Soil erosion is a serious problem arising from agricultural intensification, land degradation and other anthropogenic activities. Assessment of soil erosion is useful in planning and conservation works in a watershed ...Soil erosion is a serious problem arising from agricultural intensification, land degradation and other anthropogenic activities. Assessment of soil erosion is useful in planning and conservation works in a watershed or basin. Modelling can provide a quantitative and consistent approach to estimate soil erosion and sediment yield under a wide range of conditions. In the present study, the soil loss model, Revised Universal Soil Loss Equation （RUSLE） integrated with GIS has been used to estimate soil loss in the Nethravathi Basin located in the southwestern part of India. The Nethravathi Basin is a tropical coastal humid area having a drainage area of 3128 km2 up to the gauging station. The parameters of RUSLE model were estimated using remote sensing data and the erosion probability zones were determined using GIS. The estimated rainfall erosivity, soil erodibility, topographic and crop management factors range from 2948.16 to 4711.4 MJ/mm.ha-1hr-1/year, 0.10 to 0.44 t ha-1 -MJ-1.mm 1, 0 to 92,774 and 0 to 0.63 respectively. The results indicate that the estimated total annual potential soil loss of about 473,339 t/yr is comparable with the measured sediment of 441,870 t/yr during the water year 2002 2003. The predicted soil erosion rate due to increase in agricultural area is about 14,673.5 t/yr. The probability zone map has been derived by the weighted overlay index method indicate that the major portion of the study area comes under low probability zone and only a small portion comes under high and very high probability zone. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the Nethravathi Basin.展开更多
Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors.Such factors vary over space and time,making the assessment of soil erosion even more difficult.Empirical erosion ...Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors.Such factors vary over space and time,making the assessment of soil erosion even more difficult.Empirical erosion models such as the Revised Universal Soil Loss Equation (RUSLE) provides a rather simple and yet comprehensive framework for assessing soil erosion and its causative factors.RUSLE considers rainfall (R),topography (LS),soil erodibility (K),cover management (C),and support practice (P) as important factors affecting soil erosion.In the past few years,RUSLE has benefited tremendously from advances in geospatial technologies like Geographic Information System (GIS) and remote sensing.In this paper,an overview of recent developments on the use of these geospatial technologies in deriving individual RUSLE factors is provided,placing an emphasis on related successes and challenges.This review is expected to improve the understanding of the role played by such technologies in deriving RUSLE parameters despite existing challenges.Future research,however,must pay special attention to error assessment of remote sensing-derived RUSLE parameters.展开更多
基于地理信息系统(GIS)和遥感技术(RS),提取了巢湖流域地表覆盖、水土保持措施、坡度坡长、土壤可蚀性、降雨侵蚀力5个主要影响水土流失的因子,并运用修正的通用土壤侵蚀模型(revised univer-sal soil loss equation,RUSLE)估算土壤侵蚀...基于地理信息系统(GIS)和遥感技术(RS),提取了巢湖流域地表覆盖、水土保持措施、坡度坡长、土壤可蚀性、降雨侵蚀力5个主要影响水土流失的因子,并运用修正的通用土壤侵蚀模型(revised univer-sal soil loss equation,RUSLE)估算土壤侵蚀量,生成水土流失等级分布图,从而完成对巢湖流域水土流失现状和空间分布特征的评估分析。结果表明,巢湖流域水土流失主要为微度侵蚀和轻度侵蚀,分别占流域总面积的93.87%和6.04%。此外,坡度和植被覆盖是影响流域土壤侵蚀的主要因素。研究结果可为巢湖流域水土流失治理及决策提供科学参考。展开更多
Mining operations result in the generation of barren land and spoil heaps which are subject to high erosion rate during the rainy season. The present study uses the Revised Universal Soil Loss Equation (RUSLE) and SCS...Mining operations result in the generation of barren land and spoil heaps which are subject to high erosion rate during the rainy season. The present study uses the Revised Universal Soil Loss Equation (RUSLE) and SCS-CN (Soil Conservation Service - Curve Number) process to estimate in Kiruburu and Meghahatuburu mining sites areas. The geospatial model of annual average soil loss rate was determined by integrating environmental variables parameters in a raster pixels-based GIS framework. GIS layers with, rainfall passivity and runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management(C) and conservation practice (P) factors were calculated to determine their effects on annual soil erosion in the study area. The coefficient of determination (r2) was 0.834, which indicates a strong correlation of soil loss with runoff and rainfall. Sub -watersheds 5,9,10 and 2 experienced high level of highly runoff. Average annual soil loss was calculated (30*30 m raster grid cell) to determine the critical soil loss areas (Sub-watershed 9 and 5). Total soil erosion area was classified into five class, slight (10,025 ha), moderate (3125 ha), high (973 ha), very high (260 ha) and severe (53 ha). The resulting map shows greatest soil erosion of >40 t h-1 y-1 (severe) through connection to grassland, degraded and open forestry on the erect mining side-escutcheon. The Landsat pan sharpening image and DGPS survey field data were used in the verification of soil erosion results.展开更多
文摘Soil erosion is a serious problem arising from agricultural intensification, land degradation and other anthropogenic activities. Assessment of soil erosion is useful in planning and conservation works in a watershed or basin. Modelling can provide a quantitative and consistent approach to estimate soil erosion and sediment yield under a wide range of conditions. In the present study, the soil loss model, Revised Universal Soil Loss Equation （RUSLE） integrated with GIS has been used to estimate soil loss in the Nethravathi Basin located in the southwestern part of India. The Nethravathi Basin is a tropical coastal humid area having a drainage area of 3128 km2 up to the gauging station. The parameters of RUSLE model were estimated using remote sensing data and the erosion probability zones were determined using GIS. The estimated rainfall erosivity, soil erodibility, topographic and crop management factors range from 2948.16 to 4711.4 MJ/mm.ha-1hr-1/year, 0.10 to 0.44 t ha-1 -MJ-1.mm 1, 0 to 92,774 and 0 to 0.63 respectively. The results indicate that the estimated total annual potential soil loss of about 473,339 t/yr is comparable with the measured sediment of 441,870 t/yr during the water year 2002 2003. The predicted soil erosion rate due to increase in agricultural area is about 14,673.5 t/yr. The probability zone map has been derived by the weighted overlay index method indicate that the major portion of the study area comes under low probability zone and only a small portion comes under high and very high probability zone. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the Nethravathi Basin.
文摘Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors.Such factors vary over space and time,making the assessment of soil erosion even more difficult.Empirical erosion models such as the Revised Universal Soil Loss Equation (RUSLE) provides a rather simple and yet comprehensive framework for assessing soil erosion and its causative factors.RUSLE considers rainfall (R),topography (LS),soil erodibility (K),cover management (C),and support practice (P) as important factors affecting soil erosion.In the past few years,RUSLE has benefited tremendously from advances in geospatial technologies like Geographic Information System (GIS) and remote sensing.In this paper,an overview of recent developments on the use of these geospatial technologies in deriving individual RUSLE factors is provided,placing an emphasis on related successes and challenges.This review is expected to improve the understanding of the role played by such technologies in deriving RUSLE parameters despite existing challenges.Future research,however,must pay special attention to error assessment of remote sensing-derived RUSLE parameters.
文摘基于地理信息系统(GIS)和遥感技术(RS),提取了巢湖流域地表覆盖、水土保持措施、坡度坡长、土壤可蚀性、降雨侵蚀力5个主要影响水土流失的因子,并运用修正的通用土壤侵蚀模型(revised univer-sal soil loss equation,RUSLE)估算土壤侵蚀量,生成水土流失等级分布图,从而完成对巢湖流域水土流失现状和空间分布特征的评估分析。结果表明,巢湖流域水土流失主要为微度侵蚀和轻度侵蚀,分别占流域总面积的93.87%和6.04%。此外,坡度和植被覆盖是影响流域土壤侵蚀的主要因素。研究结果可为巢湖流域水土流失治理及决策提供科学参考。
文摘Mining operations result in the generation of barren land and spoil heaps which are subject to high erosion rate during the rainy season. The present study uses the Revised Universal Soil Loss Equation (RUSLE) and SCS-CN (Soil Conservation Service - Curve Number) process to estimate in Kiruburu and Meghahatuburu mining sites areas. The geospatial model of annual average soil loss rate was determined by integrating environmental variables parameters in a raster pixels-based GIS framework. GIS layers with, rainfall passivity and runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management(C) and conservation practice (P) factors were calculated to determine their effects on annual soil erosion in the study area. The coefficient of determination (r2) was 0.834, which indicates a strong correlation of soil loss with runoff and rainfall. Sub -watersheds 5,9,10 and 2 experienced high level of highly runoff. Average annual soil loss was calculated (30*30 m raster grid cell) to determine the critical soil loss areas (Sub-watershed 9 and 5). Total soil erosion area was classified into five class, slight (10,025 ha), moderate (3125 ha), high (973 ha), very high (260 ha) and severe (53 ha). The resulting map shows greatest soil erosion of >40 t h-1 y-1 (severe) through connection to grassland, degraded and open forestry on the erect mining side-escutcheon. The Landsat pan sharpening image and DGPS survey field data were used in the verification of soil erosion results.
