A probabilistic approach to stormwater runoff control through permeable pavements beneath urban trees.

Sci Total Environ

Department of Civil and Environmental Engineering, Politecnico di Milano, P.zza L. da Vinci 32, 20133 Milano, Italy. Electronic address:

Published: December 2023

One of the most current and urgent challenges is making cities sustainable and resilient to climate change. From this perspective, Nature-Based Solutions (NBSs) are well-recognized strategies for stormwater control and water cycle restoration. Urban trees are an example of NBS. However, the high degree of soil sealing typically found in urban environments limits natural processes such as infiltration and hinders the water and nutrient supply for proper root development, which weakens tree stability. Permeable pavements at the base of urban trees, on the one hand, facilitate infiltration, which helps runoff control, and on the other hand, improve stormwater retention and soil humidity, which enhance root feeding. This paper proposes an analytical-probabilistic approach to estimate the contribution of permeable pavements to stormwater management. The equations developed in this study relate the runoff probability to the storage volume, the infiltration rate into the underlying soil, and the average values of the hydrological variables in the input. The model allows us to select different runoff thresholds and considers the possibility that residual volume from previous rainfall events prefills the storage capacity. An application to a case study in Sao Paulo (Brazil) has been presented. It investigates the influence of the different parameters used in the model on the results. The comparison of the outcomes obtained using the developed equations with those obtained from the continuous simulation of measured data confirmed the effectiveness of the proposed analytical-probabilistic approach and the suitability of using permeable pavements at the base of urban trees for improving stormwater retention.

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Source
http://dx.doi.org/10.1016/j.scitotenv.2023.167196DOI Listing

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