Sabarmati Watershed analysis using SRTM 30m dem

Spatial Analysis Techniques

Watershed Analysis Using DEM

SPATIAL ANALYSIS TECHNIQUES WATERSHED ANALYSIS USING DEM

TEJ CHAVDA (PG191052) Guided by Dr. Dipak Samal & Ashish Upadhyay 1

Spatial Analysis Techniques

Watershed Analysis Using DEM

ABSTRACT The present study highlights the importance of Digital Elevation Model (DEM) and satellite images for assessment of watershed delineation and extraction of their relative parameters for the Sabarmati river watershed, Gujarat and Rajasthan, India.

Hydrological parameters such as drainage analysis, topographic parameters and land use pattern were evaluated and interpreted for watershed management of the area.

Hydrological module of ARC GIS software was utilized for calculation and delineation of the watershed and morphometric analysis of the watershed using SRTM(Shuttle Radar Topography Mission) DEM having Spatial Resolution is 30m.The stream order of watershed ranges from first to sixth order showing dendritic type drainage network which is a sign of the homogeneity in texture and lack of structural control of the watershed. The drainage density in the area has been found to be low to medium which indicates that the area possesses highly permeable soils and low relief. The bifurcation ratio varies from 4.32 to 4.66. The mean Rb of the entire basin is 4.00 which indicates that the drainage pattern is not influenced by geological structures. A circularity ratio of the basin is 0.35 which indicates strongly elongated and highly permeable homogenous geologic materials. The form factor value should always be less than 0.7854. The smaller the value of the form factor, the more elongated will be the basin. Basins with high-form factors experience larger peak flows of shorter duration Because Form factor is high 0.6129 it is understood that the chances of flood is high so Check dam is proposed and hence the propose site suitability

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Contents ABSTRACT.................................................................................................................................... 2 1. Introduction ................................................................................................................................. 6 1.1 Overview of basin ................................................................................................................. 6 1.2 What is Digital Elevation Model (DEM)? ............................................................................ 8 1.3 Study Area: - ....................................................................................................................... 11 2. METHODOLOGY ................................................................................................................... 15 3. TERRAIN ANALYSIS: ........................................................................................................... 16 3.1 Elevation Analysis: ............................................................................................................. 16 3.2 Contour Analysis: ............................................................................................................... 17 3.3 Slope Analysis: ................................................................................................................... 18 3.4 Slope to Aspect Analysis: ................................................................................................... 19 4. WATERSHED ANALYSIS USING DEM .............................................................................. 20 4.1 Hydrology Tools used for Watershed Analysis: ................................................................. 21 4.2 Model Builder ..................................................................................................................... 26 5. TOPOLOGY CORRECTION .................................................................................................. 26 6. Estimating Morphometric Parameters: ..................................................................................... 28 6.1 Conclusion .......................................................................................................................... 32 7. Site Suitability........................................................................................................................... 33 7.1 Introduction ......................................................................................................................... 33 7.2 METHODOLOGY: ............................................................................................................ 34 7.3 ANALYSIS: ........................................................................................................................ 35 7.4 THEMATIC MAPS AND DATA ANALYSIS ................................................................. 37 8. Reference .................................................................................................................................. 53

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Figure 1 Sabarmati Basin In india map........................................................................................... 7 Figure 2 DEM ................................................................................................................................. 8 Figure 3 SRTM(Shuttle Radar Topography Mission) DEM having Spatial Resolution is 30m. ... 9 Figure 4 State wise basin area ...................................................................................................... 11 Figure 5 Sabarmati Basin .............................................................................................................. 11 Figure 6 Pour Point Selection ....................................................................................................... 12 Figure 7 POUR POINT ................................................................................................................. 13 Figure 8 Districts Comes Under Watershed ................................................................................. 14 Figure 9 Taluka Comes Under Watershed .................................................................................... 14 Figure 10 Elevation Map of the Sabarmati watershed ................................................................. 16 Figure 11 Contour Map of the Sabarmati watershed .................................................................... 17 Figure 12 Slope Map of the Sabarmati watershed ........................................................................ 18 Figure 13 Slope to Aspect Map of the Sabarmati watershed ........................................................ 19 Figure 14 Fill in DEM................................................................................................................... 21 Figure 15 Flow direction one value .............................................................................................. 21 Figure 16 Flow Direction in value ranage .................................................................................... 21 Figure 17 Flow Direction Map of the Sabarmati watershed ......................................................... 21 Figure 18 Visual Map for Flow Direction using D8 matrix ......................................................... 22 Figure 19 Flow Accumulation Map of the Sabarmati watershed ................................................. 23 Figure 20 Visual Map for flow accumulation using change in symbology .................................. 23 Figure 21 visual interpretation of topological sheet and streams for threshold value .................. 24 Figure 22 Flow accumulation Threshold > 100 ............................................................................ 24 Figure 23 Flow accumulation Threshold > 50 .............................................................................. 24 Figure 24 Drainage map with stream order of the Sabarmati watershed ...................................... 25 Figure 25 Data Processing with Model Builder ............................................................................ 26 Figure 26 TOPOLOGY CORRECTION ...................................................................................... 27 Figure 27 Number of Stream in watershed after topology correction .......................................... 27 Figure 28 Number of Stream in watershed before topology correction ....................................... 27 Figure 29 Bedrock Map After Resampling ................................................................................... 37 Figure 30 Bedrock soil Map of Sabarmati Watershed .................................................................. 37 Figure 31 After Rescale of LULC ................................................................................................ 38 Figure 32 Satellite image LISS 3 .................................................................................................. 38 Figure 33 Supervised classification .............................................................................................. 38 Figure 34 After Reclassify Slope .................................................................................................. 39 Figure 35 Slop Map of Sabarmati river ........................................................................................ 39 Figure 36 Processing by using Model Builder .............................................................................. 39 Figure 37 Site Suitability .............................................................................................................. 40

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Figure 38 Suitable sites ................................................................................................................. 41 Figure 39 power 1 for IDW interpolation ..................................................................................... 43 Figure 40 power 2 for IDW interpolation .................................................................................... 43 Figure 41 IDW for Rainfall data for Sabarmati watershed ........................................................... 43 Figure 42 RMSE error .................................................................................................................. 44 Figure 43 Error Map for RMSE Error of rainfall for Sabarmati watershed ................................. 44 Figure 44 Interpolation for rainfall data for Sabarmati watershed ............................................... 45 Figure 45 Kriging interpolation for rainfall for Sabarmati Watershed ......................................... 46 Figure 46 Methodology for runoff ................................................................................................ 47 Figure 47 Hydrological Soil Group Map of Sabarmati watershed ............................................... 48 Figure 48 Runoff Map for Sabarmati Watershed ......................................................................... 49 Figure 49 Zonal statistic for Elevation in districts for Sabarmati watershed ................................ 50 Figure 50 Zonal Statistic on Runoff in Sabarmati watershed ....................................................... 51 Figure 51 More Suitable site for check dam ................................................................................. 52

Table 1 Salient features of Sabarmati basin .................................................................................. 10 Table 2 Methodology adopted for computations of morphometric parameters ........................... 29 Table 3 Linear aspect of the watershed......................................................................................... 31 Table 4 Areal aspect of the watershed .......................................................................................... 31 Table 5 Relief characteristics of the watershed ............................................................................ 32 Table 6 Pairwise Comparison Matrix ........................................................................................... 35

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Spatial Analysis Techniques

Watershed Analysis Using DEM

1. Introduction 1.1 Overview of basin River basins form the basic hydrological units for water resources planning. The basin has been recognized as a practical hydrological unit for water resources management.

Sabarmati River is one of the major west flowing rivers of India. The Sabarmati basin extends over the states of Rajasthan and Gujarat having an area of 21,674 Sq. km with maximum length and width of 300 km and 150 km respectively. It lies between 70°58’ to 73°51’ east and 22°15’ to 24°47’ north. The basin is bounded by Aravalli hills in the north and north-east, Rann of Kutch in the west and Gulf of Khambhat in the south. The Sabarmati basin extends over parts of Udaipur, Sirohi, Pali and Dungarpur districts of Rajasthan, Sabarkantha, Kheda, Ahmedabad, Mahesana, Gandhinagar and Banaskantha districts of Gujarat.

As far as water resources are concerned, the average annual runoff and average annual water potential of the basin is 3.81 BCM. The utilizable surface water in the basin accounts to 1.9 BCM. The basin is divided into 2 sub-basins viz. Sabarmati Upper and Sabarmati Lower Sub-Basin.

They have been further clustered into 51 watersheds each of which represents a different tributary system. The Sabarmati and its tributaries are an interstate river system, flowing through the states of Rajasthan and Gujarat. The drainage network of Sabarmati River consists of 5 major tributaries.

The basin is roughly triangular in shape with the Sabarmati River as the base and the source of the Watrak River as the apex point. Sabarmati originates from Aravalli hills at an elevation of 762 m near village Tepur in Udaipur district of Rajasthan. The total length of river from origin to outfall into the Arabian Sea is 371 km and its principal tributaries joining from left are Wakal, Hathmati and Watrak whereas Sei joins the river from right.

Figure 1 shows the geographical location of the basin with terrain features from DEM. The highlighted blue boundary shows the basin extent overlaid on state boundary. Figure 5 gives a detailed view of the basin where the drainage network and its pattern across the basin is also shown. Table 1 gives a glance at the salient features of the basin.

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Spatial Analysis Techniques

Figure 1 Sabarmati Basin In india map

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Watershed Analysis Using DEM

Spatial Analysis Techniques

Watershed Analysis Using DEM

1.2 What is Digital Elevation Model (DEM)?

A digital elevation model (DEM) is any raster representation of a terrain surface. In simple words, a DEM is a 3D representation of a terrain surface.

Elevation Values

Figure 2 DEM

Pixel with Elevation value

Pixels with lower Elevation Elevation Values Pixels with higher Elevation Satellite scans the Earth surface in the form of pixel

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Figure 3 SRTM(Shuttle Radar Topography Mission) DEM having Spatial Resolution is 30m.

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Spatial Analysis Techniques

Watershed Analysis Using DEM Table 1 Salient features of Sabarmati basin

Sl. No. 1

Features Basin Extent

Description 70° 58’ to 73° 51' E 22° 15’ to 24° 47’ N

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Area (Sq.km)

21,674*

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States in the basin

Gujarat (87.15 %), Rajasthan (12.85 %)

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Districts (Census 2011)

15

5

Parliamentary Constituencies (2009)

16

6

Mean Annual Rainfall (mm)

689.90

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Mean Maximum Temperature (o C)

39.33

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Mean Minimum Temperature (o C)

10.95

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Total Population (Census 2011)

3,69,08,052

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Number of villages

4,720

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Highest Elevation (m)

1,173

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Avg. Annual Water Potential (BCM)

3.81

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Utilizable Surface Water (BCM)

1.90

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Number of Sub-basins

2

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Number of Watersheds

51

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Number of water resources structures

Dams (50), Barrages (2) ,Weirs (10)

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Highest Dam

Sabarmati Dam (46 m)

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Longest Dam

Mulbavla Dam (9735 m)

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Highest Barrage

Wasna Barrage (20.75 m)

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Longest Barrage

Varanai Barrage (1544 m)

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Number of Irrigation projects

Major: 9,Medium: 11, ERM:4

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Number of Hydro - Electric projects

-

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Number of Ground water observation

243

wells 24

Number of Hydro-Observation Sites

15

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Number of Flood Forecasting Sites

2

26

Water tourism sites

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*GIS based calculated area : 30,680 Sq. km.

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Figure 4 State wise basin area

1.3 Study Area: -

Figure 5 Sabarmati Basin

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Shape Area: 8720.521 Sq.km

Spatial Analysis Techniques

Watershed Analysis Using DEM

Pour point is a point used for deriving contributing watershed. Flow accumulation attains highest value at pour point.Watershed having an area of 2271 Sq.km.

In map, Circle indicate the pour points or outlet of the watershed.

Figure 6 Pour Point Selection

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Figure 7 POUR POINT

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Figure 8 Districts Comes Under Watershed

Figure 9 Taluka Comes Under Watershed

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Spatial Analysis Techniques

Watershed Analysis Using DEM

2. METHODOLOGY

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Spatial Analysis Techniques

Watershed Analysis Using DEM

3. TERRAIN ANALYSIS: 3.1 Elevation Analysis:

Figure 10 Elevation Map of the Sabarmati watershed

This map shows the elevation in Sabarmati basin, Contour elevation lies between the less than 494m and greater than 1178m.Terrain of this basin is Descending uniform grade in nature in the direction of North east to south west.

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Spatial Analysis Techniques

Watershed Analysis Using DEM

3.2 Contour Analysis: “An Imaginary line joining the equal elevation on the ground is known as Contour”.

⚫ This map shows the contour elevation on the Sabarmati basin, Contour elevation lies between 400m and 1000m. Terrain of this basin is Descending uniform grade in nature in the direction of North east to south west. ⚫ A contour map is a map illustrated with contour lines, for example a topographic map, which thus shows valleys and hills, and the steepness or gentleness of slopes. The contour interval of a contour map is the difference in elevation between successive contour lines. Here, the contour interval is 200m. ⚫ Contour lines are curved, straight or a mixture of both lines on a map describing the intersection of a real or hypothetical surface with one or more horizontal planes.

Figure 11 Contour Map of the Sabarmati watershed

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Spatial Analysis Techniques

Watershed Analysis Using DEM

3.3 Slope Analysis: Slope is the measure of change in surface value over distance and can be expressed in degrees or as a percentage. In a raster format, the Digital Elevation Model (DEM) is a grid where each cell is a value referenced to a common datum. For extraction of elevation from remote sensing dedicated software packages are required but most GIS packages have routines for point or contour line interpolation. Any two points on the grid will be sufficient to ascertain a slope.

Once the slopes have been calculated, then the maximum difference can be found and the gradient can be determined (Burrough and McDonnell, 1998; Maathuis, 2006; Jha et al. 2007).

Topographical elevation map for the study area was developed by Digital Elevation Model (DEM) extracted from the Shuttle Radar Topography Mission (SRTM) data. For this, the DEM was subjected to two directional gradient filters. The resultant maps were used to generate a slope map of the study area using ARCGIS Spatial Analyst tools. The highest topographic elevations (1178 m and lowest 259m) exist in the northeast portions of the area which induces highest runoff (Fig. 48) and hence less possibility of rainfall infiltration. The slope map of the study area has grouped Figure 12 Slope Map of the Sabarmati watershed in five classes in degrees viz. 1–6 (Gentle) , 6–12 (Moderate) , 12–19 (Steep) , 19–28 (Very Steep) and >28 (Very Very Steep) (Fig. 14). It is observed that the most of the area of Sabarmati river basin comes under gentle and very steep slope which indicates flat topography of the area.

Gentle slopes were designated in the ‘‘Medium’’ category for groundwater management as the nearly flat terrain is the most favorable for infiltration. Moderate slopes also come under good zone due to slightly undulating topography which gives maximum percolation or partial runoff. The steep class and having a high surface runoff with a negligible amount of infiltration are marked under good zone for construction of stop dams etc. Slope is a critical parameter which directly controls runoff and infiltration of any terrain. Runoff in higher slope regions causes less infiltration.

Planar method: the slope is measured as the maximum rate of change in value from a cell to its immediate neighbors.

The calculation is performed on a projected flat plane using a 2D Cartesian coordinate system. The slope value is calculated using the average maximum technique (Burrough, 1998).

Basin Slope is in degree. The slope lies between 6 to 70.73 degree. In this map the yellow and orange color shows the average steep slope (0 to 19 degree) and red color shows the very steep slope or extreme steep slope (19 to 70 degree).

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Spatial Analysis Techniques

Watershed Analysis Using DEM

3.4 Slope to Aspect Analysis: Aspect map generally refers to the direction to which a mountain slope faces. The aspect map is a very important parameter to understand impact of sun on local climate of the area. Generally, west facing slope showing the hottest time of day in the afternoon and in most cases a westfacing slope will be warmer than sheltered an east-facing slope. Aspect map has major effects on the distribution of vegetation type of area. The aspect map derived from SRTM DEM represents the compass direction of the aspect. 0_ is true north; a 90_ aspect is to the east (Fig. 13).

The Sabarmati watershed shows southeast-facing slopes and therefore, measured clockwise in degrees from 0 to 360, where 0 is north-facing, 90 is east-facing, 180 is south-facing, and 270 is west-facing.

Figure 13 Slope to Aspect Map of the Sabarmati watershed

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Spatial Analysis Techniques

Watershed Analysis Using DEM

4. WATERSHED ANALYSIS USING DEM Watershed defined by topographic divides; a watershed is an area that drains surface water to a common outlet. A watershed is a hydrologic unit that is often used for the management and planning of natural resources.

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Spatial Analysis Techniques

Watershed Analysis Using DEM

4.1 Hydrology Tools used for Watershed Analysis: 1. Filled DEM: A filled DEM or elevation raster is void of depressions.

A depression is a cell or cells in an elevation raster that are surrounded by higher elevation values, and thus represents an area of internal drainage. Although some depression is real, such as quarries or glaciated potholes, many are imperfection in the DEM.

2. Flow Direction:

Figure 14 Fill in DEM

When water flows in the east direction, it has a value of 1.

When water flows west, it has a value of 16. All 8 adjacent directions at a given point can be described using the eightdirection pour point model.

Figure 15 Flow direction one value

When running the flow direction algorithm, the resulting values ranges from 1, 2, 4, 8, 16, 32, 64 and 128. In the eight direction pour-point model diagram, you can understand which flow direction water travels.

A flow direction raster shows the direction water will flow out of each cell of a filled elevation raster. A widely used method for deriving flow direction is the D8 method. Used

by ArcGIS, the D8 method assigns a cell’s flow direction to the one of its eight surrounding cells that has the steepest Figure 16 Flow Direction in value ranage distance-weighted gradient.

(O’ Callagham and mark 1984)

Figure 17 Flow Direction Map of the Sabarmati watershed

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Figure 18 Visual Map for Flow Direction using D8 matrix

⚫

Model help how surface runoff contributes to flooding

⚫

Flow direction calculates the direction water will flow using slope from neighboring cells.

⚫

A widely used method for deriving flow direction is the D8 method

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Spatial Analysis Techniques ⚍

Watershed Analysis Using DEM

The flow direction is determined along the direction of steepest descent, or maximum drop, from each cell.

3 Flow Accumulation: A flow accumulation raster tabulates for each cell the number of cells that will flow to it. A flow accumulation raster records how many upstream cells will contribute drainage to each cell (the cell itself not counted). A flow accumulation raster can be interpreted in two ways. First, cells having high accumulation values generally correspond to stream channels, whereas cells having an accumulation value of zero generally correspond to ridge lines. Second, if multiplied by the cell size, the accumulation value equals the drainage area.

Figure 20 Visual Map for flow accumulation using change in symbology

Figure 19 Flow Accumulation Map of the Sabarmati watershed

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Flow Accumulation threshold Flow accumulation Threshold > 50 (adequate) Flow accumulation Threshold > 100(under classified) The drainage network has been extracted by considering the pixels greater than a threshold of 100, 50 by a trial-and-error approach (Mark, 1983) and verified with help of toposheet

(http://www.surveyofindia.gov.in/) Figure 21 visual interpretation of topological sheet and streams for threshold value

Figure 22 Flow accumulation Threshold > 100 Figure 23 Flow accumulation Threshold > 50

⚍

The threshold value is a necessary input to watershed analysis. But the choice of a threshold value can be arbitrary.

⚍

A threshold value between 50 and 500 cells seems to best capture the stream network in the area.

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Spatial Analysis Techniques

Watershed Analysis Using DEM

4 Stream Order: ⚫

The Stream Order tool only supports a D8 input flow direction raster. D8 flow directions can be created using the Flow Direction tool, run with default flow direction type D8.

⚫

Stream ordering is the hierarchical ranking of stream networks.

➢ The method used for assigning stream order: -

1952. of

STRAHLER —The method of stream ordering proposed by Strahler in Stream order only increases when streams the same order intersect. Therefore, the intersection of a first-order and secondorder link will remain a second-order link, rather than creating a third-order link. This is the default.

SHREVE —The method of stream ordering by magnitude, proposed by Shreve in 1967. All links with no tributaries is assigned a magnitude (order) of one.

Magnitudes are additive downslope. When two links intersect, their magnitudes are added and assigned to the downslope link.

In the Strahler method, all links without any tributaries are assigned an order of 1 and are referred to as first order. The stream order increases when streams of the same order intersect.”

The

Figure 24 Drainage map with stream order of the Sabarmati watershed

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first stream order streams are the perennial streams.

Because these streams have no associated tributaries with them and are self-reliant, these streams are going to be flow throughout these years.

Spatial Analysis Techniques

Watershed Analysis Using DEM

5 Stream to feature: ➢ This tool converts raster polylines into vector form. ➢ Converts a raster representing a linear network to features representing the linear network. ➢ There should be contiguous features with the same value, such as the results of the Stream Order or Stream Link tool. Stream to Feature should not be used on a raster in which there are few adjacent cells of the same value. ➢ This feature enables us to estimate morphometric parameters.

4.2 Model Builder

Figure 25 Data Processing with Model Builder

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Spatial Analysis Techniques

Watershed Analysis Using DEM

5. TOPOLOGY CORRECTION TOPOLOGY is a set of rules how points, lines and polygons share their geometry. Topology checks and validates the spatial relationship of neighboring and overlapping features.

Must Not Overlap

Figure 26 TOPOLOGY CORRECTION

Must Not Intersect

Figure 28 Number of Stream in watershed before topology correction

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Must Not Have Pseudo Nodes Must Not Have Dangles

Figure 27 Number of Stream in watershed after topology correction

Spatial Analysis Techniques

Watershed Analysis Using DEM

6. Estimating Morphometric Parameters: Assessment of watershed using quantitative morphometric analysis can provide information about the hydrological nature of the rocks exposed within the watershed. A drainage map of a basin provides a reliable index of permeability of the rocks and gives an indication of the yield of the basin.

The DEM has been obtained with a pixel size of 30 m and furthermore, it has been used to calculate slope and aspect maps of the watershed. The development of drainage networks depends on geology, precipitation apart from exogenic and endogenic forces of the area. Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM) data were used for preparing slope, aspect maps and morphometric analysis of the watershed. Linear, areal and relief aspects of the watershed were evaluated in GIS environment using Arc GIS PRO software. The assessment of drainage basin has been more accurate and precise for morphometric parameter evaluation with better accuracy. Satellite data and GIS have been successfully utilized to generate data on the spatial deviations in drainage characteristics thus providing an insight into hydrologic conditions necessary for developing watershed management strategies (Das and Mukherjee, 2005).

Hydrogeological observations, integrated with drainage analysis, provide useful clues regarding broad relationships among the geological framework of the basin. The morphometric analysis can be achieved through measurements of linear, areal and relief aspects of basin.

Quantitative analysis of Sabarmati watershed has been carried out to evaluate the drainage characteristics using GIS software for calculation and topology building of different morphometric parameters. Important Linear and Arial parameters and their characteristic were calculated such as basin area, perimeter , basin length , bifurcation ratio (Rb), drainage density (Dd), stream frequency (Fs) circulatory ratio (Rc), elongation ratios (Re) etc. The drainage patterns of the watershed are dendritic with sixth order streams. The details of various morphometric parameter and law used in the present work are shown in Table 2.

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Spatial Analysis Techniques

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Table 2 Methodology adopted for computations of morphometric parameters

Sr. No. 1 2 3 4 5 6 7 8 9 10 11 12 13

Parameters Stream order (U ) Stream length (L u) Mean stream length(Lsm) Bifurcation ration (R b) Mean bifurcation ratio (Rbm) Drainage density (D d) Drainage texture (T ) Stream frequency (F s ) Drainage Intensity (Di) Elongation ratio (R e) Circularity ratio (R c) Relief Relief ratio

Formulae Hierarchical rank Length of the stream Lsm = L u/N u (R b) = Nu/Nu + 1 Rbm = average of bifurcation ratios of all order Dd = L u /A T = D d × Fs Fs = N u/A Di = F s / D d Re = 2/Lb*(A/π) ^0.5 Rc = 4πA/P^2 R=H −h Rr = R / L

References Strahler (1964) Horton (1945) Strahler (1964) Schumm (1956) Strahler (1957) Horton (1945) Smith (1950) Horton (1945) Schumm (1956) Strahler (1964) Hadley and Schumm(1961) Schumm (1963)

Lu=Sum of all length of stream, Nu=Sum of total stream, A=Basin Area, Lb=Length of basin, P= Perimeter,

NI=No.of stream in first order, L= Basin length

a) Stream order (U): - Stream ordering is the first step of quantitative analysis of the watershed. The stream ordering systems has first advocated by Horton (1945), but Strahler (1952) has proposed this ordering system with some modifications. It has observed that the maximum frequency is in the case of first order streams. It has also noticed that there is a decrease in stream frequency as the stream order increases. b) Stream Number (Nu): - The Sabarmati watershed encompasses a dendritic drainage pattern which indicates homogenous subsurface strata of the study area. In the present study the stream ordering has been ranked based on a method proposed (Strahler, 1964) The order wise stream numbers and their linear characteristics are shown in Table 3. The drainage pattern analysis of the Sabarmati river basin indicated that the area is having a lake of structural tectonic control. Maximum number of streams was found in the first order and as the stream order increases with a decrease in stream number. The drainage map with stream order of the Sabarmati river basin is shown in fig.24

c) Bifurcation Ratio (Rbf):- The term bifurcation ratio (Rb) may be defined as ratio of the number of stream segments of a given order to the number of segments of the next higher.

Bifurcation ratio values of Sabarmati river basin ranging between 4.3 and 5 are considered to be characteristics of the basin, which have experience minimum structural disturbances (Strahler, 1964) .The mean bifurcation ratio of the basin is observed as 4.00. This indicates that the drainage pattern of the basin has not been affected by structural disturbances (Table 3). d) Stream length (Lu), mean stream length (Lsm) : The total length of stream segments decreases as the stream order increases (Table 3). Stream length and their ratio is very

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Watershed Analysis Using DEM

important parameter to scan the hydrological characteristics of the river basin because they permeability of the rock formations in a basin. It also indicates if there is a major change in the hydrological characteristics of the underlying rock surfaces with the basin (Singh et al., 2013). The relationship between the bifurcation ratio and the stream length ratio is determined by hydrogeologic, physiographic and geological characteristics. The values of total length and mean length of different stream orders of the Sabarmati river basin are shown in Table 3.

e) Drainage density (Dd), Drainage texture (T): - Horton (1932) has introduced drainage density as an expression to indicate the closeness of spacing of channels. It is a measure of the total length of the stream segment of all orders per unit area and controlled by the Slope gradient and relative relief of the basin. The drainage density of the study area has been calculated and the value is 3.20 (Table 4). Smith (1950) has classified drainage density into five different textures. The Drainage density less than 2 indicates very coarse, between 2 and 4 is related to coarse, between 4 and 6 is moderate, between 6 and 8 is fine and greater than 8 is very fine drainage texture. It is observed that, if the drainage texture is 46.83 it indicates the presence of highly resistant permeable material with High relief. The variation in the value of drainage texture (T) depends upon a number of natural factors such as climate, rainfall, vegetation, rock, soil type and their infiltration capacity and relief of the basin. The relation between geology and hydrological analysis of watershed in semi arid regions has low drainage density and generally results in the areas of highly resistant or permeable subsoil material, dense vegetation and low relief. High drainage density is the resultant of weak or impermeable sub surface material, thin vegetation and mountainous relief. The low drainage density of the watershed reveals that they are composed of permeable subsurface material, good vegetation cover, and low relief which results in more infiltration capacity in the watershed. f) Stream frequency (Fs) :- Stream frequency (Fs) or channel frequency is the total number of stream segments of all orders per unit area Horton (1932). Fs values indicate a positive correlation with the drainage density of the basin suggesting that an increase in stream population occurs with respect to increase in drainage density. An observed stream frequency (Fs) of 5.83 for the basin exhibits a positive correlation with the drainage density value of the area indicating an increase in stream population with respect to increase in drainage density (Table 4).

g) Elongation ratio (Re): - Elongation ratio (Re) is the ratio between the diameter of the circle of the same area as the drainage basin and the maximum length of the basin (Schumm, 1956). The values of Re generally vary from 0.6 to 1.0 over a wide variety of climatic and geologic conditions. Values close to 1.0 are typical of regions of very low relief, whereas values in the range 0.6â&#x20AC;&#x201C;0.8 are usually associated with high relief and steep ground slope (Strahler, 1964). These values can be grouped into three categories namely (a) circular (>0.9), (b) oval (0.9â&#x20AC;&#x201C;0.8), (c) elongated (<0.7). The elongation ratio of the basin is 0.88, which suggests that the basin belongs to the oval shape basin and High relief (Table 4).

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h) Circularity ratio (Rc): - Miller (1953) defined dimensionless circularity ratio (Rc) as ratio of basin area to the area of circle having the same perimeter as the basin. Rc is influenced by the length and frequency of streams, geological structures, land use/land cover, climate, relief and slope of the basin. A circularity ratio of the basin is 0.35 which indicates strongly elongated and highly permeable homogenous geologic materials. The observed circularity ratio of the basin indicates that the basin is elongated in shape, has low discharge of runoff and highly permeable subsoil conditions (Table 4).

i) Form factor (Ff):- According to Horton (1932), form factor (Ff) may be defined as the ratio of the basin area to square of the basin length. The form factor indicates the flow intensity of a basin for a defined area. The form factor value should always be less than 0.7854.

The smaller the value of the form factor, the more elongated will be the basin. Basins with high-form factors experience larger peak flows of shorter duration, whereas elongated basin with low-form factors experience lower peak flows of longer duration. The observed form factor value of the basin is 0.612 suggesting that the shape of the basin is elongated (Table 4). High form factors experience larger peak flows of shorter duration so high chance of flooding. j) Relief ratio of the Basin:- The elevation difference between the highest and lowest points on the valley floor of a basin is known as the total relief of that basin. The relief ratio (Rh) of maximum relief to horizontal distance along the longest dimension of the basin parallel to the principal drainage line is termed as relief ratio (Schumm, 1956). It measures the overall steepness of a drainage basin and is an indicator of the intensity of the erosion processes operation on the slope of the basin.

Table 3 Linear aspect of the watershed

Stream Order(w) 1 2 3 4 5 6 7

No. Of Stream (Nu) Total Length of Stream (Km) Mean length of stream (Lu) 10390 3782.964442 0.364096674 2245 1729.40261 0.770335238 488 907.1798153 1.858975031 112 415.661487 3.711263277 24 224.6492951 9.360387296 5 130.648027 26.1296054 1 81.76689662 81.76689662 Table 4 Areal aspect of the watershed

stream length ratio 2.115743684 2.413202641 1.996402972 2.522156634 2.791509002 3.129281723

31

Cumulative stream length (km)

7272.272573

Bifurcation Ratio (RbF) Mean Bifurcation Ratio (Rbm) 4.628062361 4.600409836 4.357142857 4.666666667 4.007468817 4.8 5

Spatial Analysis Techniques

Watershed Analysis Using DEM

Basin Area Length (km2) Perimeter (km) 2271.8445 283.219

60.88

Elongation ratio (Re) 0.883438091

Circularity ratio (R c) Drainage density (D) km Stream frequency (F) Drainage texture (T) 0.355901572 3.201043281 5.838867933 46.83649406

asin z)m(m) Basin relief (H) m 494

Relief ratio 684

Form factor ratio 0.01123 0.61295602 Table 5 Relief characteristics of the watershed

Maximum Height ofHeight the basin of basin (z)m(m) Basin relief (H) m 1178 494

Relief ratio 684

0.01123

Form factor ratio 0.61295602

6.1 Conclusion The study reveals that remotely sensed data (SRTM-DEM 30m) and GIS based approach in evaluation of drainage morphometric parameters at river basin level is more appropriate than the conventional methods. GIS based approach facilitates analysis of different morphometric parameters. GIS techniques characterized by very high accuracy of mapping and measurement prove to be a competent tool in morphometric analysis. The morphometric analyses were carried out through measurement of linear, areal and relief aspects of the watershed with more than 13 morphometric parameters. The morphometric analysis of the drainage network of the watershed show dendritic and radial patterns with moderate drainage texture. The bifurcation ratio in the watershed indicates normal watershed category and the presence of moderate drainage density suggesting that it has moderate permeable sub-soil, and coarse drainage texture. The value of stream frequency indicate that the watershed show positive correlation with increasing stream population with respect to increasing drainage density. The value of form factor and circulator ration suggests that Sabarmati watershed is highly elongated. Hence, from the study it can be concluded that SRTM-DEM data, coupled with GIS techniques, prove to be a competent tool in morphometric analysis.

The form factor value should always be less than 0.7854. The smaller the value of the form factor, the more elongated will be the basin. Basins with high-form factors experience larger peak flows of shorter duration Because Form factor is high 0.6129 it is understood that the chances of flood is high so Check dam is proposed and hence the propose site suitability

32

Spatial Analysis Techniques

Watershed Analysis Using DEM

7. Site Suitability 7.1 Introduction Water harvesting structures are extremely important to conserve precious natural resource like, soil and water. Water is essential for all life forms and is used in different ways such as for food production, drinking, domestic, industrial, power generation and recreation. Out of 2.5% global fresh water only 1% is available for human consumption (Anon., 2002). The ground water table is rapidly depleting due to over exploitation of groundwater. Statistics on water budget indicates that our country gets about 400 Mha.m of precipitation annually, out of which 200 Mha.m is lost in evapotranspiration. About 135 Mha.m is available on the surface and remaining portion of precipitation joins groundwater through percolation. As per estimate about 92 Mha.m of the available surface water ultimately goes to the sea despite of construction of large dams, reservoirs, check dams, water harvesting structures etc.

The precipitation in India is highly variable over time and space due to monsoon climate and land-mountain topography. In order to conceptualize the runoff occurring from the humid regions. The need and importance of water harvesting and water conservation has been given weightage in national water policy and national agricultural policy of government of India. The various rainwater harvesting structures viz., check dams, farm ponds, nala bunds, percolation tanks etc are constructed at appropriate site that check flood, conserve soil and provide irrigation to downstream.

GIS is an effective tool not only for collection, storage, management and retrieval of a multitude of spatial and non-spatial data, but also for spatial analysis and integration of these data to derive useful outputs and modelling (Gupta and Srivastava 2010; Srivastava et al. 2011).

The present study is focused on the identification of suitable sites for positioning of water harvesting structure such as check dams in Sabarmati River based on GIS. This study is an attempt to identify water harvesting site based on the Remote Sensing and GIS study to increase water potential of the area for irrigation and domestic purpose.

Objective: • To reduce runoff velocity thereby minimizing erosion.

• Increasing recharge to the wells located downstream.

• Water use in agriculture Site conditions: • Areas having less slope.

• Constructed on lower order streams (third order and fourth order).

• Bedrock soil depth (Less bedrock economical structure) • Flow accumulation (high flow accumulation) •

33

Land use/ landcover (near to agriculture land)

Spatial Analysis Techniques

Watershed Analysis Using DEM

7.2 METHODOLOGY: In this work some criteria were taken. The main criteria considered for the spatial analysis are proximity of the Stream odder, Agricultural land, Bedrock soil. These criteria were taken into account for the preparation of the maps. For suitability analysis it is required to put some values for each criterion as per the requirement for the development of the urban region. For, this reason the pairwise comparison matrix has been developed using Saatyâ&#x20AC;&#x2122;s nine-point scale of weights (Table. 7). Different criteria are required to develop a ratio matrix. These pairwise comparability is taken as the input and the outputs obtained are the relative weights.

34

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Watershed Analysis Using DEM

7.3 ANALYSIS: PART-1 [Analytical Hierarchy Process (AHP)]: Table 6 Pairwise Comparison Matrix

Criteria Distance From Streams Aggriculture land Flow Accumulation Bed Rock Depth Slope %

Dis. From Streams

Aggriculture land

Flow Accumulation

Bed Rock Depth

Slope %

1

3

5

8

9

0.333

1

4

6

7

0.200

0.250

1

3

4

0.125

0.167

0.333

1

2

0.111

0.143

0.250

0.500

1

➢ Matrix generation based on weights given Criteria

Dis. From Streams

Aggriculture land

Flow Accumulation

Bed Rock Depth

Slope %

Distance From Streams

1

3

5

8

9

Aggriculture land Flow Accumulation Bed Rock Depth

0.333

1

4

6

7

0.200

0.250

1

3

4

0.125

0.167

0.333

1

2

Slope%

0.111

0.143

0.250

0.500

1

Column Sum

1.769

4.560

10.583

18.500

23.000

➢ Add all the Columns

35

Spatial Analysis Techniques Criteria Distance From Streams Aggriculture land Flow Accumulation Bed Rock Depth Slope%

Watershed Analysis Using DEM

Dis. From Streams

Aggriculture land

Flow Accumulation

Bed Rock Depth

Slope %

WEIGHTS

0.565

0.658

0.472

0.432

0.391

0.504

0.188

0.219

0.378

0.324

0.304

0.283

0.113

0.055

0.094

0.162

0.174

0.120

0.071

0.037

0.031

0.054

0.087

0.056

0.063

0.031

0.024

0.027

0.043

0.038 1.000

➢ Divide each element in the Metrix by its own column total and add along rows. ➢ Normalized pairwise comparison matrix Criteria

Dis. From Streams

Aggriculture land

Flow Accumulation

Bed Rock Depth

Slope %

TEMP

Distance From Streams

0.503858062

0.84859746

0.598423509

0.447526089

0.338855897

2.737

5.432603398

Bed Rock Depth

0.167952687

0.28286582

0.478738807

0.335644567

0.263554587

1.529

5.404528789

Flow Accumulation Slope

0.100771612

0.070716455

0.119684702

0.167822283

0.150602621

0.610

5.093363348

0.062982258

0.047144303

0.039894901

0.055940761

0.075301311

0.281

5.027881774

Urban

0.055984229

0.040409403

0.029921175

0.027970381

0.037650655

0.192

5.09780884

Lambda

5.21123723

➢ Normalized weights multiplied by every element in the respective column of PCM ➢ Determine consistency vector by dividing the weighted sum vector by the criterion weights determined previously ➢ Calculate (): it is the avg value of consistency vector.

Random Index

Calculate CI Compute CR using Random index

= 0.052809307

= 0.047151167

CR < 0.10 Reasonable level of consistency 36

Spatial Analysis Techniques

Watershed Analysis Using DEM

7.4 THEMATIC MAPS AND DATA ANALYSIS 1. Bedrock soil (https://soilgrids.org) Bedrock, a deposit of solid rock that is typically buried beneath soil and other broken or unconsolidated material (regolith). Bedrock is made up of igneous, sedimentary, or metamorphic rock, and it often serves as the parent material (the source of rock and mineral fragments) for regolith and soil.

Figure 30 Bedrock soil Map of Sabarmati Watershed

Figure 29 Bedrock Map After Resampling

The Rescale by Function tool allows you to use a mathematical function (line or curve) to assign suitability values to an input raster along a continuous scale (typically 1 to 10). Many times, the suitability changes continuously with the changing values of the criterion and often does so in a nonlinear manner.

The Rescale by Function tool expands your options for transforming data in a suitability model. You can use the Reclassify tool to reclassify data into categories and the Rescale by Function tool to rescale (reclassify) continuous data without creating discrete categories. The Rescale by Function tool provides a variety of functions to model suit abilities which change on a continuous scale.

MS Small â&#x20AC;&#x201D; Rescale input data based on the mean and standard deviation, where smaller values in the input raster have higher preference.

When highly permeable strata of gravel, sand or cavities are present in the foundation of dam it permits heavy seepage of water through it causing erosion of soil which will formation of piping

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Spatial Analysis Techniques

Watershed Analysis Using DEM

2. Landuse / landcover Classification Land use map The land use map shows the spatial extent of agriculture land built up area, Forest area, open land, Water body etc. The domain used in Khed Brahma, Gogunda, Udaipur taluka is agriculture which occupies 10.74% of total geographic area.

Built up area is 3.17% of the total study area. The forest plantation, deciduous forest and naturally grown forest plantation occupies 65.68% of total study area. The class of land includes ponds, lakes, depression storage, perennial river/stream, etc. Water body category occupies a small area of about 2.32% of the total study area.

Figure 32 Satellite image LISS 3 (18 jan 2017) 23.5 M

38

Area

3729896.5

70072793.5 9313144 59408846 597644950

Lake River Bank River URBAN

144955795 0

Figure 33 Supervised classification (6 classes)

17005986.5

Agriculture Open Land

Figure 31 After Rescale of LULC

Spatial Analysis Techniques

Watershed Analysis Using DEM

3. Slope map

Figure 35 Slop Map of Sabarmati river

Figure 36 Processing by using Model Builder

39

Figure 34 After Reclassify Slope

Spatial Analysis Techniques

Watershed Analysis Using DEM

4. Location of Suitable Site Figure 37 Site Suitability

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Spatial Analysis Techniques

Watershed Analysis Using DEM

Figure 38 Suitable sites

5. Rainfall Data Interpolation Rainfall data downloaded from CHRS portal.42 points rainfall point taken. A dense network is required to estimate accurately spatial distribution of a given area. 42 points are used for interpolation on the entire watershed and then interpolated rainfall map of the study area was clipped. Interpolation was used to estimate rainfall for the areas not having rainfall point measurements. The interpolation has been done in ArcGIS PRO using Inverse Distance Weight (IDW). Inverse distance weighted (IDW) interpolation determines, cell values using a linearly weighted combination of a set of sample points. The weight is a function of inverse distance. The interpolated raster map shows variation in average annual rainfall. In the north part of the study area having high rainfall.

41

Spatial Analysis Techniques

Watershed Analysis Using DEM

5.1 Inverse Distance Weighted Interpolation Estimate the unknown points through interpolation. Inverse distance weighting (idw) interpolation is mathematical (deterministic) assuming closer values are more related than further values with its function. Interpolation that estimates cell values by averaging the values of sample data points in the neighborhood of each processing cell While good if your data is dense and evenly-spaced, letâ&#x20AC;&#x2122;s look at how IDW works and where it works best.

A power of 1 smooths out the interpolated surface.

42

Spatial Analysis Techniques

Watershed Analysis Using DEM

For a power of 1, that cell value is equal to: ((12/350) + (10/750) + (10/850)) / ((1/350) + (1/750) + (1/850)) = 11.1

Figure 39 power 1 for IDW interpolation

A power of 2 increases the overall influence it has from the known values. You can see how the peaks and values are more localized and are not averaged out as much as a power of 1.

For a power of 2, that cell value is equal to: = ((12/3502) + (10/7502) + (10/8502)) / ((1/3502) + (1/7502) + (1/8502)) = 11.4

Figure 40 power 2 for IDW interpolation

POWER 2 20 Points for this interpolation, the north part of the study area having high rainfall.

43

Figure 41 IDW for Rainfall data for Sabarmati watershed

Spatial Analysis Techniques

Watershed Analysis Using DEM

Root Mean Square Error (RMSE) measures how much error there is between two data sets. In other words, it compares a predicted value and an observed or known value. The smaller an RMSE value, the closer predicted and observed values are

Figure 42 RMSE error

RMSE = (Original value â&#x20AC;&#x201C; predicted value) The white area and green area represents higher RMS error due to the Disperse nature of point the other area where the points are closer to each other have lesser error Because the points are nearer

Figure 43 Error Map for RMSE Error of rainfall for Sabarmati watershed

44

Spatial Analysis Techniques

Watershed Analysis Using DEM

A dense network is required to estimate accurately spatial distribution For that 42 points are used for interpolation on the entire watershed

Figure 44 Interpolation for rainfall data for Sabarmati watershed

Dark Red color cluster shows more rainfall in watershed, north east side more rainfall in watershed in 2019 year.

45

Spatial Analysis Techniques

Watershed Analysis Using DEM

5.2 Kriging Interpolation If a weatherman makes a forecast saying it’s going to rain tomorrow, how sure are you that it’s going to rain?

Instead of only saying here’s how much rainfall at specific locations, kriging also tells you the probability of how much rainfall at a specific location.

You use your input data to build a mathematical function with a semi variogram, create a prediction surface and then validate your model with cross-validation. Not only does geostatistics provides an optimal prediction surface, it delivers a measure of confidence of how likely that prediction will be true.

PREDICTION: This surface straight predicts the values of your variable you are kriging.

ERROR OF PREDICTION: If depicts the standard error with higher standard of error where there isn’t as much input data.

PROBABILITY: The probability surface highlights when it exceeds a threshold.

QUANTILE: This surface represents a best or worst case scenarios as a 99th percentile.

Figure 45 Kriging interpolation for rainfall for Sabarmati Watershed

As Distance increases in the semi-variogram, we can see that the semi-variance is increasing and spatial co-relation is decreasing. The information provided through semi-variogram has been used to achieve optimal weighting functions, by which certain location surrounded by certain points got more prioritization than others.

46

Spatial Analysis Techniques

Watershed Analysis Using DEM

5.3 Rainfall Runoff Rain water harvesting is a hydrological intervention which can best be depicted through hydrological models that are able to show directions of flow, runoff and run on area and identify locations for impounding structures. Runoff modeling is relationships for the basin are considered using the SCS curve number method. In undertaking hydrological modeling using remote sensing data in GIS environment the SCS curve runoff model is largely suitable due to its reliance on land cover parameters which can be extracted from remote sensing (Senay et al., 2004).

Runoff curve number equation estimates total runoff from total rainfall and this relationship excludes time as a variable and rainfall intensity. Its stability is ensured by the fact that runoff depth (Q) is bounded between the maximum rainfall depth (P). This implies that as rainfall amount increase the actual retention (P-Q), approaches a constant value; the maximum potential retention (USDA, 2004) The runoff estimation related runoff (Q) to precipitation (P) and the curve number (CN) which is in turn related to storage (S). CN is based on the following parameters; hydrologic soil group, land use and treatment classes, hydrologic surface conditions. Equation 1 known as the runoff curve number gives the relationship between the parameters described below.

Where; Q = runoff depth (mm) ,P = rainfall (mm) ,S = potential maximum retention after runoff starts (mm) ,Ia =

initial abstraction (mm) Initial abstraction consists mainly of interception, infiltration during early parts of the storm, and surface depression storage. Its determination is not easy due to the variability of infiltration during the early part of the storm since it depends on conditions of the watershed at the start of a storm such as the land cover, surface conditions and rainfall intensity; thus it is assumed to be a function of the maximum potential retention. (USDA, 2004) Potential maximum retention (S) can be calculated by the Curve Number as below

The soil conservation service (SCS) model depends on the runoff Curve Number (CN). Curved Number is estimated via the effect of soil and land cover on the rainfall runoff processes. The range of the Curve Number (CN) is between 1 (100 % rainfall infiltration) and 100, lower values of the Curve Number indicate lower runoff, while higher values of Curve Number refer to higher values of runoff.

5.3.1 Factors Determining the Curve Number Value Land Use or Land Cover:- Land use represents the surface conditions in area and is related to the degree of cover.

Treatment or Practice in relation to Hydrological Condition:- Land treatment applies mainly to agricultural land uses; it includes mechanical practices such as contouring or terracing, and management practices such as rotation of crops, grazing control, or burning.

Hydrological Soil Group(Group A,B,C,D):- Soil properties greatly influence the amount of runoff. In the SCS method, these properties are represented by a hydrological parameter: the minimum rate of infiltration obtained for a bare soil after prolonged wetting.

Antecedent Moisture Condition(AMC-I,II,III):- The soil moisture condition in the drainage basin before runoff occurs is another important factor influencing the final CN value.

47

Figure 46 Methodology for runoff

Spatial Analysis Techniques

Watershed Analysis Using DEM

HSG Soil % % Area CN CN*Area a 48.2 1,095,029,049.02 76 83222207725 b 45.62 1,036,415,460.92 85 88095314178 c 5.23 118,817,467.35 89 10574754594 d Latitude 0.93 21,128,153.85 91 Runoff 1922662000 Longitude Year Annual Rainfall total 24.335 100 73.411 2271844500 2019 170.2936364 1.83815E+11 139.4870246 24.351 73.279 2019 170.2936364 139.4870246 area wieighted CN no.

80.91 24.356 24.362 Latitude 24.455 24.335 24.459 24.351 24.494 24.356 24.499 24.362 24.616 24.455 24.636 24.459 24.786 24.494 24.873 24.499 24.654 24.616 24.332 24.636 24.475 24.786 24.489 24.873 24.344 24.654 24.335 24.332 24.265 24.475 24.319 24.489 24.458 24.344 24.29 24.335 24.326 24.265 24.613 24.319 24.358 24.458 24.59 24.29 24.745 24.326 24.762 24.613 24.7 24.358 24.614 24.59 24.476 24.745 24.464 24.762 24.393 24.7 24.329 24.614 24.228 24.476 24.462 24.464 24.323 24.393 24.416 24.329 24.587 24.228 24.619 24.462 24.623 24.323

24.416 24.587 24.619 24.623 48

73.048 2019 169.9272727 139.1258837 73.177 Year 2019 Annual 169.9272727 139.1258837 Longitude Rainfall Runoff 73.081 2019 169.9272727 139.1258837 73.411 2019 170.2936364 139.4870246 73.439 2019 170.2936364 139.4870246 73.279 2019 170.2936364 139.4870246 73.471 2019 170.2936364 139.4870246 73.048 2019 169.9272727 139.1258837 73.114 2019 169.9272727 139.1258837 73.177 2019 169.9272727 139.1258837 73.323 2019 176.8481818 145.9516002 73.081 2019 169.9272727 139.1258837 73.472 2019 176.8481818 145.9516002 73.439 2019 170.2936364 139.4870246 73.335 2019 169.9272727 139.1258837 73.471 2019 170.2936364 139.4870246 73.363 2019 169.9272727 139.1258837 73.114 2019 169.9272727 139.1258837 73.534 2019 191.4590909 160.3830746 73.323 2019 176.8481818 145.9516002 73.253 2019 170.2936364 139.4870246 73.472 2019 176.8481818 145.9516002 73.205 2019 169.9272727 139.1258837 73.335 2019 169.9272727 139.1258837 73.28 2019 170.2936364 139.4870246 73.363 2019 169.9272727 139.1258837 73.463 2019 170.2936364 139.4870246 73.534 2019 191.4590909 160.3830746 73.394 2019 170.2936364 139.4870246 73.253 2019 170.2936364 139.4870246 73.353 2019 170.2936364 139.4870246 73.205 2019 169.9272727 139.1258837 73.257 2019 170.2936364 139.4870246 73.28 2019 170.2936364 139.4870246 73.219 2019 169.9272727 139.1258837 73.463 2019 170.2936364 139.4870246 73.26 2019 170.2936364 139.4870246 73.394 2019 170.2936364 139.4870246 73.414 2019 170.2936364 139.4870246 73.353 2019 170.2936364 139.4870246 73.545 2019 191.4590909 160.3830746 73.257 2019 170.2936364 139.4870246 73.129 2019 169.9272727 139.1258837 73.219 2019 169.9272727 139.1258837 73.25 2019 176.8481818 145.9516002 73.26 2019 170.2936364 139.4870246 73.404 2019 162.1108333 131.4261851 73.414 2019 170.2936364 139.4870246 73.331 2019 146.5758333 116.1579116 73.545 2019 191.4590909 160.3830746 73.514 2019 175.5041667 144.6255139 73.129 2019 169.9272727 139.1258837 73.543 2019 175.5041667 144.6255139 73.25 2019 176.8481818 145.9516002 73.529 2019 169.7166667 138.9182896 73.404 2019 162.1108333 131.4261851 73.582 2019 169.7166667 138.9182896 73.331 2019 146.5758333 116.1579116 73.545 2019 169.7166667 138.9182896 73.514 2019 175.5041667 144.6255139 73.51 2019 169.7166667 138.9182896 73.543 2019 175.5041667 144.6255139 73.215 2019 155.2566667 124.683501 73.529 2019 169.7166667 138.9182896 73.285 2019 156.1025 125.5150779 73.582 2019 169.7166667 138.9182896 73.008 2019 155.7666667 125.1848876 73.545 2019 169.7166667 138.9182896 73.042 2019 169.9272727 139.1258837 73.51 2019 169.7166667 138.9182896 73.314 2019 162.1108333 131.4261851 73.215 2019 155.2566667 124.683501 73.

157 2019 161.0033333 130.3360915 73.285 2019 156.1025 125.5150779 73.422 2019 162.1108333 131.4261851 73.008 2019 155.7666667 125.1848876 73.042 2019 169.9272727 139.1258837 73.314 2019 162.1108333 131.4261851 73.157 2019 161.0033333 130.3360915 73.422 2019 162.1108333 131.4261851

Figure 47 Hydrological Soil Group Map of Sabarmati watershed

Spatial Analysis Techniques

Watershed Analysis Using DEM

It's too crucial to predict run off in the basin area.

Because of the limited data set, IDW method has been used here to know how the runoff is flowing in entire region.

Figure 48 Runoff Map for Sabarmati Watershed

49

Spatial Analysis Techniques

Watershed Analysis Using DEM

5. Zonal Statistic Zonal statistics calculates or performs the statistics with the values of the value raster. Then get the statistics values for each zone based on the zone raster. A zone is defined as all the cells that have the same value in the input (the discontinuous cells of same value are accepted to be a zone). Zone raster defines the shape, value and position of the zone, and the input value raster provides the original data for calculation. Ten statistics types are available, Majority, Minority, Maximum, Mean, Minimum, Median, Range, Standard deviation, Sum and Variety.

5.1 Maximum elevation in district Zonal statistics analyzes the situation in zones. For instance, users can analyze the lowest elevation of each District using the zone statistics analysis. In this Zonal Raster is District Shape file and Value Raster is Elevation DEM And I used Majority for showing districts having high elevation so in this Gounda district have higher elevation and starting of river form that and comes to kotra than khed brahmar higher elevation from lover.

50 Figure 49 Zonal statistic for Elevation in districts for Sabarmati watershed

Spatial Analysis Techniques

Watershed Analysis Using DEM

5.2 Runoff in various LULC

Zonal Raster

Value Raster

Figure 50 Zonal Statistic on Runoff in Sabarmati watershed

51

Use Zonal statistic for land-use classification and Runoff of watershed for where high runoff happening in watershed open land have more runoff this red color shows high runoff and in land use there open ground now we can select more precise site suitability with help of this where is high runoff we can locate our check dam there

Spatial Analysis Techniques

Watershed Analysis Using DEM

Figure 52 More Suitable site for check dam

Figure 51 More Suitable site for check dam

cv 52

Spatial Analysis Techniques

Watershed Analysis Using DEM

Reference ➢

Hydrological inferences from watershed analysis for water resource management using remote sensing and GIS techniques Prafull Singh *, Ankit Gupta, Madhulika Singh

➢

www.india-wris.nrsc.gov.in

➢

Selection of Sites for Water Harvesting Structures in part of Sabarmati River Basin, Gujarat, India using Remote Sensing and Geographical Information System

➢

Water Resources Assessment of Sabarmati River Basin, India A document to analyse the future scenarios of a water-deficit basin as support to country water policies

➢

https://gisgeography.com

➢

https://www.mathopenref.com

➢

https://www.ras-exam.com/rajasthan-geography/sabarmati-river-origin-tributaries-basin/

➢

http://chrsdata.eng.uci.edu/

➢

https://soilgrids.org

➢

Site Suitability Analysis for Small Multipurpose Dams Using Geospatial Technologies Saima iftikhar* ,Zeshan Hassan, Rida Shabbir

➢

Site Suitability Analysis of Water Harvesting Structures Using Remote Sensing and GIS – A Case Study of Pisangan Watershed, Ajmer District, Rajasthan Harish Chand Prasad, Parul Bhalla and Sarvesh Palria Dept. of Remote Sensing and Geo-informatics

➢ Drainage morphometry and its inflfluence on hydrology in an semi arid region: Using SRTM data and GIS

53

Spatial Analysis Techniques

Tej Chavda PG191052

54

Watershed Analysis Using DEM