Droughts and soil erosion are among the most prominent climatic driven hazards in drylands,leading to detrimental environmental impacts,such as degraded lands,deteriorated ecosystem services and biodiversity,and incre...Droughts and soil erosion are among the most prominent climatic driven hazards in drylands,leading to detrimental environmental impacts,such as degraded lands,deteriorated ecosystem services and biodiversity,and increased greenhouse gas emissions.In response to the current lack of studies combining drought conditions and soil erosion processes,in this study,we developed a comprehensive Geographic Information System(GIS)-based approach to assess soil erosion and droughts,thereby revealing the relationship between soil erosion and droughts under an arid climate.The vegetation condition index(VCI)and temperature condition index(TCI)derived respectively from the enhanced vegetation index(EVI)MOD13A2 and land surface temperature(LST)MOD11A2 products were combined to generate the vegetation health index(VHI).The VHI has been conceived as an efficient tool to monitor droughts in the Negueb watershed,southeastern Tunisia.The revised universal soil loss equation(RUSLE)model was applied to quantitatively estimate soil erosion.The relationship between soil erosion and droughts was investigated through Pearson correlation.Results exhibited that the Negueb watershed experienced recurrent mild to extreme drought during 2000–2016.The average soil erosion rate was determined to be 1.8 t/(hm2•a).The mountainous western part of the watershed was the most vulnerable not only to soil erosion but also to droughts.The slope length and steepness factor was shown to be the most significant controlling parameter driving soil erosion.The relationship between droughts and soil erosion had a positive correlation(r=0.3);however,the correlation was highly varied spatially across the watershed.Drought was linked to soil erosion in the Negueb watershed.The current study provides insight for natural disaster risk assessment,land managers,and stake-holders to apply appropriate management measures to promote sustainable development goals in fragile environments.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
定量研究达州市土壤侵蚀的时空分布状况以及不同坡度,海拔高度下的侵蚀状况,可以为达州市开展水土保持工作提供科学参考。本研究选用降雨、土壤、地形、植被覆盖度、土地利用5个侵蚀因子,基于GIS平台结合RUSLE模型得到研究区2000—2020...定量研究达州市土壤侵蚀的时空分布状况以及不同坡度,海拔高度下的侵蚀状况,可以为达州市开展水土保持工作提供科学参考。本研究选用降雨、土壤、地形、植被覆盖度、土地利用5个侵蚀因子,基于GIS平台结合RUSLE模型得到研究区2000—2020年5期的土壤侵蚀值,并分析其时空分布特征。结果表明:①在研究时段以无明显水土流失为主,无明显水土流失的面积占比由53.21%上升至86.44%;②海拔在500~1000 m的区域侵蚀情况最为严重,侵蚀面积达4540.52 km 2,中度及以上高等级侵蚀占比为28.00%;③坡度与侵蚀面积呈负相关关系,与侵蚀严重程度呈正相关关系。展开更多
在2016年发表关于企业转型升级模型时,将CTU-Model定义为Company Transformation and UpgradingModel(企业转型升级模型),经过几年的实践验证及相应的理论研究,在此将这个管理模型进行了升级。将之从仅仅针对于企业转型升级场景的应用...在2016年发表关于企业转型升级模型时,将CTU-Model定义为Company Transformation and UpgradingModel(企业转型升级模型),经过几年的实践验证及相应的理论研究,在此将这个管理模型进行了升级。将之从仅仅针对于企业转型升级场景的应用管理系统升级为应用于一般企业持续成长管理的系统,称之为企业价值创新战略,又称为企业转型升级模型2.0(CTU-Model2.0)。展开更多
Soil erosion in the Hare watershed led to significant land degradation,water pollution,and reduced agricultural productivity.Despite its effects,very few researchers have used combined morphometric and RUSLE model tec...Soil erosion in the Hare watershed led to significant land degradation,water pollution,and reduced agricultural productivity.Despite its effects,very few researchers have used combined morphometric and RUSLE model techniques to quantify soil erosion and thereby prioritize impacted areas.This work used an automated GIS-based tool(SWPT)to prioritize crucial areas based on topohydrological and morphometric factors and predict soil loss in sub-watersheds using the RUSLE model.Land use/cover data were obtained from Landsat imagery,while slope and morphometric information were extracted from digital elevation data with a resolution of 12.5 m.Soil erodibility was determined using Ethiopian soil maps,and rainfall erosivity was computed using meteorological data.An average annual soil loss of 49 t ha-1 yr-1 was observed in the Hare watershed.Sub-watershed 11 was found to be the most affected,with an average annual soil loss of 85.12 t ha-1 yr-1and a compound parameter value(CPV)of 0.059.Subwatershed 17 has the least amount of soil loss,with 3.67t ha-1 yr-1 and a CPV of 1.32.The study emphasizes the usefulness of integrating RUSLE and morphometric analysis for soil and water conservation planning,suggesting a variety of modeling tools in data-sparse locations to quantify and prioritize erosion-prone areas.展开更多
基金Chinese Academy of Sciences (CAS)The World Academy of Science (TWAS) for providing financial support
文摘Droughts and soil erosion are among the most prominent climatic driven hazards in drylands,leading to detrimental environmental impacts,such as degraded lands,deteriorated ecosystem services and biodiversity,and increased greenhouse gas emissions.In response to the current lack of studies combining drought conditions and soil erosion processes,in this study,we developed a comprehensive Geographic Information System(GIS)-based approach to assess soil erosion and droughts,thereby revealing the relationship between soil erosion and droughts under an arid climate.The vegetation condition index(VCI)and temperature condition index(TCI)derived respectively from the enhanced vegetation index(EVI)MOD13A2 and land surface temperature(LST)MOD11A2 products were combined to generate the vegetation health index(VHI).The VHI has been conceived as an efficient tool to monitor droughts in the Negueb watershed,southeastern Tunisia.The revised universal soil loss equation(RUSLE)model was applied to quantitatively estimate soil erosion.The relationship between soil erosion and droughts was investigated through Pearson correlation.Results exhibited that the Negueb watershed experienced recurrent mild to extreme drought during 2000–2016.The average soil erosion rate was determined to be 1.8 t/(hm2•a).The mountainous western part of the watershed was the most vulnerable not only to soil erosion but also to droughts.The slope length and steepness factor was shown to be the most significant controlling parameter driving soil erosion.The relationship between droughts and soil erosion had a positive correlation(r=0.3);however,the correlation was highly varied spatially across the watershed.Drought was linked to soil erosion in the Negueb watershed.The current study provides insight for natural disaster risk assessment,land managers,and stake-holders to apply appropriate management measures to promote sustainable development goals in fragile environments.
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.
文摘定量研究达州市土壤侵蚀的时空分布状况以及不同坡度,海拔高度下的侵蚀状况,可以为达州市开展水土保持工作提供科学参考。本研究选用降雨、土壤、地形、植被覆盖度、土地利用5个侵蚀因子,基于GIS平台结合RUSLE模型得到研究区2000—2020年5期的土壤侵蚀值,并分析其时空分布特征。结果表明:①在研究时段以无明显水土流失为主,无明显水土流失的面积占比由53.21%上升至86.44%;②海拔在500~1000 m的区域侵蚀情况最为严重,侵蚀面积达4540.52 km 2,中度及以上高等级侵蚀占比为28.00%;③坡度与侵蚀面积呈负相关关系,与侵蚀严重程度呈正相关关系。
文摘在2016年发表关于企业转型升级模型时,将CTU-Model定义为Company Transformation and UpgradingModel(企业转型升级模型),经过几年的实践验证及相应的理论研究,在此将这个管理模型进行了升级。将之从仅仅针对于企业转型升级场景的应用管理系统升级为应用于一般企业持续成长管理的系统,称之为企业价值创新战略,又称为企业转型升级模型2.0(CTU-Model2.0)。
文摘Soil erosion in the Hare watershed led to significant land degradation,water pollution,and reduced agricultural productivity.Despite its effects,very few researchers have used combined morphometric and RUSLE model techniques to quantify soil erosion and thereby prioritize impacted areas.This work used an automated GIS-based tool(SWPT)to prioritize crucial areas based on topohydrological and morphometric factors and predict soil loss in sub-watersheds using the RUSLE model.Land use/cover data were obtained from Landsat imagery,while slope and morphometric information were extracted from digital elevation data with a resolution of 12.5 m.Soil erodibility was determined using Ethiopian soil maps,and rainfall erosivity was computed using meteorological data.An average annual soil loss of 49 t ha-1 yr-1 was observed in the Hare watershed.Sub-watershed 11 was found to be the most affected,with an average annual soil loss of 85.12 t ha-1 yr-1and a compound parameter value(CPV)of 0.059.Subwatershed 17 has the least amount of soil loss,with 3.67t ha-1 yr-1 and a CPV of 1.32.The study emphasizes the usefulness of integrating RUSLE and morphometric analysis for soil and water conservation planning,suggesting a variety of modeling tools in data-sparse locations to quantify and prioritize erosion-prone areas.
