Delineation of Flood-Prone Areas in Data-Scarce Environment Using Linear Binary Classifiers

Abstract

The knowledge and understanding of areas prone to flooding are critical in mitigating and reducing risks caused by extreme water events. In the Philippines, however, large scale riverine flooding still remains a huge challenge in many parts of the country as most river basins are still ungauged. This limitation has consequently led to data scarcity and deficiency and has prevented the application of comprehensive floodplain mapping techniques. This study aims to address such limitations by introducing a simplified method for the preliminary identification of flood exposed areas within a river system using geomorphic classifiers. The Geomorphic Flood Index (GFI), a linear binary classification technique, is used in delineating flood-prone areas in a watershed within the Cagayan de Oro River Basin. The index used three morphological features – the drainage network, the contributing area, and the water level to perform the linear binary classification. Results of the study showed the potential of the GFI in delineating flood-prone areas in data-scarce environments particularly in the watershed of the Cagayan de Oro River.