Estimating Flood Characteristics Using Geomorphologic Flood Index with Regards to Rainfall Intensity-Duration-Frequency-Area Curves and CADDIES-2D Model in Three Iranian Basins

Farid Faridani,Rosa Lasaponara,Alireza Faridhosseini,Raziyeh Farmani,Sirus Bakhtiari,Micheal J Gibson

doi:10.3390/su12187371

Abstract

There is not enough data and computational power for conventional flood mapping methods in many parts of the world, thus fast and low-data-demanding methods are very useful in facing the disaster. This paper presents an innovative procedure for estimating flood extent and depth using only DEM SRTM 30 m and the Geomorphic Flood Index (GFI). The Geomorphologic Flood Assessment (GFA) tool which is the corresponding application of the GFI in QGIS is implemented to achieved the results in three basins in Iran. Moreover, the novel concept of Intensity-Duration-Frequency-Area (IDFA) curves is introduced to modify the GFI model by imposing a constraint on the maximum hydrologically contributing area of a basin. The GFA model implements the linear binary classification algorithm to classify a watershed into flooded and non-flooded areas using an optimized GFI threshold that minimizes the errors with a standard flood map of a small region in the study area. The standard hydraulic model envisaged for this study is the Cellular Automata Dual-DraInagE Simulation (CADDIES) 2D model which employs simple transition rules and a weight-based system rather than complex shallow water equations allowing fast flood modelling for large-scale problems. The results revealed that the floodplains generated by the GFI has a good agreement with the standard maps, especially in the fluvial rivers. However, the performance of the GFI decreases in the less steep and alluvial rivers. With some overestimation, the GFI model is also able to capture the general trend of water depth variations in comparison with the CADDIES-2D flood depth map. The modifications made in the GFI model, to confine the maximum precipitable area through implementing the IDFAs, improved the classification of flooded area and estimation of water depth in all study areas. Finally, the calibrated GFI thresholds were used to achieve the complete 100-year floodplain maps of the study areas.

Highlights

Floods are among the most disastrous events in the world and problems associated with them have increased greatly [1]
Some studies in recent years focused on developing simple 2D flood models using cellular automata (CA), which offers a method for modelling complicated physical systems using simple operations
Manfreda et al [28] demonstrated that parameter “ a ” in Equation (2) does not affect the calibration results of flood prone areas and suggested that Geomorphic Flood Index (GFI) can estimate the maximum inundation depth by assuming a surrogate GFI (GFI’): GFI = GFI − ln(a = ln H = ln h

Summary

Introduction

Floods are among the most disastrous events in the world and problems associated with them have increased greatly [1]. Samela et al [22] developed the Geomorphologic Flood Assessment (GFA) tool in QGIS software (version 3.14) which delineates the river extents based on the GFI method, DEM, and the standard flood risk map of a basin.

Results

Conclusion