Land Degradation Risk Assessment in District Dir, Pakistan

Durr-e-Adan, Kalim-Ullah, Arshad Ashraf, Maria Anum, Nouman Khan, Noor-Ul-Huda ()
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Durr-e-Adan, Kalim-Ullah, Arshad Ashraf, Maria Anum, Nouman Khan, Noor-Ul-Huda: Department of Meteorology, Comsats University Islamabad, Islamabad. National Agriculture Research Centre, NARC Park Road,Islamabad. Department of Geography and Geomatics, University of Peshawar, Peshawar,Pakistan. Department of Geography, University of Gujrat, Hafiz Hayat Campus, Gujrat

International Journal of Innovations in Science & Technology, 2025, vol. 7, issue 9, 187-201

Abstract: Soil erosion is a global concern, influenced by terrain, vegetation, soil, and climate factors. Traditionally, field-based techniques have been utilized for the measurement of soil erosion. In the present study, Remote Sensing and Geographic Information System (RS/GIS) techniques are used for soil erosion estimation. The Revised Universal Soil Loss Equation (RUSLE) is frequently utilized, incorporating various elements such as soil erodibility, rainfall erosivity, slope steepness, Land Use and Land Cover (LULC), and conservation practices. This study focuses on the Dir district in Pakistan, integrating the RUSLE model with RS and GIS to identify soil erosion-prone areas. The goal is to implement targeted interventions and sustainable land management practices to mitigate soil erosion in these areas. The output of the RUSLE model identifies key zones that need to be addressed to prevent further land degradation. This study also indicates higher C-factor values in Upper and Lower Dir, ranging from 0.001 to 0.2. Soil loss was calculated using all factors (R, K, LS, CP), showing that soil loss is approximately 31.6 tons/ha/yr in Upper Dir and 22.88 tons/ha/yr in Lower Dir, which is higher in Upper Dir due to high elevation (>30m) and more rainfall in Upper Dir (1275mm). Furthermore, annual rainfall values ranging from 508 mm to 1275 mm were noted, resulting in maximum rainfall erosivity values of 572.87 MJ mm ha/h/year in Upper Dir and 568.16 MJ mm ha/h/year in Lower Dir. Thus, this study provides critical data for society and policymakers to implement targeted soil conservation measures and sustainable land management systems, thereby mitigating soil erosion and preventing further land degradation in the district of Dir

Keywords: Remote Sensing; GIS; Soil Erosion; Revised Universal Soil Loss Equation; Land-Use & Land-Cover (search for similar items in EconPapers)
Date: 2025
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