Rajashree V Bothale, J R Sharma
Regional Remote Sensing Service Centre, Jodhpur
S C Gupta
R S Directorate, CWC, New Delhi
The natural hydrologic processes like erosion of soil, movement of soil and its deposition in various parts of reservoir are very crucial phenomena occurring in any watershed. Erosion of soil is a very complex process which is affected by many factors and the loss caused is irreversible. Soil erosion starts from the upper reaches of watersheds and then slowly gets transported to the downstream reservoir causing the reduction in useful storage capacity of reservoir. Land and water management on watershed basis has a scientific proven base, which helps in reducing soil erosion, increasing the productivity along with proper and sustainable utilisation of resources.
For larger watersheds, where the detailed soil maps are not available and preparation is costly and time consuming, a method which uses the layers derived from satellite data is most convenient. Priority of watershed depends upon various parameters. The present paper analyses the response from a watershed using Erosion Response Model (ERM). In this method vegetation density, soil brightness, slope and morphometric parameters are used for watershed prioritisation. ERM utilises drainage and slope characteristics of watershed for prioritisabon. ERM model adds the weights of each affecting parameter and calculates the response of watershed.
Study area is Bajaj Sagar sub catchment of Mahi basin. The Mahi river rises from the Northern slope of Vindhyan ranges in Madhya Pradesh and after flowing for about 120 km in the North-Westedy direction enters Banswara district of Rajasthan state. It is located between 22030′ – 24000′ latitude and 74030′ – 75015′ longitude. Total study area is 6233 sq km. Figure 1 shows the watersheds of study area.
|Figure 1 : Watershed map||
Figure 2 : Contour maps
Preparation of theme layer –
Various theme layers viz. drainage layer, contour layer, vegetation index layer, soil brightness layer were generated using Remote Sensing data and SOI toposheets. Drainage lines were digitised from 1:50,000 scale toposheets and drainage density layer was generated. Form factor for the watersheds was also calculated. DEM of the study area was generated from contour layer from which a slope layer was generated. Rescaled Density Vegetation Index was calculated for each pixel in the study area using the formula (Rescaled NDVI = NDVI * 200 + 50) and area weighted value was calculated for each micro watershed. Soil brightness Index was calculated and a texture layer was generated from that.
Assigning the weight-
Relative weights were assigned to all the micro watersheds keeping in view the range of value for each parameter. Instead of dividing the entire range in to equal intervals, narrow range has been used for higher priority and a larger range is used for lower order priority. Less than 30% of the range was assigned as weight 2 and 90% to 100% of the range was assigned as weight 5.
Since a watershed contains many slope, vegetation and texture categories, area weighted averages were for slope, texture and vegetation. Using the values and the relative ranges, weights were assigned to all micro watersheds.