Global warming has increased the frequency of compound disaster events, posing significant threats to ecosystems. Among these, compound droughts are difficult to identify due to complex spatiotemporal interactions among different drought types. Most existing studies emphasize temporal overlaps, overlooking the spatiotemporal continuity of drought evolution. To address this limitation, we propose a dual spatiotemporal coupling framework. It first applies three-dimensional clustering to identify spatiotemporally continuous drought events within individual drought types and then performs event-level spatiotemporal coupling across drought types from a propagation perspective to identify compound drought events. Applied to a typical arid region in Northwest China from 1987 to 2020, the framework effectively identified multiple compound drought types and enabled systematic evaluation of their characteristics and compoundness (i.e. dependence) relative to single-type droughts. In addition, the variable importance in projection (VIP) method was employed to identify dominant hydrometeorological drivers. The result showed that the framework detected 32 meteorological–hydrological (MH), 33 meteorological–ecological (ME), 33 hydrological–ecological (HE), and 17 meteorological–hydrological–ecological (MHE) events. Notably, the identified compound drought events in the study area have exhibited a marked trend of increasing severity since the 2000s. In terms of compoundness, MH droughts exhibited a higher degree of compoundness with meteorological drought (MD) than with hydrological drought (HD), particularly in terms of duration, whereas ME, HE, and MHE droughts showed the highest compoundness with ecological drought (ED). Regarding driving factors, meteorological variables dominated MH, ME, and MHE compound droughts, but hydrological variables predominantly influenced HE compound droughts. Overall, this framework offers a novel approach for capturing the spatiotemporal complexity of compound droughts, providing critical insights for drought monitoring under climate change scenarios • A dual spatiotemporal coupling framework identifies multiple compound drought types. • Compound droughts have intensified markedly since the 2000s. • Compound drought periods feature more severe hydrometeorological anomalies. • Driving factors are inherited from the initial drought type during propagation.
Guo et al. (Thu,) studied this question.