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Northern Bangladesh, consisting of 16 administrative districts, has suffered from several drought phenomena in the last few decades. This study aims to formulate a drought susceptibility map considering three different types of droughts, which later, was referred to as composite drought, and was derived from three different indices. Standardized Precipitation Index (SPI) along with Vegetation Condition Index (VCI) from MODIS-NDVI, and Standardized Water Index (SWI) were considered for assessing the meteorological, agricultural, and hydrological drought, respectively. Drought condition was estimated for winter and pre-monsoon months (November to June) for 18 years, from 2000 through 2017. Individual drought maps for each month within the specified period were first prepared and then superimposed in the ArcGIS platform to produce an integrated drought map. Afterward, three different drought maps were incorporated to show the composite drought scenario. Then, extreme drought hot spots within the combined map were further identified using local indicators of spatial autocorrelation (LISA) method. Analyses showed that around 65% of the study area faced moderate to severe meteorological drought and mild to moderate agricultural and hydrological drought. The most extreme drought-prone month was March, and among 16 districts, Dinajpur and Naogaon faced the highest level of drought severity. This study is essentially important to unveil the individual drought susceptibility condition for a particular location. Detection of the composite drought hot spots will help in adopting short as well as long term adaptation and mitigation programs. At the same time, the methodology is reproducible for other drought-prone regions around the globe.
Islam et al. (2021) studied this question.