Low Impact Development Implementation Research Articles

Development of a multi-layer green-ampt infiltration based modeling framework for hydrologic process simulation and design of various low impact development measures for mitigating urban flooding

ABSTRACT Low Impact Development (LID) measures have proven to be effective in reducing the runoff volume and the peak of runoff at small spatial scales. Assessment of the hydrological impacts of LID measures at river basin scales is currently limited by the absence of adequate physically-based process models that can simulate LID processes at such scales. In this study, an attempt has been made to develop LID modules to simulate the water balance and hydrological processes based on the Multi-Layer Green-Ampt (MLGA) infiltration method, which is an advancement to the existing LID modeling techniques. The performance of the MLGA-based LID modules was benchmarked with the process-intensive numerical tool HYDRUS 1D for about 5000 soil samples across the soil textural classes. The results indicated that the MLGA-based model simulates the hydrological processes in close agreement with HYDRUS for soils with moderate-to-high hydraulic conductivity values, which are amenable for LID implementation.

A Framework Based on LIDs and Storage Pumping Stations for Urban Waterlogging

Climate change has resulted in an increase in extreme rainstorm events, posing the challenges of urban waterlogging and runoff pollution. Low Impact Development (LID) is widely used to address the issues above, but its effectiveness is unknown in mountainous areas. Due to a flash flood and high flood peak, storage pumping stations are also needed to drain. Thus, a framework composed of storage pumping stations and Low Impact Developments (LIDs) was proposed based on the topography and the regional upstream and downstream relationships. The water quantity in this framework is applied to YI County in Hebei Province, China. The results showed that individual LIDs effectively reduced runoff volume, with the implementation area being more crucial than the location. Combining storage pumping stations with LIDs significantly reduces peak outflow and delays it by 5 to 51 min. The combined downstream implementation of storage pumping stations and LIDs yielded the most effective results. These findings offer important insights and management strategies for controlling waterlogging in mountainous cities of developing countries.

Hydrological reduction and control effect evaluation of sponge city construction based on one-way coupling model of SWMM-FVCOM: A case in university campus

The exacerbation of global warming, the frequent incidence of extreme weather events, and the rapid urbanization have collectively contributed to the heightened prevalence of flooding in urban areas. As a result of this challenge, sponge city (SPC) has been adopted in China as an efficient means of preventing and controlling urban floods. To evaluate the hydrological reduction and control effect of sponge city construction (SPCC) within a university campus, a one-way coupled model integrating one-dimensional sewer hydrodynamic model (SWMM) and two-dimensional surface flow model (FVCOM), namely SWMM-FVCOM model, was established. The Nash-Sutcliffe efficiency (NSE) of the SWMM were greater than 0.75 under there rainfalls with different intensity, indicating the good reliability and stability of this model could be used in the subsequent simulation. An analysis of drainage capacity and the risk of urban flooding was conducted using this model before and after the implementation of SPCC, considering six rainfall scenarios. Implementing SPCC demonstrated an effective performance in mitigating surface runoff, regulating inspection well overflow, and reducing overflow volume in the study region. However, the efficacy of runoff control diminished proportionally with the escalation of rainfall return period. Simultaneously, the implementation of low impact development (LID) measures can significantly decrease the extent and magnitude of surface inundations. The reduction rate of SPCC on the area of waterlogging ranged from 55.84% to 72.50%. But the control rate decreased with increasing rainfall return periods, demonstrating that adopting SPCC can effectively mitigate the severity of urban flooding resulting from low rainfall return period events (Tr < 20 years). This study can provide scientific foundation for environment managers to evaluate the impact of urban flooding prevention and control on runoff pollution mitigation when adopting the implementation of SPCC.

Urban rainfall-runoff flooding response for development activities in new urbanized areas based on a novel distributed coupled model

The development and construction activities of new urbanized areas lead to drastic changes in land use, resulting in severe flood disasters. The main purpose is to systematically reveal the response process to urban stormwater under different urban development degree (DD) and low-impact development (LID) implementation. A novel distributed hydrological and hydrodynamic coupled model (DHHCM), consisting of a sub-catchment-based hydrological method for plot areas and a grid-based hydrodynamic method for road areas was developed in this study. The Fengxi New Town, China was applied as the research object, a total of 11 combined events of DDs (0%, 20%, 40%, 60%, 80% and 100%) and LID deployment were simulated under five rainfall return periods (P = 2a, 5a, 30a,50a and 100a) to explore their impact on the flood process. The results indicated that the DD and the LID implementation have no obvious impact on road flood when P ≤ 5a. However, the road flood increases significantly with the increase of DD when P ≥ 30a. The peak discharge of the drainage system significantly increases with the increase in DD under different return periods, and the average peak discharge increases the most obviously (2.62 m3/s) under P = 30a. The implementation of LID measures has significantly improved the mitigation effect of surface inundation, drainage system discharge and runoff control, and its effect has increased with the DD increase. It is with great significance to accurately control the flood disaster evolution process in urban development activities, and provide data and technical support for quantifying the risks and losses in policy making.

Assessing runoff control of low impact development in Hong Kong's dense community with reliable SWMM setup and calibration

Low impact development (LID) is a sustainable practice to managing urban runoff. However, its effectiveness in densely populated areas with intense rainfall, such as Hong Kong, remains unclear due to limited studies with similar climate conditions and urban patterns. The highly mixed land use and complicated drainage network present challenges for preparing a Storm Water Management Model (SWMM). This study proposed a reliable framework for setting up and calibrating SWMM by integrating multiple automated tools to address these issues. With a validated SWMM, we examined LID's effects on runoff control in a densely built catchment of Hong Kong. A designed full-scale LID implementation can reduce total and peak runoffs by around 35–45% for 2, 10 and 50-year return rainfalls. However, LID alone may not be adequate to handle the runoff in densely built areas of Hong Kong. As the rainfall return period increases, total runoff reduction increases, but peak runoff reduction remains close. Percentages of reduction in total and peak runoffs decline. The marginal control diminishes for total runoff while remaining constant for peak runoff when increasing the extent of LID implementation. In addition, the study identifies the crucial design parameters of LID facilities using global sensitivity analysis. Overall, our study contributes to accelerating the reliable application of SWMM and deepening the understanding of the effectiveness of LID in ensuring water security in densely built urban communities located near the humid-tropical climate zone, such as Hong Kong.

Key performance indicators for small and medium-sized urban water systems in a semi-arid region: a case study of Okanagan Valley, Canada

ABSTRACT Drinking water, wastewater, and stormwater are three components of an Urban Water System. Maintenance of these components requires evaluation of the existing performance of the water system. The evaluation becomes more significant in small and medium-sized water systems because these systems wrestle with various constraints, such as insufficient funds, inadequate infrastructure and water governance. In this study, Key Performance Indicators (KPIs) are identified for each UWS component considering six performance criteria. A questionnaire was distributed to water utilities across the Okanagan Valley. KPIs were identified by combining Delphi technique and Preference Ranking Organization Method for Enrichment Evaluation methods. Ninety-six KPIs were identified with 39, 30, and 27 KPIs for drinking water, wastewater, and stormwater. Based on the available literature, agriculture water use, low impact development implementation (LID), average annual life cycle investment, and swimming advisories are a few notable KPIs that are unique to the Valley.

Multi-objective decision-making based on theories of cooperative game and social choice to incentivize implementation of low-impact development practices

Urbanization growth leads to shifting hydrological factors which in turn represent a challenge for urban stormwater management. In this situation, policy strategies can be employed by governments to incentivize stakeholders to use green infrastructure for effective runoff management. This study presents a novel framework evaluating the application of Low-Impact Development (LID) practices for runoff quality and quantity management from a socio-economic point of view. The proposed framework investigates the potential of cooperative game theory to find a fair allocation based on the concept of justice. In this regard, first, the Non-dominated Sorting Genetic Algorithm (NSGA-II) was coupled with the Storm Water Management Model (SWMM) to find optimal runoff management scenarios considering minimization of runoff volume, peak flow, Total Suspended Solid (TSS) load, and costs of LIDs implementation. In the next step, in order to conflict resolution, stakeholders' preferences and interactions were incorporated into the cooperative game theory to determine management scenarios' worth of coalition. In the third step, benefits are allocated among stakeholders by defining three different sharing rules. Then, to select the most capable runoff management scenario, social choice methods of Condorcet choice, Borda scoring, and median voting rule support cooperative game decisions. The proposed methodology is explored in District 10 of Tehran municipality in Iran. According to the findings, solutions with stricter plans for runoff management correspond to more worth of coalition. In addition, the higher worth of coalition, the higher the reduction of peak flow, TSS load, and the total runoff volume. The results also reveal that the Borda scoring procedure tends to select scenarios with less reduction in TSS load, runoff volume, and peak flow in comparison with the others, and as expected, the minimum value for the worth of coalition. Additionally, the cooperative game targets a management scenario with the highest worth of coalition and the maximum value for the reduction in runoff volume, peak flow, and TSS removal. Our framework warrants runoff volume, TSS load, and peak flow can be reduced by 32.8, 31.9, and 32.7 percent, respectively. This framework, in addition to incentivize the stakeholders for implementing runoff management strategies, can effectively consider their conflict of interests in the decision-making process.

Multi-objective robust decision-making for LIDs implementation under climatic change

Decision-makers in urban water systems have long searched for robust runoff management alternatives that can resist deviations from the performance for which they were designed. In this study, with the development of a new comprehensive framework consisting of Many- Objective Robust Decision-Making (MORDM) and Storm Water Management Model (SWMM), robust alternatives for the implementation of Low Impact Development (LID) practices are presented under future climate change. The proposed methodology has been applied to District 10 of the Tehran municipality, located in the central part of Tehran, Iran. In the first step, the performances of General Circulation Models (GCMs) in predicting rainfall in the base period (1986–2005) were compared, and MPI-ESM-LR was selected as the best model for predicting rainfall in the future period (2021–2040). In the next step, by developing the SWMM hydrological model, runoff quality and quantity were simulated under RCP8.5 and RCP2.6. By coupling SWMM with the NSGA-II multi-objective evolutionary algorithm and specifying objective functions, the most optimal LIDs implementation scenarios were produced. Then, well-characterized uncertainties were changed into deep uncertainties, and the robustness of each design alternative was quantified using two robustness assessment methods. Finally, system vulnerabilities were discovered using the patient rule induction method (PRIM) and classification and regression tree (CART). This study showed that scenarios with a higher percentage of LIDs are more robust against deep uncertainties. Using different RCP scenarios also revealed that methodological selection of future climate scenarios can affect the robustness of candidate alternatives. Implementing SWMM-MORDM enables decision-makers to effectively generate runoff management scenarios and visually evaluate their robustness against deep uncertainties.

Surrogate-based multiobjective optimization to rapidly size low impact development practices for outflow capture

The optimal implementation of low impact development (LID) practices remains an open research issue. Multiobjective optimization (MOO) based on physically-based models facilitates LID sizing but requires large computational budgets. We developed and validated a surrogate MOO framework based on machine learning (ML) models to obtain satisfactory optimal solutions with an affordable computational cost. First, a calibrated and validated storm water management model (SWMM) was driven by a 2-year, 120 min Chicago pattern storm with random LID areas for generating 10,000 samples. Second, ML models, including multiple linear regression (MLR), generalized regression neural network (GRNN), and backpropagation neural network (BPNN), were trained and validated to predict catchment total outflow (CTO) and catchment peak outflow (CPO). Third, using the outperformed ML models as surrogates, the LID areas were optimized by non-dominated sorting genetic algorithm-II to minimize construction costs, CTO, and CPO. The results obtained for an urban catchment in Fengxi, China, demonstrated that: (1) BPNN outperformed MLR and GRNN in terms of accuracy, while the training time (∼40 min) was ∼6857 times and ∼706 times that of MLR (∼0.35 s) and GRNN (3.4 s) models, respectively. (2) The optimization process using BPNN models as surrogates converged well, indicating the efficiency of the proposed framework. (3) Under the marginal effect, the permeable pavement was identified as the leading practice for most Pareto solutions, followed by bioretention cell and green roof. Moreover, a subcatchment with a higher runoff coefficient was deemed preferable for LID implementation. (4) Outflow reduction by the LIDs was significant (CTO and CPO were reduced by 28.6–56.9 % and 27.5–48.3 %, respectively) but negligible for retarding the time of CPO. (5) The optimization time was reduced by ∼95.82 % using the surrogate-based MOO instead of the SWMM-based model when the training time of the BPNN models was ignored. This study provides insights into the efficient optimization of LIDs.

The influence of Low Impact Development (LID) on basin runoff in a half-urbanized catchment: A case study in San Antonio, Texas

Low Impact Development (LID) was promoted as an alternative to conventional urban drainage methods. The effects of LID at the site or urban scales have been widely evaluated. This project aims to investigate the impact of LID implementation on basin runoff at a regional scale in a half-urbanized catchment, particularly the overlap of urban and rural sub-flows at peak times. A SUPERFLEX conceptual model framework is adapted as a semi-distributed model to simulate the rainfall-runoff relationship in the catchment for San Antonio, Texas, as a case study. Scenario analyses of both urban development and LID implementation are conducted. Results show that (1) the infill urban development strategy benefits more from runoff control than the sprawl urban development; (2) in non-flood season, permeable pavements, bioretention cells, and vegetated swales decrease peak runoff significantly, and permeable pavements, bioretention cells, and green roofs are good at runoff volume retention; (3) contrary to the general opinion about the peak reduction effect of LID, for a partly urbanized, partly rural basin, the LID implementation delays urban peaks and may cause larger stacking of rural and urban peak runoffs, leading to larger basin peaks under extremely wet conditions.

Verification of PCSWMM's LID processes and their scalability over time and space

IntroductionThis paper explores the scalability of PCSWMM's Low Impact Development (LID) modeling tools within the urban stormwater computer model.MethodsThe scalability is assessed for a variety of spatial and temporal scales and for event (50-year return storm) and continuous inputs (daily rainfall for an 11 month period), and with a focus on bioretention cells. The model is calibrated for a moderate to large scale, semi-urban watershed on Vancouver Island, British Columbia, Canada. Sensitivity analysis and specialized metrics are used to verify internal model processes at a variety of scales.ResultsWith regard to spatial scaling, changes in flow path length and slope derived from Digital Elevation Models were the most impactful spatial information when modeling flood event and the model's surface layer was the dominant contributor to peak flowrate and volume mitigation by the bioretention cell. However, when modeling the continuous rainfall inputs, storage layer related parameters dominated model outputs. Aside from the soil layer's depth, soil layer parameters such as hydraulic conductivity, showed negligible influence on response to time series rainfall. Parameters that are kept static by the model such as vegetation cover, hydraulic conductivity and storage void ratio (but are naturally dynamic), were tested for their impact on response if allowed to change seasonally or with excessive loading. Runoff coefficients were greatly impacted by storage layer parameter dynamics with very little impact from vegetation. For event simulations, the berm height in the surface layer was the dominant player in reducing peak flow as well as total volume. An analysis to help illustrate sensitivity across spatial scales is proposed.DiscussionThe Spatial Dynamic Sensitivity Analysis shows that parameter sensitivity changes dynamically as LID implementation percentage changes. In particular, the clogging factor, which is a parameter associated with the storage layer, was highly influential for time series rainfall analysis. The LID model concepts in PCSWM seem appropriate for events because the surface layer dominates the response for very large storms. For smaller storms, continuous time series, and larger spatial scales, the model could be revised to better represent soil layer dynamics and vegetation cover, which were both currently inconsequential to the model's output.

Spatial allocation of LID practices with a water footprint approach

Urban water problems due to stormwater have been aggravated by the higher frequency of high-intensity precipitation events and the increase of paved surfaces. However, with appropriate stormwater management practices, such as low-impact development (LID), stormwater can provide an additional urban water resources rather than cause damage. This study aims to apply a water footprint to location determination of LID practices in the urban area. The LID planning procedure was demonstrated with the highest population density region in Taipei, Taiwan. In order to improve the spatial resolution of LID allocation, the “first-level dissemination area” with 450 residents was used as a spatial unit. The performance of LID practices was then evaluated with the simulation using the Storm Water Management Model (SWMM). Three LID practices, rainwater harvesting systems, permeable pavements, and bioretention systems, were selected. After the water footprint accounting, ten sites were suggested for LID implementation. The runoff reduction rate reached up to 65 % by rainwater harvesting systems or at least 3 % by permeable pavements. This study provides a simpler and more effective approach to ways of integrating an urban water footprint into LID planning and stormwater management in urban areas.

Catchment scale effects of low impact development implementation scenarios at different urbanization densities

• The study quantified the increase of catchment runoff induced by urbanization and climate change using the SWMM model. • The study quantified the impact of different implementation strategies of low impact development (LID) on runoff mitigation. • The most sensitive parameter of SWMM catchment model were the baseflow of drainage pipes, the depression storage of pervious areas and the hydraulic conductivity. • Intense urbanization scenario (90%) resulted in increased peak drainage discharge of 100% and the total volume outflow by 20%. • Implementing LID measures at the downstream subcatchments achieved the highest peak and flooding reduction at the catchment’s outlet, while placing LID measures at the upper parts of the catchment reduces flooding at downstream manholes. Climate change and urbanization put stress on urban stormwater systems, triggering hydraulic overloading and urban flooding increase. Low Impact Development (LID) techniques have a high potential to mitigate their impacts. This study investigates the consequences of climate change and urbanization on the urban runoff in the Risvollan catchment in Trondheim, Norway, and the effects of LID implementation and the influence of LID spatial distributions on their performance. A SWMM model of Risvollan was implemented, along with different scenarios of urbanization and climate change. The performance of various spatial distributions of LID infrastructures in the catchment was investigated, using the outflow volume and the peak runoff at the outfall as indicators. The rainfall event-based simulation results confirmed the negative effects of urbanization and climate change on urban runoff. These effects were partially mitigated by a homogenous LID implementation. The different spatial distributions of LID had little impact on volume reduction but targeting the most downstream zones of the model was more efficient in reducing the peaks at the catchment’s outlet. These findings confirm that the spatial configuration of LID might be a determinant parameter towards an efficient design of LID infrastructure in urban settings, depending on the local stakes and criteria of urban water management.

Optimal configuration of low impact development practices for the management of urban runoff pollution under uncertainty

The urbanization process has seen an accelerated increase in recent decades, leading to urban runoff pollution becoming more prominent. However, uncertainty of the pollution output and complexity of management systems have made controlling urban runoff pollution challenging. Therefore, it is necessary to propose advanced modeling methods for these challenges. This research presents an integrated urban runoff pollution management (IURPM) model for optimal configuration of low impact development (LID) practices under multiple uncertainties. The IURPM model combines the hybrid land-use prediction and improved pollution estimation models with interval parameter, stochastic parameter, and multi-objective programming. The proposed IURPM model can not only predict the output characteristics, but also provide optimal configuration schemes for the LID practices in the management of urban runoff pollution under multiple scenarios. In addition, uncertainties expressed as discrete intervals and probability density function in the management systems can be effectively addressed. A case study of the IURPM model was conducted in Dongguan City, South China. Results show that considerable amounts of urban runoff pollutants would export from Dongguan City by 2025. The export loads and pollution output flux per unit area would have significant spatial heterogeneity. The results further indicate that population size, gross domestic product, and regional area size are expected to play important roles in the pollution export, while impervious surface coverage and population density would likely have great influences on the output flux of urban runoff pollution. Based on the model findings, multiple LID practices should be adopted in Dongguan City to reduce the urban runoff pollution loads. Using the IURPM model, multiple LID implementation schemes can be obtained under different pollution reduction scenarios and significance levels, that can provide decision-making support for urban water environmental management, considering variations in the policymaker's decision-making preferences. This study demonstrates that the IURPM model can be applied to the optimal configuration of LID practices for the management of urban runoff pollution under uncertainty.

Bioretention Systems Optimization and Design Characterization Model Using Fuzzy Rough Set Theory

Urban stormwater has become a persistent concern on a global scale due to its adverse environmental implications. It is the prime vector of aquatic contaminants worldwide that causes pollutants when water bodies drain. Bioretention systems are increasingly used to alleviate setbacks associated with stormwater run-off in urban locales. It has played a substantial role in the implementation of low impact development (LID), a concept that addresses urban stormwater problems caused by land changes and development. The use of LID technologies is an innovative approach. However, it is beset with challenges, such as the insufficiency of data on rainfall distribution and difficulty in interpreting data. To address these research gaps, the present study developed a fuzzy rough set data algorithm for bioretention systems. Event mean concentration calculations and fuzzification of rainfall were performed to produce a rough set-based decision rule. Using the Weibull probability distribution, fuzzification of rainfall and parameter data, rule induction, and Preece testing, bioretention design considerations were determined. The bioretention characterizations generated evident pollutants present in the catch basin before and after filtration. In addition, the bioretention characterization conducted in this study was able to reduce the number of tests needed for rainfall identification based on the different attributes.

Multi-criteria Decision-making Approach for Characterizing the Best Low Impact Development (LID) Techniques for Stormwater Management

Low impact development (LID) techniques are known as a novel stormwater management approach designed to mitigate the adverse effects of stormwater runoff and nonpoint source pollution. This study proposes a methodology for selecting the best LIDs based on multi-criteria decision analysis (MCDA) while incorporating different stakeholder priorities. The proposed methodology comprises analysis of alternatives, stakeholder analysis, and application of the MCDA methods. The results show that most LID techniques received ratings of more than three from the Weighted Average Method (WAM; performing well) other than green roofs and constructed filters, and no techniques averaged lower than 2.29 out of five. There is a general consensus on how vegetated filter strips and infiltration practices would perform, while there is little consensus on bioretention, level spreaders, and porous pavements. The ratings show that the majority of stakeholders thought most LIDs would perform well (a rating of more than three). The findings of this study provide an initial insight into how to support effective and widespread LID implementation for all decision-makers such as planners, designers, engineers, and stormwater managers.

Perspective of the Application of Low Impact Development (LID) to Deal with Floods to Strengthen the Economic Structure of Pontianak City

Pontianak city is the capital of West Kalimantan Province, undergoing dynamic growth and development in various sectors. However, it is often hit by inundation or flooding, affecting region development, particularly economic structure. The effort that can be made is the Low Impact Development (LID) Approach to overcome flooding and inundation in urban areas while providing economic value benefits. This research analyzed the economic structure of Pontianak City with an analysis of LQ, Typology Klassen and Shifted Share to look at the growth of the base sector and the movement of economic structures. AHP analysis is used to look at the perspective of LID application in Pontianak City. The results showed that the water procurement, waste management, by products, and recycling sectors became one of the base sectors in Pontianak City. However, the results of shift-share analysis on the competitive advantage component (Cij) showed the sector was moving more slowly than the Provincial level. Policies are needed to accelerate the growth of the water management sector, one of which is a policy to overcome the problem of flooding and inundation in Pontianak city and concomitantly strengthen its economic structure. The results of the AHP analysis showed the selected form of LID application, namely water tanks, rain gardens, bioretention, filter strips, infiltration trenches, porous pavement, and infiltration wells that lead to small-scale or self-contained applications. Sensitivity analysis shows that the criteria for land needs are very sensitive and most affect other measures, namely cost, in determining LID application. Therefore, the commitment of the Pontianak City Government as a regulator, dynamic actor, and facilitator is needed to support policies and budgets that strengthen the economic structure of Pontianak City as well as a cross-sectoral working atmosphere and healthy investment to support the implementation of LID

Effects of low impact development on the stormwater runoff and pollution control

The frequent urbanization and extreme rainfall events have posed the threat to the urban environment. The implementation of low impact development (LID) practices with great potential for control urban flood and overflow pollution is not comprehensively understood yet due to the influence of complex factors (i.e., hydrological pattern, installation location, and vertical parameter setting). In this study, the hydraulic and water quality model were used to analyze the hydrological and pollution reduction of outfall and storage under different hydrological patterns, vertical parameter setting, and green infrastructure installation locations, which can determine the best implementation of the scheme for overflow pollution control. The results showed that nine parameters of the vertical layer regarding the four parameters impacted the peak value and load of suspended solids (SS). The combination scheme of the LID practices was further proposed based on the selection and analysis of the single LID practice. Besides, considering the installation location, the downstream installed location was a better choice. The horizontal connection of overflow runoff and pollution could be reduced by up to 9.75% and 36.46%, respectively. In addition, the horizontal connection can effectively reduce the peak value of inflow and pollutants at the time of assessing storage tank impact, which reach the maximum of 14.08% and 29.25%, respectively. The pollutants distribution became uniform and showed better resilience against rainfall intensity, which is beneficial to the management of stormwater. Our findings can provide guidance for Sponge City construction and effectively alleviate the combined sewer overflow.

Toward sustainable stormwater management: Understanding public appreciation and recognition of urban Low Impact Development (LID) in the San Francisco Bay Area

In the United States, regulators, planners, and designers have promoted Low Impact Development (LID) as a landscape-based approach to better manage urban stormwater for ecological benefits. However, the projects have often failed to achieve positive public responses due to their unattractive and unkempt appearances. This study provides empirical insights into public perception of urban LID practices by studying user reactions to 16 sites located in the San Francisco Bay Area—eight with LID design and eight with conventional landscape design. Most of the 502 respondents, although expressing some misconceptions and limited stormwater knowledge, showed their appreciation and recognition of the LID landscapes. This finding implies that the implementation of new LID facilities can be continued and expanded without serious concern about strong public resistance, and suggests that the design of these existing LID sites can serve as models for the future projects in the San Francisco Bay Area, along with other urban areas. The study confirms the important role of picturesque beauty, naturalness, and neatness in satisfying public expectations, especially for aesthetic and ecological landscapes. Interestingly, interpretive signs appeared to be the preferable means for motivating stormwater education and the powerful means for producing positive public reactions to LID sites, suggesting the potential of urban LID projects as the venues for public education and outreach. The study not only emphasizes the alignment of aesthetics and ecology to enhance public satisfaction, but also promotes the aesthetic qualities and didactic opportunities as the essential components of LID implementation.

Modelling the effect of rainfall patterns on the runoff control performance of permeable pavements.

With the implementation of low impact development (LID) in urban areas, it is necessary to quantify the actual effectiveness of LID facilities. In this study, a coupled hydrology-hydrodynamic numerical model was utilized to investigate the runoff control effectiveness of permeable pavements in the city centre of Shijiazhuang, China. Two groups of designed rainfall events with the same duration but different rainfall amounts and peak rainfall intensity locations were presented, and the effectiveness of permeable pavement was demonstrated by the reduction in the total runoff volume, water depth, and inundated area. The results indicate that the rainfall amount is the main factor affecting the runoff control of permeable pavements, and their effectiveness decreases with increasing rainfall amounts and peak intensity coefficients. Moreover, permeable pavements are more effective in reducing the residential waterlogging area, and the proportion of the inundated area above a depth of 0.2 m is considerably diminished. This study reveals the response of the runoff control of permeable pavements to different rainfall patterns, which is essential for supporting the design and practical operation of permeable pavements.