How fitting are open-source flood models in capturing flood risks over mountainous regions: A prudent analysis over Chamkar Chu Basin, Bhutan using HEC-RAS v6.3

Abstract

On a global scale, the frequency and magnitude of flooding are getting worse. Although hydrologists around the globe have developed sophisticated flood models, their performance, especially over mountainous regions, is not comprehensively understood. The situation is challenging for flood-affected low-income nations, as sufficient resources are needed to procure commercial flood models with appropriate technical know-how. For instance, Bhutan, a mountain-dominated landscape in Asia, has been experiencing unprecedented flooding due to its fragile topography and climate change impacts. Unfortunately, a comprehensive data-driven modeling approach to determining flood hazard zones is missing in this region. The present study quantifies flood risks while considering a robust hydrodynamic flood model over Bhutan’s Chamkhar Chu River basin, a severely flood-prone area. The recently released open-source HEC-RAS v6.3 by the U.S. Army corps of Engineers, whose efficacy for flood inundation modeling is less explored, is considered to derive a set of flood risk maps. The coupled 1D-2D flood model setup is developed to simulate various flooding scenarios corresponding to design discharge and rainfalls for 50-yr, 100-yr, and 200-yrs. A corrected high-resolution Digital Elevation Model (DEM) from the ALOS-PALSAR product was utilized to reduce uncertainties in the final flood risk values. The simulated flood hazard maps for the settlements along the Chamkhar chu river are quantified in terms of flood depth, velocity, and a product of depth and velocity. A set of performance statistics are derived from testing the model performance while comparing the simulated inundation maps with the past inundation maps from MODIS satellite imagery. It was noticed that a significant portion of the central region is at a potential threat of very high flood risk as the simulated depth exceeds 3 m and velocities surpassing over 1.6 m/s. Such research will assist flood management agencies in prioritizing affordable structural and non-structural flood mitigation measures for the public that will reduce the impact of flood hazards in the future. Given the efficient computational performance of HEC-RAS v6.3 over a sensitive terrain, the study encourages the adoption of the model for accurately identifying flood risks over global mountainous regions for effective flood management.