Surjit Singh Saini Research Scholar,

Department of Geography, Kurukshetra University Kurukshetra, Haryana

Vulnerability Assessment for Soil Erosion Using Geospatial TechniquesA Geographic Study of Upper Catchment of Markanda River

3rd International Geography Congress06-08 May, 2011 Kozhikode, Kerala, India

Dr. S.P Kaushik Associate Professor,

Department of Geography, Kurukshetra University Kurukshetra, Haryana

• In this study GIS and remote Sensing techniques is used to establish an geospatial data base to characterize a watershed and evaluated vulnerability to soil erosion using multi-criteria assessment based on weight assignment to each factor responsible for soil erosion.

• The model located potential erosion areas which need control and preventive measures according to the degree of erosion.

Introduction

• Singh et al. (1992) have estimated that the annual rate of soil erosion is more than 15-20 tons /ha/year in Shiwalik region. Consequently, Shiwalik environment considered most fragile ecosystem in the country

• Soil erosion hazard is a major land degradation problem in Shivalik region of sub Himalayan mountainous environment. Singh et al. (1992) clearly indicated that Shiwalik are comprised of sandstone, grit, and conglomerates, with characters of fluvial deposits, but slopes near the foothills contain pebbles and boulders and these formations are geologically weak and unstable resultant these areas are highly vulnerable to soil erosion.

OBJECTIVES

I.To Identify vulnerable area to soil erosion based on influencing factors such as rainfall, vegetation, soil type, slope, drainage density, land use and aspect of slope using GIS & Remote Sensing techniques.

II.To Prepare the composite map showing level of vulnerability to soil erosion hazard.

• The Upper Catchment of Markanda River

• Part of Shivalik region of sub Himalayan mountainous environment

• Geographical Extent: • 760 06′19” to 770 22′56”E • 300 18′52” to 300 41′18”N

• Total area:593 km2

• 53% in Himachal

• 47% in Haryana

Study Area

Remote Sensing Data

TM Landsat imagery of year 2009, 30 m resolution (path 147 and row 039) http://ftp.glcf.umd.edu

Georeference Satellite Imageries in Erdas Imagine 2010

Rainfall

SOI-Toposheet on 50k scale

Contour

Slope &Aspect

Database and Methodology

Soil Type

Multi Criteria Evaluation using Rank Sum Methods and Weighted Overlay Analysis Using Raster Calculator in ArcGIS 9.2

Vegetation cover NDVI= (NIR-VIS)/(NIR+VIS)

Digital Elevation Model (DEM)

Land Use Drainage Network & Density

Delineation of Area Vulnerable to Soil Erosion

Weight Assign to Parameters According to Relative Importance with Respect to their contribution to Soil Erosion

District wise Report on Ground Water prepared by CGWB

Other Ancillary Maps & Data

Factors & Weighting Scheme used for Assessment Area Vulnerable to Soil Erosion

Erosion Parameters Sub-class of Parameters Sub-Class Weightages Per cent of Influence

1.Rainfall More than – 1200 mm 3 25.01101 mm – 1200 mm 21000 mm – 1100 mm 1

2. Vegetation cover Very less vegetation 5 21.4Less vegetation 4Moderate vegetation 3High vegetation 2Very high vegetation 1

3. Soil Eurtrochrepts/ Udorthents (shallow & loamy) 3 17.9Udipsamments/Udorthents (loamy sand to sandy loam 2Udipsamments/Udorthents ( sandy loam to clayey loam) 1

4. Slope Very Steep (>40%) 5 14.3Steep (30.1-40%) 4Moderate (20.1-30%) 3Gentle (10.1-20%) 2Very Gentle (<10%) 1

5. Drainage Density >6 km/sq.km 5 10.75.1-6.0 km/sq.km 44.1-5.0 km/sq.km 32.1-4.0 km/sq.km 2<2 km/sq.km 1

6.Landuse Agriculture 5 7.1Sparse vegetation 4Forest 3Water bodies 2Settlement 1

7. Aspect of Slope West direction 5 3.6East direction 4Flat 3South direction 2North direction 1

Analysis, Result and Discussion

Weight Calculation Using Rank Sum Method

Sr.no Parameter of

Criteria

Straight

Rank (rj)

Weight

(n-rj+1)

Normalized

Weight (wj)

Weight (%)

1 Rainfall 1 7 0.25 25.0

2 Vegetation Cover 2 6 0.21 21.4

3 Soil 3 5 0.17 17.9

4 Slope 4 4 0.14 14.3

5 Drainage Density 5 3 0.10 10.7

6 Land use 6 2 0.07 7.1

7 Aspect of Slope 7 1 0.03 3.6

N=7  Sum   28 1.00 100

Where wj is the normalized weight for the jth criterion, n is the number of criteria under consideration (j=1, 2… n), rj is the rank position of the criterion. Each criterion is weighted (n-rj+1) and then normalized by the sum of weights, that is, Σ (n-rj+1).

Rainfall Factor

Vegetation Factor

Soil erosion potential is increased if the soil has no or very little vegetative cover of plants and/or crop residues. Plant and residue cover protects the soil from raindrop impact and splash, tends to slow down the movement of surface runoff and allows excess surface water to infiltrate.

Very Less Vegetation

Less Vegetation

Moderate Vegetation

High Vegetation

Very High Vegetation

Vegetation Categories Weight

1

5

4

3

2

12345

Weight

.

Soil Type

Udipsamments / Udorthents (sandy loam to clayey loam)

Eurtrochrepts/ Udorthents (shallow & loamy)

Udipsamments/Udorthents (loamy sand to sandy loam

Weight

3

1

2

Soil FactorSoils differ in their resistance to erosion, which is a function of a range of soil properties such as texture, structure, soil moisture, roughness, and organic matter content. The susceptibility of soil to erosion agents is generally referred to as soil erodibility (Lal, 2001). Soil classifications are often used to account for spatial differences in erodibility. Important factors on the basis of which soils can be classified include soil properties, climate, vegetation, topography, and lithology.

.

Slope FactorWeight

1

543

2

Slope ( % )

Very Gentle

Gentle

Moderate

Steep

Very Steep

< 10

10.1 - 20

20.1 - 30

30.1 - 40

> 40

Categories

Very Steep

Steep

Moderate

Gentle

Very Gentle

>40

30.1-40

20.1-30

10.1-20

<10

5

4

3

2

1

Slope (%) Weight

.

Slope affects soil erosion rates in several different ways. As slope gradient increases, the impact angle of raindrops becomes more acute. The amount of soil loss from erosion by waters with the steeper the slope. As a result of gravity, a greater proportion of the mass and the momentum of the soil, water, and sediment particles act in the down slope direction.

Elevation

High : 1519 Low : 278

DEM

Weight

1

5

432

6

Drainage Density

< 2.0

2.1 - 4.0

4.1 - 5.0

5.1 - 6.0

> 6

( Km. / Sq.km )

Drainage Density

Aspect of slope

North

South

Flat

East Direction

West Direction

Aspect of Slope

5

4

3

2

1

Weight

Agriculture

Forest

Settlement

Waterbodies

Sparse Vegetation

Weight

5

1

2

3

4

Land Use Classes

Land Use

rainfallvegetationsoilsslopedrainage densityland useaspect

CalculationValue

High : 360.60

Low : 125.00

Level of Vulnerability to Soil Erosion

Weighted Overlay Analysis using Raster Calculator in ArcGIS 9.2

Final ResultRe-classified Composite Map

Degree of Vulnerability to soil Erosion

Area (Hectares)

% to total

10904 18.39

13996 23.60

16061 27.09

14399 24.28

3939 6.64

Total 59299 100

Very High

High

Medium

Low

Very Low

During monsoon Rain water with High Turbidness, Markanda Bridge at SH-1, Sadaura, Ambala

• This study demonstrates that geospatial techniques are indeed valuable tools in assessment and mapping of areas vulnerable to soil erosion hazard.

• Existing methods for identifying the erosion potential area is based on physical survey but in practices when erosion problem is very wide it is difficult task and time consuming. Therefore, Geospatial techniques based spatial modeling (weighted overlay) produce useful information for solving complex problems by identifying relationship among various geographic features clearly and logically.

• Such models based integrated maps are important in planning conservation and control measures for soil erosion as per the degree of vulnerability.

Conclusion

Thanks for your kind attention