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Evaluation of Supporting flood Forecast-Based Action and Learning (SUFAL) Project in the 2020 Monsoon Floods

Países
Bangladesh
Fuentes
CARE
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EXECUTIVE SUMMARY

Background: ‘Supporting flood Forecast-based Action and Learning’ (SUFAL) project was designed to contribute to reducing the adverse impacts of the increasing frequency of catastrophic flooding on the vulnerable and poor communities through Forecast-based Action (FbA). The project was funded by The Directorate-General for European Civil Protection and Humanitarian Aid Operations (ECHO) and was implemented through a consortium led by CARE Bangladesh, with Concern Worldwide, Islamic Relief and Regional Integrated Multi-Hazard Early Warning System for Africa and Asia (RIMES). The project was implemented in three northern districts of Bangladesh: Jamalpur, Gaibandha, and Kurigram. FbA contributed to disseminating Flood Early Warning messages with a lead time of 10 – 15 days with timely and accurate weather forecast information, while and it also helping to identify potential flooding areas.

Methodology: The primary purpose of the study was to “Evaluate the impact of early actions” applied through the SUFAL project on household and community beneficiaries in responding to the 2020 monsoon floods. Customized OECD-DAC criteria, Quasi-experimental design (Difference-in-Difference Method), Knowledge, Attitude and Practices (KAP) framework and Value for Money (VfM) framework were used as guiding methods and tools to design study instruments and evaluate the impact of early actions at every stakeholder level. The study covered a control group in non-project areas and three treatment groups in the project areas: Treatment group 1 (EWM support), Treatment group 2 (EWM + Evacuation + Shelter + WASH support), Treatment group 3 (EWM + Evacuation + Shelter + WASH + Cash-grant support). Treatment groups were categorized in three different groups to conduct cost-effectiveness analysis. The study areas were in the districts of Kurigram (Hatia, Begumganj, Buraburi, Shaheber Alga unions), Gaibandha (Bharatkhali, Saghata, Ghuridaha, Haldia unions) and Jamalpur (Kulkandi, Chinaduli, Noarpara, Shapdhor. The survey sample consisted of 224 control respondents (of which 153 were women) and 754 treatment respondents (of which 426 were women), among which Sample for treatment group 1, 2, and 3 were 293 (100 women), 292 (192 women) and 169 (134 women), respectively. A total of 118 of the 754 treatment households interviewed through the survey were women-headed households and 38 out of 224 control group households were women headed households. The team had conducted 7 FGDs with community members in the three implementation areas, and 27 KIIs with community volunteers, project staff, government officials, and other related NGOs.

Demographic information: In case of the treatment group, the average age of a female respondent was 44 years, and the average age of a male respondent was 46. In case of the control group, the average age of a female respondent was 43 years, and the average age of a male respondent was 45 years. The average annual income for the households was found to be BDT 110,732 for treatment group respondents and BDT 98,724 for control group respondents.