Assessing spatiotemporal variation in global soil erosion is essential for identifying areas that require greater attention and management under the effects of anthropogenic activities and climate change.Soil erosion ...Assessing spatiotemporal variation in global soil erosion is essential for identifying areas that require greater attention and management under the effects of anthropogenic activities and climate change.Soil erosion can be modelled using the universal soil loss equation(USLE),which includes rainfall erosivity(R-factor),vegetation cover(C-factor),topography(LS-factor),soil erodibility(K-factor),and management practices(P-factor).However,global soil erosion modeling faces numerous challenges,including data acquisition,calculation processes,and parameter calibration under different climatic and topographic backgrounds.Thus,we presented an improved USLE-based model using highly distributed parameters.The R-,C-,and P-factors were modified by the climate zone,country,and topography.This distributed model was applied to estimate the intensity and variations in global soil erosion from 1992 to 2015.We validated the accuracy of this model by comparing simulations with measurements from 11,439 plot years of erosion data.The results showed that i)the average global erosion rate was 5.78 t ha^(-1)year^(-1),with an increase rate of 4.26×10^(-3)t ha^(-1)year^(-1);ii)areas with significantly increasing erosion accounted for 16%of the land with water erosion,whereas those with significantly decreasing erosion accounted for 7%;and iii)areas with severe erosion included the western Ghats,Abyssinian Plateau,Brazilian Plateau,south and east of the Himalayas,and western coast of South America.Intensified erosion occurred mainly on the Amazon Plain and the northern coast of the Mediterranean.This study provides an improved water erosion prediction model and accurate information for researchers and policymakers to identify the drivers underlying changes in water erosion in different regions.展开更多
基金This work was funded by the National Natural Science Foundation of China(U2102209).
文摘Assessing spatiotemporal variation in global soil erosion is essential for identifying areas that require greater attention and management under the effects of anthropogenic activities and climate change.Soil erosion can be modelled using the universal soil loss equation(USLE),which includes rainfall erosivity(R-factor),vegetation cover(C-factor),topography(LS-factor),soil erodibility(K-factor),and management practices(P-factor).However,global soil erosion modeling faces numerous challenges,including data acquisition,calculation processes,and parameter calibration under different climatic and topographic backgrounds.Thus,we presented an improved USLE-based model using highly distributed parameters.The R-,C-,and P-factors were modified by the climate zone,country,and topography.This distributed model was applied to estimate the intensity and variations in global soil erosion from 1992 to 2015.We validated the accuracy of this model by comparing simulations with measurements from 11,439 plot years of erosion data.The results showed that i)the average global erosion rate was 5.78 t ha^(-1)year^(-1),with an increase rate of 4.26×10^(-3)t ha^(-1)year^(-1);ii)areas with significantly increasing erosion accounted for 16%of the land with water erosion,whereas those with significantly decreasing erosion accounted for 7%;and iii)areas with severe erosion included the western Ghats,Abyssinian Plateau,Brazilian Plateau,south and east of the Himalayas,and western coast of South America.Intensified erosion occurred mainly on the Amazon Plain and the northern coast of the Mediterranean.This study provides an improved water erosion prediction model and accurate information for researchers and policymakers to identify the drivers underlying changes in water erosion in different regions.
