article · International Journal of Digital Earth
Satellite remote sensing and geographical information systems were combined with the Revised Universal Soil Loss Equation to evaluate annual soil degradation across District Chakwal in Pakistan. Satellite imagery enabled rapid classification of land use, supporting the calculation of essential environmental variables including rainfall erosivity, soil erodibility, slope length, and crop management factors. The analysis revealed that over thirty-eight percent of the studied region faces severe threats from very high soil erosion. Expansion of agricultural land within the district contributes substantially to this vulnerability, generating high predicted soil loss rates. By mapping spatial erosion zones and comparing calculated losses against measured sediment data from the 2020 water year, the methodology provides mapped outputs that assist regional land-use planners and decision-makers in targeting conservation efforts and soil management strategies.
Uncontrolled soil loss strips fertile land of vital nutrients, undermining agricultural productivity and destabilising local watersheds in arid environments. Accurately mapping where severe erosion takes place allows environmental managers and public authorities to direct limited conservation resources to the most vulnerable locations, preventing catastrophic land degradation and supporting long-term food and water security.
This applied research provides an analytical workflow and spatial dataset ready for adoption by regional land-use planners, public environmental agencies, and watershed management authorities. While primarily a public-sector planning tool rather than a standalone commercial product, the methodology offers immediate utility for consultancy services conducting environmental impact assessments, targeted conservation planning, and land-management interventions in arid zones.
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In this research, we used the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS) to predict the annual rate of soil loss in the District Chakwal of Pakistan. The parameters of the RUSLE model were estimated using remote sensing data, and the erosion probability zones were determined using GIS. The estimated length slope (LS), crop management (C), rainfall erosivity (R), soil erodibility (K), and support practice (P) range from 0–68,227, 0–66.61%, 0–0.58, 495.99–648.68 MJ/mm.t.ha−1.year−1, 0.15–0.25 MJ/mm.t.ha−1.year−1, and 1 respectively. The results indicate that the estimated total annual potential soil loss of approximately 4,67,064.25 t.ha−1.year−1 is comparable with the measured sediment loss of 11,631 t.ha−1.year−1 during the water year 2020. The predicted soil erosion rate due to an increase in agricultural area is approximately 164,249.31 t.ha−1.year−1. In this study, we also used Landsat imagery to rapidly achieve actual land use classification. Meanwhile, 38.13% of the region was threatened by very high soil erosion, where the quantity of soil erosion ranged from 365487.35 t.ha−1.year−1. Integrating GIS and remote sensing with the RUSLE model helped researchers achieve their final objectives. Land-use planners and decision-makers use the result's spatial distribution of soil erosion in District Chakwal for conservation and management planning.
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DOI: 10.1080/17538947.2023.2243916
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