Abstract: The development of adaptation and mitigation strategies to tackle anthropic and climate changes impacts is becoming a priority in drought-prone areas. This study examines the capabilities of indigenous rainwater harvesting techniques (RWHT) to be used as a viable solution for flood mitigation. The study analyses the hydraulic performance of the most used micro-catchment RWHT in sub-Saharan regions, in terms of flow peak reduction (FPR) and volume reduction (VR) at the field and basin scale. Parametrized hyetographs were built to replicate the extreme precipitations that strike Sahelian countries during rainy seasons. 2D hydrodynamic simulations showed that half-moons placed with a staggered configuration (S-HM) have the best performances in reducing runoff. At the field scale, S-HM showed a remarkable FPR of 77% and a VR of 70% in case of extreme rainfall. Instead at the basin scale, in which only 5% of the surface was treated, 13% and 8% respectively for FPR and VR were obtained. In addition, the reduction of the runoff coefficient (Rc) between the different configuration was analyzed. The study critically evaluates hydraulic performances of the different techniques and shows how pitting practices cannot guarantee high performance in case of extreme precipitations. These results will enrich the knowledge of the hydraulic behavior of RWHT; aspect marginally investigated in the scientific literature. Moreover, this study presents the first scientific application of HEC-RAS as a rainfall-runoff model. Despite some limitations, this model has the effective feature of using very high-resolution topography as input for hydraulic simulations. The results presented in this study should encourage stakeholders to upscale the use of RWHT in order to lessen the flood hazard and land degradation that oppresses arid and semi-arid areas.

Abstract: Real-Time Control (RTC) technology is increasingly applied in Rainwater Harvesting (RWH) systems to optimise their performance related to water supply and flood mitigation. However, most studies to date have focussed on testing the benefits at an individual site scale, leaving the potential benefits for downstream stormwater networks largely untested. In this study, we developed a methodology to predict how at-source RTC RWH systems influence the behaviour of a stormwater network. Simulation was enabled by coupling the drainage model in SWMM with an RTC RWH model coded using the R software. We modelled two different RTC strategies across a range of system settings (e.g. storage size for RWH and proportion of storage to which RTC is applied) under two different climate scenarios—current and future climates. The simulations showed that RTC reduced flooding volume and peak flow of the stormwater network, leading to a potential mitigation of urban flooding risks, while also providing a decentralised supplementary water supply. Implementing RTC in more of RWH storages yielded greater benefits than simply increasing storage capacity, in both current and future climates. More importantly, the RTC systems are capable of more precisely managing the resultant flow regime in reducing the erosion and restoring the pre-development conditions in sensitive receiving waters. Our study suggests that RTC RWH storages distributed throughout a catchment can substantially improve the performance of existing drainage systems, potentially avoiding or deferring expensive network upgrades. Investments in real-time control technology would appear to be more promising than investments in detention volume alone.

Abstract: Mitigation of localized pluvial flooding is one of the major resiliency goals in urban environments, and Green Stormwater Infrastructure (GSI) has the potential to deliver such an outcome. However, there is a lack of systematic approaches to prioritize investment in different candidate areas. This study provides a framework to identify vulnerable stormwater drainage inlets and their contributing areas, prioritize them, identify dominant factors in their selection, assess the potential of GSI in mitigating their overflows, and compare the impact and its cost to gray infrastructure upgrade alternatives. Using SWMM 5.1.013, decision trees, and a volumetric-based assessment of GSI overflow capture, we applied the framework to the City of Dallas, Texas, for three design storms with three GSI practices— bioretention cells, raingardens, and rainwater harvesting tanks. Results showed that there was a significant increase in the number of overflowing stormwater drainage inlets, referred to as hotspots, and their contributing subwatersheds, referred to as opportunity areas, with more intense storms especially in problematic watersheds. Also, prioritization results provided a series of maps to rank the opportunity areas based on overflow severity, recurrence of the overflows, and GSI availability. Moreover, classification results showed that inlet features, especially the inlet depth, were the dominant factors in the identification of the non-problematic inlets. Finally, the GSI impact assessment showed substantial overflow mitigation even at the “very high” severity levels when GSI is comprehensively deployed across opportunity areas. Despite gray infrastructure upgrades yielding higher reduction levels, their cost per cubic meter was higher than GSI. Therefore, a combination of GSI and gray results in maximum overflow reduction at a lower cost compared to common practices.