{"title":"基于地理空间整合和修正通用水土流失方程的巴基斯坦Dir Lower地区土壤侵蚀定量研究","authors":"Abdullah Khan, Atta-ur-Rahman","doi":"10.53560/ppasb(58-4)678","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":36960,"journal":{"name":"Proceedings of the Pakistan Academy of Sciences: Part B","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantification of Soil Erosion by Integrating Geospatial and Revised Universal Soil Loss Equation in District Dir Lower, Pakistan\",\"authors\":\"Abdullah Khan, Atta-ur-Rahman\",\"doi\":\"10.53560/ppasb(58-4)678\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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. 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引用次数: 0
摘要
利用修正通用土壤流失方程(RUSLE)和地理空间工具对东兴都库什邦下迪尔地区的土壤侵蚀风险进行估算。土壤侵蚀是农业生产面临的最大威胁之一。巴基斯坦的山区由于地质不成熟、边坡脆弱和森林砍伐而面临侵蚀危险。RUSLE因子来源于从各种来源获得的数据。降雨侵蚀力(R)因子来源于白沙瓦巴基斯坦气象局的月度数据。土壤可蚀性(K)因子是根据巴基斯坦调查的土壤图编制的。地形(LS)因子是根据从阿拉斯加卫星设施下载的12.5 m DEM计算的。利用从美国地质调查局地球探测器下载的Landsat 8卫星图像的红、近红外波段计算覆盖管理因子(C)。将数字高程模型(DEM)和陆地卫星(Landsat)图像整合,制备支持实践(P)因子。综合这些因素对研究区土壤侵蚀进行评价。估算土壤侵蚀量在0 ~ 25407吨/公顷/年之间,平均土壤流失量为230吨/公顷/年。绘制侵蚀区带图,将侵蚀区划分为极低、低、中、高、高侵蚀区。22%的区域受低至中度侵蚀影响,67%的区域受非常高侵蚀影响。雨量多、坡度陡的地区更容易受到侵蚀的危害。因此,在那些侵蚀严重的地区,控制侵蚀的活动是必不可少的,以确保一个可行的生态系统。
Quantification of Soil Erosion by Integrating Geospatial and Revised Universal Soil Loss Equation in District Dir Lower, Pakistan
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.