Flood modeling of a large transboundary river using WRF-Hydro and microwave remote sensing

Abstract

The Brahmaputra River, a trans-boundary river between India and Bangladesh experiences large scale floods with frequent inundation events affecting millions of people annually. An integrated approach for quantitative understanding of flood wave characteristics and real time flood modeling framework can be helpful for effective decision making and planning of flood risk management strategies. In this study, we have characterized the flood wave propagation in the Brahmaputra River using gauge observations and model simulations. The spatio-temporal variation of flood lift is estimated using stage hydrograph of different gauge stations along the river. The temporal variation in flood hydrograph is characterized by different flood wave parameters for a gauge station which govern the flood condition in the Brahmaputra River. These flood wave characteristics are used in the categorization of different intensity of flood events. To estimate the river discharge, the WRF-Hydro model was set-up over the Brahmaputra river basin for hourly discharge estimation. The satellite observations form altimeter and Synthetic Aperture Radar (SAR) are used to estimate river flood-plain elevation and inundation. Altimetry data from Jason-3 satellite was used for water level retrieval and compared with gauge and simulated discharge time-series for further validation of model capabilities. Sentinel-1 satellite SAR images are used to assess the flood inundation extent and probability based on flood wave characteristics in the downstream flood-plain region of Guwahati. Finally, we have integrated these data-sets for a flood modeling and forecasting framework for a braided transboundary river system. This integrated system is studied in detail for an extreme event that occurred during July 2019 in the Brahmaputra River. An hourly estimate of each event for the flood period proved the capability of this system for operational deployment in near real-time flood assessment and forecasting purposes for the flood-prone region of South Asia. © 2021 Elsevier B.V.