Determination of the effective utilization coefficient of irrigation water based on geographically weighted regression

This study uses geographically weighted regression to determine the spatial distribution of the effective utilization coefficient of irrigation water in Zhejiang Province, China, owing to the influences of spatial attributes on the irrigation efficiency. The sample set of this study comprised 165 agricultural test sites. A multivariate linear regression model and a geographically weighted regression model were established using the effective utilization coefficient of agricultural irrigation water as the dependent variable in addition to a suite of independent variables, including the actual irrigation area, the percentage of farmland using water-saving irrigation, the type of irrigation area, the net water consumption per mu, the water intake method, the terrain slope, and the soil field capacity. Results revealed a positive spatial correlation and noticeable agglomeration features in the effective utilization coefficient of irrigation water in Zhejiang Province. The geographically weighted regression model performed better in terms of fit and prediction accuracy than the multivariate linear regression model. The obtained findings confirm the suitability of the geographically weighted regression model for determining the spatial distribution of the effective utilization coefficient of irrigation water in Zhejiang, and offer a new approach on a regional scale.