Flash flood modeling in the data-poor basin: A case study in Matina River Basin

Abstract

Forecasting flooding hazards is a very effective non-engineering measure for flood control. Presently, the commonly used forecasting method in simulating flash flood events is through a watershed hydrological model. Many Asia-Pacific countries like the Philippines are prone to frequent hydrometeorological hazards such as tropical cyclones, resulting in frequent heavy rainfall events. However, most rivers in the many basins lack water flow observation data, which makes it challenging to use lumped and data-driven models for flash flood forecasting. With the continuous progress of remote sensing (RS) and geographic information system (GIS) techniques, the physically-based distributed hydrological model (PBDHMs) has rapidly advanced. PBDHMs can directly determine the model parameters according to the underlying surface characteristics from remotely-sensed data, which makes it possible for flood forecasting in areas with little to virtually no data. In this study, the Matina River basin in Davao City was selected as a case study in simulating a small data-poor basin in the region. The Liuxihe model was used to formulate a forecasting scheme and simulated the past flash flood events. The results show that there is a good correspondence between the past heavy rainfall events and their corresponding simulated river discharges. The results conform to the hydrological regularities, which can be used for flood forecasting and can serve as a baseline for the development of a flood forecasting system in the rivers of Davao City and elsewhere.