Evaluating the Effect of DEM and Boundary Condition Data for Hydrodynamic Flood Modeling in a Data Scarce Area Akaki Catchment

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Addis Ababa University


Accurate flood inundations mapping is challenged by data availability for model calibration and validation. In this regard, evaluating the effect of input data for improving flood inundation mapping is necessary. In this study, a high-resolution digital elevation model (DEM) of 5m × 5m was obtained from the Ethiopia Geospatial information institute. However, the high-resolution DEM (5m) was found to have some limitations in capturing the river channel geometry of Akaki. As a result, field-measured (fifteen cross-sections) data was merged with DEM to improve the accuracy of the DEM. To fill the gap of boundary condition data, water depths of a flood event were measured at upstream (for simulating the model) and middle (for evaluated simulated water levels) parts of the model domain. For the tributary river, a stage hydrograph was developed based on community consultation and channel characteristics. HEC-RAS was used in this study to perform one-dimensional (1D) flood modeling of the Akaki floodplain and HEC-GeoRAS 10.4 was used for the processing of geospatial data and analysis of water surface profile results. The limitation of the DEM to capture the channel geometry was significantly improved by using field-collected cross-sections. The type of downstream boundary condition is found significant error source in modeling the flood of Akaki. Error statistics for model simulations show that the mean absolute error of water level is 1.65m when using the uncorrected DEM as model input. However, this was reduced by half as a result of correcting the DEM. The model results show that the two tributaries have a large contribution to the flood inundation of the study area. Overall, this study demonstrates how input data source and associated errors significantly affect the accuracy of flood characteristics that are simulated by a hydrodynamic flood model. As a result, researchers and concerned institutions should develop strategies to develop data gaps for enhanced understanding of flood hazard in the Akaki catchment.



Flood Hazard, Flood Inundation, Flood Model, Uncertainty, HEC RAS, DEM, Akaki Catchment, Addis Ababa