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Global assessment of socio-economic drought events at the subnational scale: a comparative analysis of combined versus single drought indicators

作者
Sneha Kulkarni,Yohei Sawada,Yared Bayissa,Brian Wardlow
出处
期刊:Hydrology and Earth System Sciences [Copernicus Publications]
卷期号:29 (18): 4341-4370
标识
DOI:10.5194/hess-29-4341-2025
摘要

Abstract. The accurate assessment of the propagation of drought hazards to socio-economic impacts poses a significant challenge and is still less explored. To address this, we analysed a subnational disaster dataset called Geocoded Disaster (GDIS) and evaluated the skills of multiple drought indices to pinpoint global drought areas identified by GDIS. For the comparative analysis, a widely used standardised precipitation index (SPI), normalised difference vegetation index (NDVI), standardised soil moisture index (SSMI), and standardised temperature index (STI) were globally computed at the subnational level for the period 2001–2021. Out of 1641 drought events recorded in GDIS, NDVI identified 1541 (93.9 %), SPI 1458 (88.8 %), STI 1439 (87.7 %), and SSMI 1376 (83.9 %). NDVI showed better performance in highly vegetated areas due to its sensitivity to precipitation and soil moisture and its inverse relationship with temperature. Recognising the limitations of single-input drought indices in capturing the complex propagation of droughts, we also introduced a novel combined drought indicator (CDI), which integrates meteorological (rainfall and temperature) and agricultural (NDVI and soil moisture) anomalies using a weighted approach to identify droughts and plays a key role in minimising inaccuracies in drought assessment. CDI successfully identified 1550 (94.5 %) of the GDIS documented drought events, outperforming all individual indices. Based on CDI, the highest frequency of severe droughts (greater than seven events) was observed in sub-Saharan Africa and South Asia. It also captured persistent droughts in Argentina, Brazil, the Horn of Africa, western India, and North China – areas that are highly vulnerable to socio-economic droughts. Our findings highlight the importance of using CDI for improved identification of socio-economic drought events and for prioritising regions at greater risk.
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