Urban meteorological drought comprehensive index based on a composite fuzzy matter element-moment estimation weighting model

Abstract

Summary: Due to rapid urbanization and climate change, cities face hidden drought risks. A single drought index may inadequately reflect urban meteorological drought. The indicator weight combination method does not fully consider index correlation and weight. This study constructed an urban meteorological drought evaluation index system and developed the Composite Fuzzy Matter Element Meteorological drought Comprehensive Index (CFEMCI) by combining the moment estimation weighting model. Analyzing Zhengzhou City from 2000 to 2019, CFEMCI effectively captured meteorological drought events, with a probability of detection (POD) > 0.78, critical success index (CSI) > 0.70, false alarm rate (FAR) < 0.13 and failure ratio (FR) < 0.22. Most meteorological droughts were classified as Grade I (no drought), with 26% being light and moderate (Grades II-III). Droughts mainly occurred in spring, and the summer drought showed a more significantly aggravating trend. This index provides reliable urban drought monitoring and supports disaster prevention and mitigation efforts.

Keywords

• Geography
• Atmospheric science
• Meteorology
• Global change