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.

Abstract: Leaky dams are an increasingly popular natural flood management measure, yet their impacts on flood peak magnitude have not yet been empirically quantified for a range of event types and magnitudes, even at the stream scale. In this study, the novel application of a transfer function noise modelling approach to empirical Before-After-Control-Impact stage data from an upland catchment allowed leaky dam effectiveness in reducing flood peak magnitude to be quantified. Flood peak stage and discharge magnitude changes were assessed from empirical data for 50 single and multi-peaked high flow events with return periods ranging from less than one year to six years. Overall, event peak magnitude was significantly reduced following the installation of eight leaky dams on the impact stream. Effectiveness was highly variable, but on average, flood peak magnitude was reduced by 10% for events with a return period up to one year. Some of the variability was explained by the size of the event and whether it was a single or multi-peaked event. This finding emphasises the need to manage expectations by considering both a range of event magnitudes and types when designing or assessing leaky dam natural flood management schemes.

Abstract: In urban environments there is a severe reduction of infiltration and groundwater recharge due to the existence of large impervious areas. During rain events, large volumes of water that could have recharged groundwater and surface water bodies are diverted into the municipal drainage system and lost from the freshwater storage. Moreover, extreme rain events impose high peak flows and large runoff volumes, which increase the risk of urban floods. Recent studies have suggested the use of rainwater harvesting for groundwater recharge, as a plausible solution for these challenges in dense urban environments. While the benefits of this approach are well understood, research on its practical, engineering, and hydrological aspects is relatively limited. The objective of the present study was to examine the use of infiltration wells for groundwater recharge with harvested rainwater collected from building rooftops under Mediterranean climate conditions. Two types of wells with similar hydraulic and technical properties were examined: a well that reaches the groundwater (wet well); and a well that discharges the harvested water into the unsaturated zone (dry well). Infiltration capacities of the wells were compared in controlled experiments conducted during summer months, and in operational recharge of harvested rainwater, during winter. Both dry and wet wells were found to be suitable for purposes of groundwater recharge with rooftop-harvested rainwater. Infiltration capacity of the wet well was about seven times greater than the infiltration capacity of the dry well. While the infiltration capacity of the wet well was constant throughout the entire length of the study (∼10 m3/h/m), the dry well infiltration capacity improved during winter (from 0.5 m3/h/m to 1.5 m3/h/m), a result of development of the dry well with time. Considering Tel-Aviv, Israel, as a case study for a dense modern city in a Mediterranean climate, it is demonstrated herein that the use of infiltration wells may reduce urban drainage by ∼40 %.

Abstract: Cities have experienced rapid urbanization-induced harsh climatic events, especially flooding, inevitably resulting in negative and irreversible consequences for urban resilience and endangering residents’ lives. Numerous studies have analyzed the effects of anthropogenic practices (land use changes and urbanization) on flood forecasting. However, non-structural mitigation’s effectiveness, like Nature-Based Solutions (NBS), has yet to receive adequate attention, particularly in the Middle East and North Africa (MENA) region, which have become increasingly significant and indispensable for operationalizing cities efficiently. Therefore, our study investigated the predictive influence of incorporating one of the most common NBS strategies called low-impact development tools (LID) (such as rain gardens, bio-retention cells, green roofs, infiltration trenches, permeable pavement, and vegetative swale) during the urban planning of Alexandria, Egypt, which experiences the harshest rainfall annually and includes various urban patterns. City characteristics-dependent 14 LID scenarios were simulated with recurrence intervals ranging from 2 to 100 years using the LID Treatment Train Tool (LID TTT), depending on calibrated data from 2015 to 2020, by the Nash-Sutcliffe efficiency index and deterministic coefficient, and root-mean-square error with values of 0.97, 0.91, and 0.31, respectively. Our findings confirmed the significant effectiveness of combined LID tools on total flood runoff volume reduction by 73.7%, revealing that different urban patterns can be used in flood-prone cities, provided LID tools are considered in city planning besides grey infrastructure to achieve optimal mitigation. These results, which combined multiple disciplines and were not explicitly mentioned in similar studies in developing countries, may assist municipalities’ policymakers in planning flood-resistant, sustainable cities.

Abstract: Floods are one of the most common natural disasters, resulting in the extensive destruction of infrastructure, property, and human life. The destructive potential of a flood depends on numerous factors, including the size of the flood, the rate of flooding, the time it takes for the water to move through a given area, the river’s planform and cross-section geometry, and other similar factors. The present study is a unique analysis of flood mapping that was accomplished with the help of the Analytical Hierarchy Process (AHP), Frequency Ratio (FR), and hydrogeomorphic response to floods by integrating geospatial analysis and unit stream power modeling. The Indus catchment region of Pakistan is where the subject topic is put into practice. According to the hydrologic analysis of the yearly peak discharge, the hydro-station in Gilgit-Baltistan can move boulders measuring up to 0.5 m in height during significant flooding. On the other hand, there will be no change to the geometry of the cross-section throughout 1980–2020 in Gilgit-Baltistan. The flood susceptibility map is constructed using data from twelve influencing parameters, including elevation, proximity to the drainage network, slope, drainage density, geomorphology, rainfall, the curvature of the topography, flow accumulation, geology, land use, Topographic Wetness Index (TWI), and Stream Power Index (SPI). The area under the curve (AUC) approach, which demonstrates a substantial degree of accuracy (85% and 83%), is utilized to evaluate the effectiveness of the AHP and FR. The current study fills the gaps between the geospatial approach and the hydrogeomorphic assessment of flood to determine flood susceptibility.