Bangladesh is highly vulnerable to recurring hazards and this situation is going to exacerbate due to the impacts of climate change. There is a dearth of data-driven decision-making in the country and typically poverty data is used to guide decisions. This study was an attempt to address that gap by providing data-centric decision-making frameworks using widely accepted global methodologies such as the INFORM index. This study is primarily based on seven years of disaster-related data extending from 2014 to 2020, the major disasters considered were monsoon flood, flash flood, cyclone and storm surge, landslide, and riverbank erosion; however, other hazards were also reviewed such as nor’wester, cold wave, hailstorm, etc. The data sources were NDRCC, DGHS, IDMC, MRVAM, and NIRAPAD hazards reports, etc. The results were verified with long-term datasets such as the EM-DAT. First, data for major disasters were analyzed to understand the pattern of impact, then it helped the multi-hazard risk quantification using INFORM risk index with 24 indicators. Secondly, exposure was quantified up to 2025 using projected data where climate change has been considered. Then, the JIAF severity scale was contextualized, and the severity of needs was calculated using nine indicators. Finally, all the triggers and thresholds of different disasters from numerous sources such as BMD, BWDB, FFWC, GDACS, GloFAS, etc. were analyzed to bring them into a similar pattern for a better understanding accompanied by risk matrices.
Within the considered period, 15 major disasters affected 42 million people, displaced 9.4 million people, damaged 4.6 million houses either fully or partially, caused 1,053 deaths, and resulted in an economic loss of $4.1 billion. Among the four major disasters, flood (including both Monsoon and Flash flood) affected 34.9 million people- it is the highest and 83% of the total affected 42 million, the next one to have a large impact was cyclone and storm surge which affected 7.05 million people and constitutes 16.78% of the affected population. The results reveal that all districts of the country are exposed to at least one or multiple hazards, however, exposure does not necessarily equate to impact. The multi-hazard risk analysis shows that Kurigram, Gaibandha, Jamalpur, and Sirajganj districts in the north of Bangladesh are at very high risk (>=6.5 out of 10) and high risk (>=5-6.49) districts are mostly spread in the northeast, coastal south and southeast hilly region. The deterministic analysis shows that the impacted population varies significantly ranging from 5 to 778 per 1,000 people. Based on the impact distribution data, an inference can be made with 95% confidence that annually 660 people per 1,000 will be impacted by climate-related hazards from 2021 to 2025. Moreover, annually a total of -12.10 million people (2.71 million households) could be impacted out of 18.33 million exposed people(4.10 million households) in the next five years considering the multi-hazard risk level. The potentially impacted population was then divided among four severity phases after contextualizing the 2021 JIAF framework to answer questions on where to allocate resources, to whom and when, to how many people, plus on what should be done. Out of 2.71million households, Extreme, Severe, Stress and Minimal class consecutively contains 0.72 million, 0.91 million, 0.63 million and 0.44 million households. In addition, the similar risk matrices generated for the considered hazards based on a detailed literature review of global and local reliable sources is another significant addition to this study.
The findings and frameworks of this study can be used and applied in data-driven decision-making by relevant agencies such as MoDMR, UN agencies, Start Fund Bangladesh, etc. The multi-hazard risk analysis method could be used to identify areas that are likely to be impacted whereas the severity framework could be used to identify the population in need plus these frameworks can be customized for different administrative areas such as the Upazila level. Moreover, this study suggests Household Economy Analysis (HEA), a country-wide sub-national INFORM risk index and climate change integrated hazard modeling to improve future planning and an in-depth evidence-based understanding of hazards, their impacts, and likely needs of the at-risk population of Bangladesh.