Abstract
Most flood inundation models do not come with an uncertainty analysis component chiefly because of the complexity associated with model calibration. Additionally, the fact that the models are both data- and compute-intensive, and since uncertainty results from multiple sources, adds another layer of complexity for model use. In the present study, flood inundation modeling was performed in the Godavari River Basin using the Hydrologic Engineering Center—River Analysis System 2D (HEC-RAS 2D) model. The model simulations were generated for six different scenarios that resulted from combinations of different geometric, hydraulic and hydrologic conditions. Thus, the resulted simulations account for multiple sources of uncertainty. The SRTM-30 m and MERIT-90 m Digital elevation Model (DEM), two sets of Manning’s roughness coefficient (Manning’s n) and observed and estimated boundary conditions, were used to reflect geometric, hydraulic and hydrologic uncertainties, respectively. The HEC-RAS 2D model ran in an unsteady state mode for the abovementioned six scenarios for the selected three flood events that were observed in three different years, i.e., 1986, 2005 and 2015. The water surface elevation (H) was compared in all scenarios as well as with the observed values at selected locations. In addition, ‘H’ values were analyzed for two different structures of the computational model. The average correlation coefficient (r) between the observed and simulated H values is greater than 0.85, and the highest r, i.e., 0.95, was observed for the combination of MERIT-90 m DEM and optimized (obtained via trial and error) Manning’s n. The analysis shows uncertainty in the river geometry information, and the results highlight the varying role of geometric, hydraulic and hydrologic conditions in the water surface elevation estimates. In addition to the role of the abovementioned, the study recommends a systematic model calibration and river junction modeling to understand the hydrodynamics upstream and downstream of the junction.
Highlights
Flooding is one of the natural hazards that is observed globally; flood events have different aspects and generating mechanisms, and localized geomorphological processes such as erosion and sediment deposition along the river play a key role in flood inundation, and flood impacts [1]
The research presented in this paper aims to provide insights on the uncertainty in the model output from six scenarios, which are formed with Shuttle Radar Topographic Mission (SRTM)—30 m-and Multi Error Removed Improved Terrain (MERIT)—90 m digital elevation models (DEMs), initial and optimized Manning’s n values and observed and estimated flow boundary conditions
The MERIT-90 m and SRTM-30 m DEMs are used to extract elevations, which are used in developing the 2D geometry for the study area
Summary
Flooding is one of the natural hazards that is observed globally; flood events have different aspects and generating mechanisms, and localized geomorphological processes such as erosion and sediment deposition along the river play a key role in flood inundation, and flood impacts [1]. With the advent of efficient numerical methods in combination with high-performance computing resources in recent times, flood inundation models have made a significant leap in their modeling capabilities, including their capability for producing reliable and accurate estimates of various flow aspects [3]. Knowing that uncertainties in model estimates are unavoidable [10,11,12], and the increased perception about uncertainty and ensemble forecasts [13,14], in combination with enhanced activity in the recent decade in both the research and operational hydrologic realm [15,16,17,18,19], makes it clear that the uncertainty concept should be adopted in flood inundation modeling
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