aSoil degradation caused by soil erosion is one of the world's most critical environmental issues.Soil erosion in the Tianshan Mountains has caused various environmental problems in the surrounding areas.This stud...aSoil degradation caused by soil erosion is one of the world's most critical environmental issues.Soil erosion in the Tianshan Mountains has caused various environmental problems in the surrounding areas.This study used remote sensing data to analyze the distribution of the factors influencing soil erosion,and the revised universal soil loss equation(RUSLE)to calculate the total amount and distribution characteristics of soil erosion in the Tianshan Mountains in 2019.Due to the large error of RUSLE in soil erosion estimation in mountainous areas,this study modified RUSLE equation based on the characteristics of snow cover in the Tianshan Mountains.The results show that the average soil erosion was 1690.3 t/(km^(2)·year),of which insignificant erosion,slight erosion and moderate erosion accounted for 42,8%,22.4%and 9.9%,respectively.Severe erosion and above accounted for 13.3%.The accuracy of the soil erosion modulus calculated by the RUSLE was only 61.9%,with an average error of 1631.9 t/(km^(2)·year).The average error of the double-coefficient correction method was 1259.1 t/(km^(2)·year),and the average error of the modified formula method was reduced by 40.3%compared with the RUSLE,reaching 973.7 t/(km^(2)·year),and its accuracy reached 76.2%.Very severe erosion and catastrophic erosion are distributed on mountain ridges with higher elevation and on the northern area with higher precipitation.Snow cover has a certain inhibitory effect on soil erosion,and snow cover in alpine mountains is a factor that cannot be ignored in soil erosion research.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
应用2010—2020年的地面雨量站、卫星遥感等资料,开展基于修正通用水土流失方程(revised universal soil loss equation,RUSLE)的长汀土壤侵蚀时空变化特征分析,评价南方典型红壤侵蚀区(长汀县)水土流失治理过程的土壤侵蚀时空分布特征...应用2010—2020年的地面雨量站、卫星遥感等资料,开展基于修正通用水土流失方程(revised universal soil loss equation,RUSLE)的长汀土壤侵蚀时空变化特征分析,评价南方典型红壤侵蚀区(长汀县)水土流失治理过程的土壤侵蚀时空分布特征。结果表明:(1)近10 a长汀水土保持成效持续稳定,各年土壤侵蚀面积均是微度(或轻度)>中度>强烈>极强烈>剧烈,中度及以下侵蚀等级面积占比89.43%,强烈、极强烈、剧烈侵蚀等级面积占比分别为6.59%、3.47%、0.51%;(2)降水侵蚀力因子是土壤侵蚀强度的重要影响因子,2012及2016年降水量多,强烈及以上侵蚀等级占比分别达28.06%、14.09%,其余年份在4.13%~13.59%;(3)长汀各区域强烈以上侵蚀等级占比由大到小分别为东部>北部>西部>中部,其中土壤侵蚀核心区中部区域强烈、极强烈、剧烈侵蚀等级面积占比分别为3.98%、1.58%、0.18%,均低于其他区域相同侵蚀等级的比例,东部区域非水土流失区土壤侵蚀强度有增强的趋势。展开更多
基金supported by the Third Xinjiang Scientific Expedition and Research Program (Grant No. 2022xjkk0602)National Cryosphere Desert Data Center (No. 2021kf02)Xinjiang Jiaotou’s Unveiling and Commanding System Project in 2021 (ZKXFWCG 2022060004)。
文摘aSoil degradation caused by soil erosion is one of the world's most critical environmental issues.Soil erosion in the Tianshan Mountains has caused various environmental problems in the surrounding areas.This study used remote sensing data to analyze the distribution of the factors influencing soil erosion,and the revised universal soil loss equation(RUSLE)to calculate the total amount and distribution characteristics of soil erosion in the Tianshan Mountains in 2019.Due to the large error of RUSLE in soil erosion estimation in mountainous areas,this study modified RUSLE equation based on the characteristics of snow cover in the Tianshan Mountains.The results show that the average soil erosion was 1690.3 t/(km^(2)·year),of which insignificant erosion,slight erosion and moderate erosion accounted for 42,8%,22.4%and 9.9%,respectively.Severe erosion and above accounted for 13.3%.The accuracy of the soil erosion modulus calculated by the RUSLE was only 61.9%,with an average error of 1631.9 t/(km^(2)·year).The average error of the double-coefficient correction method was 1259.1 t/(km^(2)·year),and the average error of the modified formula method was reduced by 40.3%compared with the RUSLE,reaching 973.7 t/(km^(2)·year),and its accuracy reached 76.2%.Very severe erosion and catastrophic erosion are distributed on mountain ridges with higher elevation and on the northern area with higher precipitation.Snow cover has a certain inhibitory effect on soil erosion,and snow cover in alpine mountains is a factor that cannot be ignored in soil erosion research.
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.
