基于水文-作物耦合模型和CWAPI指数的农业干旱评估

基于模拟土壤含水量构建的干旱指数可反映农业干旱的时空发展过程，已被广泛用于大范围农业干旱评估中。当前模拟用于干旱评估的土壤含水量时，常采用水文模型进行模拟。然而，水文模型常过于简化作物模块甚至缺少作物模拟方案，无法模拟作物需水量，因此仅基于土壤含水量构建的土壤干旱指数因忽略作物需水而难以准确评估实际的农业干旱情况。研究构建了考虑灌溉过程影响的水文-作物耦合模型VIC-EPIC（Variable Infiltration Capacity-Environmental Policy Integrated Climate），提出了基于VIC-EPIC模拟作物需耗水过程的作物缺水距平指数CWAPI（Crop Water Anomaly Percentage Index），在青口河流域开展了区域农业干旱评估方法研究。验证分析表明，构建的CWAPI因考虑作物需水影响可直接反映作物的缺水状态和缺水对作物生长的累积影响；由于在干旱评估中引入了作物种植比例、轮作类型和灌溉的影响，CWAPI能够较SMAPI（Soil Moisture Anomaly Percentage Index）更客观地反映区域作物旱情。因此评估农业干旱时，需要考虑作物种植比例、轮作和灌溉过程的影响。

Agricultural drought assessment based on the coupled hydrology-crop growth model and CWAPI

The temporal and spatial development of agricultural drought is revealed using the drought index based on the simulated soil water content, which was widely applied to agricultural drought assessment on a large scale. Currently, when simulating soil water content for drought assessment, hydrological models are often used. However, hydrological models often oversimplify the crop module or even lack the crop simulation scheme, cannot simulate the crop water demand, and the soil drought index only based on the soil water content cannot accurately assess the actual agricultural drought due to the neglected crop water demand. In this study, the coupled hydrology-crop growth model, namely Variable Infiltration Capacity-Environmental Policy Integrated Climate (VIC-EPIC), was built considering irrigation influences, the Crop Water Anomaly Percentage Index (CWAPI) based on the variation process of crop water demand and consumption from the simulation of VIC-EPIC was proposed, and the method of regional agricultural drought assessment was studied in the Qingkou river basin of China. The built CWAPI showed the state and cumulated impact of crop water stress on the crop growth based on the verification results due to the consideration of the influence of crop water demand; because the influences of the crop planting ratio, crop rotation types, and irrigation were considered, CWAPI revealed the regional crop drought degree more objectively than Soil Moisture Anomaly Percentage Index (SMAPI). The results showed that the effect of the crop planting ratio, crop rotation types, and irrigation needed to be considered when assessing the agricultural drought.