The frequent recent drought events in the Great Plains of United States have led to significant crop yield reductions and crop price surges. Using an integrated water-food-energy nexus modelling and optimization approach, this study laid the basis for developing an effective agricultural drought management system by combining real-time drought monitoring with real-time irrigation management. The proposed water-food-energy simulation and optimization method is spatially explicit and was applied to one major corn region in Nebraska. The crop simulations, validated with yield statistics, showed that a drought year like 2012 can potentially reduce the corn yield by 50% as compared to a wet year like 2009. The simulation results show that irrigation can play a key role in halting crop losses due to drought and in sustaining high yields of up to 20 t/ha. Nevertheless, the water-food-energy relationship shows that significant investments on water and energy are required to limit the negative effects of drought. The multi-criteria optimization problem developed in this study shows that the optimal crop yield does not necessarily correspond to the maximum yield, resulting in potential water and energy savings.

美国大平原最近频繁发生的干旱事件导致农作物单产大幅下降和农作物价格飞涨。该研究使用集成的水-食物-能源关系建模和优化方法，为通过将实时干旱监测与实时灌溉管理相结合而开发有效的农业干旱管理系统奠定了基础。所提出的水-食物-能量模拟和优化方法在空间上是明确的，并已应用于内布拉斯加州的一个主要玉米地区。通过单产统计数据进行的作物模拟显示，与2009年这样的干旱年相比，像2012年这样的干旱年可能会使玉米单产降低50％。模拟结果表明，灌溉在遏制因干旱造成的作物损失方面可以发挥关键作用干旱并维持高达20吨/公顷的高产。然而，水-食物-能源的关系表明，要限制干旱的负面影响，就需要在水和能源上进行大量投资。本研究中开发的多准则优化问题表明，最佳作物产量不一定与最大产量相对应，从而潜在地节约了水和能源。