{"title":"使用半经验 RUSLE 模型估算土壤侵蚀风险:恰蒂斯加尔邦马尼亚里盆地案例研究","authors":"Dipak Bej, N. K. Baghmar, Uma Gole","doi":"10.52228/jrub.2024-37-1-7","DOIUrl":null,"url":null,"abstract":"\n Soil is the protective skin of our earth's surface, but today’s numerous population pressures on land, along with industrialization, climatic variability such as a vigorous increase in temperature, acid rain, and deforestation, definitely degrade the quality of land. It should have to evaluate the quality of the land and find out the nutrition status as well as the soil health. The present study is employed in a Geographic Information System (GIS) environment to predict erosion risk using the Semi-Empirical Revised Soil Loss Erosion Model (RUSLE). The physiographic soil map has been prepared by visual interpretation of the Sentinal 2 satellite image, from which the soil erodibility factor has been derived. The digital elevation model (DEM) has been prepared from a contour map and used as the base map for the topographic-related analysis. In this model, the slope length (LS) factor has been prepared from the DEM. The crop conservation and management factor (C) and support practice factor (P) factors have been derived from the LULC map. It has been found that 4.45% of the watershed comes under very high erosion, 3.50% under high erosion, 7.80% under moderate erosion, 11.37% under low erosion, and 51.36% under a very low erosion-prone zone. \n","PeriodicalId":17214,"journal":{"name":"Journal of Ravishankar University (PART-B)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Soil Erosion Risk Estimation by using Semi Empirical RUSLE model: A case study of Maniyari Basin, Chhattisgarh\",\"authors\":\"Dipak Bej, N. K. Baghmar, Uma Gole\",\"doi\":\"10.52228/jrub.2024-37-1-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Soil is the protective skin of our earth's surface, but today’s numerous population pressures on land, along with industrialization, climatic variability such as a vigorous increase in temperature, acid rain, and deforestation, definitely degrade the quality of land. It should have to evaluate the quality of the land and find out the nutrition status as well as the soil health. The present study is employed in a Geographic Information System (GIS) environment to predict erosion risk using the Semi-Empirical Revised Soil Loss Erosion Model (RUSLE). The physiographic soil map has been prepared by visual interpretation of the Sentinal 2 satellite image, from which the soil erodibility factor has been derived. The digital elevation model (DEM) has been prepared from a contour map and used as the base map for the topographic-related analysis. In this model, the slope length (LS) factor has been prepared from the DEM. The crop conservation and management factor (C) and support practice factor (P) factors have been derived from the LULC map. It has been found that 4.45% of the watershed comes under very high erosion, 3.50% under high erosion, 7.80% under moderate erosion, 11.37% under low erosion, and 51.36% under a very low erosion-prone zone. \\n\",\"PeriodicalId\":17214,\"journal\":{\"name\":\"Journal of Ravishankar University (PART-B)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Ravishankar University (PART-B)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52228/jrub.2024-37-1-7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Ravishankar University (PART-B)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52228/jrub.2024-37-1-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Soil Erosion Risk Estimation by using Semi Empirical RUSLE model: A case study of Maniyari Basin, Chhattisgarh
Soil is the protective skin of our earth's surface, but today’s numerous population pressures on land, along with industrialization, climatic variability such as a vigorous increase in temperature, acid rain, and deforestation, definitely degrade the quality of land. It should have to evaluate the quality of the land and find out the nutrition status as well as the soil health. The present study is employed in a Geographic Information System (GIS) environment to predict erosion risk using the Semi-Empirical Revised Soil Loss Erosion Model (RUSLE). The physiographic soil map has been prepared by visual interpretation of the Sentinal 2 satellite image, from which the soil erodibility factor has been derived. The digital elevation model (DEM) has been prepared from a contour map and used as the base map for the topographic-related analysis. In this model, the slope length (LS) factor has been prepared from the DEM. The crop conservation and management factor (C) and support practice factor (P) factors have been derived from the LULC map. It has been found that 4.45% of the watershed comes under very high erosion, 3.50% under high erosion, 7.80% under moderate erosion, 11.37% under low erosion, and 51.36% under a very low erosion-prone zone.