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[1]NIE Puxuan,FANG Shenghui,GONG Yan,et al.Research on Spatial Variation of Soil Moisture in Hebei Province Based on GWR Model[J].Research of Soil and Water Conservation,2019,26(01):98-105.

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Research on Spatial Variation of Soil Moisture in Hebei Province Based on GWR Model

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 26 Number of periods: 2019 01 Page number: 98-105 Column: Public date: 2019-02-28

Title:: Research on Spatial Variation of Soil Moisture in Hebei Province Based on GWR Model

Author(s):: NIE Puxuan¹, FANG Shenghui¹, GONG Yan¹, LIU Jin²; 1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China;
2. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

Keywords:: soil moisture; influencing factors; geographically weighted regression model (GWR); spatial variation; Hebei Province

CLC:: S152.7

DOI:: -

Abstract:: In order to study the influence of environmental factors on the spatial differentiation of soil moisture in Hebei Province, SMOS Level-3 soil moisture data from 2013 to 2017 were used to select precipitation, DEM, slope, vegetation, and land surface temperature as environmental factors affecting soil moisture. Spatial autocorrelation analysis of soil moisture in Hebei Province was conducted to establish the geographically weighted regression model between soil moisture contents and impact factors. The GWR model was compared with the general linear regression model to analyze the heterogeneity of the effect of the influencing factors on soil moisture in space. The results showed that the soil moisture in Hebei Province had spatial heterogeneity and obvious agglomeration characteristics. The fitting effect of GWR model was far better than the OLS model in terms of fitting goodness and spatial distribution. The fitting goodness (R²) of the GWR model was 43% higher than that of the OLS model. The ability of the GWR model to explain the soil moisture impact factor was 34.6% higher than that of the OLS model. The residual square sum and AIC value of the GWR model were much smaller than those of OLS model. The effect parameters of the impact factors on soil moisture in the study area had spatial differentiation characteristics, and the degrees of influence of the influence factors were also different with DEM having the greatest impact followed by slope gradient, land surface temperature, precipitation, and NDVI. Each factor had both negative and positive effects on soil moisture in space, but it had the negative effect in most areas. The research results are of great significance to the development of precision agriculture, soil and water conservation, resource utilization, and ecological construction in the study area.

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