The formation mechanism and influencing factors identification of soil erosion are the core and frontier issues of current research. However, studies on the multi-factor synthesis are still relatively lacked. In this ...The formation mechanism and influencing factors identification of soil erosion are the core and frontier issues of current research. However, studies on the multi-factor synthesis are still relatively lacked. In this study, the simulation of soil erosion and its quantitative attribution analysis have been conducted in different geomorphological types in a typical karst basin based on the RUSLE model and the geodetector method. The influencing factors, such as land use type, slope, rainfall, elevation, lithology and vegetation cover, have been taken into consideration. Results show that the strength of association between the six influencing factors and soil erosion was notably different in diverse geomorphological types. Land use type and slope were the dominant factors of soil erosion in the Sancha River Basin, especially for land use type whose power of determinant(q value) for soil erosion was much higher than other factors. The q value of slope declined with the increase of relief in mountainous areas, namely it was ranked as follows: middle elevation hill> small relief mountain> middle relief mountain. Multi-factors interactions were proven to significantly strengthen soil erosion, particularly for the combination of land use type with slope, which can explain 70% of soil erosion distribution. It can be found that soil erosion in the same land use type with different slopes(such as dry land with slopes of 5° and above 25°) or in the diverse land use types with the same slope(such as dry land and forest with a slope of 5°), varied much. These indicate that prohibiting steep slope cultivation and Grain for Green Project are reasonable measures to control soil erosion in karst areas. Based on statistics of soil erosion difference between diverse stratifications of each influencing factor, results of risk detector suggest that the amount of stratification combinations with significant difference accounted for 55% at least in small relief mountain and middle relief mountainous areas. Therefore, the spatial het展开更多
Soil erosion has been recognized as a critical environmental issue worldwide.While previous studies have primarily focused on watershed-scale soil erosion vulnerability from a natural factor perspective,there is a not...Soil erosion has been recognized as a critical environmental issue worldwide.While previous studies have primarily focused on watershed-scale soil erosion vulnerability from a natural factor perspective,there is a notable gap in understanding the intricate interplay between natural and socio-economic factors,especially in the context of spatial heterogeneity and nonlinear impacts of human-land interactions.To address this,our study evaluates the soil erosion vulnerability at a provincial scale,taking Hubei Province as a case study to explore the combined effects of natural and socio-economic factors.We developed an evaluation index system based on 15 indicators of soil erosion vulnerability:exposure,sensitivity,and adaptability.In addition,the combination weighting method was applied to determine index weights,and the spatial interaction was analyzed using spatial autocorrelation,geographical temporally weighted regression and geographical detector.The results showed an overall decreasing soil erosion intensity in Hubei Province during 2000 and 2020.The soil erosion vulnerability increased before 2000 and then.The areas with high soil erosion vulnerability were mainly confined in the central and southern regions of Hubei Province(Xiantao,Tianmen,Qianjiang and Ezhou)with obvious spatial aggregation that intensified over time.Natural factors(habitat quality index)had negative impacts on soil erosion vulnerability,whereas socio-economic factors(population density)showed substantial spatial variability in their influences.There was a positive correlation between soil erosion vulnerability and erosion intensity,with the correlation coefficients ranging from-0.41 and 0.93.The increase of slope was found to enhance the positive correlation between soil erosion vulnerability and intensity.展开更多
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
基金National Basic Research Program of China,No.2015CB452702National Natural Science Foundation of China,No.41671098,No.41530749
文摘The formation mechanism and influencing factors identification of soil erosion are the core and frontier issues of current research. However, studies on the multi-factor synthesis are still relatively lacked. In this study, the simulation of soil erosion and its quantitative attribution analysis have been conducted in different geomorphological types in a typical karst basin based on the RUSLE model and the geodetector method. The influencing factors, such as land use type, slope, rainfall, elevation, lithology and vegetation cover, have been taken into consideration. Results show that the strength of association between the six influencing factors and soil erosion was notably different in diverse geomorphological types. Land use type and slope were the dominant factors of soil erosion in the Sancha River Basin, especially for land use type whose power of determinant(q value) for soil erosion was much higher than other factors. The q value of slope declined with the increase of relief in mountainous areas, namely it was ranked as follows: middle elevation hill> small relief mountain> middle relief mountain. Multi-factors interactions were proven to significantly strengthen soil erosion, particularly for the combination of land use type with slope, which can explain 70% of soil erosion distribution. It can be found that soil erosion in the same land use type with different slopes(such as dry land with slopes of 5° and above 25°) or in the diverse land use types with the same slope(such as dry land and forest with a slope of 5°), varied much. These indicate that prohibiting steep slope cultivation and Grain for Green Project are reasonable measures to control soil erosion in karst areas. Based on statistics of soil erosion difference between diverse stratifications of each influencing factor, results of risk detector suggest that the amount of stratification combinations with significant difference accounted for 55% at least in small relief mountain and middle relief mountainous areas. Therefore, the spatial het
基金supported by the National Natural Science Foundation of China(42377354)the Natural Science Foundation of Hubei province(2024AFB951)the Chunhui Plan Cooperation Research Project of the Chinese Ministry of Education(202200199).
文摘Soil erosion has been recognized as a critical environmental issue worldwide.While previous studies have primarily focused on watershed-scale soil erosion vulnerability from a natural factor perspective,there is a notable gap in understanding the intricate interplay between natural and socio-economic factors,especially in the context of spatial heterogeneity and nonlinear impacts of human-land interactions.To address this,our study evaluates the soil erosion vulnerability at a provincial scale,taking Hubei Province as a case study to explore the combined effects of natural and socio-economic factors.We developed an evaluation index system based on 15 indicators of soil erosion vulnerability:exposure,sensitivity,and adaptability.In addition,the combination weighting method was applied to determine index weights,and the spatial interaction was analyzed using spatial autocorrelation,geographical temporally weighted regression and geographical detector.The results showed an overall decreasing soil erosion intensity in Hubei Province during 2000 and 2020.The soil erosion vulnerability increased before 2000 and then.The areas with high soil erosion vulnerability were mainly confined in the central and southern regions of Hubei Province(Xiantao,Tianmen,Qianjiang and Ezhou)with obvious spatial aggregation that intensified over time.Natural factors(habitat quality index)had negative impacts on soil erosion vulnerability,whereas socio-economic factors(population density)showed substantial spatial variability in their influences.There was a positive correlation between soil erosion vulnerability and erosion intensity,with the correlation coefficients ranging from-0.41 and 0.93.The increase of slope was found to enhance the positive correlation between soil erosion vulnerability and intensity.
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。
