Use Of Satellite Remote Sensing And Gis In Soil Erosion Modeling

The potential utility of remotely sensed data in the form of aerial photographs and satellite sensors data has been well recognized in mapping and assessing landscape attributes controlling soil erosion, such as physiography, soils, land use/land cover, relief, soil erosion pattern (e.g. Pande et al., 1992). Remote Sensing can facilitate studying the factors enhancing the process, such as soil type, slope gradient, drainage, geology and land cover. Multi-temporal satellite images provide valuable information related to seasonal land use dynamics. Satellite data can be used for studying erosional features, such as gullies, rainfall interception by vegetation and vegetation cover factor. DEM (Digital Elevation Model) one of the vital inputs required for soil erosion modeling can be created by analysis of stereoscopic optical and microwave (SAR) remote sensing data.

Geographic Information System (GIS) has emerged as a powerful tool for handling spatial and non-spatial geo-referenced data for preparation and visualization of input and output, and for interaction with models. There is considerable potential for the use of GIS technology as an aid to the soil erosion inventory with reference to soil erosion modeling and erosion risk assessment.

Erosional soil loss is most frequently assessed by USLE. Spanner et al. (1982) first demonstrated the potential of GIS for erosional soil loss assessment using USLE. Several studies showed the potential utility of RS and GIS techniques for quantitatively assessing erosional soil loss (Saha et al., 1991; Saha and Pande, 1993; Mongkosawat et al., 1994). Satellite data analyzed soil and land cover maps and DEM derived and ancillary soil and agro-climatic rainfall data are the basic inputs used in USLE for computation of soil loss. Kudrat and Saha (1996) showed the feasibility of GIS to estimate actual and potential sediment yields following Sediment Yield Prediction Equation (SYPE) using RS derived soil and land use information, DEM derived slope and ancillary rainfall and temperature data. MMF model was used for quantification of soil loss by water erosion in Doon Valley, Dehra Dun, India, in GIS environment using various satellite remote sensing derived inputs (ASD, 2002).

The availability of GIS tools and more powerful computing facilities makes it possible to overcome difficulties and limitations and to develop distributed continuous time models, based on available regional information. Recent development of deterministic models provides some spatially distributed tools, such as AGNPS (Young et al., 1989); ANSWERS (Beasley et al„ 1980), and SWAT (Arnold et al., 1993). The primary layers required for soil erosion modeling are terrain slope gradient and slope length which can be generated by GIS aided processing of DEM. Flanagan et al. (2000) generated the necessary topographic inputs for soil erosion and model simulations by linking WEPP model and GIS and utilizing DEM.

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