Rainwater harvesting is an ancient practice currently used for flood and drought risk mitigation. It is a well-known solution with different levels of advanced technology associated with it. This study is aimed at reviewing the state of the art with regards to rainwater harvesting, treatment, and management. It focuses on the environmental and social benefits of rainwater harvesting and links them to the Sustainable Development Goals. The review identifies characteristics of laws and regulations that encourage this practice and their current limitations. It presents methodologies to design a rainwater harvesting system, describes the influence of design variables, and the impact of temporal and spatial scales on the system’s performance. The manuscript also analyzes the most advanced technologies for rainwater treatment, providing insights into various processes by discussing diverse physiochemical and biological technology options that are in the early stages of development. Finally, it introduces trends and perspectives which serve to increase rainwater harvesting, water reuse, and effective management.

Green roofs can be an effective tool for sustainable urban drainage, since they reduce and retain runoff by delaying its peak. Most studies analysing the retention capacity of green roofs are usually referred to a specific place and roof condition and do not consider the possibility that the roof could be partially pre-filled from previous rainfalls at the beginning of the given event. The aim of this paper is to develop an analytical probabilistic approach to evaluate green roof performance for stormwater control in terms of runoff that could be applied for different sites and climate conditions. To this end, the possibility that the green roof retention capacity could not be completely available owing to pre-filling from previous rainfall events has been considered and equations for an optimum green roof design, relating the runoff average return interval to the water retention capacity, have been proposed. The influence of parameters affecting the runoff process has been examined in depth and a case study to test the goodness of fit of the resulting equations has been developed.

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 density functions is often using the frequency histograms. However, this approach cannot avoid arbitrariness 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 facilities.

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.

Flood control detention facilities are widely used for stormwater control in urban areas. Standard design procedures are in most cases based on the design storm approach: a single flood event at a time is considered, at the beginning of which the facility is assumed completely empty. The possibility of pre-filling from previous events is then neglected and underestimation of storage volume may occur. In this paper an analytical probabilistic approach to estimate the probability of pre-filling is presented and its effects, due to outflow rate and storage volume, are investigated. Two different strategies for the outlet control are analysed. Results are validated on a case study.

Encouraging the implementation of non-conventional water resources (NCWR) is a fundamental strategy to face the future challenges due to urban population growth and resource scarcity. The implementation of a systematic process of Cost Benefit Analysis (CBA) offers reliable economic indicators to support decision makers in taking actions shifting towards NCWR. While infrastructure costs are directly estimated, while the benefits depend upon the considered stakeholders and require a tough estimation of the achieved ecosystem services. This research provides a framework for CBA analysis adopting NCWR at municipal level. The framework has been then applied to two case studies in Milan focused on the exploitation of shallow groundwater, where the obtained economic indicators has stressed out the importance of considering a complete benefits analysis that could support incentive policies on shifting part of the financial benefits to direct users leading to benefits for the whole community.