Evaluating Agricultural Drought in the Haihe River Basin Using an Improved Crop Moisture Index

作者：Mingzhi Yang, Xinyang Li, Jijun Xu, Huan Jing, Xinyi Zhang, Lianhai Sang · 发表于：Water · 年份：2025 · DOI：10.3390/w17233372 · 被引用次数：3 · 研究领域：Hydrology and Drought Analysis、Soil Moisture and Remote Sensing、Plant Water Relations and Carbon Dynamics

In large irrigated agricultural regions under intensive human management, irrigation profoundly influences agricultural drought dynamics. High-frequency irrigation markedly alters natural farmland soil moisture, causing traditional drought indices to distort the actual severity of human-modified agricultural drought and leading to substantial monitoring deviations. In this work, an improved agricultural drought index based on the Crop Moisture Index (CMI) was developed to accurately characterize drought conditions, using the Haihe River Basin as a case study. The CMI’s water balance equation was revised by incorporating an auto-irrigation threshold method with crop coefficients and water stress coefficients. Furthermore, the improved CMI explicitly models irrigation by defining auto-irrigation thresholds based on the critical growth stages of the main crops. The performance of the original and improved CMI was evaluated by comparing their simulated soil moisture and drought detection accuracy against benchmark data derived from measurements across yearly, monthly, and weekly scales. The spatial evolution of a major 2002 drought in North China was also reconstructed to assess the indices’ performance. The results showed that: (1) The revised soil water balance equation achieved significantly lower relative errors than the original equation across all time scales; (2) The improved CMI consistently demonstrated higher drought identification accuracy rates than the original CMI; ...