Soil Erosion Susceptibility Mapping And Sediment Yield Estimation Using Gis Based Compound Factor Approach: A Study Of Kunhar River Basin, Pakistan

Abstract

The Kunhar River basin (KRB) suffers significant soil erosion, reducing agricultural production and dumping about 0.1 million tons of silt into the Mangla Reservoir each year. It has the region's highest suspended sediment load, measuring 5.21 gm/L in the spring, 2.75 gm/L in the summer, and 1.92 gm/L in the winter. The purpose of this work is to prioritize sub-watersheds susceptible to soil erosion in a geospatial context utilizing a morphometric-based Compound Factor approach. The primary data source is the ASTERG DEM (V3) with a spatial resolution of 30m obtained from NASA Earth data (ASTER Global Digital Elevation Map (nasa.gov). The DEM analysis in ArcMap 10.8 yielded 18 morphometric MP. Based on the available literature, the computed MPs were divided into two groups. Group one includes MPs which have a direct association with soil erosion. The second group of MPs has an inverse association with soil erosion, meaning that greater values indicate a reduced chance of erosion. The CFA evaluates soil erosion by taking into account all the MPs associated with soil erosion. This approach considers the combined effects of all the MPs on soil erosion rather than relying just on specific variables. The analysis has three steps: 1) Sub-basins (SB) are ranked based on their effectiveness in soil erosion. The SB with the highest Group 1 MPs score is ranked first, while the SB with the lowest score is rated nth. In contrast, the SBs with the lowest Group 2 MP score were ranked first, followed by the SB with the highest value, which would be ranked nth. 2) The CF is calculated by adding up all of the MP rank values and dividing by the total number of MPs. The CF depicts the total effect of all MPs on the likelihood of soil erosion in that particular SB. 3) SB final rankings using equation 1: where x is the number of used MPs, and R represents the ranking. The analysis reveals that 7 SBs (33%) are the most vulnerable to soil erosion. Similarly, eight SBs (38% of the total) are very vulnerable, four SBs (19%) are moderately susceptible, and two SBs (10%) are generally less susceptible to soil erosion. The SBs with very high soil erosion susceptibility has very high to high group one MPs values and low to very low group two MPs values. The study's findings highlight the necessity of targeted soil conservation measures based on knowledgeable watershed management approaches.