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

Abstract

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.

Keywords

effective utilization coefficient of irrigation water / spatial autocorrelation / multivariate linear regression / geographically weighted regression

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Acknowledgments

This study was supported by the National Key R&D Program of China (Nos. 2016YFC0401005 and 2016YFA0601703), the National Natural Science Foundation of China (Grant Nos. 42075191, 92047203 and 91847301), and Nanjing Hydraulic Research Institute Fund (No. Y520009). We thank Chinese Academy of Meteorological Sciences for providing monitoring data of the study area.

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