ABSTRACT

Predicting the impacts of projected change in precipitation (P) and temperature (T) on occurrence of drought and extreme events is essential for managing natural resources and setting policy. This study compares future occurrence of excessively dry and wet periods based on P, T, stream flow, soil moisture, and extreme P and T events. The comparisons are based on coupled future climate projections from multiple Earth system models downscaled using site-specific weather data and hydrologic model outputs for the Goodwater Creek Experimental Watershed, Missouri, USA. The use of multiple drought indices, downscaled climate data, and process model output facilitated drought prediction for different land surface processes and its comparison. The P and T extremes and droughts were calculated using standardized indices. The results based on drought and extreme indices indicate increased frequency and duration of drought in the future, primarily due to a projected decline in summer precipitation resulting in summer droughts. The streamflow and soil water-based drought indices indicated increased spring drought risks in the future despite a precipitation increase, indicating the importance of process representation with hydrologic models for drought computation.

摘要

预测降水 (P) 和温度 (T) 的预计变化对干旱和极端事件发生的影响对于管理自然资源和制定政策至关重要。本研究根据 P、T、河流流量、土壤水分和极端 P 和 T 事件比较了未来过度干燥和潮湿时期的发生情况。这些比较基于多个地球系统模型的耦合未来气候预测，这些模型使用特定地点的天气数据和美国密苏里州古德沃特溪实验流域的水文模型输出进行缩小。多个干旱指数、缩减气候数据和过程模型输出的使用促进了不同地表过程的干旱预测及其比较。使用标准化指数计算 P 和 T 极端和干旱。基于干旱和极端指数的结果表明未来干旱的频率和持续时间会增加，主要是由于预计夏季降水减少导致夏季干旱。径流和土壤水基干旱指数表明，尽管降水量增加，但未来春季干旱风险增加，表明过程表征与水文模型对干旱计算的重要性。