Simulation of the spatial distribution of soil erosion risk in Mellah Watershed, North-eastern Algeria
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Mellah watershed is one of the semi-arid regions in Eastern Algeria confronted with the problem of erosion due to the effects of climate change, population growth and rapid expansion of urbanization. The aim of this study is to identify and map soil erosion sensitivity areas in Mellah Watershed, using an empirical model (RUSLE: Revised Universal Soil Loss Equation), a semi quantitative model (AHP: Analytic Hierarchy Process) and a statistical model (FR: Frequency Ratio). Geographic Information System (GIS) and Remote Sensing (RS) techniques were used to identify and characterize a set of factors influencing water erosion in the watershed, including rainfall, ground elevation, slope, land cover, soil type, Normalized difference vegetation index (NDVI), Stream Power Index (SPI), Topographic Wetness Index TWI and distances from road and stream. The results of soil erosion susceptibility, obtained on a GIS platform, were categorized into five classes, including very low, low, moderate, high and very high erosion risk. Based on this analysis, the area distribution and the percentage of sensitivity levels were calculated. The corresponding results showed that the region characterized by very high sensitivity represent 4.2%, 9.8% and 10.1% using RUSLE, FR and AHP models respectively. The results obtained were validated by comparing the generated maps to a soil erosion inventory map, which was prepared based on 200 field observations of rill erosion. In this context, ROC (Receiver Operating Characteristics) curve was adopted. The values for the Area Under the Curve (AUC) were 93.6%, 93.1%, and 95.7% for RUSLE, AHP and FR models respectively, implying reasonably good performances for the three adopted models. Finally, it is important to note that the soil erosion susceptibility maps developed in this study may be considered as a decision support tool for watershed management strategies to alleviate water erosion in El Mellah Watershed.