Assessing grain crop water productivity of China using a hydro-model-coupled-statistics approach: Part I: Method development and validation

Identifying and quantifying the links between water resources and food production is crucial in addressing the intensified conflicts between water scarcity and food security. We proposed an integrated framework for quantifying relationships between food and water based on the concept of green water (GW), blue water (BW) and crop water productivity (CWP). An estimation method coupling hydrologic model and crop and water statistics was developed and validated to quantify basin-scale GW, BW and CWP in breadbasket basins of China. A basin-scale GW and BW assessment method was developed by using the Soil and Water Assessment Tool (SWAT). Monthly-step calibration and validation were performed at 15 discharge flow stations in seven first-order river basins of the country. The coefficient of determination (r²) and Nash-Sutcliffe Efficiency (NSE) in calibration stage ranged from 0.18 to 0.95, and −4.22 to 0.93, respectively; while in validation period, r² ranged from 0.02 to 0.97 and NSE ranged from −266.7 to 0.96. The simulated available soil water was validated against the observed soil moisture data, and the results showed that the model can reflect the yearly average values of soil water storage. Overall, the modeling performance for river basins with 4.94 million km² of drainage areas in total was acceptable. The simulated hydrologic components were then coupled with crop-and-water-statistics-based estimation method for assessing basin-scale CWP on four staple grain crops, i.e. rice, wheat, maize, and soybean. The results were validated by comparing with the similar investigations in China and around the globe. It was concluded that the overall performance of the estimation method was acceptable, and the method can be applied in assessing basin-scale GW, BW and CWP in China.