Estimating Net Irrigation Across The North China Plain Through Dual Modeling Of Evapotranspiration

Irrigation is the greatest human interference with the terrestrial water cycle. Detailed knowledge on irrigation is required to better manage water resources and to increase water use efficiency (WUE). This study applies a framework to quantify net irrigation at monthly timescale at a spatial resolution of 1 km(2) providing high spatial and temporal detail for regional water resources management. The study is conducted in the Haihe River Basin (HRB) in China encompassing the North China Plain (NCP), a global hot spot of groundwater depletion. Net irrigation is estimated based on the systematic evapotranspiration (ET) residuals between a remote sensing-based model and a hydrologic model that does not include an irrigation scheme. The results suggest an average annual net irrigation of 126 mm yr(-1) (15.2 km(3) yr(-1)) for NCP and 108 mm yr(-1) (18.6 km(3) yr(-1)) for HRB. It is found that net irrigation can be estimated with higher fidelity for winter crops than for summer crops. The simulated water balance for NCP is evaluated with Gravity Recovery and Climate Experiment (GRACE) data, and the net irrigation estimates can close the water balance gap. Annual winter wheat classifications reveal an increasing crop area with a trend of 2,200 km(2) yr(-1). This trend is not accompanied by a likewise increasing trend in irrigation water use, which suggests an increased WUE in the NCP, which is further supported by net primary productivity data. The proposed framework has potential to be transferred to other regions and support decision makers to support sustainable water management.