A Semi-Probabilistic Gis-Based Method for Meso-Scale Flood Hazard Zonation

Identification of the flood-prone areas can be considered as a fundamental step in a flood risk management procedure. This work focuses on a fast procedure for hazard zoning within the flood-prone areas at a meso-scale. To this end, a semiprobabilistic GIS-based methodology for hazard zoning of the potentially flood-prone areas is presented. The main output consists of GIS-compatible maps for the hazard zoning (by flood height) of the potentially flood-prone areas. A flood heightdependent extension of the topographic wetness index (TWI) threshold is proposed as the lower-limit TWI for zones with flood height larger than a prescribed value. This procedure relies on calibrating the flood height-dependent topographic wetness index (TWI) threshold through maximum likelihood estimation and based on the inundation profiles calculated at micro-scale level for a given spatial window. This calibration is performed for different values of flood depth in order to investigate the correlation between the TWI threshold and the flood depth conditioned on return period, through simple linear regression. The resulting regression model is used in order to up-scale the results from the micro-scale spatial window to the meso-scale level. As a demonstration, the procedure has been applied for the city of Addis Ababa, Ethiopia.