Application of ArcGIS Model Builder and Python Scripting for urban Flood Modeling

Abstract

Accurate projection of flood extents in urban catchments has become a challenging task. Accurate data on inundation is useful for identifying flood risk areas and developing flood management strategies to mitigate the negative consequences. Owing to high costs of sophisticated flood simulation modeling software, currently, the required flood data for different studies and projects in Sri Lanka is collected through gauging stations, GPS devices and participatory based mapping approaches. However, these methods are highly time consuming and limited in accuracy. Hence, this paper presents an integrated model that simulates flood prone areas, flood levels and flood water accumulation time in urban areas using ArcGIS model builder and Python scripting. The model was calibrated and validated considering part of the urbanized area beside Kelani River. The results indicated that there is a high level of consistency between the observed and simulated results. Accordingly, the model presented in this paper can be used to simulate the flood inundation information in urban areas in a relatively fast, inexpensive and accurate manner