Evaluating the effectiveness of catchment-scale approaches in mitigating urban surface water flooding

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Abstract

The argument for natural flood management in the UK has strengthened in recent years with increasing awareness of the potential benefits gained from upstream interventions (especially improvements in water quality, public amenities and biodiversity). This study aims to develop an understanding of another potential benefit—interventions promoting free discharge at downstream urban drainage outfalls by moderating water levels in receiving watercourses. A novel, coupled model (linking dynamic TOPMODEL, HEC-RAS and Infoworks ICM) is calibrated for the Asker catchment in Dorset, England. This predominantly rural watershed drains to the town of Bridport, frequently submerging a surface drainage outfall in a nearby housing estate. Two forms of upstream, catchment-scale intervention (hillslope tree planting and in-channel large woody debris) are modelled to understand their impacts on the functioning of the drainage network during both the calibration period and a range of design storms. The results indicate that interventions have the greatest positive impact during frequent events. For example, during a storm with a 10% annual exceedance probability (AEP), upstream NFM could reduce outfall inundation by up to 3.75 h and remove any surcharging of flow within the drainage system in Bridport. In more severe storms, the results suggest interventions could slightly prolong the time the outfall was submerged. However, by slowing the wider catchment’s response during the 3.3% AEP storm, upstream interventions allow more water to escape the urban drainage system and reduce the maximum surface flooding extent within the housing estate by 35%. This article is part of the theme issue ‘Urban flood resilience’.

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Ferguson, C., & Fenner, R. (2020). Evaluating the effectiveness of catchment-scale approaches in mitigating urban surface water flooding. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 378(2168). https://doi.org/10.1098/rsta.2019.0203

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