Analyzes drought characteristics and assesses hazard levels in Inner Mongolia, indicating implications for risk management.
This study identifies and extracts two typical drought characteristics, drought frequency and drought severity, based on the Meteorological Drought Composite Index (MCI), and systematically analyzes their spatiotemporal evolution in Inner Mongolia. Using a two-stage geographical detector approach, the dominant factors of drought characteristics and their spatial variations are quantitatively identified across different drought grades and subregions, and the weights of drought indicators are determined accordingly. Finally, a multi-level drought hazard assessment is conducted using a drought hazard index model, providing scientific support for drought risk management and disaster prevention in Inner Mongolia. The results indicate that (1) drought characteristics exhibit significant spatial heterogeneity. Drought frequency presents a distinct east–high to west–low gradient, while high values of drought severity are concentrated in the central and southwestern regions. Temporally, drought frequency shows an increasing trend, whereas drought severity demonstrates periodic fluctuations and relative stability. (2) Results from factor and interaction detection reveal that light, moderate, and extreme drought levels are primarily influenced by the combined effects of regions with extremely high drought frequency and drought severity. In contrast, severe drought is mainly driven by regions with extremely high frequency and high severity. Moreover, the interaction between multiple factors significantly enhances the explanatory power for drought severity levels compared to individual factors. (3) The drought hazard assessment shows that high-hazard areas are mainly concentrated in Alxa League, Tongliao City, and other regions. The spatial distribution of hazard levels is highly consistent with historical drought statistics, thereby validating the rationality and practical applicability of the proposed model.
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Li et al. (2026) studied this question.
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