Soil Erosion Susceptibility and Soil Loss Estimation of Data Scarce Region Based on Remotely Sensed Data

Abstract

Fluvial erosion is the second-most significant socio-economic and ecological challenge threateningtheearthinthetwenty-firstcentury,afterrapidpopulationexpansion.Thestudy purpose is to determine the yearly Kunhar River basin (KRB), Pakistan soil loss, and identify regions with high soil loss usingthe Revised Universal Soil Loss Equation (RUSLE). It relies on five components: rainfall (R), soil erodibility (K), Slope length and steepness (LS), crop management (C), and support practice (P). Remotely sensed data were employed to determine these parameters, and the erosion hotspots were delineated usingintegratedGISandRS.TheRfactorforKRBvariesfrom282.76to582.15 ????????.????????ℎ????−1ℎ−1????????????????−1,Kfactorvariesbetween0.139and0.154 ????????.????????ℎ????−1ℎ−1????????????????−1,LSfactor 0-62.2, C factor varies between 0 for snow and 0.15 for the cultivated area, and the P factor value is from0.1to0.2.The estimatedannualsoillossfromKRBis5.13million????.????????????????−1,averaging21.19????.ℎ−1????????????????−1.Theresultssuggestthat98.32%ofthelandhasalowerosionrate(20????.ℎ−1????????????????−1, which accounts for 98.84% of the entire annual soil loss. Conversely, 1.08% and 0.52% of the area, which have moderate and high erosion rates, respectively, constitute 2.05% and 2.95% of the total annual soil loss. The basin’s small part (0.07%) is sensitive to very high erosion rates, contributing 2.17% of the annual soil loss. This approach provides a systematic method for assessing soil loss, allowing for targeted interventions to mitigate erosion. The study's findings offer important insights that can inform decision-making and the implementation of sustainable land management practices