Quantification of Soil Erosion by Integrating Geospatial and Revised Universal Soil Loss Equation in District Dir Lower, Pakistan: Soil Erosion Estimation using RUSLE Model - Khan, Abdullah; Atta-ur-Rahman (Proceedings of the Pakistan Academy of Sciences: B. Life and Environmental Sciences, 2021)
This study is aimed to estimate soil erosion risk by integrating Revised Universal Soil Loss Equation (RUSLE) and geospatial tool in District Lower Dir, Eastern Hindu Kush. Soil erosion is among the biggest threats to agricultural production. Mountainous areas of Pakistan are exposed to erosion hazards due to immature geology, fragile slope, and deforestation. RUSLE factors were derived from data acquired from various sources. The Rainfall erosivity (R) factor was derived from monthly data obtained from Pakistan Meteorological Department, Peshawar. The soil erodibility (K) factor was prepared from the map of soil, Survey of Pakistan. The topography (LS) factor was calculated from 12.5 m DEM downloaded from the Alaska Satellite Facility. The cover management (C) factor was calculated from the Red and Near-Infrared band of Landsat 8 satellite image downloaded from USGS earth explorer. The Digital Elevation Model (DEM) and Landsat image were integrated to prepare the Support practice (P) factor. These factors were combined to assess soil erosion in the study area. The estimated soil erosion ranges between 0-25407 tons/hectare/year, with a mean soil loss of 230 tons/hectare/year. The erosion zonation map was then prepared and was classified as very low, low, moderate, high, and very high erosion. 22 % of the district was affected by low to moderate erosion while 67 % area is affected by very high erosion. The areas having more rainfall and steep slopes are more exposed to erosion hazards. Therefore, Erosion control activities are essential in those areas where erosion is high to assure a viable ecosystem.