Contribution of public squares to the reduction of urban flooding risk

Abstract

Urbanization is directly linked to the process of impermeabilization of the soil in urban areas that contributes to the emergence of flood risks. The purpose of this study was to determine the hydrodynamic properties of the public squares in a flood-prone Brazilian city and determine to what extent they could contribute to the reduction of flooding. The Beerkan method was used to determine the hydrodynamic properties of the soil in nine squares located at critical flooding points in the city of Recife. This method uses simple ring infiltration and the collection of soil samples to obtain the soil granulometric distribution, thereby generating the soil water retention curve θ(h) and the hydraulic conductivity K(θ). The squares studied have similar hydrodynamic characteristics because of their similar soil texture classes, such as Loamy Sand and Sandy Loam. This made it possible for eight of the nine squares studied to be able to contribute positively to the reduction of flood risks by adapting them into micro infiltration basins that can receive the surface flows that overload the drainage network.

Mathematical modeling of the infiltration in a permeable pavement on the field scale

“…The Ks values estimated by the BEST Intercept were also higher than the values of Ks estimated by BEST Slope for Sand soil. These results for Loamy Sand and Sandy Loam are in accordance with several studies in the literature (Souza et al, 2008;Di Prima et al, 2017;Sousa et al, 2019;Lassabatère et al, 2019). The Sorptivity values estimated by BEST slope and intercept were similar, with BEST slope values slightly higher.…”

Estimation of the Hydrodynamic Parameters of Soils Subjected to Water Scarcity: Application of BEST and Introduction of a Specific Methodology

“…It was demonstrated that the BEST-intercept which contains the modifications proposed by [8] presented better results than the BEST method which was originally proposed by [10]. According to [11], the K s values estimated by BESTintercept and BEST-slope are different. Regarding Sandy Loam and Loamy Sand soils, BEST-intercept estimates were higher than BEST-Slope's.…”