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Application of Remote Sensing and GIS on soil erosion assessment at Bata River Basin, India
M. H. Mohamed Rinos1, S. P. Aggarwal2, Ranjith Premalal De Silva3
1
& 3Department of Agricultural Engineering, Faculty of Agriculture,
University of Peradeniya, Peradeniya, Sri Lanka.
1mohamed-rinos@hotmail.com, 3Ranjith@ageng.pdn.ac.lk
2Water Resources Division
Indian Institute of Remote Sensing, Dehradun, India.
s-p-a@hotmail.com
Abstract
Soil erosion assessment is a capital-intensive and time-consuming exercise. A number of parametric models have been developed to predict soil erosion at drainage basins, yet Universal Soil Loss Equation (USLE) (Wischmeier and Smith, 1978) is most widely used empirical equation for estimating annual soil loss from agricultural basins. While conventional methods yield point-based information, Remote Sensing (RS) technique makes it possible to measure hydrologic parameters on spatial scales while GIS integrates the spatial analytical functionality for spatially distributed data. Some of the inputs of the model such as cover factor and to a lesser extent supporting conservation practice factor and soil erodibility factor can also be successfully derived from remotely sensed data. Further, Modified USLE (MUSLE) uses the same empirical principles as USLE. However, it includes numerous improvements, such as monthly factors, influence of profile convexity/concavity using segmentation of irregular slopes and improved empirical equations for the computation of LS factor (Foster & Wischmeier 1974, Renard et al. 1991). In this study, IRS-1D LISS III and ID Pan data were used to identify the land use status of the Bata river basin. Based on maximum likelihood classifier, the area was classified into eight land use classes namely, Dense Forest, Moderate Forest, Open Forest, Wheat, Sugarcane, Settlement, River Bed, Water Body. A 12-day intensive field checking was undertaken in order to collect ground truth information. Digital Elevation Model (DEM) of Bata river basin was created by digitizing contour lines and spot heights from the SOI toposheets at 1:50,000 scale. Modified Fournier index was used to derive parameters for modified erosivity factor. The modified LS factor map was generated from the slope and aspect map derived from the DEM. The K factor map was prepared from the soil map, which was obtained from the previous studies done at Geo-Science Division of IIRS, Dehradun. The P and C factor values were chosen based on the research findings of Central Soil and Water Conservation Research and Training Institute, Dehradun and spatial extent was introduced from land use/ cover map prepared from LISS III data. Maps covering each parameter (R, K, LS, C and P) were integrated to generate a composite map of erosion intensity based on the advanced GIS functionality. This intensity map was classified into different priority classes. Study area was further subdivided into 23 subwatersheds to identify the priority areas in terms of soil erosion intensity. Each subwatershed was analyzed individually in terms of soil type, average slope, drainage length, drainage density, drainage order, height difference, landuse/landcover and average NDVI with soil erosion to find out the dominant factor leads to higher erosion.
Introduction
Problems associated with soil erosion, movement and deposition of sediment in rivers, lakes and estuaries persist through the geologic ages in almost all parts of the earth. But the situation is aggravated in recent times with man's increasing interventions with the environment. At present, the quality of available data is extremely uneven. Land use planning based on unreliable data can lead to costly and gross errors. Soil erosion research is a capital-intensive and time-consuming exercise. Global extrapolation on the basis of few data collected by diverse and non-standardized methods can lead to gross errors and it can also lead to costly mistakes and misjudgments on critical policy issues.
Remote sensing provides convenient solution for this problem. Further, voluminous data gathered with the help of remote sensing techniques are better handled and utilized with the help of Geographical Information Systems (GIS). In this case study, GIS functionality were extensively utilized in the preparation of erosion and natural resources inventory and their analysis for assessing soil erosion and soil conservation planning.
Scientific management of soil, water and vegetation resources on watershed basis is, very important to arrest erosion and rapid siltation in rivers, lakes and estuaries. It is, however, realized that due to financial and organizational constraints, it is not feasible to treat the entire watershed within a short time. Prioritization of watersheds on the basis of those sub-watersheds within a watershed which contribute maximum sediment yield obviously should determine our priority to evolve appropriate conservation management strategy so that maximum benefit can be derived out of any such money-time-effort making scheme.
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