Effects of rainfall spatial-temporal variability on flash flood modelling

Abstract

<p>Precipitation time series with high spatial and temporal resolutions are the driving force for hydrodynamic modelling of floods. Spatially-uniform precipitation correlated to a certain return period which typically is derived based on point rainfall records have been used for flood risk evaluation. This is mainly due to reasons such as limited observed data, low-density measuring networks or merely the inherent simplicity of using spatially-uniform rain storms in flood simulations. While the use of such rainfalls is convenient, spatially-uniform design storms tend to neglect the impact of rain spatial variability on the hydrological response of the hydrological catchment. Additionally, extreme storm events with high temporal and spatial variability are predicted to occur more often as a result of climate change.</p><p>In this work, we study the extent spatially explicit precipitation can affect flooded areas, water levels and surface flow generation in catchment areas in flood modelling. Moreover, the influence of rainfall spatial resolution is also taken into account. This is achieved by means of physically-based, spatially explicit surface flow simulations using the tool ProMaIDes (2021), a free software for risk-based evaluation of flood risk mitigation measures. Precipitation data is generated based on the Poisson distribution and furthermore spatially interpolated in different resolutions using interpolation methods such as the Inversed Distance Squared method and Kriging.</p><p>Our study area is the Kan river catchment located in the province of Tehran (Iran) with a total area of 836 km&#178;, which has experienced multiple flooding events in recent years. Due to its semi-arid climate and steep topography, the area has high potential for flash flood occurrence as a result of high intensity precipitation.</p><p>The results of this study show a range of possible magnitudes of influence of rainfall spatial variability on the catchment&#180;s runoff response. The resulting flood maps highlight the importance of rainfall spatial-temporal variability in the estimation of flood likelihood in urban catchment areas. Moreover, the flood maps resulting from spatially explicit rain signals provide a more comprehensive assessment of flooding in contrast to the spatially-uniform rainfall events, which allows for better flood risk mitigation decisions.</p><p>ProMaIDes (2021): Protection Measures against Inundation Decision support. https://tinyurl.com/promaides77 (last access 11.1.2021)</p><p>Acknowledgment: This work is part of the BMBF-IKARIM funded project HoWaMan (Sustainable Strategies and Technologies for Flood Risk Management in Arid and Semi-arid Areas)</p>