Soil erosion modeling using MMF model -A remote sensing and GIS perspective

Abstract

Hardly any part of the world has remained unchanged since the arrival of the speciesHomo sapiens including the mountain ecosystems. Himalayan physiographic unit of India in due course has become populated and is tolerating all kinds of human interventions. Soil erosion in this region has been identified as a major problem due to both natural and anthropogenic factors. Remote sensing and Geographical Information system (GIS) techniques hold great promises in the assessment and conservation of natural resources including the surface soil. The major objective of the present study was to apply a process based model to quantify soil erosion and to prioritize the sub-watershed on this basis. The sub-watershed located at Jakhan rao area of Western Dun in lower Himalayan belt was taken as the test site for the study at 1: 50,000 scale. Deforestation, unscientific agricultural practices, terrace farming, cattle grazing and land degradation in the sub-watershed are some of the anthropogenic factors causing soil erosion in the area. Here, MMF model was used for estimation of soil erosion by incorporating layers derived from both remote sensing and ancillary data. IRS 1C LISS III satellite data was used for the preparation of land use map that was used to derive RD map, BD map and K map. Digital Elevation Model (DEM) provided slope map, an intermediate layer used in equation 6 to generate G map, and soil map provided MS map, BD map and K map. The above intermediate layers generated were then integrated in GIS domain to estimate the amount of soil erosion in the sub-watershed area. Results show high values 4572.333 kg/m2 for G map, which depicted transport capacity of overland flow. Comparatively lower values 13.15, and 7.98 kg/m2were observed for F map, which depicted soil detachment by raindrop impact. The subtracted image of the aforesaid layers produced the real picture, where in the highest value 3.770 kg/m2 was found in the midland region of the site. The crossed erosion map was then classified into different erosion classes for sub-watershed area. This study illustrates the applications of remote sensing and GIS techniques for soil erosion modeling.