Early warning is a key element of disaster risk reduction and in recent decades, there have been major advancements in medium-range and seasonal forecasting. IRDR’s RIA project (Risk Interpretation and Action) looks at decision-making for uncertainty resilience and risk management – in this case while using an early warning system.
Bapon Fakhruddin, member of IRDR’s Scientific Committee, and his co-author’s developed an experimental medium-range (1–10 days) probabilistic flood-forecasting model for Bangladesh which was successfully implemented in Kaijuri Union, Bangladesh. The research was published as Community responses to flood early warning system: Case study in Kaijuri Union, Bangladesh by S.H.M. Fakhruddin,* Akiyuki Kawasaki,** Mukand S. Babel* on pages 323–331 in Volume 14, Part 4 (December 2015) in the International Journal of Disaster Risk Reduction.
The paper describes an integrated system of medium-range flood forecasts based on agricultural users’ needs. For example, 1- to 10-day forecasts provide farmers a range of decision options such as changing cropping patterns or planting times. The method included risk and vulnerability assessments conducted through community consultation. The forecast lead-time requirement, impacts, and management options for crops and livestock were identified through focus group discussions, informal interviews, and surveys. The study involved developing a flood risk map and response options to flood risk probabilistic forecasts based on farmers’ needs for early warning.
Understanding the use of probabilistic forecasts is still very limited, and operational forecasters are often skeptical about the ability of forecast recipients to understand the prediction system. This study showcases the ability of community members to use probabilistic forecasts for operational decision-making. The results included flood risk mapping according to the vulnerability of the communities in the study area and the early warning impacts during and after the flood events.
* Water Engineering and Management, School of Engineering and Technology, Asian Institute of Technology, Thailand
** Department of Civil Engineering, The University of Tokyo, Japan