USLE/RUSLE是土壤侵蚀监测与预报的核心工具,方程中各因子赋值的合理性决定了方程应用结果的准确度。然而,由于我国地形条件的复杂性等原因,方程在我国范围内的应用受到限制。因此,为明晰土壤流失方程各因子计算中需把握的关键因素,以...USLE/RUSLE是土壤侵蚀监测与预报的核心工具,方程中各因子赋值的合理性决定了方程应用结果的准确度。然而,由于我国地形条件的复杂性等原因,方程在我国范围内的应用受到限制。因此,为明晰土壤流失方程各因子计算中需把握的关键因素,以及当前我国研究中存在的主要问题,采用文献综合对比研究的方法,通过CNKI中国学术期刊全文数据库和Web of Science数据库,搜集了土壤流失方程因子相关文献共373篇。文献综合分析结果表明:各因子的研究普遍存在缺乏估算公式选用和估算结果的精度检验,坡长坡度因子存在公式误用的情况,作物覆盖与管理因子、水土保持措施因子缺少系统性定量计算的方法,土壤可蚀性因子计算的背景条件差异大,难以进行横向比较。为此,提出两条提高模型使用精度的建议,一是通过建设标准化的地面监测系统,系统观测和建立土壤侵蚀因子定量方法,二是明确此类模型应用边界,在较为适合的环境应用。展开更多
Among Universal Soil Erosion Equation (USLE) factors (R, K, L, S and P), Soil Erodibility Factor (K) is one of the most important and key factors which determines soil particles resistance to be detachment by water er...Among Universal Soil Erosion Equation (USLE) factors (R, K, L, S and P), Soil Erodibility Factor (K) is one of the most important and key factors which determines soil particles resistance to be detachment by water erosion (rainfall and/or runoff) forces. In fact, K factor is the rate of soil loss per rainfall erosion index unit and affected by 6 parameters including soil primary particles (silt, sand and clay), organic matter content and also permeability and structure of soil. The USLE nomograph is one of the most rapid and common methods for calculating K factor based on mentioned parameters. In this study, 38 samples of surface soil (0 - 15 cm) were collected from Yamchi watershed and the percentage of silt, sand, clay and organic matter content were determined in soil laboratory. Also textures of soil samples were determined to choice soil permeability and structure class codes based on United States Department of Agriculture (USDA) published information. Using USLE nomograph equation, K factor was calculated for each soil sample and based on kriging interpolation method, soil erodibility factor (K) map was constructed for entire study area which average soil erodibility factor and average standard error of interpolated map were 0.442 and 0.0076 t·ha·h·ha-1·Mj-1·mm-1, respectively.展开更多
The rainfed region in Iraq comprises an area of more than 5 million ha of forest,grazing and farmland areas.Except the plains,the region suffers from moderate to severe water erosion due mainly to overgrazing and land...The rainfed region in Iraq comprises an area of more than 5 million ha of forest,grazing and farmland areas.Except the plains,the region suffers from moderate to severe water erosion due mainly to overgrazing and land mismanagement.Due to population growth and the shortage in water resources,an expansion in land used for agriculture in the region is expected.Terracing is an option when utilizing sloping land for agricultural production.A terrace design criterion was developed for the region in which terrace spacing was determined using the Revised Universal Soil Loss Equation(RUSLE);terrace channel specifications were determined using conventional hydraulic computations.Analyses showed that terracing is feasible on rolling and hilly sloping land in the high rainfall zone(seasonal rainfall 4600 mm)where economic crops are grown to offset the high cost of terrace construction and maintenance.In the medium and low rainfall zones(seasonal rainfall 400–600 mm and 300–400 mm),terracing for water erosion control is generally not needed on cultivated land less than 10%in slope where wheat and barley crops are normally grown;however,pioneer research projects are needed to assess the feasibility of terraces of the level(detention)type to conserve rain water in these two zones for a more successful rainfed farming venture.展开更多
Slope length and slope steepness are critical topographic factors(L and S)in the Universal Soil Loss Equation(USLE)and Chinese Soil Loss Equation(CSLE)for soil erosion modelling.Both slope length and slope gradient ar...Slope length and slope steepness are critical topographic factors(L and S)in the Universal Soil Loss Equation(USLE)and Chinese Soil Loss Equation(CSLE)for soil erosion modelling.Both slope length and slope gradient are potentially sensitive to spatial resolution when calculated in a GIS framework.The resolution effect on the LS factor and approaches suitable for improving the LS factor at a coarse resolution have not been well identified.To address this problem,the LS factor at 5-m and 30-m resolution in twenty-four watersheds with various terrains was estimated.And a downscale model based on matching of the lower resolution LS cumulative frequency curves to a higher resolution("Histogram Matching"method)was tested for its potential to improve LS factor estimation accuracy.In the larger relief mountainous area,compared to 5-m resolution,the 30-m resolution generated LS was generally overestimated by more than 20%and in lower relief areas underestimated by more than 15%.This bias is less than 10%in medium relief areas.The downscale model improved LS factor estimates compared to the 30-m resolution estimate by more than 10%when comparing frequency distribution curves and more than 20%in mean values in larger relief areas.The downscale model worked well in all regions except for the low relief areas,which intuitively are the low soil erosion potential areas.The results of this research help quantify the uncertainty in soil erosion estimates and may ultimately help to improve the assessment of soil erosion through its impact on LS factor estimates,especially at regional and global scales.展开更多
文摘USLE/RUSLE是土壤侵蚀监测与预报的核心工具,方程中各因子赋值的合理性决定了方程应用结果的准确度。然而,由于我国地形条件的复杂性等原因,方程在我国范围内的应用受到限制。因此,为明晰土壤流失方程各因子计算中需把握的关键因素,以及当前我国研究中存在的主要问题,采用文献综合对比研究的方法,通过CNKI中国学术期刊全文数据库和Web of Science数据库,搜集了土壤流失方程因子相关文献共373篇。文献综合分析结果表明:各因子的研究普遍存在缺乏估算公式选用和估算结果的精度检验,坡长坡度因子存在公式误用的情况,作物覆盖与管理因子、水土保持措施因子缺少系统性定量计算的方法,土壤可蚀性因子计算的背景条件差异大,难以进行横向比较。为此,提出两条提高模型使用精度的建议,一是通过建设标准化的地面监测系统,系统观测和建立土壤侵蚀因子定量方法,二是明确此类模型应用边界,在较为适合的环境应用。
文摘Among Universal Soil Erosion Equation (USLE) factors (R, K, L, S and P), Soil Erodibility Factor (K) is one of the most important and key factors which determines soil particles resistance to be detachment by water erosion (rainfall and/or runoff) forces. In fact, K factor is the rate of soil loss per rainfall erosion index unit and affected by 6 parameters including soil primary particles (silt, sand and clay), organic matter content and also permeability and structure of soil. The USLE nomograph is one of the most rapid and common methods for calculating K factor based on mentioned parameters. In this study, 38 samples of surface soil (0 - 15 cm) were collected from Yamchi watershed and the percentage of silt, sand, clay and organic matter content were determined in soil laboratory. Also textures of soil samples were determined to choice soil permeability and structure class codes based on United States Department of Agriculture (USDA) published information. Using USLE nomograph equation, K factor was calculated for each soil sample and based on kriging interpolation method, soil erodibility factor (K) map was constructed for entire study area which average soil erodibility factor and average standard error of interpolated map were 0.442 and 0.0076 t·ha·h·ha-1·Mj-1·mm-1, respectively.
文摘The rainfed region in Iraq comprises an area of more than 5 million ha of forest,grazing and farmland areas.Except the plains,the region suffers from moderate to severe water erosion due mainly to overgrazing and land mismanagement.Due to population growth and the shortage in water resources,an expansion in land used for agriculture in the region is expected.Terracing is an option when utilizing sloping land for agricultural production.A terrace design criterion was developed for the region in which terrace spacing was determined using the Revised Universal Soil Loss Equation(RUSLE);terrace channel specifications were determined using conventional hydraulic computations.Analyses showed that terracing is feasible on rolling and hilly sloping land in the high rainfall zone(seasonal rainfall 4600 mm)where economic crops are grown to offset the high cost of terrace construction and maintenance.In the medium and low rainfall zones(seasonal rainfall 400–600 mm and 300–400 mm),terracing for water erosion control is generally not needed on cultivated land less than 10%in slope where wheat and barley crops are normally grown;however,pioneer research projects are needed to assess the feasibility of terraces of the level(detention)type to conserve rain water in these two zones for a more successful rainfed farming venture.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences,Grant No.XDA20040202SKL Foundation Grant No.A314021402-1718+1 种基金Na tional Natural Science Foundation of China,Grant No.41977062,41601290,41771315,41930102Program for Key Science and Technology Innovation Team in Shaanxi Province,Grant No.2014KCT-27
文摘Slope length and slope steepness are critical topographic factors(L and S)in the Universal Soil Loss Equation(USLE)and Chinese Soil Loss Equation(CSLE)for soil erosion modelling.Both slope length and slope gradient are potentially sensitive to spatial resolution when calculated in a GIS framework.The resolution effect on the LS factor and approaches suitable for improving the LS factor at a coarse resolution have not been well identified.To address this problem,the LS factor at 5-m and 30-m resolution in twenty-four watersheds with various terrains was estimated.And a downscale model based on matching of the lower resolution LS cumulative frequency curves to a higher resolution("Histogram Matching"method)was tested for its potential to improve LS factor estimation accuracy.In the larger relief mountainous area,compared to 5-m resolution,the 30-m resolution generated LS was generally overestimated by more than 20%and in lower relief areas underestimated by more than 15%.This bias is less than 10%in medium relief areas.The downscale model improved LS factor estimates compared to the 30-m resolution estimate by more than 10%when comparing frequency distribution curves and more than 20%in mean values in larger relief areas.The downscale model worked well in all regions except for the low relief areas,which intuitively are the low soil erosion potential areas.The results of this research help quantify the uncertainty in soil erosion estimates and may ultimately help to improve the assessment of soil erosion through its impact on LS factor estimates,especially at regional and global scales.
