Abstract

Urban flood hazard model needs rainfall with high spatial and temporal resolutions for flood hazard analysis to better simulate flood dynamics in complex urban environments. However, in many developing countries, such high-quality data are scarce. Data that exist are also spatially biased toward airports and urban areas in general, where these locations may not represent flood-prone areas. One way to gain insight into the rainfall data and its spatial patterns is through numerical weather prediction models. As their performance improves, these might serve as alternative rainfall data sources for producing optimal design storms required for flood hazard modeling in data-scarce areas. To gain such insight, we developed Weather Research and Forecasting (WRF) design storms based on the spatial distribution of high-intensity rainfall events simulated at high spatial and temporal resolutions. Firstly, three known storm events (i.e., 25 June 2012, 13 April 2016, and 16 April 2016) that caused the flood hazard in the study area are simulated using the WRF model. Secondly, the potential gridcell events that are able to trigger the localized flood hazard in the catchment are selected and translated to the WRF design storm form using a quantile expression. Finally, three different WRF design storms per event are constructed: Lower, median, and upper quantiles. The results are compared with the design storms of 2- and 10-year return periods constructed based on the alternating-block method to evaluate differences from a flood hazard assessment point of view. The method is tested in the case of Kampala city, Uganda. The comparison of the design storms indicates that the WRF model design storms properties are in good agreement with the alternating-block design storms. Mainly, the differences between the produced flood characteristics (e.g., hydrographs and the number of flood gird cells) when using WRF lower quantiles (WRFLs) versus 2-year and WRF upper quantiles (WRFUs) versus 10-year alternating-block storms are very minimal. The calculated aggregated performance statistics (F scores) for the simulated flood extent of WRF design storms benchmarked with the alternating-block storms also produced a higher score of 0.9 for both WRF lower quantiles versus 2-year and WRF upper quantile versus 10-year alternating-block storm. The result suggested that the WRF design storms can be considered an added value for flood hazard assessment as they are closer to real systems causing rainfall. However, more research is needed on which area can be considered as a representative area in the catchment. The result has practical application for flood risk assessment, which is the core of integrated flood management.

Highlights

  • With the increasing effect of urbanization and climate change in recent times, urban floods are becoming more frequent and devastating (Hirabayashi et al 2013; Duan et al 2016)

  • In order to do this, we developed Weather Research and Forecasting (WRF) design storms based on the spatial distribution of high-intensity rainfall events simulated at high spatial and temporal resolutions

  • The potential gridcell events were selected and translated to the WRF design storm form using a quantile expression of the cumulative rainfall distribution

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Summary

Introduction

With the increasing effect of urbanization and climate change in recent times, urban floods are becoming more frequent and devastating (Hirabayashi et al 2013; Duan et al 2016). There is a growing effort at national, regional, and local levels focusing on urban flood hazard modeling as part of integrated flood management (IFM) to cope with urban floods (Sy et al 2016; Sy et al 2020; Pérez-Molina et al 2017). Strategies to cope with urban floods, such as adaptation and mitigation measures, require an urban flood hazard assessment, where a high-quality input dataset is essential for effective flood hazard modeling. Flood hazard is an analysis that combines hazard intensity with a return period or probability of occurrence. The return periods and associated rainfall values are based on annual maximum 24-h rainfall. It is important to take these established maximum rainfall values as a starting point so that the results of any alternative method can be clearly related to flood mitigation activities

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