Recent Changes in Drought Events over South Asia and Their Possible Linkages with Climatic and Dynamic Factors

Abstract

South Asia is home to one of the fastest-growing populations in Asia, and human activities are leaving indelible marks on the land surface. Yet the likelihood of successive observed droughts in South Asia (SA) and its four subregions (R-1: semi-arid, R-2: arid, R-3: subtropical wet, and R-4: tropical wet and dry) remains poorly understood. Using the state-of-the-art self-calibrated Palmer Drought Severity Index (scPDSI), we examined the impact of different natural ocean variability modes on the evolution, severity, and magnitude of observed droughts across the four subregions that have distinct precipitation seasonality and cover key breadbaskets and highly vulnerable populations. The study revealed that dryness had significantly increased in R-1, R-2, and R-4 during 1981–2020. Temporal analysis revealed an increase in drought intensity for R-1 and R-4 since the 2000s, while a mixed behavior was observed in R-2 and R-3. Moreover, most of the sub-regions witnessed a substantial upsurge in annual precipitation, but a significant decrease in vapor pressure deficit (VPD) during 1981–2020. The increase in precipitation and the decline in VPD partially contributed to a significant rise in Normalized Difference Vegetation Index (NDVI) and a decrease in dryness. In contrast, a strong positive correlation was found between drought index and precipitation, and NDVI across R-1, R-2, and R-4, whereas temperature and VPD exhibited a negative correlation over these regions. No obvious link was detected with El-Niño Southern Oscillation (ENSO) events, or Indian Ocean Dipole (IOD) and drought evolution, as explored for certain regions of SA. The findings showed the possibility that the precipitation changes over these regions had an insignificant relationship with ENSO, IOD, and drought onset. Thus, the study results highlight the need for considering interactions within the longer climate system in describing observed drought risks rather than aiming at drivers from an individual perspective.

Future Amplification of Multivariate Risk of Compound Drought and Heatwave Events on South Asian Population

“…Overall, our results concur with the findings of earlier studies that suggest a significant increase in dry and warm episodes in SA and surrounding states due to rapid increase in global warming (Aadhar & Mishra, 2019;Gong et al, 2014;Krishnan & Sugi, 2003;Ullah, Ma, Ren, et al, 2022;. For example, Ummenhofer et al (2011) stated that El Nino events accompanied by severe Indian monsoon failures in the recent few decades, however, this period was associated with the prolonged absence of co-occurring IOD and El Nino events and high June-September monsoon precipitation variability.…”

DROUGHT MONITORING FROM 2001–2019 IN NORTHEAST THAILAND USING MODIS NDVI IMAGE TIME SERIES AND Savitzky-Golay APPROACH

“…Our study highlighted anomalies in drought distribution patterns from 2001 to 2019 across Northeast Thailand. Future studies should apply climatic and dynamic factors for largescale drought monitoring, following the recent study of Ullah et al (2022), to further improve the accuracy of drought monitoring.…”

“…Drought is an ubiquitous and recurring natural phenomenon worldwide, resulting in a lack of water supplies, decreased agricultural productivity, and increased socioeconomic risks (Ding et al, 2011). Drought occurrences have become more severe, prolonged, and frequent in recent decades as a result of climate change and population development, particularly in tropical and subtropical regions (AghaKouchak et al, 2015;Ullah et al, 2022). With this, drought management and monitoring offer valuable historical information.…”

“…EO data have been collected by numerous sensors such as Landsat-5, the Thematic Mapper (L5 TM); Landsat-7, the Enhanced Thematic Mapper (L7 ETM+); Landsat-8, the Operational Land Imager (L8 OLI); and Moderate Resolution Imaging Spectroradiometer (MODIS). The EO data is increasingly being used for drought monitoring (Ghaleb et al, 2015;Klisch & Atzberger, 2016;Ullah et al, 2022). These mapping results have proven to be highly satisfactory for monitoring drought events, particularly when detailed temporal EO data is used.…”

Hybrid model outperformed individual models in predicting droughts in a semi-arid region of Bangladesh

“…There is a worldwide agreement that increasing temperature and altering precipitation patterns have substantially changed the climatic conditions in South Asia (Aadhar and Mishra 2019;Ullah et al 2022) and across the world (IPCC 2021). The increasing frequency and intensity of dry climatic events are mostly caused by the interruption of the summer monsoon (Hossain et al 2014), which delivers roughly 80% of total annual rainfall and is vital to the survival of millions of people, especially the rural and marginalized people in Bangladesh.…”