Probabilistic Analysis of the Retention Time in Stormwater Detention Facilities

AbstractStormwater detention facilities are often used in modern drainage systems to reduce the hydraulic load on existing sewers, due to the increase of impermeable surfaces and to the more frequent extreme rainfalls, consequence of climate changes. Although their design is mainly aimed to limit uncontrolled spills into receiving water bodies, storage capacity for water quality enhancement is often considered, mainly with the purpose of increasing the retention time. Standard analysis is usually based on empirical methods or on continuous simulations. This paper focuses on the probabilistic analysis of retention times aimed to provide guidance to engineers for the design of stormwater detention facilities. In particular, the influence on retention time of the possibility of water mixing from consecutive rainfall events, due to the pre-filling of the storage capacity from previous runoffs has been investigated. Derived expression has been tested by their application to a case study

The role of urban trees in water cycle restoration

Urban development leads to an increment of impervious cover that drastically reduces infiltration rates and increases the risk of stormwater floods, also reinforced by the rise of extreme events due to climate change. In this context, urban trees represent a valid system for sustainable stormwater management. They decrease the runoff discharged in the sewer network and/or in the receiving water bodies. Trees impact the hydrological cycle through the processes of interception, evapotranspiration and infiltration strictly depending on several factors such as tree features, soils properties, climate, and storm event characteristics. The objective of the study is to propose an analytical-probabilistic approach to model the contribution of urban trees to the restoration of the water cycle, with particular focus on the evapotranspiration component

Probabilistic design of multi-use rainwater tanks

AbstractMany studies have revealed that traditional approaches in urban stormwater drainage may sometimes be insufficient to manage properly the unbalance of water cycle due to urbanization. In response to these increasing concerns, many cities have encouraged the applications of local disposal of rainwater. In particular multi-use rainwater tanks, combine the advantages of infiltration basins and tanks for rainwater use.This paper proposes a procedure for their design based on an analytical probabilistic approach. Finally, an application to a case study is presented

Permeable Asphalt Hydraulic Conductivity and Particulate Matter Separation With XRT

Permeable asphalt (PA) is a composite material with an open graded mix design that provides a pore structure facilitating stormwater infiltration. PA is often constructed as a wearing course for permeable pavements and on impervious pavements to reduce aquaplaning and noise. The pore structure of PA functions as a filter promoting particulate matter (PM) separation. The infiltrating flow characteristics are predominately dependent on pore diameter and pore interconnectivity. X-Ray microTomography (XRT) has successfully estimated these parameters that are otherwise difficult to obtain through conventional gravimetric methods. Pore structure parameters allow modeling of hydraulic conductivity (k) and filtration mechanisms; required to examine the material behavior for infiltration and PM separation. In this study, pore structure parameters were determined through XTR for three PA mixture designs. Additionally, the Kozeny-Kovav model was implemented to estimate k. PM separation was evaluated using a pore-to-PM diameter categorical model. This filtration mechanism model was validated with data from a rainfall simulator. The filtration model provided a good correlation between measured and modeled data. The identification of filtration mechanisms and k facilitate the design and evaluation of permeable pavement systems as a best management practice (BMP) for runoff volume and peak flow as well as PM and PM-partitioned chemical separation

KDE-Based Rainfall Event Separation and Characterization

Rainfall event separation is mainly based on the selection of the minimum inter-event time (MIET). The traditional approach to determining a suitable MIET for estimating the probability den sity functions is often using the frequency histograms. However, this approach cannot avoid arbi trariness and subjectivity in selecting the histogram parameters. To overcome the above limitations, this study proposes a kernel density estimation (KDE) approach for rainfall event separation and characterization at any specific site where the exponential distributions are suitable for characterizing the rainfall event statistics. Using the standardized procedure provided taking into account the Poisson and Kolmogorov–Smirnov (K-S) statistical tests, the optimal pair of the MIET and rainfall event volume threshold can be determined. Two climatically different cities, Hangzhou and Jinan of China, applying the proposed approach are selected for demonstration purposes. The results show that the optimal MIETs determined are 12 h for Hangzhou and 10 h for Jinan while the optimal event volume threshold values are 3 mm for both Hangzhou and Jinan. The KDE-based approach can facilitate the rainfall statistical representation of the analytical probabilistic models of urban drainage/stormwater control facilitie