A Flood Forecasting Framework Coupling a High Resolution WRF Ensemble With an Urban Hydrologic Model

Abstract

Numerical weather prediction (NWP) models such as the Weather Research and Forecasting (WRF) model are increasingly used over the Indian region to forecast extreme rainfall events. However, studies which explore the application of high-resolution rainfall simulations obtained from the WRF model in urban hydrology are limited. In this paper, the utility of a model coupling framework to predict urban floods is explored through the case study of Bangalore city in India. This framework is used to simulate multiple extreme events that occurred over the city for the monsoons of years 2020 and 2021. To address the uncertainty from the WRF model, a 12-member convection permitting ensemble is used. Model configurations using Kain Fritsch and WSM6 parameterization schemes could simulate the spatial and temporal pattern of the selected event. The city is easily flooded with rainfall events above a threshold of 60 mm/day and to capture the response of the urban catchment, the Personal Computer Storm Water Management Model (PCSWMM) is used in this study. Flood forecasts are created using the outputs from the WRF ensemble and the Global Forecasting System (GFS). The high temporal and spatial resolution of the rainfall forecasts (<4 km at 15-min intervals), has proved critical in reproducing the urban flood event. The flood forecasts created using the WRF ensemble indicate that flooding and water levels are comparable to the observed whereas the GFS underestimates these to a large extent. Thus, the coupled WRF–PCSWMM modelling framework is found effective in forecasting flood events over an Indian city.