Spatiotemporal Evolution of Soil Conservation Founction Value and Its Driving Forces in Harbin City
[Objective]Soil erosion is an important environmental problem of globality,which seriously restricts human production and life.Soil maintenance conservation founction was quantitative studied to formulate the regional soil and water conservation measures,and provide scientific basis for the functional partition planning and governance of Harbin City.[Methods]Based on the InVEST model sediment delivery ratio module,this study evaluated the soil erosion and soil conservation in 2000,2010 and 2020 in Harbin,analyzed the spatial aggregation type of soil conservation with the help of spatial autocorrelation,and used the optimal geographic detector to reveal the driving forces of spatial heterogeneity.[Results]① In 2000,2010 and 2020,the soil conservation in Harbin City was 2.18 × 109,2.07 × 109,and 2.77 × 109 t,respectively,showing a trend of decreasing first and then increasing,and the overall spatial distribution pattern of"low in the west and high in the east".② The soil conservation amount showed a strong spatial positive correlation,mainly"low-low aggregation"and"high-high aggregation"types,the"low-low aggregation"type area showed a downward trend,while the"high-high aggregation"type showed a decreasing and then rising trend.③ Elevation,precipitation and slope had the strongest explanatory power on the spatial heterogeneity of soil conservation in Harbin City,with average explanatory forces of 0.225 9,0.198 9 and 0.180 4,respectively,and the interaction between slope and precipitation and other factors was the strongest explanatory interaction factor in the study area.[Conclusion]Water and soil management in the western part of Harbin City and along the Songhua River should be strengthened,while good water and soil conditions in the north and east of the city should be maintained to avoid large-scale human disturbance activities.
InVEST modelsoil conservationGeodetectorspatial autocorrelationHarbin City
国家科技期刊平台
NSTL
万方数据
维普
