Abby Dimicco

Page 1

I. Abstract

Characterizing the Hydrologic Variability of Meadows in the San Bernardino Mountains

University of Redlands, Department of Environmental Studies, 1200 E. Colton Ave, Redlands, CA 92374

III. Healthy VS Unhealthy Meadow

Climate is changing in Southern California. Climate models predict an increase in the frequency of extremely wet and extremely dry seasons, creatingwhiplash events that impact groundwater availability. Meadows are grassland ecosystems with shallow (<2 meters) water tables that provide key ecosystem services and act as early indicators of forest hydrologichealth. Because meadows are early warning signs, we use them here to assess the effect of an ever-changing climate on forest health in the San Bernardino Mountains. In this study we characterize the hydrology of 4 meadow sites, using piezometers at each site to measure the water table depth and compare this with climate variables over multiple temporal and spatialscales. Piezometer data includes discrete point data (establishedand collected in the summer of 2022) and historical data(data loggers that measure depth to water every 30 minutes in Bluff and Lodgepole) and point data(collected by previous students in the summers of 2015, 2017, 2019, and 2021). After analyzing this data, we found that Broomflat is the driest and least hydrologically healthy, Lodgepole is the wettest and most healthy, while Bluff (proximalto Lodgepole) and Wildhorse are moderately healthy. Bluff and Lodgepole show seasonal variability reflective of connection with climate, although Bluff does not exhibit strongconnectionwith precipitation in recent years, likely the result of a decline in hydrology health. Bluff and Lodgepole are well represented by a water balance model that includes evapotranspiration, temperature, radiation, relative humidity, rain and snowfall;however, a strongcorrelation between river incision and water table depth may explain intrameadow variability. This suggests that meadows with incised river systems are more likely to lose water and become hydrologically distressed. We find evidence that precipitation correlates well with Lodgepole Meadow in 2022, but Bluff, Wildhorse, and Broomflat Meadows are no longer respondingto precipitation. Understandingthis hydrologicvariability in montane meadows provides important context for how forest ecosystems in Southern Californiawill adapt to a changing climate.

II. Field Methods

IV. Results

1. Can we characterize the spatial and temporal variability of meadow hydrology in the San Bernardino Mountains?

Healthy Meadow

• Surface flow from precipitation or runoff

• Shallow water table

• Percolation & groundwater recharge

2. What drives groundwater variability in meadows?

variability in Bluff and less variability in Lodgepole

Unhealthy Meadow

• Reduced storage of water

• Deep water table

• Dry vegetation

• Deeper river incision

V. Conclusions

1. Can we characterize the spatial and temporal variability of meadow hydrology in the San Bernardino Mountains?

• Yes! There is less water table variability in Lodgepole & more rapid fluctuation in Bluff over seasonal times scales (November to June)

• We can rank all 4 meadows from most to least Hydrologically Healthy:

• 1. Lodgepole 2. Bluff 3. Wildhorse 4. Broomflat

2. What drives groundwater variability in meadows?

• Lodgepole - 13 piezometers

• Bluff - 11 piezometers

• Offloaded data from HOBO water level loggers

• Measured temp & humidity

• Measured water table depth with water level meter

River Incision

• River Incision Index: function of depth to water & proximity to well location

• Incision also drives groundwater availability

• Larger incision=deeper water table= less healthy

3. How reliant are meadow ecosystems on seasonal water availability? Is this degradation dependent?

• Precipitation drives groundwater variability

• Lodgepole follows precipitation

• Bluff, Broomflat, and Wildhorse not responding to precipitation (not reliant on precipitation)

• Climate (Inputs of Precipitation and Snowfall versus Output of Evapotranspiration)

• River Morphology (greater incision leads to water loss)

3. How reliant are meadow ecosystems on seasonal water availability? Is this degradation dependent?

• Healthy meadows are reliant; unhealthy meadows are not

• If you distress a meadow enough, it alters dependence on climate variables (more precipitation will not save meadow)

• Meadow-Climate connection broken

VI. Acknowledgements

• Advisor: Professor Hillary Jenkins

• U.S. Fish & Wildlife

• Forest Service

• Wildlands Conservancy

• Donor: Mrs. Lea

• Summer Science Research Program

kayla_smith@redlands.edu
• Built 30 piezometers • Installed 15 piezometers in Broomflat and 15 in Wildhorse • Drilled w/ automatic auger & manual auger • Inserted piezometer into ground • Measured out wire & attached HOBO logger to one end and cap to other end • Inserted logger into piezometer Lodgepole Bluff Broomflat
Inputs = Rain + Snow vs. Outputs = Evapotranspiration calculated after Dyer, 2015 following Turc (1961) • Used temperature, humidity, and radiation to calculate ET
the Water Table
Modeling
Lodgepole Bluff
Lodgepole and Bluff are characterized by a shallow water table while Broomflat exhibits the deepest water table, although all 4 meadows show variability from West to East.
Calculating Water Loss
• Over Time, wells in Bluff and Lodgepole follows similar patterns across each meadow • More water table
Figures 8A, B, and C: Spatial Interpolation of Water Table Depth of Lodgepole and Bluff (8A), Wildhorse (8B), and Broomflat (8C) Meadows during June 2022. Blue colors (negative values) mean the water table is above the land surface while red colors (positive values) denote a water table that is drier and further from the surface. Points represent the locations of piezometers installed in each meadow. All piezometers in Wildhorse and Broomflat were installed during this research project. Change in storage Inputs- rainfall & snowfall Outputsevapotranspiration Water Balance • Inputs = Outputs + Change in Storage
Figures 9 & 10: Temporal Graph of Lodgepole & Bluff Water Table Depths at Each Piezometer Location between November, 2021 and June, 2022. Figure 11: Water Balance Diagram Figure 13: Model of Water Table Depth (red) based on Water Balance Model compared with Actual Depths in Bluff (yellow) and Lodgepole (blue) Figure 12: River Incision of Wet and Dry season at each Piezometer Location at Bluff & Lodgepole Figure 14: Bluff & Lodgepole Depth to Water Compared to Precipitation Figure 15: Average Water Table Depth of Each Meadow Compared to Precipitation Rates from 2015-2022 Piezometers installed in 4 Meadow Sites to Measure subsurface Hydrology Spatial Variability Lodgepole Temporal Variability Bluff Wildhorse Broomflat Depth to Water (mm) 8A 8B 8C Figure 2: Map of Lodgepole Meadow and Bluff Meadow with piezometer locations Figure 3: Map of Broomflat Meadow with piezometer locations Figure 4: Map of Wildhorse Meadow w/ piezometer locations Figure 1: Map of Lodgepole, Bluff, Wildhorse, and Broomflat Meadows in relation to the University of Redlands • shallow = wet • deep = dry Figure 7: water table diagram retrieved from livescience.com Figure 6: unhealthy meadow diagram retrieved from nps. gov Figure 5: healthy meadow diagram retrieved from nps. gov • Used water loss to model water table depth • Used water balance to calculate water loss Water Lost = (Rain + Snow) – ET WT(i =WT(i-1) + WaterLost )
Wildhorse
• When inputs exceed outputs, water is added to the system
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