Articles | Volume 373
https://doi.org/10.5194/piahs-373-137-2016
https://doi.org/10.5194/piahs-373-137-2016
12 May 2016
 | 12 May 2016

Hydrological and hydraulic models for determination of flood-prone and flood inundation areas

Hafzullah Aksoy, Veysel Sadan Ozgur Kirca, Halil Ibrahim Burgan, and Dorukhan Kellecioglu

Abstract. Geographic Information Systems (GIS) are widely used in most studies on water resources. Especially, when the topography and geomorphology of study area are considered, GIS can ease the work load. Detailed data should be used in this kind of studies. Because of, either the complication of the models or the requirement of highly detailed data, model outputs can be obtained fast only with a good optimization. The aim in this study, firstly, is to determine flood-prone areas in a watershed by using a hydrological model considering two wetness indexes; the topographical wetness index, and the SAGA (System for Automated Geoscientific Analyses) wetness index. The wetness indexes were obtained in the Quantum GIS (QGIS) software by using the Digital Elevation Model of the study area. Flood-prone areas are determined by considering the wetness index maps of the watershed. As the second stage of this study, a hydraulic model, HEC-RAS, was executed to determine flood inundation areas under different return period-flood events. River network cross-sections required for this study were derived from highly detailed digital elevation models by QGIS. Also river hydraulic parameters were used in the hydraulic model. Modelling technology used in this study is made of freely available open source softwares. Based on case studies performed on watersheds in Turkey, it is concluded that results of such studies can be used for taking precaution measures against life and monetary losses due to floods in urban areas particularly.

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Short summary
The proposed methodology is easy to use and inexpensive (a free software with minimum amount of data requirement); yet it is very effective in terms of pinpointing the flood-prone locations in urban areas particularly. Expectation is that it provides simple modelling concepts to be help of decision makers in preventing life and monetary losses due to floods. The study is based on an EU project aiming at using simple tools for applicable results.