Floods are the most impactful natural disasters on earth, and reliable flood warning systems are critical for disaster preparation, mitigation, and response. The GEOGloWS ECMWF Streamflow Services (GESS) provide forecasted streamflow throughout the world. While forecasted discharge is essential to flood warning, forecasted inundation extents are required to understand and predict flood impact. In this research, I sought to expand GESS flood warning potential by generating inundation extents from streamflow forecasts. I compared Height Above Nearest Drainage (HAND), a method beneficial for flood mapping on a watershed scale, to a 2D hydrodynamic model, specifically Sedimentation and River Hydraulics â€“ Two Dimension (SRH-2D), a method localized to specific areas of high importance. In three study areas in the Amazon basin, I validated HAND and SRH-2D flood maps against water maps derived from satellite SAR imagery. Specifically, I analyzed what features of an SRH-2D model were required to generate more accurate flood extents than HAND. I also analyzed the practicality of using SRH-2D for forecasting by comparing flood extents generated from simulating a complete forecast hydrograph to flood extents precomputed at predetermined, incremental flowrates. The SRH-2D models outperformed HAND, but their accuracy decreased at flowrates different than those used for calibration, limiting their reliability for forecasting and impact analysis. Based on this study, the key features necessary for a reliable SRH-2D model for forecasting include (1) a high-resolution DEM for an accurate representation of the floodplain, (2) correct representation of channel flow control, and (3) a channel bathymetry approximation and exit boundary rating curve that correctly predict water levels at a range of input flowrates. For forecasting practicality, the precomputed flood extents had accuracies comparable to the complete hydrograph simulations, showing their potential for estimating forecasted inundation extents. Future research should include (1) a more comprehensive analysis using existing SRH-2D models in areas with more bathymetry information and calibration data, (2) further assessment of the reliability of precomputed flood maps for forecasting applications, and (3) quantifying the effect of error in the streamflow forecasts on the accuracy of the resulting flood extents.
College and Department
Ira A. Fulton College of Engineering and Technology; Civil and Environmental Engineering
BYU ScholarsArchive Citation
Edwards, Christopher Hyde, "Forecasting Inundation Extents in the Amazon Basin Using SRH-2D and HAND Based on the GEOGloWS ECMWF Streamflow Services" (2021). Theses and Dissertations. 9255.
flood forecasting, flood mapping, SRH-2D, HAND, SAR, GEOGloWS, SMS