Spatial Investigation of Soil Erosion Risk in the High Rainfall Zone of Pakistan by Using Rusle Model

Ihtisham Khan ()
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Ihtisham Khan: School of Geosciences and Info Physics, Central South University, Changsha, 410083, China

International Journal of Innovations in Science & Technology, 2024, vol. 6, issue 2, 532-549

Abstract: The degradation of soil quality and agricultural sustainability is threatened by soil erosion, which poses a serious threat to livelihoods and food security. Maintaining soil fertility and reducing the danger of erosion require efficient evaluation and management strategies. This research presents an innovative approach to assess soil erosion in Nowshera District, leveraging remote sensing technology coupled with Geographic Information System (GIS) tools. The study intends to offer a thorough and accurate understanding of erosion patterns and drivers in the area by incorporating these cutting-edge approaches. Cloud-free LANDSAT 8 multispectral images, characterized by minimal vegetation cover, serve as the primary dataset for this analysis. The integration ofthe RUSLE model with GIS and remote sensing techniques enables the calculation of soil erosion rates throughout the research region. The study demonstrates variation in soil erosion parameters across different locations, as indicated by R factor values, which range from 603.43 to 696.43 MJ mm/ha/h/year. The southeastern portion demonstrates significantly lower erosion rates than the northwestern part, which can be linked to variations in topography and land use patterns. This study highlights the significance of using remote sensing techniques to evaluate soil erosion changes over time and provide valuable information for land management plans in Nowshera District, Pakistan. The study results can prove valuable during decision-makingregarding conservation planning and agricultural sustainability.

Keywords: Geospatial Analysis; Remote Sensing; Revised Universal Soil Loss Equation (RUSLE); Soil Erosion; Landsat (search for similar items in EconPapers)
Date: 2024
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