An efficient flash flood forecasting system for the un-gaged Meghna basin using open source platform Delft-FEWS. (March 2023) - Chowdhury, Md. Enayet; Islam, AKM Saiful; Lemans, Matthijs; Hegnauer, Mark; Sajib, Ashfaqur Rahaman; Pieu, Nahruma Mehzabeen; Das, Mohan Kumar; Shadia, Nur; Haque, Akramul; Roy, Binata; Billah, Maruf; Abdullah, Faruque; et al.
Abstract: The northeast region of Bangladesh is highly vulnerable to flash floods which often damage the only crop of that region, the boro rice. Developing an efficient and real-time flash flood forecasting system for that region is found essential. The traditional model-centric approach requires plenty of time and manpower to effectively model flash floods. This paper discusses an open-source data-centric integrated flash flood modelling approach using a platform named Delft-FEWS. It is based on three inter-dependent models, e.g., meteorological, hydrologic, and hydrodynamic. The model was calibrated and validated with the flash flood data of 2010-12 and 2013-15, respectively. The performance of the model in real-time was assessed in the context of the 2021 flash flood season. In both cases, it performed satisfactorily. The entire system helps the practitioners to work in a flexible environment to generate flash flood forecasting and early warnings. Highlights: We developed a customizable integrated flash flood forecasting system using Delft-FEWS. This system coupled weather forecast, hydrological, & hydrodynamic model for a data-poor complex transboundary river basin. The model provides satisfactory results in most of the stations (R 2 > 0.7; NSE> 0.8) after calibration and validation. The model performed satisfactorily (R 2 > 0.7; NSE>0.8; PBIAS within ±1%; RMSE<0.1) in real-time water level forecasting during the 2021 flash flood season.