pliocene/Pleistocene rivers and the ongoing entrenchment of Holocene rivers across Madison County (Figure 2A). The Wilcox Group 236

(Figure 6D) and Porters Creek Clay (Figure 6E) thicken to the northwest, and the Cretaceous section thickens southerly (Figure 6F). The Claiborne Group averages 33 m thick, Wilcox Group 37 m, Porters Creek Clay 107 m, and the Cretaceous strata averages 237 m thick in Madison County.

Seismic Ground Motion Maps USGS seismic ground motion maps are based on a uniform standard geology and do not include the effects of near-surface geology (Petersen et al., 2014). Seismic ground motion maps for Madison County were developed (Cramer et al., 2023) using the geological model described in this paper. The shear wave velocities (Vs) used in the USGS hazard model calculations (Petersen et al., 2014) are uniformly higher than the average shear wave velocity over the uppermost 30 m (Vs30) used to develop our ground motion maps. The actual shallow Vs values are averages with uncertainty within a geological formation from multichannel analysis of surface waves/ refraction microtremor (MASW/ReMi) measurements at representative sites in Madison County. The deeper Vs values, which have a much smaller impact on seismic hazard, are from the measurements in similar geological strata in Shelby County, adjusted for differences in depth of burial. Vs values for hazard calculations in Madison County are assigned to the formations in the 3D geology model using formational averages and uncertainty in the manner used in Gomberg et al. (2003). Two of the most important earthquake probabilistic maps from Cramer et al. (2023) are illustrated here (Figure 8) corresponding to the response of structures less than two stories high (PGA) and structures 10 stories high (1.0 seconds).

The units shown on these maps are acceleration in g, which is the acceleration at the earth’s surface of 980.655 cm/s/s. At short periods (PGA), soil response in western Madison County de-amplifies ground motions (Figure 8C) relative to the USGS maps (Figure 8A) due to nonlinear effects at higher ground motions closer to the earthquake source. But nonlinear effects are reduced in eastern Madison County due to increased distance from the earthquake source and increased soil stiffness (consolidation) of the near-surface geology, and hence, short period ground motions are significantly amplified. At long periods (1.0 seconds), soil response is less affected by nonlinear soil effects, and hence, ground motions are amplified (Figure 8D) relative to the USGS maps (Figure 8B), which depends on the distance from the source and soil stiffness (Cramer et al., 2023).

Geotechnical Engineering Results Whereas the LPCs for P[LPI.5] were introduced in Cramer et al. (2023), the LPCs for P[LPI.15] are newly presented in this paper. Figure 9A and B show the LPCs

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Figure 5. Holocene lowland floodplain alluvium thickness measurements. The map on the top right shows numbered locations of floodplain topographic 1-m Lidar profiles and corresponding bridge measurements with the white line showing the border of Madison County. The 1–8 floodplain surface profiles and floodplain thickness measurements are located in “A.” Red dot is bottom of channel measured at bridge locations.

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Figure 6. Isopach maps of the Lowland Holocene floodplain alluvium (A), Pliocene/Pleistocene terrace alluvium (B), Claiborne Group (C), Wilcox Group (D), Porters Creek Clay (E), and Cretaceous strata (F). Contours are in meters with respect to sea level.

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Figure 7. 3D model of the surface and subsurface geology of Madison County. Colors correspond to colors used in Figure 2A. Model is 50X vertical scale. 3D animation is in Appendix B.

for floodplain alluvium and non-floodplain strata for the probability of exceeding LPI of 5 and 15 denoted as P [LPI.5] and P[LPI.15] versus the ratio of PGA over magnitude scaling factor (MSF). MSF corrects for earthquake magnitudes other than 7.5 and is computed using the revised relationship by Idriss (1999).

As was expected, the Forked Deer Rivers and Hatchie River tributary floodplain alluvium LPCs are significantly higher than the non-floodplain strata LPCs for both P[LPI.5] and P[LPI.15] due to a shallow groundwater table and the presence of more sandy soils.

Cramer et al. (2023) evaluated earthquake liquefaction potentials for Madison County over a range of New Madrid earthquake magnitudes and epicenter locations.

One such evaluation was made assuming a M 7.3 Axial fault earthquake. Such an earthquake would result in an LPI . 5 on the floodplains in Madison County (Figure 3), thus resulting in moderate liquefaction potential.

CONCLUSIONS Holocene alluvium, with estimated thicknesses ranging from 1 to 9 m, underlies the Middle Fork and South Fork of Forked Deer River and Hatchie River tributary

floodplains in Madison County. The surface geology of Madison County also consists of extensive Pliocene/ Pleistocene river terraces that have been incised by Holocene rivers. We speculate that the terraces of Madison County are remnant headwater floodplains of the ancestral Mississippi/Ohio river. There are no radiometric dates for the Madison County terraces, but it is believed that the terraces are equivalent to those mapped in westernmost Tennessee (Saucier, 1987; Van Arsdale et al., 2007; Lumsden et al., 2016; Odum et al., 2020; Harrison, 2022; Reichenbacher et al., 2022). Specifically, the highest Madison County terrace may be equivalent to the 3.6 Ma Upland Complex and sequentially lower terraces equivalent to the Henderson, Humboldt, and Hatchie terraces preserved in the downstream reaches of the Forked Deer River in Dyer and Lauderdale counties and the Hatchie River in Lauderdale and Tipton counties (Figure 1A) (Harrison, 2022; Reichenbacher et al., 2022). This terrace interpretation is consistent with the regional terrace mapping by Saucier (1987) wherein he mapped Humboldt and Hatchie terraces along the Hatchie River in southwestern Madison County.

Surface and subsurface geologic mapping has provided the 3D geology (Figure 7 and Appendix B) and

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Figure 8. Two percent–in–50 year hazard maps showing the 2014 U.S. Geological Survey’s national seismic hazard map for site class BC conditions for (A) peak ground acceleration (PGA) and (B) 1.0 second spectral acceleration. (C) and (D) equivalent hazard maps accounting for the effects of local geology for Madison County (from Cramer et al., 2023).

the Pliocene-Quaternary geologic history of Madison County. This research is of value to those who seek subsurface information, such as potential sand and gravel resources in the river terraces of Madison County. As shown in Figure 8, the local near-surface geology significantly influences the expected ground motions during future earthquakes and, thus, provides a more accurate and detailed seismic hazard assessment than the uniform regional geology used in the 2014 USGS seismic hazard maps (Petersen et al., 2014). When comparing the ground motion map in this study with the USGS seismic hazard maps at short periods (PGA), the surface geology 240

de-amplifies the ground motion effects in western Madison County and amplifies these effects in eastern Madison County (Figure 8). This is due to an increase in consolidation in the Cretaceous strata and closer proximity to the New Madrid earthquake source in the west.

When comparing 1.0-second hazard maps, there is an overall increase in ground-shaking hazard in Madison County that depends on soil stiffness and distance from the earthquake source. The LPCs and the associated liquefaction hazard maps developed for Madison County indicate that liquefaction potential is higher in the Forked Deer River and Hatchie River tributary floodplains due to

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3D Geologic Mapping of Madison County, Tennessee

Figure 9. Madison County liquefaction potential index (LPI)–based liquefaction probability curves (LPCs) of floodplains (A) and non-floodplains (B) from standard penetration test data. The graphs show the probability of exceeding LPI of 5 and 15 versus the ratio of peek ground acceleration over magnitude scaling factor. The LPCs for P[LPI.5] were introduced in Cramer et al. (2023), but the LPCs for P[LPI.15] are new to this paper.

shallow groundwater table and the presence sandy soils.

This study of Madison County, Tennessee, further illustrates the importance of knowing the local near-surface stratigraphy and strata thickness in the appraisal of potential seismic ground shaking and liquefaction.

ACKNOWLEDGMENTS We thank Luke Ewing, William Mann, and Elaine Foust of the Tennessee Department of Environment and Conservation (TDEC), and the U.S. Army Corps of Engineers, the Tennessee Department of Transportation, and Construction Materials Laboratory, Inc., for providing data needed in this project. We also acknowledge the importance of the quadrangles mapped by Vince Antonacci of TDEC, which were integral in making this geological model, and the Jackson Energy Authority and Dr. John Smith for providing well groundwater data.

REFERENCES ANTONACCI, V. AND HOYAL, M., 2011, Geologic Map of the Medina Quadrangle, Tennessee: State of Tennessee Department of Environment and Conservation, Division of Geology, scale 1:24,000.

ANTONACCI, V. AND HOYAL, M., 2012a, Geologic Map of the Adair Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

ANTONACCI, V. AND HOYAL, M., 2012b, Geologic Map of the Humboldt Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

ANTONACCI, V. AND HOYAL, M., 2014, Geologic Map of the Bells Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology. Draft Open File Map, scale 1:24,000.

BROWN, D. L., 1968a, Geologic Map of the Henderson Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

BROWN, D. L., 1968b, Geologic Map of the Luray Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

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241

Harrison, Tohidi, Van Arsdale, Cramer, and Arellano CHIU, J. M.; JOHNSTON, A. C.; AND YANG, Y. T., 1992, Imaging the active faults of the central New Madrid seismic zone using PANDA array data: Seismological Research Letters, Vol. 63, pp. 375–393.

COX, R. T.; CHERRYHOMES, J.; HARRIS, J. B.; LARSEN, D.; VAN ARSDALE, R. B.; AND FORMAN, S. L., 2006, Paleoseismology of the southeastern Reelfoot rift in western Tennessee and Implications for intraplate fault zone evolution: Tectonics, Vol. 25, pp. 1–17.

COX, R. T.; LUMSDEN, D. N.; AND VAN ARSDALE, R. B., 2014, Possible relict meanders of the Pliocene Mississippi River and their implications: Journal Geology, Vol. 122, pp. 609–622.

COX, R. T.; VAN ARSDALE, R. B.; HARRIS, J. B.; AND LARSEN, D., 2001, Neotectonics of the southeastern Reelfoot Rift zone margin, central United States, and implications for regional strain accommodation: Geology, Vol. 29, pp. 419–422.

COX, R. T.; VAN ARSDALE, R.; CLARK, D.; HILL, A.; AND LUMSDEN, D., 2013, A revised paleo-earthquake chronology on the southeast Reelfoot rift margin near Memphis, Tennessee: Seismological Research Letters, Vol. 84, pp. 402–408.

CRAMER, C. H., 2006, Quantifying the uncertainty in site amplification modeling and its effects on site-specific seismic-hazard estimation in the Mississippi embayment and adjacent area: Bulletin Seismological Society America, Vol. 96, pp. 2008–2020.

CRAMER, C. H. AND BOYD, O. S., 2014, Why the New Madrid Earthquakes are M7-8 and the Charleston Earthquake is »M 7: Bulletin Seismological Society America, Vol. 104, pp. 2884–2903. doi:10.

1785/0120120257 CRAMER, C. H.; DHAR, M. S.; AND ARELLANO, D., 2018a, Update of the urban seismic and liquefaction hazard maps for Memphis and Shelby County, Tennessee: liquefaction probability curves and 2015 hazard maps: Seismological Research Letters, Vol. 89, pp. 688–701.

CRAMER, C. H.; VAN ARSDALE, R.; ARELLANO, D.; PEZESHK, S.; HORTON, S.; WEATHERS, T.; NAZEMI, N.; JIMENEZ, J.; TOHIDI, H.; AND OGWENO, L., 2018b, Seismic and liquefaction hazard maps for Lake County, northwestern Tennessee: Geological Society America Abstracts Programs, Vol. 50, No. 3. doi:10.1130/abs/2018SE-312570 CRAMER, C. H.; VAN ARSDALE, R.; ARELLANO, D.; PEZESHK, S.; HORTON, S. P.; WEATHERS, T.; NAZEMI, N.; TOHIDI, H.; REICHENBACHER, R.; HARRISON, V.; BHATTARAI, R.; AKHANI, M.; BOUZEID, K.; AND PATTERSON, G. L., 2023, Seismic and liquefaction hazard maps for file western Tennessee counties: Seismological Research Letters, Vol. 94, pp. 2813–2830.

CRAMER, C. H.; VAN ARSDALE, R.; HARRISON, V.; ARELLANO, D.; PEZESHK, S.; HORTON, S. P.; WEATHERS, T.; NAZEMI, N.; JIMENEZ, J.; TOHIDI, H.; AND OGWENO, L. P., 2019, Lake County Seismic and Liquefaction Hazard Maps: Center for Earthquake Research and Information Report, 129 p.

CRAMER, C. H.; VAN ARSDALE, R.; HARRISON, V.; ARELLANO, D.; TOHIDI, H.; AND BHATTARAI, R., 2021, Tipton County Seismic and Liquefaction Hazard Maps: Center for Earthquake Research and Information Report, 89 p.

CRAMER, C. H.; VAN ARSDALE, R.; HARRISON, V.; ARELLANO, D.; TOHIDI, H.; BHATTARAI, R.; PEZESHK, S.; AND SENEJANI, M., 2022, Madison County Seismic and Liquefaction Hazard Maps: Center for Earthquake Research and Information Report, 99 p.

CRAMER, C. H.; VAN ARSDALE, R.; HARRISON, V.; BOUZEID, K.; ARELLANO, D.; TOHIDI, H.; PEZESHK, S.; HORTON, S. P.; BHATTARAI, R.; NAZEMI, N.; AND FARHADI, A., 2020a, Lauderdale County Seismic and Liquefaction Hazard Maps: Center for Earthquake Research and Information Report, 85 p.

CRAMER, C. H.; VAN ARSDALE, R.; REICHENBACHER, R.; ARELLANO, D.; TOHIDI, H.; PEZESHK, S.; HORTON, S.; BHATTARI, R.; NAZEMI, N.; AND FARHADI, A., 2020b, Dyer County Seismic and Liquefaction Hazard Maps: Center for Earthquake Research and Information Report, 89 p.

CSONTOS, R. AND VAN ARSDALE, R., 2008, New Madrid seismic zone fault geometry: Geosphere, Vol. 4, No. 5, pp. 802–813.

242

CUPPLES, W. AND VAN ARSDALE, R., 2014, The preglacial “Pliocene” Mississippi River: Journal Geology, Vol. 122, pp. 1–15.

GOMBERG, J.; WALDRON, B.; SCHWEIG, E.; HWANG, H.; WEBBERS, A.; VAN ARSDALE, R.; TUCKER, K.; WILLIAMS, R.; STREET, R.; MAYNE, P.; STEPHENSON, W.; ODUM, J.; CRAMER, C.; UPDIKE, R.; HUTSON, S.; AND BRADLEY, M., 2003, Lithology and Shear-Wave Velocity in Memphis, Tennessee: Seismological Society of America, Vol. 93, No 3, doi:10.

1785/0120020164 HARRISON, V. J., 2022, 3D geologic mapping of Lauderdale and Tipton Counties, Tennessee: A geostatistical approach: Memphis, TN, Department of Earth Sciences, University of Memphis, MS Thesis, 112 p. doi:10.1785/0220230036 IDRISS, I. M., 1999, Presentation notes: an update of the Seed-Idriss simplified procedure for evaluating liquefaction potential. In Proceedings of TRB Workshop on New Approaches to Liquefaction: Federal Highway Administration, Washington, D.C., Annual Publication No. FHWARD-99-165.

IWASAKI, T.; TATSUOKA, F.; TOKIDA, K.; AND YASUDA, S., 1978, A practical method for assessing soil liquefaction potential based on case studies at various sites in Japan. In Proceedings of the 2nd International Conference on Microzonation for Safer Construction Research and Application, pp. 885–896.

IWASAKI, T.; TOKIDA, K.; TATSUOKA, F.; WATANABE, S.; YASUDA, S.; AND SATO, H., 1982, Microzonation for soil liquefaction potential using simplified methods. In Proceedings 3rd International Conference on Microzonation, pp. 1319–1330.

JEWEL, J. W., 2006, Geologic Map of the Jackson North Quadrangle, Tennessee: State of Tennessee Department of Environment and Conservation, Division of Geology, scale 1:24,000.

LUMSDEN, D. N.; COX, R. T.; VAN ARSDALE, R. B.; AND CUPPLES, W. B., 2016, Petrology of Pliocene Mississippi River alluvium: Provenance implications: Journal Geology, Vol. 124, pp. 501–517.

MARKEWICH, H. H.; WYSOCKI, D. A.; PAVICH, M. J.; RUTLEDGE, E. M.; MILLARD, H. T.; RICH, F. J.; MAAT, P. B.; MEYER, R..; AND MCGEEHIN, J. P., 1998, Paleopedology plus TL, 10Be, and 14C dating as tools in stratigraphic and paleoclimatic investigations, Mississippi River valley, U.S.A.: Quaternary International, Vol. 51, pp. 143–167. doi:10.1016/s1040-6182(97)00041-4 ODUM, W.; HOFMANN, F.; VAN ARSDALE, R.; AND GRANGER, D., 2020, New 26Al/10Be and (U-Th)/He constraints on the age of the Upland Complex, central Mississippi River Valley: Geomorphology, Vol. 371, pp. 1–9.

PARKS, W. B., 1968a, Geologic Map of the Beech Bluff Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

PARKS, W. B., 1968b, Geologic Map of the Cedar Grove Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

PARKS, W. B., 1968c, Geologic Map of the Claybrook Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

PARKS, W. B., 1968d, Geologic Map of the Jackson South Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

PARKS, W. B., 1968e, Geologic Map of the Juno Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

PARKS, W. B., 1968f, Geologic Map of the Medon Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology, scale 1:24,000.

PARKS, W. S., 1968g, Geologic Map of the Beech Bluff Quadrangle, Tennessee: State of Tennessee Department of Conservation, Division of Geology. Draft Open File Map, scale 1:24,000.

PETERSEN, M. D.; MOSCHETTI, M.; POWERS, P.; MUELLER, C.; HALLER, K.; FRANKEL, A.; ZENG, Y.; REZAEIAN, S.; HARMSEN, S.; BOYED, O.;

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3D Geologic Mapping of Madison County, Tennessee FIELD, N.; CHEN, R.; RUKSTALES, K.; LUCO, N.; WHEELER, R.; WILLIAMS, R.; AND OLSEN, A., 2014, The 2014 Update of the United States National Seismic Hazard Models: United States Geological Survey, OFR 2014-X1091, 255 p.

REICHENBACHER, R.; VAN ARSDALE, R; COX, R.; AND CRAMER, C., 2022, New Madrid Seismic Zone in Dyer County, Tennessee: Environmental Engineering Geoscience Journal, Vol. 28, No. 2, pp. 147–171.

RIX, G. J. AND ROMERO-HUDOCK, S., 2006, Liquefaction potential mapping in Memphis and Shelby County, Tennessee: Report to U.S. Geological Survey, Denver, Colorado, 27 p.

RODBELL, D. T., 1996, Subdivision, subsurface stratigraphy, and estimated age of fluvial terrace deposits in northwestern Tennessee: U.S. Geologic Survey Bulletin, Vol. 2128, 24 p.

SAUCIER, R. T., 1987, Geomorphological interpretations of late Quaternary terraces in western Tennessee and their regional tectonic implication: U.S. Geologic Survey Professional Paper 1336-A, 19 p.

SAUCIER, R. T., 1994, Geomorphology and quaternary geologic history of the Lower Mississippi Valley: Vicksburg, Mississippi: U.S. Army Engineer Waterways Experiment Station, Vol. 1, 364 p., and Vol. 2, map plates.

SCHRADER, T. P., 2008, Potentiometric surface in the Sparta-Memphis aquifer of the Mississippi embayment Spring 2007: U.S. Geological Survey Scientific Investigations Map 3014.

SEED, H. B. AND IDRISS, I. M., 1971, Simplified procedure for evaluating soil liquefaction potential: Journal Soil Mechanics Foundations Division, Vol. 97, No. 9, pp. 1249–1273.

TOHIDI, H., 2022, Evaluation of surficial non-liquefiable soil layer impacts on liquefaction surface manifestation of the West Tennessee area based on finite difference methods: Memphis, TN, Department of Civil Engineering, University of Memphis, Doctoral Dissertation.

TOHIDI, H.; ARELLANO, D.; AND CRAMER, C. H., 2021, Initial liquefaction hazard mapping of northwest Tennessee based on liquefaction probability curves: Geo-Extreme 2021, ASCE, Climatic Extremes and Earthquake Modeling, doi:10.1061/9780784483695.029 TOPRAK, S. AND HOLZER, T. L., 2003, Liquefaction potential index: Field assessment: Journal Geotechnical Geoenvironmental Engineering, Vol. 129, No. 4, pp. 315–322.

TUTTLE, M. P.; SCHWEIG, E. S.; SIMS, J. D.; LAFFERTY, R. H.; WOLF, L. W.; AND HAYNES, M. L., 2002, The earthquake potential of the New Madrid seismic zone: Seismological Society America Bulletin, Vol. 92, pp. 2080–2089.

TUTTLE, M. P.; WOLF, L. W.; STARR, M. E.; VILLAMOR, P.; MAYNE, P. W.; LAFFERTY, R. H.; et al., 2019, Evidence for large New Madrid earthquakes about A.D. 0 and B.C. 1050, Central United States: Seismological Research Letters, Vol. 90, No. 3, pp. 1393–1406.

VAN ARSDALE, R. B.; BRESNAHAN, R. P.; MCCALLISTER, N. S.; AND WALDRON, B., 2007, The Upland Complex of the central Mississippi River Valley: Its origin, denudation, and possible role in reactivation of the New Madrid seismic zone. In Stein, S. and Mazzotti, S. (Editors), Continental Intraplate Earthquakes: Science, Hazard, and Policy Issues: Geological Society of America Special Paper 425, pp. 177–192.

YOUD, T. L. AND IDRISS, I. M., 2001, Liquefaction Resistance of Soils: Summary Report from the 1996 NCEER and 1998 NCEER/NSF Workshops on Evaluation 992 of Liquefaction Resistance of Soils: Journal Geotechnical Geoenvironmental Engineering, Vol. 127, No. 4, pp. 297–313.

ZHU, Y.; WANG, Z.; CARPENTER, N. S.; WOOLERY, E. W.; AND HANEBERG, W. C., 2021, Mapping fundamental-mode site periods and amplifications from thick sediments: An example from the Jackson Purchase region of western Kentucky, central United States: Bulletin Seismological Society America, Vol. 111, pp. 1868–1884. doi:10.

1785/0120200300

APPENDICES Appendix A contains spreadsheets of the data points used to create the structure contour maps. Appendix B contains a video animation of the 3D geological model of Madison County, Tennessee.

The Appendices can be found at: https://www.aegweb. org/e-eg-supplements

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Using Landslides to Locate the Epicenter for the Historic 1882 Earthquake in Colorado JUSTIN MARCHLEWICZ* 512 Cavett Street, Van Wert, OH 45891

PAUL SANTI 1516 Illinois Street, Golden, CO 80401

Key Terms: Landslides, Seismic, Colorado ABSTRACT On November 7, 1882, the largest earthquake in Colorado’s recorded history impacted an area estimated to be 470,000 km2 (181,000 mi2). While differing accounts of intensity were recorded by various communities at the time, the distribution of reported damages indicated a likely magnitude between 6 and 7. This study aimed to refine this estimate using landslides within the region that were likely to be co-seismic. Previously proposed methodology was used to calculate surface roughness values for landslides mapped at various scales digitized and compiled by the Colorado Geological Survey. A search radius of 54 km surrounding the epicentral estimate for the earthquake was chosen to evaluate the relative ages of landslides within the defined region.

While the proposed methodology requires a calibration using age-dated landslides within the data set, the use of surface roughness as a relative age scale proved to be sufficiently useful to constrain an area within the study that showed anomalously high surface roughness values. Based on this earthquake being one of the only large earthquakes to have occurred in recorded history in Colorado, as well as a lack of wide distribution in the anomalous region expected from a storm event, this anomalous area containing high surface roughness landslides across varying base lithologies was concluded to have a high probability of being co-seismically induced. Utilizing this information, a new initiation ellipse was generated from these data.

INTRODUCTION On November 7, 1882, the largest earthquake recorded in Colorado’s history affected an area estimated to be 470,000 km2 (181,000 mi2). The reported Mercalli intensities at the time ranged from II to VII, and by utilizing regression equations that compared intensity to area *Corresponding author email: jmarchlewicz@mines.edu

felt, Kirkham and Rogers (1986) assigned a magnitude of ML 6.2 6 0.3. While many attempts have been made by prior researchers to constrain the epicenter of this historic earthquake, it is still uncertain on precisely which fault the slip occurred. While Colorado has not had additional earthquakes close to this magnitude since 1882 or in recorded history, it is important to attempt to decipher where this earthquake occurred so that additional studies of the fault can be conducted to see if another earthquake like the one felt in 1882 is possible to occur again.

The purpose of this study was to constrain a new epicenter estimate for the 1882 earthquake by utilizing co-seismic landslides resulting from this event, a distinctly new approach. If it is possible to differentiate those landslides that likely occurred around the same time as this earthquake, then these landslides can be used to confirm the current epicenter estimate or identify a new location.

BACKGROUND Several previous studies have been undertaken to better understand this earthquake. The primary study on which this research is based comes from Kirkham and Rogers (1986), who compiled reported intensities following the 1882 earthquake. As stated within their study, based on the work of Dames and Moore (1981), it was found that fewer than 200,000 people lived in Colorado at the time of the earthquake, with many living in rural areas. Additionally, several other factors complicated the accuracy of how the earthquake was reported at the time, with the earthquake occurring on a major election day as polls closed, causing some newspapers to entirely neglect reporting the tremor. Other sources tended to exaggerate the impacts of the earthquake’s effects or to simply not report it at all, as their readers only wanted to read uplifting stories. Finally, hearsay reports emerged in certain newspapers, where earthquake effects in towns with damage were reported by towns where no major damage occurred. By attempting to minimize these effects when evaluating published reports of damage from this earthquake, Kirkham and Rogers (1986) assembled an isoseismal map from this data set, noting the particular difficulty that emerged due to

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Figure 1. Kirkham and Rogers (1986) isoseismal map constructed utilizing reported intensities following the 1882 earthquake. Colorization provided

by Colorado Geological Survey.

conflicting reports and a somewhat nonsensical geographic distribution of reported intensities. After a reevaluation of the reports, and by assigning differing levels of credibility to the published articles pertaining to damage reported, they constructed an isoseismal map of the felt area, choosing a predicted epicenter that they stated in their report may be off by up to half a degree of latitude or longitude.

An updated and colorized version of this map (Kirkham and Rogers, 1986) published by the Colorado Geological Survey (CGS) is shown in Figure 1.

Prior reports from Dames and Moore (1981) had suggested an epicenter along the Dudley Gulch graben (see location on Figure 2), but from radiocarbon dating of unfaulted deposits above the fault, Kirkham and Rogers (1986) concluded that no surface ruptures along that fault had emerged for at least 1,230 6 60 years. Additionally, Eckert (1982) thoroughly studied the Dudley Gulch graben and found no evidence of either historic or recent movement along the fault. Before the Dames and Moore report, another estimate was made by Hadsell (1968) utilizing a similar technique to Kirkham and Rogers (1986) but 246

relying on a different weighting of reported intensities (Figure 2). For the isoseismal map that Kirkham and Rogers (1986) generated, the reported intensities from Colorado Springs were assigned a less credible weight than given by Hadsell, leading to an epicentral estimate farther north than Hadsell had predicted (Figure 2). Additionally, the Kirkham and Rogers (1986) estimate was later given further credibility by Spence et al. (1996), who analyzed the 1984 Laramie Mountains earthquake and compared the generated isoseismal map for that event with the one created for the 1882 earthquake. From their study, it was proposed that while the felt area for the 1882 earthquake should likely have been larger, the Kirkham and Rogers (1986) epicenter estimate was roughly central to this new proposed felt area, consistent with the data found from the 1984 Laramie Mountains isoseismal map.

METHODOLOGY To conduct this study, the epicenter estimate made by Kirkham and Rogers (1986) was used as a starting point

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Landslides Reveal Epicenter of 1882 Earthquake

Figure 2. Locations of predicted epicenters for the 1882 earthquake proposed by Kirkham and Rogers (1986), Dames and Moore (1981), and Hadsell (1968) within Colorado. ESRI base map is included for reference.

as a likely zone for landslides initiated by the earthquake.

The Kirkham and Rogers (1986) epicenter was used due to additional support for the epicentral area from Spence et al. (1996). Utilizing estimates from Keefer (1984), a maximum likely initiation radius would be approximately 36 km around the epicentral location, with a 54 km radius included due to uncertainty in the estimated epicentral location. While attempting to verify the validity of this initiation radius, archived newspaper accounts of the event were searched in a similar manner to that done by Kirkham and Rogers (1986) to determine if rockfalls or landslides being initiated from this earthquake were recorded. From The Pueblo Daily Chieftain (1882) published on November 11, 1882, an article titled “Mother Earth” was found describing rockfalls and a landslide as recounted by ranchmen living in the Rocky Mountains near Pueblo, CO, at the time.

While these accounts fall well outside the initiation radius

predicted by Keefer (1984), it is likely that the low attenuation of seismic energy through the igneous/metamorphic bedrock of the Rocky Mountains helps to account for these observations. Due to uncertainties in the true extent of possible co-seismic landslides initiated by this event, a 54 km radius was chosen as the largest search radius to represent 150% the size of the primary search radius. An additional, smaller search radius of 18 km was included as 50% of the primary search radius to observe varying spatial trends between these regions. A representation of the search radii away from the Kirkham and Rogers (1986) epicenter estimate is shown in Figure 3, with an inlay of prior mapped landslides digitized by the CGS used to conduct this study. Once this data set was loaded into ArcGIS Pro, the lithology within the study area was derived from Tweto (1979), as shown in Figure 4. Additionally, light detection and ranging (LiDAR) and 1 m digital elevation model (DEM) data for the study region were loaded

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Figure 3. Area of interest with landslides identified by Colorado Geological Survey colored by source and radii overlain with maximum landslide initiation radius defined by Keefer (1984) and Front Range epicenter predicted by Kirkham and Rogers (1986).

through the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) LidarExplorer application (U.S. Geological Survey, 2024), and a slope angle map was generated, as shown in Figure 5.

Within the study area, significant numbers of CGSidentified landslides overlie regions designated as glacial drift or unconsolidated material. The remainder of designated landslides lie on top of Mesozoic-aged sedimentary clastic rock, the Ingleside and Fountain Formations, Proterozoic metamorphic rocks, and granitic rocks of the 1700 Ma age group. From a study of this information, the landslides present within the study area generally fell into two categories: high slope angles (.40°) underlain by what was considered to be competent bedrock (igneous and metamorphosed igneous rock), and shallower slope angles (,40°) underlain by what was considered to be less competent bedrock or sediments (sedimentary formations and glacial drift).

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In addition to an analysis of slope, the range of slope aspects within the study area was also calculated, using the aspect tool within ArcGIS Pro (Figure 6). Following this, a summation of raster cells within the data set identified by 45° aspect increments was performed, and the data were exported to visualize the quantity of cells identified across the entire study region within the 54 km search radius as well as only on CGS-identified landslides.

While these attempts to understand and characterize the study area were useful, in order to identify landslides that were likely to be co-seismic, it was necessary to estimate an age for landslides in the region. Following the methodology defined by LaHusen et al. (2016), a calculation of surface roughness was performed for the 611 defined landslides within the data set. To conduct this analysis, first, the slope map generated using the USGS 1 m DEM was clipped to the extent of landslides identified by the CGS within the study area across several mapped

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Landslides Reveal Epicenter of 1882 Earthquake

Figure 4. Generalized lithology for the study area for the U.S. Geological Survey. The central portion of the Front Range is primarily defined by igneous and metamorphic components, with sedimentary and unconsolidated sediments lying to the east and west. Mapping was conducted by Tweto (1979).

scales (24,000, 48,000–100,000, 250,000, and Boulder County LiDAR data set). From the defined methodology, surface roughness is defined as the average standard deviation of slope within a landslide deposit. To achieve this, the focal statistics tool within ArcGIS Pro was used to calculate the standard deviation within landslide deposits for a 3 m 3 3 m window per cell.

Next, histograms of recorded standard deviations were generated for each landslide, and a mean standard deviation value was recorded for each landslide.

While the proposed methodology advised the use of the zonal statistics tool to calculate the mean of the standard deviation values assigned to all pixels within each landslide polygon, ArcGIS Pro was unable to successfully complete this calculation for an unknown reason, so mean standard deviations determined from histograms were used instead.

Overall, there is no difference in the mean values that were

calculated, with the only difference being the amount of time that processing required. The methodology from LaHusen et al. (2016) also calls for a calibration of this relative age-dating method with absolute dating of landslide deposits within the data set, but this was beyond the scope and funding of this study. As such, this study primarily focused on the use of these relative ages with the assumption that higher calculated surface roughness values indicated younger landslide deposits, and lower values indicated older landslide deposits, due to younger landslide deposit surfaces having had less time to weather to less variable topography.

RESULTS Following the summation of aspects per raster cell within both the 54 km study area and only within

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Figure 5. Slope angles calculated from U.S. Geological Survey 1 m digital elevation model from light detection and ranging (LiDAR) data utilizing the slope tool within ArcGIS Pro.

CGS-identified landslides, rose diagrams were generated from this process split by identified cardinal directions for aspect, illustrated in Figure 7. Overall, the rose diagram for the entire study area shows no clear pattern, as expected for an indiscriminate analysis of a large area.

However, for the rose diagram generated only for cells identified by CGS as landslides, a clear preference for E-W orientations emerges, as well as a distinct lack of N-S orientations. While it is not immediately clear why this trend exists, it is possible that preferential weathering may occur on N-S slopes within the study area, which made identification of landslides more challenging, or simply that fewer N-S–oriented slopes are present within the study area.

Following the calculation of surface roughness values per landslide, an analysis of these values was conducted to evaluate the distribution within each of the four scales at which landslides were mapped, as well as a combined 250

set with all recorded landslides included. Figure 8 shows the distribution of surface roughness values calculated within the entire data set. While a few notable outliers exist within the data, overall a normal distribution of roughness values appears to emerge. Additionally, a review of landslides given particularly high or low average standard deviation values was conducted to evaluate the validity of the scoring. No topographic irregularities or clear errors in data were seen for these outliers.

While the data appear to follow a roughly normal distribution overall, the next step was to evaluate whether a spatial distribution existed within the data set. If an area of anomalously high surface roughness values can be found over a region, then it is possible that a “recent” triggering event caused these landslides to form. While this study used a qualitative form of age dating, this data set could be calibrated from quantitative age dating of landslides included within the data set for further validation.

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Figure 6. Aspect map of the study area generated utilizing the aspect tool within ArcGIS Pro with U.S. Geological Survey 1 m digital elevation model.

To begin this analysis, centroids for the landslides present within the study area were calculated to better visualize the clustering of data present within the data set, as well as to prepare for data contouring. Figure 9 is a map of the study area with landslide centroids colored by surface roughness values. To gauge if there was a spatial trend between the Kirkham and Rogers (1986) epicenter and the surface roughness values assigned to the landslide centroids, the near tool within ArcGIS Pro was used to calculate distances between landslide centroids and the Kirkham and Rogers (1986) epicenter. Figure 10 is a chart comparing surface roughness values per landslide centroid compared against the distance of the centroid to the Kirkham and Rogers (1986) epicenter. As shown, there is not a strong trend between distances to the Kirkham and Rogers (1986) epicenter and surface roughness values, with a general negative trend emerging (containing some data scatter) around 35 km.

Based on the color patterns in Figure 9, a spatial trend appeared to exist within the data, with a grouping of rougher (younger) values in the mid-lower left quadrant.

To investigate this possibility, a kriged raster was generated to contour the surface roughness values of all points within the data set. This rougher region is even more apparent in Figure 11. Overlain on this figure is a data set of mapped faults within Colorado from the USGS (Tweto, 1979) to identify faults that intersected this region. We chose a new epicenter along the fault lying closest to the center of the region, indicated on the map as a point. Additionally, once this new epicenter was chosen, surface roughness values were plotted against the distances of the landslide centroids to this new epicenter, and the results are shown in Figure 12. From this graph, the data scatter seen when conducting the same process as that conducted for the Kirkham and Rogers (1986) epicenter in Figure 10 demonstrates an increase in the correlation with a negative linear

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Figure 7. Rose diagram of tabulated aspect pixels within the entire study area (left) and over the pixels within digitized landslide regions identified by the Colorado Geological Survey (right). Color scale represents calculated angle of pixel, and radii represent the number of pixels identified for each aspect.

trend, more than doubling the R2 value associated with the fit. While not every landslide contained within this data set is likely to have a co-seismic origin, for such a strong trend to emerge from this analysis, it is logical to conclude that a large event in recent history occurred in this region, causing several landslides at a similar time.

DISCUSSION Kirkham and Rogers (1986) concluded that even though their methodology required a re-analysis of reported intensities, they were still able to identify a relatively constrained region in which the earthquake epicenter

Figure 8. Distribution of surface roughness values for the 611 landslides within the study area. With the exception of a few outliers, a generally normal distribution is formed within the data.

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Figure 9. Centroids of landslides within the study area colored by calculated surface roughness values.

was likely to fall. They noted that their estimate of the exact epicenter was likely to be off by as much as a half degree of latitude or longitude. From our use of the methodology proposed by LaHusen et al. (2016),

even without an absolute age calibration, the relative ages estimated by calculating the surface roughness values of landslides identified a region of anomalously high roughness values. This identified region

Figure 10. Surface roughness values for each landslide compared to the distance of their centroid from the epicenter indicated by Kirkham and Rogers (1986).

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Figure 11. Kriged surface roughness map generated using landslide centroids, overlain by Colorado faults mapped by U.S. Geological Survey (from Tweto, 1979). An alternate epicenter marked by a filled red circle is located approximately 35 km southwest of Kirkham and Rogers (1986) epicenter.

falls within the estimation of error cited by Kirkham and Rogers (1986), with the new predicted epicenter being 35 km away. While the new epicenter estimate was chosen based on proximity to the center portion

of the identified region of high roughness, it is more appropriate to designate an ellipse based on the information obtained to further constrain the likely area where the epicenter may have been. Figure 13 shows

Figure 12. Surface roughness values for each landslide compared against their centroid’s distance to the new predicted epicenter.

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Figure 13. New proposed initiation ellipse compared to the original initiation ellipse defined by Kirkham and Rogers (1986).

a new ellipse defining a zone of likely initiation for the 1882 earthquake, centered around our new estimated epicenter. This ellipse was defined to best contain the region with surface roughness values above 2.707, representing the anomalous zone this study identified.

To better illustrate the size of this ellipse compared to previous studies, the possible earthquake initiation ellipse proposed by Kirkham and Rogers (1986) is included within the figure. Based on our results, we demonstrate a significant reduction in the size of the likely initiation area.

While the original aim of this study was to identify landslides within the study area that had the potential to be co-seismic for a statistical determination of an epicenter, the strong spatial trend observed within the surface roughness values for the region identified a likely product of the 1882 earthquake. While it is possible that a localized storm could have produced a large number of temporally consistent landslides within this relatively

small area, we presume it is unlikely that such a localized and powerful storm occurred in the past. To further support this reasoning, data collected during and following the exceptionally large 2013 Front Range rainfall event were incorporated into the study utilizing data compiled by Colorado State University (CSU, 2013) for peak cumulative rainfall totals over 12 hours during the event (Figure 14), and this data set was then compared with USGS-compiled debris flows/landslides recorded following this event (Figure 15). As shown, regions with higher 12 hour rainfall totals appear to be correlated with the number of recorded debris flows/landslides, but the correlation is not perfect. The zone of debris flows and landslides from 2013 covers an area over 50 km in width and over 150 km long, encompassing the main concentration of the inventory in Figure 15. This is similar to the area of high roughness landslides from the inventory we used in Figure 11, using a roughness of 1.77 (approximately the

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Figure 14. Cumulative rainfall measurements over 12 hours during the 2013 Front Range rainfall event (right) paired with locations exceeding 50, 100, 500, and 1,000 year recurrence intervals for 12 hour precipitation totals (left). Data are from CSU (2013).

median value in Figure 8) as the threshold—these are the three colors in Figure 11 indicating the areas of highest roughness. In this brief comparison, then, a storm as large as the 2013 storm would be needed to affect an area this large. Given that the 2013 storm surpassed the 1,000 year recurrence interval, it would be rare to have experienced a storm of this magnitude recently enough that the landslides would still have the high roughness values measured, and even more rare for such an event to have occurred but remain unrecorded in contemporaneous newspaper accounts.

CONCLUSION The 1882 earthquake that occurred in Colorado caused widespread damage to existing structures across large distances based on reported damages and eyewitness accounts. While Dames and Moore (1981) indicated that some of the reports were exaggerated or under-representative of the true impacts of this earthquake and its aftershocks, Kirkham and Rogers (1986) effectively deciphered the data available to them at the time to develop a geographical ellipse that they were confident contained the epicenter for this earthquake. Their specific assignment of an epicenter had less confidence but was chosen as the best fit for the available data. While their methodology was based on data that had variable credibility, our work for this study corroborates their estimations, including the likely error in the distance between their chosen 256

epicenter and the location we suggest for a new initiation ellipse. By utilizing data available today, such as a USGS 1 m DEM for the study area and a digitized repository of landslides from prior Front Range mapping efforts at various map scales compiled by the CGS, a more precise constraint on the epicenter location was identified using the methodology proposed by LaHusen et al. (2016) that relied on topographic surface roughness as a proxy for age. By determining a region within the study area with a concentration of higher than average surface roughness values for landslides, we suggest that this ellipse provides a better constraint on the location of the 1882 earthquake epicenter. Furthermore, we suggest that the region was unlikely to have experienced a large and focused precipitation event within the recent time frame needed to generate such a concentration of young landslides with high roughness values.

Additional work to confirm the new epicenter location would include age dating of landslides and of unfaulted sediments above some of the faults located within this region. On the other hand, the possibility exists that the fault responsible for this earthquake is blind, with Kirkham and Rogers (1986) estimating the hypocentral depth to be roughly 20 km beneath the surface. While it may prove challenging to find the fault directly responsible for this earthquake, it is of importance to know more information about the causative structure due to the potential hazards that an additional earthquake of this magnitude could pose to the Front Range and surrounding regions should it occur again.

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Figure 15. Debris flows/landslides identified by U.S. Geological Survey following the 2013 Front Range rainfall event overlying Colorado State University cumulative rainfall measurements (CSU, 2013).

ACKNOWLEDGMENTS

REFERENCES

I would like to thank Dr. Jim McCalpin for bringing this project to my attention, as this research has large implications for the future estimation of the possibility for large earthquakes within the Front Range and as such was worthy of additional consideration beyond the constraints that prior conducted research was able to place upon the suspected epicenter of Colorado’s 1882 earthquake. Additionally, I would like to thank Dr. Paul Santi for his continued support throughout this project in providing ideas for next steps and best practices for processing and viewing the data that were able to be obtained. Finally, I would like to thank my wife Tess for her support during my time at Colorado School of Mines, as none of this would have been possible without her at my side.

CSU (Colorado State University), 2013, 12 Hour Precipitation Totals and Recurrence Intervals for 9/12/2013 [created 9/13/2013]: Colorado State University Precipitation Systems Research Group, Fort Collins, CO. DAMES AND MOORE, 1981, Geologic and Seismological Investigations for Rocky Flats Plant: Report prepared for U.S. Department of Energy under Contract Number DE-AC04-80AL10890.

E CKERT, A. D., 1982, The Geology and Seismology of the Dudley Gulch Graben and Related Faults, Piceance Creek Basin, Northwestern Colorado: M.S. Thesis, University of Colorado at Boulder, CO, 139 p.

HADSELL, F. A., 1968, History of earthquake activity in Colorado: Colorado School of Mines Quarterly, Vol. 63, No. 1, pp. 57–72.

KEEFER, D. K., 1984, Landslides caused by earthquakes: Geological Society of America Bulletin, Vol. 95, No. 4, pp. 406–421.

KIRKHAM, R. M. AND ROGERS, W. P., 1986, An interpretation of the November 7, 1882, Colorado earthquake. In Rogers, W. P. and Kirkham, R. M. (Editors), Contributions to Colorado Seismicity and Tectonics—A 1986 Update: Special Publication 28, Colorado

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Marchlewicz and Santi Geological Survey, Department of Natural Resources, Denver, CO. Electronic document, available at https://coloradogeologicalsurvey. org/publications/colorado-seismicity-tectonics-1986 LAHUSEN, S. R.; DUVALL, A. R.; BOOTH, A. M.; AND MONTGOMERY, D. R., 2016, Surface roughness dating of long-runout landslides near Oso, Washington (USA), reveals persistent postglacial hillslope instability: Geology, Vol. 44, No. 2, pp. 111–114.

SPENCE, W.; LANGER, C. J.; AND CHOY, G. L., 1996, Rare, large earthquakes at the Laramide Deformation Front—Colorado (1882) and Wyoming (1984): Bulletin of the Seismological Society of America, Vol. 86, No. 6, pp. 1804–1819.

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The Pueblo Daily Chieftain, 1882, Mother Earth, Page 4: Electronic document, available at https://www.coloradohistoricnewspapers.org/? a¼d&d¼CFT18821111-01.2.17&srpos¼2&e¼––—en-20-CFT-1– img-txIN%7ctxCO%7ctxTA-%22MotherþEarth%22––1882— 2––– TWETO, O., 1979, Geologic Map of Colorado: U.S. Geological Survey Open-File Report OFR 92-0507. https://pubs.usgs.gov/of/1992/ofr92-0507/ U.S. Geological Survey, 2024, 3DEP LiDAR Explorer: Electronic application, available at https://apps.nationalmap.gov/lidarexplorer/#/. Accessed 7 September 2023.

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Book Review Introduction to Waste Management: A Textbook

(SYED E. HASAN) Review by: Thomas Oommen Department of Geology and Geological Engineering, University of Mississippi, University, MS-38677

INTRODUCTION The United Nations Human Settlements Program notes, “Managing solid waste well and affordably is one of the key challenges of the 21st century, and one of the key responsibilities of a city government” (UN-Habitat 2010, p. xix). Improper waste management can lead to environmental degradation, soil and water pollution, and wildlife harm. Mismanagement of hazardous waste can pose significant health risks to communities and the environment. Waste management helps conserve natural resources by reducing waste sent to landfills and recovering materials that can be recycled or reused.

Landfills are a significant source of methane emissions, a potent greenhouse gas contributing to climate change. Landfill space is finite and expensive, and as the amount of waste generated continues to increase, finding new landfill sites becomes more difficult. Therefore, proper waste management practices and policies are essential to protect public health and the environment and conserve resources. In Introduction to Waste Management, Hasan (2022), an experienced educator, has come forth with a college textbook in waste management, distilling information from a 35-year teaching career. The book is written for students majoring in environmental science, environmental engineering, environmental studies, environmental geology, resource management, and sustainability programs. It covers all major types of waste: municipal solid waste (MSW), hazardous waste, medical/health care waste (MW), nuclear/radioactive waste, and electronic waste in addition to a chapter on waste minimization and pharmaceuticals and personal care products (PPCPs).

SCOPE AND ORGANIZATION OF THE TEXT This book by Professor Hasan provides an overview of the waste management industry, including its history, current practices, and prospects. It covers key topics, such as waste generation and characterization, collection and transportation, treatment and disposal, and environmental impacts from its mismanagement. The author presents the material clearly and concisely, making the book understandable to readers with little to no prior

knowledge of the subject. The book is well-organized with each chapter building on the previous one to provide a comprehensive understanding of the topic at hand. One of the book’s strengths is its use of real-world examples and case studies to illustrate the concepts discussed. The content is illustrated with 85 figures—nearly all in color—and 87 tables, which make the material easier to understand. The book includes discussion of contemporary topics, such as COVID-19 waste, its proper management, and how to deal with MW from future pandemics/epidemics that are projected to increase in frequency and intensity in the wake of climate change.

The book is organized into 10 chapters that can be utilized as the content for a one-semester course to introduce students to waste management. The 10 chapters provide students with a fundamental understanding of waste management. Each chapter begins with the chapter’s learning objectives and concludes with chapter summary, study questions, related supplementary readings, web resources, and detailed references. Solved numerical problems on calculation of landfill life and area, waste quantities, groundwater flow, etc., enhance the value of the book. A textbook flavor permeates throughout the book, and this style makes it easy for the faculty to adopt it for an introductory course in waste management.

Chapter 1 discusses the evolution of waste management practices and the development of modern waste management systems. The chapter also defines waste and its classification into different categories. Overall, this chapter provides a solid introduction to the subject, providing a comprehensive overview of the field of waste management and its history. Chapter 2 discusses the essentials of geology, its relevance to waste management, the various geotechnical aspects of earth materials, and their significance in the selection of waste disposal facilities and remediation of contaminated sites. The chapter also explains the principles of toxicology and relates them to human and ecological health issues caused by waste mismanagement. Chapter 3 describes the history and evolution of environmental laws in the United States and explains laws dealing with waste management and pollution control. The chapter also discusses the European Union’s environmental laws along with United Nations

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guidelines and recommendations. Chapter 4 reviews the historical evolution of MSW management in the United States and provides detailed discussions of common waste disposal methods, such as landfills and incinerators, and environmental and health impacts associated with them. Chapter 5 begins with differentiation between hazardous substances and hazardous waste and explains health problems caused by hazardous waste mismanagement. The chapter also covers sources and generators of hazardous waste and methods for its storage, transportation, treatment, and disposal. Chapter 6 describes the history and need for regulating MW, and describes the types, sources, and hazards associated with MW and its safe management. The chapter discusses waste types generated in hospitals, best management practices, and the benefits of segregating common waste from regulated medical waste (RMW); summarizes methods of treatment and disposal of RMW; and reviews SARS-Cov-2 and other emerging diseases and their impacts on MW management. Chapter 7 describes the history of radioactivity, nuclear fission, atomic physics, and nuclear technology.

The chapter also provides a sound knowledge of nuclear waste management and the global status of high-level waste disposal. Chapter 8 describes the nature and source of electronic waste and the laws governing e-waste management. The chapter also summarizes the problem of increasing e-waste quantity and the health and environmental impacts associated with its informal recycling, highlighting the urgent need for dealing with its management in a sustainable

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way. Chapter 9 discusses the historical development of waste minimization approaches and compares and contrasts integrated waste management and source reduction. The chapter also explains the zero-waste concept and U.S. laws related to waste minimization and recycling and describes innovative waste minimization trends. Chapter 10 defines PPCPs; explains their nature and threat to human and ecological health; and identifies the source, occurrence, and hazards of PPCPs. SUMMARY Introduction to waste management: A textbook is the only book available in the market that offers a comprehensive coverage of all five major types of waste: solid, hazardous, medical, nuclear, and electronic. Overall, this book is an excellent resource for students, professionals, and anyone interested in learning about waste management. The author’s expertise in the field is evident, and the book provides a thorough and up-to-date overview of the subject. If you are looking for a comprehensive guide to waste management, this book is a must-read.

REFERENCES HASAN, S. E., 2022, Introduction to Waste Management: A Textbook: John Wiley & Sons, Hoboken, NJ. 436 p.

UN-Habitat, 2010, Solid Waste Management in the World’s Cities: Water and Sanitation in World’s Cities 2010: Earthscan, London.

257 p.

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Environmental & Engineering Geoscience Journal (ISSN 10787275), Copyright © 2024 by the Association of Environmental & Engineering Geologists (AEG) and the Geological Society of America (GSA) is published quarterly. Editorial Offices: The University of Mississippi, Dept of Geology and Geological Engineering, University, MS 38677. Accounting and Circulation Offices: AEG, 2840 West Bay Drive #141, Belleair Bluffs, FL 33770-2620. Call (727) 940-2658 x2004 to subscribe. Periodicals postage is paid at AEG, 2840 West Bay Drive #141, Belleair Bluffs, FL 33770-2620.

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Cover photo Limestone quarry in the Edwards Aquifer Recharge Zone, where nitrates and fuel oil used in quarry excavation may enter the aquifer. Photograph courtesy of George Veni. See article on page 173.