modelling of soil erosion estimation in upper catchment

Received: 05 February 2018

Reviewed and Accepted: 11 April 2018

Published: 23 April 2018

Journal of Water and Land use Management

ISSN: 0973-9300, Volume 16, Issue 2

Modelling of Soil Erosion Estimation in Upper Catchment Area of Bhagirathi River

Suresh Kumar Bandooni, Virender Singh Negi, Suman Das,1 Gourav Nain

Abstract Soil erosion is a significant challenge, especially for reservoir resulting

in siltation and causing the loss of topsoil and fertility in agricultural land over the

mountain region. In this study, soil loss of Tehri reservoir catchment is calculated

using Sediment yield Index (SYI) method. Remote sensing data and GIS

techniques has been used to compute runoff and soil erosion in the catchment area

of upper Bhagirathi river covering an area of approximately 7286 km2. Different

thematic layers, for soil, topography, rainfall erosivity and land use parameters,

were generated for 13 micro watersheds of upper Bhagirathi Catchment. Data

integration was done by use of the weighting rating technique, a conventional

qualitative method, as per the SYI model and minimum and maximum sediment

yield values were calculated. The priority ranks as per the sediment yield values

were assigned to all micro-watersheds. Then the values were classified into four

priority zones according to their composite scores. Sub-watershed 10,11 was

assigned a very high priority with SYI mean average value 2065.78, approximately

24.80 per cent of the study area fell under the high priority zones. Most of the lands

in these sub-watersheds are covered by reservoir area of Tehri Dam. Sub-watershed

7,4,8,9 and 13 were assigned a high priority with SYI mean average value

1971.47cover almost 33.18 percent of the study area. Together very high and high

priority zone covers nearly 58 percent of the study area. These areas require

immediate attention. Therefore, proper designing of integrated watershed

management and conservation strategies is proposed to reduce the current rate of

siltation of the reservoir, environmental degradation, and boost up agricultural

production in the sub-watersheds.

Keywords: Soil erosion; Bhagirathi catchment; Tehri dam; sediment yield index

(SYI); rainfall erosivity

Suman Das ()⚫ Gourav Nain ⚫ Suresh Kumar Bandooni ⚫ Virender Singh Negi Department of Geography, Shaheed Bhagat Singh Evening College, University of Delhi.

2

Introduction

The Himalayan terrain of India is generally characterized by steep slopes and

complex geological setting which provide challenges for river harnessing schemes,

a number of which are at the planning stage in the Bhagirathi river basin watershed

is a discrete and complex system where a diverse number of factors govern its

quality and health. Soil erosion by water is the most dominant factor that determines

a watershed quality and considered as one of the most significant forms of land

degradation that affects sustained productivity of land use. The objective of this

paper is to utilise spatial-based soil erosion information to assess land suitability at

a watershed level (Baja et. Al., 2014)

The soil erosion is the most serious environmental problem in watershed areas

in the Bhagirathi River. The main factors affecting the amount of soil erosion

include vegetation cover, topography, soil, and climate. To describe the areas with

high soil erosion risks and to develop adequate erosion prevention measures in the

watersheds of dams, erosion risk maps should be generated considering these factors

(Yuksel. et. Al., 2008). Remote Sensing and Geographic Information System

technique were used for erosion risk mapping in the catchment area of Bhagirathi

River. Tehri Dam Reservoir of, based on the methodology implemented in the

model. CARTOSET imagery was used to generate a land use/cover classification in

QGIS. The digital raster maps of the other factors (topography, soil types, and

climate) were generated in QGIS. The model integrated with RS and GIS

technologies has great potential for producing accurate and inexpensive erosion risk

maps.

Statement of Problem

“Reduction in the capacity and life of the Tehri dam Reservoir became a major

concern. The Tehri dam, located in the north of India, was commissioned in 2006 to

provide water for electricity generation, irrigation and drinking water. It has a

sediment trap efficiency of 95 per cent and was designed to offset 150 years of

sedimentation. Watershed management is the principal measure in use for reducing

the sediment inflow into the Tehri reservoir”(IHA, 2006).

“The catchment tributary to the Tehri dam comprises 7,691 km2 and forms part

of the Himalayan mountain range and is characterised by four months of a rainy

season called „monsoonʼ. The monsoon lasts from June to September, with July and

August considered the peak flow period.

Both the Bhagirathi and the Bhilangana Rivers originate from a glacier. The

annual average precipitation varies from 1,016 mm to 2,630 mm during the rainy

season when the 40-60 per cent of the annual rainfall occurs. The Tehri reservoir is

designed to store the surplus flow during the monsoon season, resulting in about

one-third of the average annual water yield of the Bhagirathi River - about 2,615

Mm3 - being stored in the Tehri dam. The fragile geology and the topographical

features of the catchment, with its steep slope valleys, combined with development

activities such as deforestation and terrace cultivation, increased the erosion rate in

the area. The Bhagirathi River transports large amounts of sediment, with a mean

annual suspended sediment load of about 6.8 Mt. The river bed material consists of



boulders, sand, and silt. The most significant sediment transport occurs during the

rainy season. The specific annual sediment yield in the watershed is 907 t/km2. The

Brune curve estimates the trap efficiency of the Tehri dam to be 95 percent”(IHA,

2017).

Objective

(i) To develop a technique based on a GIS and parameter of a soil erosion model,

which is designed for use at a large scale assessment;

(ii) To assess and map the spatial distribution of hotspot of soil losses in upper

Tehri Catchment;

Study Area

The Study area covers an upper catchment area of Tehri Reservoir. Which includes

Bhagirathi catchment area of Uttarkashi and Tehri Garhwal district of Uttarakhand

and south-Eastern part of Kinnaur district of Himachal Pradesh. Tehri dam

Reservoir is extending for over 44km in the Bhagirathi river valley and 25 km in

Bhillangna river valley a sub-basin of the river Bhagirathi.

The study area covers approximately 7285.65 sq km with an elevation of 713 to

7010 m and slopes of 0 to 83%. The land use/cover of the area contains agriculture,

forest, rangeland, bare rock, water bodies, and residential areas. Average annual

precipitation and temperature are 730 mm and 17.6 C, respectively. The highly

erosive storms occur during fall and spring seasons. The Tehri Dam is one of the

most important dams in the country. The 260.5 m high dam stores about h m water

in the approximately The construction of the dam was started in the year of 1978,

and Phase 1 was completed in 2006. The total catchment area of the reservoir is

about sq. Km. and gross command area is sq. Km. The maximum height of this

earthen dam is 24.53 m and length is 2,906.43 m respectively. The location map of

the study area is shown in Figure 1.

4

Figure 1 Location map of Upper Catchment of Bhagirathi watershed in Uttarakhand, India.

Methodology and data set

Data on Climate (Total precipitation and its frequency and intensity),

Geomorphology (Landform, Physiography, Slope and Drainage Characteristics),

Soil characteristics (Texture, structure), Land Use/ Land cover (Density of forest or

grassland, plant residue, crops etc.) and Soil management were calculated using

standard reported methods (Naqvi et al., 2015). Most importmant factors that have

been observed in the estimation of an integrated watershed management approach

were calculated using standard methods. The slope was calculated using the Digital

Elevation Model. LULC map is prepared by using Google Earth Engine. Raster

images showing Digital Elevation Map (DEM) of the watershed was downloaded

from USGS Earth Explorer using Geographic Coordinate System GCS WGS 1984



UTM 44 Zone and Datum D WGS 1984 for projections in maps and rasters. QGIS

2.6 and QSWAT software were used for Soil Yield Index modelling. Soil Yield

Index (SYI) is calculated using formula

𝑆𝑒𝑑𝑖𝑚𝑒𝑛𝑡 𝑌𝑖𝑒𝑙𝑑 𝐼𝑛𝑑𝑒𝑥 (𝑆𝑌𝐼) =∑(𝐴𝑖×𝑊𝑖×𝐷𝑖)

𝐴𝑤× 100

Where i=1 to n

Ai= Area of ith mapping unit

Wi= Weightage of assigned to ith unit

Di= Delivery ratio assigned to ith unit

Aw=Total area of the watershed

Figure 2 Flow chart of the methodology adopted for SYI modelling

6

Table 1 Parameter, source and criteria adopted for SYI calculations

S.No. Parameter Source Criteria adopted for weightage value

1.

Landuse/landcover LANDSAT-8 Surface

Reflectance – 18th March

2015.

Barren land is an indicator of anthro pogenic pressure in naturally fragile areas. More the barren land cover more the weightage value.

More the forest coverage lower the

weightage value.

2. Soil Texture World soil map (FAO) Soil texture influence soil loss

calculations. High value assigned for

sandy loam texture

3. Topography Cartosat-30m DEM

March 2015. Weightage is directly proportional to

the slope of the terrain.

4. Drainage Cartosat-30m DEM

March 2015. Higher the drainage density higher

the weightage.

5. Rainfall Indian Meteorology De- The most important factor for soil

partment loss ratio. Higher the rainfall higher the weightage

values are assigned.

Data Layer Preparation

Land Use Land Cover

LULC map showing dense forest in the region with barren land. The watershed

catchment area shows large snow cover. More the forest coverage lowers the

weightage value for the sedimentation in the watershed catchment. Weightage is

directly proportional to the slope of the terrain. The LULC map exhibit that in the

watershed Dense Vegetation covered 2767.57 hectors, Sparsh Vegetation cover

113.96 hectors, while barren land covered approximately 427.02 hectors,

Agricultural Land cover 283.93 hectors, Fallow Land cover 62.00 hector, built-up

areas occupied about 18.05 hector, Snow covers 296.06 hector, water body covers

105.80 hectors, and Fresh Sediment cover 30.68 hectors.



Figure 3 Land Use Land Cover map of the upper catchment of Bhagirathi.

Slope ( in Degree)

The slope is a key factor affecting the rate of soil loss. Areas in high altitude

depositions were assigned high weightage values (Fig.4.a). Slope map has been

calculated by using Cartosat 30m DEM. The slope classified into five category range

from 0 to 83.80 degree.

Rainfall erosivity

Rainfall is the most important determining factor for soils. The values of selected

stations were interpolated and categorized into classes. With higher weighted value

assigned to regions receiving high rainfall erosivity. R factor can be calculated by

an equation given by Singh et al., 1992, it is expressed as-

Rfactor = 79 + 0.363* R

Where R is the average annual rainfall in mm. Then the Rainfall erosivity (4.b) has

been classified into five categories, namely Very low, Low, Medium, High and

Very High.

Drainage Density

Drainage density/number of streams has a direct bearing on soil erosion leading to

the highly dissected landscape. Greater the Drainage Density or number of streams,

higher the weightage. Drainage has been extracted by using Cartosat DEM, then

drainage density (Fig. 4.c) was calculated. The density range from 0.14 to 3.59.

8

Figure 4 Map showing variance in Degree of Slope(A), Rainfall Erosivity(B), Drainage

Density(C) & Soil texture (D) of upper catchment of Bhagirathi watershed.

Soil texture

Soil cover map of the study area was prepared by using World Soil Map (FAO).

Three types of soil were identified in the area, i.e. gravel loam, loam, and silt loam

(Fig.4.d).

Delivery Ratio

The delivery ratio has been calculated on the basis of the nearest stream (drainage

density) distance in kilometres. The values of delivery ratio were assigned according

to the length of the stream. In the study area, most of the micro watersheds were

assigned 0.9 (Naqvi et. Al., 2015) value from delivery ratio as per the drainage

density. In this study, most of the streams are between 2 to 5 km.

Calculated SYI values for sub-watershed prioritization

The SYI method is highly useful for prioritization of sub-watersheds according to

erosion impact. In this study, several important parameters were considered (Table

3), including land use/land cover, soil texture, slope, drainage density, and rainfall

erosivity. Firstly, the weighted values for every factor were assigned on the basis of

their risk level. All these factors were added in the raster calculator to generate one

thematic map. The weighted values were assigned using the Reclassify tool. Then

Delivery ratio was taken from previously published literature (Table 4).

Then SYI were calculated, and priorities to sub-watersheds were assigned (fig. 5).



Table 3 Assigned weightage values of all factors for SYI calculation

S. no. Parameters/factors Categories/classes Assigned weightage values

1

Soil texture

Gravel loam 1

Litho Soil 3

Silty loam 5

2

Slope (degree)

0-14.13 1

14.33-23.99 3

23.99-32.53 5

32.53-41.73 7

41.73-83.80 9

3 Slope length 0-14.44 1

14.44-46.93 3

46.93-83.04 5

83.04-131.78 7

131.78-460.35 9

4

Rfactor

0-110.78 1

110.78-113.07 3

113.07-115.36 5

115.36-117.65 7

117.65-119.93 9

5

Landuse/Landcover

Snow 1

Waterbody 1

Dense Vegetation 1

Sparsh Vegetation 3

Barren Land 8

Agricultural Land 5

Fallow Land 7

Fresh Sediment 9

Buildup 3

6

Drainage Density

0.14-0.83 1

0.83-1.52 3

1.52-2.21 5

2.21-2.90 7

2.90-3.59 9

10

Figure 5 SYI value of upper Catchment of Bhagirathi Watershed

Discussion

Total five parameters were calculated, i.e. Slope, Soil texture, Drainage density, land

use/landcover and Rainfall erosivity. Weightage of each parameter on the basis of

value and classes were assigned (Table 3). In this study, we have used an odd

numbering system to assign priority to different parameters (1 to 9, where 1 indicate

the lowest priority and nine maximum priority). In the case of the slope, higher the

slope value higher will be erosion, so less priority to low slope value and vice versa.

Similar metric has flowed for slope length higher the slope length runoff will be

more, therefore, resulted in more erosion; hence higher value has assigned to large

slope length and vice versa. At higher slope, there will be more erosion and

transportation and lesser in case of low slope. In soil texture, litho soil is most

dominant soil class in the study area, followed by gravel loam and silty loam. Higher

weighted values have been assigned for silty loams because it can be eroded easily

in comparison to other soil types in the study area. Rainfall erosivity is the most

important determining factor for soil loss. Higher the values more will be weightage

has been assigned in this study area. We have classified 9



LULC classes based on their spectral signatures. Snow cover area and build-up area

will be least erodible areas because these areas have the least direct interaction with

rainfall, so we have assigned very low value to these classes. Followed by dense

forest which will have low direct interaction with rainfall, so higher value then snow

and built up is assigned for dense forest. After this, moderate weightage given to

Agricultural and fallow land and highest weightage value assigned for fresh

sediment and barren land (table 3). In drainage density, denser the value more the

erosion, so weightage values assigned to the highest value and viceversa. All

weightage maps from all factors were prepared and merged in raster calculator

(adding all weightage maps). At last SYI value were calculated using weighted map,

Delivery ratio, area of the watershed (Table 4).

Table 4 Mean SYI Value of Sub watersheds

Sub-watershed SYI Value Area in Km2

SW1 1674.91 458.77

SW2 1458.37 253.48

SW3 1595.35 248.29

SW4 1954.57 236.2

SW5 1898.18 618.6

SW6 1863.44 1149.73

SW7 1950.94 891.35

SW8 1968.94 236.53

SW9 1989.76 262.07

SW10 2019.21 488.66

SW11 2112.35 1318.52

SW12 1859.88 331.81

SW13 1993.16 791.63

Micro-watershed prioritization based on calculated SYI values

For Prioritization of Sub-watershed of the upper catchment of Bhagirathi basin, total

four classes were classified, e.g. low, moderate, high, and very high on the basis of

SYI values (fig. 5). Mean average value of each class were calculated (Table 5).

Sub-watershed 10,11 was assigned a very high priority with SYI mean average value

2065.78. Most of the lands in these sub-watersheds are covered by reservoir area of

Tehri Dam. Sub-watershed 7,4,8,9 and 13 were assigned a high priority with SYI

mean average value 1971.47. Most of the lands in these watersheds are barren land,

sand bars and Sparsh Vegetation respectively. 1, 12, 6, 5, sub-watershed was

assigned a moderate priority with SYI mean average value 182 .1 , and most of the

land under Fallow with dense forest. Least priority was given to 2, 3 sub-watersheds,

mostly covers dense forest and snow and Rocky Surface.

12

Table 5 Sub watersheds under different priority zones.

Priority categories Priority

classes

Mean SYI Value Sub-watershed Area in Km2

Area in %

Very High 1 2065.78 10, 11 4131.56 16.98

High 2 1971.47 7, 4, 8, 9, 13 9857.37 40.50

Medium 3 1824.10 1, 12, 6, 5 7296.41 29.98

Low 4 1526.86 2, 3 3053.72 12.55

Conclusion

Watershed soil erosion and reservoir sedimentation are some of the major

environmental problems that reduce the productivity of land resources in the upper

catchment of Bhagirathi Basin. In this study, the SYI method was used to calculate

soil loss in sub-watershed in the study area. Thematic layers of all parameters for

the SYI model were mapped. The sub-watersheds 10, 11 were identified as being

very high risk. Intense rainfall and reservoir area of dam coupled with poor soil

structure and steep slopes are the main drivers of soil erosion in this area. The

Integrated Watershed Management approach, as evolved in recent years, should be

employed to harmonize the comprehensive objectives of increasing agricultural

productivity and production. Therefore, the proper designing of integrated

watershed management and conservation strategies is a crucial element to reduce

the current rate of siltation of the reservoir, environmental degradation, and boost

up agricultural production in the sub-watersheds.

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modelling of soil erosion estimation in upper catchment

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