Dhanjit DEKA, Department of Geography, Gauhati University, India
Soil erosion is one of the most important land degradation problems through the water and critical environmental hazard in the modern time at worldwide. The Digaru watershed of Assam, India covering an area of 212.12 Km2 has been exposed to soil erosion due to agricultural and industrial activities, intense monsoon rainfall for several months per year, deforestation and gradually increasing of unscientific land management activities. Sheet erosion and River bank erosion contribute substantially to the soil loss as well as sedimentation problem resulting in productivity decline of agricultural land and other environmental problems in the Digaru watershed. It is of utmost need at present for assessment and mapping of soil erosion prone area for management of the said watershed. The RUSLE is most commonly empirical model used to calculating the average annual soil loss of any watershed. Again, it become easy to prioritize the sub watershed based on the soil loss estimation for proper planning and management. The present study involves the use of Remote Sensing data integrated with Geographical Information System (GIS) technique and the Revised Universal Soil Loss Equation (RUSLE) model for assessing the annual average soil loss of Digaru watershed for 2011 and 2021. The spatial analysis of the annual soil erosion rate was obtained through the integrating of good environmental variables in a GIS based raster method. Different criteria’s like R (Rainfall erosivity factor), K (Soil erodibility factor), LS (Slope length and steepness factor), C (Cover management factor) and P (Support practice factor) factors were computed to assess their effect on average annual soil loss in the said watershed. It has been estimated that the average soil loss in Digaru watershed in 2011 was 178931.6 tons and 102711 tons in 2021. Datasets like Alos Palsar DEM, Landsat TM and Sentinel satellite data, soil map and gridded rainfall data have been widely used in the analysis.
Mots clés : soil erosion|land degradation|RUSLE|GIS|Digaru
A104980DD