Real-Time Flood Forecasting System for Disaster Risk Reduction due to Flash Floods

Shahulhameed, B.; R.K., D.; Krishna, A., and Prasad, S.D., 2024. Real-time flood forecasting system for disaster risk reduction due to flash floods. In: Phillips, M.R.; Al-Naemi, S., and Duarte, C.M. (eds.), Coastlines under Global Change: Proceedings from the International Coastal Symposium (ICS) 2024 (Doha, Qatar). Journal of Coastal Research, Special Issue No. 113, pp. 1001-1005. Charlotte (North Carolina), ISSN 0749-0208. Recent flash floods in Oman have severely damaged property and brought attention to the need to control their effects once again. The creation of a real-time warning system might reduce impacts by offering timely information to start flood management procedures. For this reason, developed the novel real-time flood forecasting system (RT Flood system), which is especially susceptible to flash floods. Recently, flash floods are frequently occurring in the arid region as Oman, which counter with various challenges to the management of wadi flash floods. The creation of a real-time warning system might reduce impacts by offering timely information to start flood management procedures. Input data on rainfall was prepared so that a hydraulic model could use it later. Radar rainfall data was utilized in this module to provide forecasts using the TITAN (Thunderstorm Identification, Tracking, Analysis, and Nowcasting) rainfall model. The preparation of the input data, the timing of the hydraulic simulation, and the post-processing of the output data for display were all managed by the real-time task management system that was supplied by the RT Flood system. Using the input data, a model simulation that recreated flash floods was developed. The target urban area's drainage systems were represented using a dynamic, conceptual model called the PCSWMM, or Personal Computer version of the Stormwater Management Model. The results of the study indicated that 61.2% of the flash floods were accurately predicted with sufficient precision to provide timely pre-warning. Furthermore, it showed that compared to separate flood models that used local rain stations and radar separately, the RT Flood system warned flooding potential 20 minutes earlier. Making decisions about specific flood controls, such as pump and canal gate operations, was made possible by the earlier alert.