Assessment of Rainfall Forecasts and Flood Risk in a Coastal Urban Catchment Considering Different Urban Canopy Scenarios
ABSTRACT Climate change, urbanization, and anthropogenic activities have intensified rainfall and urban flooding, especially along coastlines. The high spatiotemporal variability and erratic pattern of rainfall highlight the incompetency of independent application of statistical forecasting techniqu...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-03-01
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| Series: | Journal of Flood Risk Management |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/jfr3.70028 |
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| Summary: | ABSTRACT Climate change, urbanization, and anthropogenic activities have intensified rainfall and urban flooding, especially along coastlines. The high spatiotemporal variability and erratic pattern of rainfall highlight the incompetency of independent application of statistical forecasting techniques, especially over the tropics, and demand the incorporation of physics‐based numerical weather prediction models along with urban feedback for improved forecasting. The current study utilizes a physics‐based numerical weather prediction model, Weather Research and Forecasting (WRF) model, for rainfall forecasting, provided as an input to a 2‐way coupled hydrodynamic flood modeling framework, considering streamflow, overland flow, and tidal impact. The influence of three urban canopy scenarios, i.e., not coupled, coupled with a single layer, and multiple layer urban canopy model, is assessed over rainfall, and subsequently the flood inundation and risk pattern, by utilizing this framework. Comparisons have been made between flood maps developed for three scenarios using WRF forecasted rainfall and maps developed using observed rainfall data. An investigation has been conducted into the extent to which the scenarios can replicate the observed pattern and extent of flooding for the comprehensive flood forecasting network. This study signifies that considering urban signatures with other meteorological parameters for rainfall forecasting is highly essential to improve the accuracy of flood risk forecasts. |
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| ISSN: | 1753-318X |