Low Impact Development Practices Research Articles

Optimal low-impact development Facility Design in Urban Environments: A multidimensional optimization approach employing slime mould and nondominated sorting genetic algorithms

This study presents the application of the slime mould algorithm (SMA) and the nondominated sorting genetic algorithm II (NSGA-II) to optimize low-impact development (LID) strategies in urban areas. The focus is on minimizing costs and improving water quality, using three LID practices (vegetated swales, bioretention systems, and porous pavements) in combination with a drainage system. The effectiveness of this stormwater management model (SWMM)-SMA-NSGA-II model is demonstrated in Tehran, Iran, where bioretention is found to be the most successful approach for improving water quality. The results also show that the SMA outperforms the NSGA-II in optimizing cost-effective LID solutions and is more computationally efficient, potentially due to its crossover operator. This research highlights the importance of considering qualitative aspects of urban runoff management. The study demonstrates that the combination of multiple LID strategies and the use of SMA and NSGA-II have the potential to achieve optimal solutions for managing stormwater in urban areas.

Application of multi-criteria decision-making on low-impact development practice selection for the Kinyerezi River sub-catchments in Dar es Salaam, Tanzania.

The impermeable areas in catchments are proportional to peak flows that result in floods in river reaches where the flow-carrying capacity is inadequate. The high rate of urbanization witnessed in the Kinyerezi River catchment in Dar es Salaam city has been noted to contribute to floods and siltation in the Msimbazi River. The Low-Impact Development (LID) practices that includes bio-retention (BR) ponds, rain barrels (RBs), green roofs (GRs), etc. can be utilized to mitigate portion of the surface runoff. This study aims to propose suitable LID practices and their sizes for mitigating runoff floods in the Kinyerezi River catchment using the Multi-Criteria Decision-Making (MCDM) approach. The results indicated that the BR and RBs were ranked high in capturing the surface runoff while the sediment control fences were observed to be the best in reducing sediments flowing into the BR. The proposed BR ponds were greater than 800 m2 with 1.2 m depth while RB sizes for Kinyerezi and Kisungu secondary schools and Kinyerezi and Kifuru primary schools were 2,730; 2,748; 1,385; and 1,020 m3, respectively. The BR ponds and RBs are capable of promoting water-demanding economic activities such as horticulture, gardening, car washing while reducing the school expenses and runoff generation.

Modeling the effect of land use change to design a suitable low impact development (LID) system to control surface water pollutants

Growth in urbanization has led to increased impervious surfaces, exacerbating flood risks and water quality degradation. This study investigated the impact of land use change and Low-Impact Development (LID) systems on urban runoff quality and quantity in the second region of Tehran. Pioneering an innovative approach, the integration of the Land Change Modeler (LCM) with the Stormwater Management Model (SWMM) signifies a paradigm shift in urban water management. Combined with other hydrological models, this new approach provides a comprehensive method for assessing the future effectiveness of LID practices. The Event Mean Concentration Method (EMC) was used in this study to measure Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), Total Phosphorus (TP), and Zinc (Zn) in urban runoff from five land uses. Results pinpointed transportation land uses as the primary source of pollutants. Using LCM, the study forecasted a surge in urban runoff pollutants by 2030, particularly in the Northwest area of the region due to anticipated land use shifts towards commercial and residential land uses. Model results showed an 11 % increase in TSS over a decade, highlighting the importance of land use change in runoff quality. The study used three types of LIDs to reduce contaminants in dense urban areas. Assessing the impact of LID scenarios on runoff pollutants using SWMM revealed that the bio-retention cell had the best performance, reducing TSS by 20.92 %, and the vegetative swale had the worst performance, reducing TSS by 8.43 %. The study also concluded that combining LIDs would be more effective than using them separately. The results of this study suggest that LID systems can be an effective way to reduce urban runoff pollutants and improve water quality in the second region of Tehran. However, more research is needed to optimize the design and placement of LID systems in different urban areas.

Efficiency evaluation of low impact development practices on urban flood risk

Urban flood risk assessment delivers invaluable information regarding flood management as well as preventing the associated risks in urban areas. The present study prepares a flood risk map and evaluate the practices of low-impact development (LID) intended to decrease the flood risk in Shiraz Municipal District 4, Fars province, Iran. So, this study investigate flood vulnerability using MCDM models and some indices, including population density, building age, socio-economic conditions, floor area ratio, literacy, the elderly population, and the number of building floors to. Then, the map of thematic layers affecting the urban flood hazard, including annual mean rainfall, land use, elevation, slope percentage, curve number, distance from channel, depth of groundwater, and channel density, was prepared in GIS. After conducting a multicollinearity test, data mining models were used to create the urban flood hazard map, and the urban flood risk map was produced using ArcGIS 10.8. The evaluation of vulnerability models was shown through the use of Boolean logic that TOPSIS and VIKOR models were effective in identifying urban flooding vulnerable areas. Data mining models were also evaluated using ROC and precision-recall curves, indicating the accuracy of the RF model. The importance of input variables was measured using Shapley value, which showed that curve number, land use, and elevation were more important in flood hazard modeling. According to the results, 37.8 percent of the area falls into high and very high categories in terms of flooding risk. The study used a stormwater management model (SWMM) to simulate node flooding and provide management scenarios for rainfall events with a return period ranging from 2 to 50 years and five rainstorm events. The use of LID practices in flood management was found to be effective for rainfall events with a return period of less than 10 years, particularly for two-year events. However, the effectiveness of LID practices decreases with an increase in the return period. By applying a combined approach to a region covering approximately 10 percent of the total area of Shiraz Municipal District 4, a reduction of 2–22.8 percent in node flooding was achieved. The analysis of data mining and MCDM models with a physical model revealed that more than 60% of flooded nodes were classified as "high" and "very high" risk categories in the RF-VIKOR and RF-TOPSIS risk models.

Effectiveness of bioretention system and vegetated swale for reducing urban flood risk in equatorial region: a case study in Kuching, Malaysia

One of the main causes of urban inundation is the rise of impermeable surfaces brought on by increasing urbanization. Low impact development (LID) practices have been employed in previous studies to mitigate urban flooding. However, the effectiveness of LID practices in reducing runoff peaks and improving water quality is unknown, especially in the equatorial region. This study explored nine alternative scenarios to evaluate the effectiveness of the bioretention system and vegetated swale using the Storm Water Management Model (SWMM). Using precipitation data of December 2021, the Swinburne University of Technology Sarawak Campus has been chosen as the case study. The findings demonstrated that these two LID practices could significantly lessen urban flooding. Under scenario 7, the combination of 28.4% bioretention system and 11.3% vegetated swale reduced the maximum runoff peaks by 22.98% at Peak A, 24.71% at Peak B, and 24.09% at Peak C. In the meantime, under scenario 7, the implemented LID practice has removed 20.09% of TSS, 19.75% of TP, and 12.26% of TN. It was discovered that runoff peak reduction increases as the area covered by vegetated swale and bioretention system increases. The outcomes showed that bioretention system performed better than the vegetated swale in reducing peak runoff and enhancing water quality. Local authorities can use the findings of this study to offer recommendations for reducing disaster risk, controlling urban flooding, and revitalizing urban areas.

Multi-method combined analysis of urban flood risks and its influencing factors under low impact development

In previous studies, the mitigation of urban floods via low impact development (LID) has typically been expressed only in terms of runoff volume reduction. The impact of duration time and flow velocity on the flood risk has not been quantitatively analyzed. This paper takes the Beiyangyuan Campus of Tianjin University (national pilot sponge campus) as the study area. Based on the constructed SWMM and MIKE21 coupled model, the effects of LID on different flood characteristics are analyzed by setting LID removal scenarios. The results show that LID mainly mitigates urban floods by reducing the runoff volume, inundation area and risk area, and the reduction effect is approximately 15%–38%. The water depth, flow velocity and duration time are not sensitive to LID practices, and the reduction effect is basically below 10%. The flood risk and its influencing factors in the study area were analyzed using combined multi-methods based on water depth (WD), water depth & duration time (WD&DT), and hazard rating (HR). The results show that the central island with numerous LID practices has an almost undetected flood risk, and the high risk is mainly distributed in the northeast of the study area. Duration time is an important influencing factor on flood risk, and after adding consideration of duration time, the proportion of risk levels upgraded to moderate or high is more than 90%. Further analysis shows that insufficient drainage capacity of the pipe network leads to prolonged ponding, which is the primary cause of flood risk in the study area. Adding the consideration of flow velocity, the 27–36% low-risk area changes to moderate risk; multiple linear regression analysis shows that the contribution of flow velocity to the flood risk is minimal. The possibility of flow impact hazard in the study area is very low, and the cumulative frequency of water depth and flow velocity product (d·v) less than 0.04 m2/s is more than 98% in each scenario.

Discovering the Perception Differences of Stakeholders on the Sustainable and Innovative Stormwater Management Practices

The overarching aim of the present work is to explore the perception differences of stakeholders, i.e., municipalities (MN), water administrations (WS), non-governmental organizations (NGO), and universities (UN), playing vital roles in the decision mechanisms regarding one of the sustainable flood mitigation techniques, i.e., low impact development (LID) practices. As being rewarding alternative to conventional drainage techniques, four different LID strategies, i.e., green roof (GR), bioretention cells (BC), permeable pavement (PP), and infiltration trench (IT), and three of their combinations were adopted to the densely urbanized Ayamama River basin, Istanbul, Turkey. The performances of the LIDs were comprehensively evaluated based on three pillars of sustainability (i.e., social, economic, and environmental) using a hybrid multi-criteria decision-making (MCDM) framework containing the implementation of fuzzy analytical hierarchy process (fuzzy AHP) and the VIKOR (VIse KriterijumsaOptimiz acija I Kompromisno Resenje) for finding the weights of constraining criteria and prioritizing the LID scenarios, respectively. The major outcomes of this research showed that experts from MN, WS, and UN put forward the environmental dimension of sustainability, whereas respondents from NGO concentrated on the social aspect. Furthermore, MN and WS highlighted initial investment cost as the most determining criterion in optimal LID selection. On the other hand, criteria weights regarding the judgments of the experts attended from NGO revealed the significance of community resistance in specifying the optimal LID practices, while aesthetic appearance was the major concern of the academia. Hence, the present study, as an initial attempt, enabled critical standpoints for discovering perceptions of stakeholders.

Optimal design of low impact development at a community scale considering urban non-point source pollution management under uncertainty

Urban non-point source (NPS) pollution management is receiving increased attention because of the environmental and ecological consequences of urbanization. We developed a Storm Water Management Model (SWMM)-based interval double-sided chance-constrained programming (SWMM–IDCCP) model for the optimal design of low impact development (LID) during urban NPS pollution management at a community scale. Pollution control efficiency and economic costs related to LID practices were considered in the SWMM–IDCCP model, simultaneously addressing uncertainties in pollutant output and decision-making processes. Specifically, by combining SWMM, Monte Carlo simulation, interval linear programming, and double-sided chance-constrained programming, the SWMM–IDCCP model can evaluate export loads of urban NPS pollutants and pollution control efficiencies of LID practices and analyze the corresponding uncertainties. Concurrently, the proposed model can provide reliable and optimal implementation schemes for LID practices under different scenarios, dealing with uncertainties such as discrete intervals and double-sided random parameters. The proposed model was applied to the Dongguan University of Technology in Dongguan City, South China. The random distribution characteristics of pollution load were identified. The ranges of pollution load for total suspended solids, chemical oxygen demand, total nitrogen, and total phosphorus were 76,430–165,698, 44,366–74,155, 2118–3,830, and 97–177 kg in 2021, respectively. Probability distribution characteristics of pollution control efficiencies of three LID practices (i.e., bio-retention cell, green roof, and permeable pavement) for the four urban NPS pollutants were obtained. Using the SWMM-IDCCP model, LID configuration schemes were obtained under diverse pollution control targets and confidence levels, taking into account variations in the decision preference of different administrators. This research indicates that the SWMM-IDCCP model can be used to manage urban NPS pollution at a community scale under uncertainty.

Characterizing hydrological-sensitive areas of the Kinyerezi river sub-catchments in Dar es Salaam, Tanzania using the topographic index approach

Abstract Several areas experience frequent floods due to anthropogenic activities. Among them, is the Dar es Salaam city, which experiences frequent floods along the Msimbazi River, whose flows originate from different tributaries including the Kinyerezi River. This study aims to evaluate the hydrological-sensitive areas of the Kinyerezi River sub-catchments using topographic index values (λ*) that enable the identification of areas with a higher probability of generating surface runoff. A digital elevation model was utilized to delineate the Kinyerezi River sub-catchment characteristics using ArcGIS 10.4. Soil infiltration rates (Ks) on selected open places were determined using a Guelph permeameter. Soil particle size distributions were analyzed and the λ* values were evaluated. The results showed the particle size distribution contains sand and silt-clay ranging from 46 to 84% and 16 to 53%, respectively. The Ks ranged from 0.6 to 7.8 mm/h while the sub-catchment KS3 scored the highest λ* value of about 10.7. Hence, there is a higher probability for generating surface runoff. Sub-catchment KS16 scored the smallest λ* value of 5.7, perceived to generate less surface runoff. Low-impact development practices capable of capturing runoff and enabling infiltration, evaporation, and detention should be employed in sub-catchments with higher λ* values.

Integrated evaluation and attribution of urban flood risk mitigation capacity: A case of Zhengzhou, China

Study regionThe Zhengzhou City in China Study focusUrban flood risk mitigation (UFRM) refers to the runoff retention capacity of land surface in urban regions. Previous studies have focused on assessing the UFRM change in central urban areas. Nevertheless, analysis of the UFRM change considering the heterogeneity of urban and rural gradient is scarce. This study aims to evaluate the spatiotemporal change of UFRM and its influencing factors in different urban functional zones. An integrated framework combining the hydrological model and geographic information system (GIS) has been established to assess the evolution of UFRM in Zhengzhou between 2000 and 2020. New hydrological insights for the regionThe findings illustrate the following: (1) The UFRM of Zhengzhou experienced a 10.76% increase from 2000 to 2010, followed by a subsequent 3.38% decrease from 2010 to 2020.(2) UFRM increased in ecological areas while decreasing in urban regions, revealing a disparity between UFRM supply and demand. (3) The adverse impact of impervious surfaces on UFRM surpasses the influence of precipitation intensity in urban regions. As a result, this study suggests that urban areas should avoid extensive expansion of impervious surfaces and prioritize implementing low-impact development practices. The ecological zones should implement rigorous policies to protect natural preservation. These findings provide policymakers a scientific foundation for devising sustainable urban development strategies to enhance urban flood resilience.

Permeable Concrete Barriers to Control Water Pollution: A Review

Permeable concrete is a class of materials that has long been tested and implemented to control water pollution. Its application in low-impact development practices has proved its efficiency in mitigating some of the impacts of urbanization on the environment, including urban heat islands, attenuation of flashfloods, and reduction of transportation-related noise. Additionally, several research efforts have been directed at the dissemination of these materials for controlling pollution via their use as permeable reactive barriers, as well as their use in the treatment of waste water and water purification. This work is focused on the potential use of these materials as permeable reactive barriers to remediate ground water and treat acid mine drainage. In this respect, advances in material selection and their proportions in the mix design of conventional and innovative permeable concrete are presented. An overview of the available characterization techniques to evaluate the rheology of the paste, hydraulic, mechanical, durability, and pollutant removal performances of the hardened material are presented and their features are summarized. An overview of permeable reactive barrier technology is provided, recent research on the application of permeable concrete technology is analyzed, and gaps and recommendations for future research directions in this field are identified. The optimization of the mix design of permeable reactive concrete barriers is recommended to be directed in a way that balances the performance measures and the durability of the barrier over its service life. As these materials are proposed to control water pollution, there is a need to ensure that this practice has minimal environmental impacts on the affected environment. This can be achieved by considering the analysis of the alkaline plume attenuation in the downstream environment.

Estimating runoff probability from precipitation data: A binomial regression analysis

AbstractThe runoff threshold of a catchment is often reported in the literature as a measure used to evaluate the effectiveness of low‐impact development (LID) techniques and is oftentimes determined using linear regression. However, due to the heteroscedastic nature of precipitation and runoff data, linear regression analyses can result in invalid conclusions, so the use of a binomial regression model was investigated. Precipitation and runoff data collected from five studies were assessed for homoscedasticity and applied to four linear regression models for the evaluation of the linear regression runoff threshold (LRRT) and the associated 95% bootstrapping confidence intervals. Log‐transformation corrected the heteroscedasticity of two of the five precipitation and runoff datasets. While mixed‐effect linear models accounted for heteroscedasticity, these models often resulted in extremely large confidence intervals. A binomial regression model was created to determine the likelihood of runoff based on precipitation depth. For each catchment, the 10%–90% runoff probability range (p10–p90) is reported to provide the user with a more comprehensive understanding of when a catchment produces runoff than the LRRT. The p10–p90 range reflects the effects that environmental factors may have on runoff generation. For example, impervious catchments with limited interaction with the vegetation and soil produce a narrow p10–p90 range. Conversely, LID practices encourage the interaction of runoff with environmental factors and result in a wider p10–p90 range. Utilization of the binomial regression methodology presented herein is recommended for evaluation of the likelihood of runoff for each precipitation depth.

Improving water quality modelling for green roof runoff using Storm Water Management Model

Modelling of green roof is important for assessing its effectiveness as a low impact development (LID) practice. This study evaluated the performance of Storm Water Management Model (SWMM)’s LID Controls for modelling runoff water quality load from a green roof in Portland, Oregon, USA, for possible improvement. Such an attempt has been made rarely, although plenty of studies have evaluated SWMM's LID Controls for predicting green roof runoff. From the evaluation, the applicability of the SWMM for evaluating water quality such as total phosphorous (TP) and total nitrogen (TN) was “not satisfactory”. Nash-Sutcliffe Efficiency (NSE) value was 0.27 for TN and −1.45 for TP when using “rain concentration”, the only parameter available for water quality simulation of green roof runoff. The applicability was improved to “very good” level for TP with an NSE value of 0.66 when buildup and washoff were made possible by creating an imaginary twin subcatchment of the same size as the original one. However, NSE value for TN was not improved. The value of the work is that it could lead to a more accurate green roof design by minimizing pollutant release with improved prediction technology for TP.

Investigating non-point pollution mitigation strategies in response to changing environments: A cross-regional study in China and Germany

Climate change and urbanization have altered regional hydro-environments. Yet, the impact of future changes on the pollution risk and associated mitigation strategies requires further exploration. This study proposed a hydraulic and water-quality modeling framework, to investigate the spatiotemporal characteristics of pollution risk mitigation by low impact development (LID) strategies under future Representative Concentration Pathways (RCP) and Shared Socioeconomic Pathways (SSP) scenarios. Results demonstrated that the LID strategies exhibited an effective performance of pollutant removal in the current hydro-environment, with the removal rates ranging from 33% to 56%. In future climate and urbanization scenarios, the LID performance declined and turned to be uncertain as the greenhouse gas (GHG) emissions increased, with the removal rates ranging from 12% to 59%. Scenario analysis suggested that the LID performance was enhanced by a maximum of 73% through the diversified implementation of LID practices, and the performance uncertainty was reduced by a maximum of 67% through the increased LID deployment. In addition, comparative analysis revealed that the LID strategies in a well-developed region (Dresden, Germany) were more resilient in response to changing environments, while the LID strategy in a high-growth region (Chaohu, China) exhibited a better pollutant removal performance under low-GHG scenarios. The methods and findings in this study could provide additional insights into sustainable water quality management in response to climate change and urbanization.

Integrated SUSTAIN-SWMM-MCDM Approach for Optimal Selection of LID Practices in Urban Stormwater Systems

Rapid urbanization has increased impervious areas, leading to a higher flood hazard across cities worldwide. Low Impact Development (LID) practices have shown efficacy in reducing urban runoff; nevertheless, choosing the best combinations in terms of implementation cost and performance is of great importance. The present study introduces a framework based on green infrastructure, multi-objective optimization, and decision support tools to determine the most cost-effective LID solutions. The Storm Water Management Model (SWMM) was employed for rainfall-runoff and hydraulic modeling in Region 1, District 11 of Tehran, Iran. Six scenarios of different combinations of LID practices were developed. The system for Urban Stormwater Treatment and Analysis Integration (SUSTAIN) was used to optimize and evaluate each scenario. The selected solutions were imported to the SWMM to evaluate the stormwater system performance. Then, two multi criteria decision making (MCDM) models, including TOPSIS and COPRAS, were employed to rank the scenarios based on four technical and economic criteria. Results showed that scenario 4, consisting of rain barrels, porous pavements, and vegetated swales, had the best performance under TOPSIS with a 7.68 million USD and reduced the runoff volume and peak flow by 20.77% and 19.2%, respectively. However, Under the COPRAS method, Scenario 2 with a combination of rain barrels, bio-retention cells, and vegetated swales showed higher performance than the other scenarios with 3.25 million USD and led to a 15% reduction in the runoff volume and 4.30% in the peak flow. The COPRAS method was more sensitive to cost weights and chose the most economical scenario as the ideal. However, Scenario 4 concluded to be more feasible due to spatial limitations in the study area. The proposed SWMM—SUSTAIN—MCDM framework could be helpful to decision-makers in the design, performance evaluation, cost estimation, and selection of optimal scenarios.

Evaluating the Effectiveness of Low Impact Development Practices against Climate Induced Extreme Floods

Short but extreme flooding events have been frequent and severe globally due to climate change and urbanization in recent years. Similarly, researchers, scientists, and water managers are suggesting the application of sustainable flood management strategies such as Low Impact Development (LID) to mitigate the impacts of such extreme flooding events. However, most of these strategies have primarily been evaluated using historical precipitation events, which may not accurately represent the impact of climate-induced flooding events, which are projected to become more extreme. In this context, this study assesses the effectiveness of LIDs in combating climate change-induced flooding events. The North American Regional Climate Change Assessment Program (NARCCAP) climate model was applied in this study to quantify the magnitude of future projected storm depths, which are expected to increase due to climate change. Similarly, Personal Computer Storm Water Management Model (PCSWMM) was used to develop a rainfall-runoff simulation model and to assess the effectiveness of three LID techniques (Permeable Pavement, Green Roof, and Bio-Retention Cell) in reducing surface runoff under various climate scenarios. The results revealed that under the climate change scenarios the future projected design depths are expected to increase by up to 104%. Similarly, peak discharge, and total flooding volume were found to increase by 37.72% and 88.73%, respectively under the most extreme climate change scenario. Furthermore, the study demonstrated that applying LID strategies decreases peak discharge, offering a viable solution to tackle flooding events induced by climate change. The results illustrated the performance of permeable pavement was superior in reducing the peak discharge by up to 28.57%. Similarly, applying green roofs and bioretention cells reduced the peak discharge by up to 19.93% and 14.25%, respectively.

Bibliometric analysis of global research on bioretention from 2007 to 2021.

Bioretention is a typical low impact development (LID) practice that helps reduce peak urban stormwater runoff and runoff pollutant concentrations (e.g., heavy metals, suspended solids, organic pollutants), which has become an important part of urban stormwater management over the past 15years. To understand the research hotspots and frontiers in the field of bioretention facility research and provide a reference for research into bioretention facilities, we conduct a statistical analysis of global bioretention literature published during 2007-2021 using the Web of Science core database and the data visualization and analysis software VOSviewer and HistCite. The number of published articles related to bioretention facilities shows a rising trend over the study period, with research from China contributing greatly to global research on bioretention facilities. However, the influence of articles needs to be increased. Recent studies mainly focus on the hydrologic effect and water purification effect of bioretention facilities and on the removal of nitrogen and phosphorus nutrients from runoff rainwater. Further studies should focus on the interaction of fillers, microorganisms, and plants in bioretention facilities and its impact on the migration, transformation, and concentrations of nitrogen and phosphorus; the purification effect and mechanism of specific emerging contaminants in runoff; the selection and configuration optimization of filler materials and plant species; and the optimization of the design parameters of the model for bioretention systems.

Quantifying and improving flood resilience of urban drainage systems based on socio-ecological criteria

In this paper, a new framework is developed for evaluating the resilience of urban drainage systems (UDSs) under floods by proposing and quantifying some technical and socio-ecological (SE) criteria. The proposed criteria are used to quantify the seven principles of building resilience in socio-ecological systems. The criteria mainly focus on preserving diversity and multiplicity in a UDS, managing variables that gradually change over time (slow variables), improving structural and functional connectivity, maintaining system adaptability, encouraging learning, broadening participation, and promoting polycentric governance systems. For evaluating the efficiency of the proposed framework, it is applied to a real-world case study of improving resilience of the UDS in the eastern part of Tehran metropolitan area. Three scenarios for flood management are proposed based on the Low Impact Development (LID) practices which are simulated using the Storm Water Management Model (SWMM). The Entropy method is used to consider the uncertainty in the relative importance of different criteria in estimating the flood resilience. The estimated values for the proposed criteria regarding the current drainage system in the study area show its undesirable condition in many sub-catchments. The results also show that using around 2.3 km2 of LID practices in this urban watershed can significantly improve the resilience in many sub-catchments (nearly, 30%) and reduce the total volume of the overflow (about 50%). The results also show that using the flood management scenarios, improving connectivity is the most influential factor that enhances the general resilience of the system.

Two-scale optimal management of urban runoff by linking LIDs and landscape configuration

Landscape composition and configuration of urban patches impact greatly on hydrological process, of which low impact development practices (LIDs) have been incorporated worldwide to management stormwater runoff quantity- and quality-related issues. Although optimization design for LIDs has been studied extensively to improve stormwater management at catchment scale, a further study of LIDs-based landscape configuration at site scale has not been fully explored. In this study, a two-scale optimization framework was constructed to integrate spatial layout and landscape configuration of LIDs using SWMM, NSGA-II and GIS techniques. The spatial optimization at catchment scale showed that area of sink landscape almost doubled as the distance to outlets decreased. A further site-scale optimization by a new landscape metric, in terms of CRSS (configuration ratio between patches of runoff sources and sink), was conduct to achieve LIDs-based landscape configuration optimization. Runoff flow and pollution were significantly correlated with CRSS in power function, quantifying CRSS thresholds of 0.57–0.69 as the most adaptive strategies for stormwater management. Notably, the CRSS thresholds were higher for ammonia nitrogen (NH3-N) and suspended solid (SS) pollution, especially targeting source patches of roofs. The optimization in this study could improve the reduction of runoff peak flow of heavy rain, peak concentration of chemical oxygen demand and SS, and initial scouring of NH3-N.

Optimizing Low Impact Development for Stormwater Runoff Treatment: A Case Study in Yixing, China

Low-impact development (LID) practices have been recognized as a promising strategy to control urban stormwater runoff and non-point source pollution in urban ecosystems. However, many experimental and modeling efforts are required to tailor an effective LID practice based on the hydraulic and environmental characteristics of a given region. In this study, the InfoWorks ICM was applied to simulate the runoff properties and determine the optimal LID design in a residential site at Yixing, China, based on four practical rainfall events. Additionally, the software was redeveloped using Ruby object-oriented programming to improve its efficiency in uncertainty analysis using the Generalized Likelihood Uncertainty Estimation method. The simulated runoff was in good agreement with the observed discharge (Nash–Sutcliffe model efficiency coefficients >0.86). The results of the response surface method indicated that when the sunken green belt, permeable pavement, and green roof covered 8.6%, 15%, and 10%, respectively, of the 11.3 ha study area, the designed system showed the best performance with relatively low cost. This study would provide new insights into designing urban rainfall-runoff pollution control systems.