Low Impact Development Best Management Practices Research Articles

Hybrid SWMM and particle swarm optimization model for urban runoff water quality control by using green infrastructures (LID-BMPs)

In the past decades, climate change, population growth, urbanization, changes in land-use, and outdated runoff collecting networks have affected the quantity and quality of urban runoff in many countries. In this research, a new methodology for planning green infrastructures (GI) for runoff water quality improvement in urban areas was proposed. This framework aims in optimized designing of the type and area of low impact development-best management practices (LID-BMPs) for urban areas. Three management practices, including infiltration trenches, bio-retention basins, and permeable pavements, were considered together with an urban drainage network. The stormwater management model (SWMM) was used for the rainfall-runoff simulation, and the multi-objective particle swarm optimization (MOPSO) algorithm was utilized for LID-BMP optimization. The proposed SWMM-MOPSO model was applied to an urban area in Northwestern Tehran, Iran, and an optimized combination of the BMPs was determined. To evaluate the performance of the optimized BMPs, its results were compared with conditions where a single type of BMPs (i.e., infiltration trenches, bio-retention basins, and permeable pavements) was implemented to each of the sub-basins. For this purpose, a single type of BMPs was allocated by different percentages of each sub-basins area. Results showed that by the application of these single BMP types, the whole basin’s concentrations of total suspended solids (TSS), total phosphorous (TP), and total nitrogen (TN) were reduced by 97%, 68%, and 72%, respectively. It was seen that the bio-retention basin was the most effective single BMP in water quality improvement. In the case of determining an optimum combination of the three BMPs, the SWMM-MOPSO model was applied to minimize the TSS concentration. Results showed that comparing the single bio-retention basins, the optimum combination of BMPs reduced the TSS concentrations by 10–12%. The proposed hybrid SWMM-MOPSO simulation-optimization model was instrumental in the optimal designing of the LID-BMPs and controlling runoff water quality.

Optimal spatial priority scheme of urban LID-BMPs under different investment periods

The optimal spatial layout of low impact development best management practices (LID-BMPs) can be used to inform LID-BMP construction to prioritize resources to achieve the highest comprehensive benefits. An objective decomposition algorithm is designed to decompose the control objectives of total rainwater runoff, peak discharge, pollution reduction and rainwater utilization for each pixel of a raster image. A type selection algorithm is then designed to optimize the types of LID-BMPs deployed in each pixel. The most suitable positions for the construction of LID-BMPs are identified using a topographic index model to determine spatial priority level of LID-BMP construction sequence. A multi-objective model, including the maximum average reduction ratios of runoff and pollution and minimum total cost, is constructed. An adaptive differential evolution algorithm (ADEA) is designed to solve the multi-objective optimization problem. The optimal grid-based priority scheme is obtained for high-resolution spatial planning. It is shown that the most suitable positions for implementing LID-BMPs are located in regions with negative soil moisture deficits. Optimal total cost and reduction ratios of runoff and pollution to construct LID-BMPs in Yinchuan, China are $49,463,516, and 0.46 and 0.38 in the first priority scheme; $50,920,496, and 0.74 and 0.62 in the second priority scheme; and $99,207,806, and 0.92 and 0.86 in the third priority scheme. The optimal spatial priority schemes of LID-BMPs obtained from the ADEA can maintain the maximum runoff and pollution controls under different investment periods.

Multi-objective decision-making for green infrastructure planning (LID-BMPs) in urban storm water management under uncertainty

Sustainable urban surface runoff management is receiving increased attention due to environmental and ecological consequences related to urbanization. This study presents a useful new framework for green infrastructure (GI) planning for the management of urban runoff quality and quantity. The proposed framework considers physical, technical, economic, and multi-stakeholder aspects related to urban runoff management while simultaneously addressing the uncertainties of the decision-making process and model parameters. The methodology is applied to regionally locating and sizing low impact development-best management practices (LID-BMPs) while considering the hydrologic and hydraulic impacts. A decision-making multi-objective optimization framework is developed by integrating: 1) a Multi-Layer Perceptron neural network founded on a Storm Water Management Model (SWMM-MLP meta-model), 2) NSGA-II multi-objective optimization, 3) fuzzy α-cut technique, and 4) a decision-making support model based on social choice theory to elicit trade-offs among system cost and LID-BMP performance indicators. The decision-making model, based on Fuzzy Social Choice (FSC) theory, is applied to simulate consensus between stakeholders for a partially cooperative group decision-making problem. The proposed methodology is explored in a catchment located in the northeastern part of Tehran, Iran. Results showed that the SWMM could be effectively replaced with a MLP-based meta-model in simulation-optimization problems for urban runoff management. In the application of FSC methods, the optimal scenarios were effective in reducing the volume of urban runoff and contamination loads while maintaining the optimality of the operation costs. Considering the optimal LID scenario, a reduction of more than 99% in runoff volume and biochemical oxygen demand (BOD), and a decrease of more than 92% of total suspended solids (TSS), occurred for the lower bound of uncertainty (lower (left) end of the α-cut = 0.3). For the upper bound of uncertainty (upper (right) end of the α-cut level = 0.3), a maximum reduction of 57% was obtained. In applying FSC methods through the decision-making process, the Borda Counting method considered the preferences of all stakeholders best. Moreover, the proposed framework allows decision-makers to decide on the acceptability and reliability of the optimal management scenarios considering their preferences and uncertainties.

Performance of low-impact development best management practices: a critical review

Low-impact development (LID), a land planning and engineering design approach for managing urban stormwater runoff, has been widely adopted across the globe. LID best management practices (BMPs) are man-made features that rely on natural processes to manage stormwater water quantity and quality. In this article, recent literature (published after the year 2008) related to nine BMPs was reviewed to highlight the ranges in treatment efficiencies for 21 of the most frequently investigated runoff parameters. The primary function, pros and cons, and factors affecting performance of each BMP were discussed. A frequency analysis of the reviewed parameters showed that total suspended solids, total phosphorous, total nitrogen, runoff reduction, and zinc concentrations were the most frequently investigated stormwater runoff parameters. Five recurring themes were observed with regards to knowledge gaps and conflicting objectives for research related to LID BMPs that include: (i) lack of consensus on which parameters to measure for effective LID adoption, (ii) BMP performance is highly variable, (iii) many BMPs are known exporters of nutrient pollutants, (iv) lack of cold weather performance-specific studies for individual BMPs, and (v) lack of human pathogen-related stormwater quality studies for individual BMPs. Suggestions for future research are discussed to address these knowledge gaps.

The influence of low impact development-best management practices implementation on surface runoff reduction: A case study in Universitas Indonesia catchment area

High population growth rate will increase the infrastructure development, so the impervious land cover in a certain area will be greater. In 2016, the percentage of impervious area in UI Depok catchment area has reached 57%. This condition causes the surface runoff volume and probability of flood will increase. LID is a new paradigm for stormwater management in micro-scale areas. LID infrastructure is designed to manage stormwater for light to moderate rainfall spectrum. Previous research has produced an applied proposal of various LID-BMP infrastructure in UI catchment area, Depok, by using BMP Siting Tools. This study aims to compare the volume of surface runoff without and with the LID infrastructures on UI catchment area, Depok, and to calculate the effectiveness of LID infrastructure for various spectrum of rainfall. The LID infrastructures used are bioretention, porous pavement, infiltration trench, infiltration basin, vegetated filter strip, sand filter non-surface, sand filter surface, rain barrel and grassed swales. By applying said infrastructures, the reduction of peak flow on various rain spectrums vary from 3-30%.

Site-Scale LID-BMPs Planning and Optimization in Residential Areas

Low-impact development best management practices (LID-BMPs) are a representative and effective approach in urban runoff management. In a planning process, it is important to optimally design and place LID-BMPs to maximize cost-effectiveness, and equally important to fully evaluate the planning’s control effects. This paper presents a case study of LID-BMPs planning and optimization in a residential community in China using SUSTAIN as the modeling tool. The LID-BMPs facilities are designed individually and placed at specific locations. Runoff volume and quality are simulated for predevelopment, basic, and planning scenarios. Optimization is conducted to reveal cost-effective schemes and to determine an optimal scheme that meets the control target. This optimization scheme achieves a 75.2% control rate with a cost of USD 1 million. In addition to the commonly used annual rainfall data, designed storm events are also input to further examine the control effects of the optimization scheme for rainfalls of different return periods. Results show that optimized site-scale LID-BMPs can provide benefits for a range of rainfall intensities, but are especially effective for short-return-period rainfall.

Modeling Watershed‐Scale Impacts of Stormwater Management with Traditional versus Low Impact Development Design

AbstractStormwater runoff and associated pollutants from urban areas in the greater Chesapeake Bay Watershed (CBW) impair local streams and downstream ecosystems, despite urbanized land comprising only 7% of the CBW area. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner to treat stormwater runoff closer to its source. This approach included the development of a novel BMP model to compare traditional and LID design, pioneering the use of comprehensively digitized storm sewer infrastructure and BMP design connectivity with spatial patterns in a geographic information system at the watershed scale. The goal was to compare total watershed pollutant removal efficiency in two study watersheds with differing spatial patterns of BMP design (traditional and LID), by quantifying the improved water quality benefit of LID BMP design. An estimate of uncertainty was included in the modeling framework by using ranges for BMP pollutant removal efficiencies that were based on the literature. Our model, using Monte Carlo analysis, predicted that the LID watershed removed approximately 78 kg more nitrogen, 3 kg more phosphorus, and 1,592 kg more sediment per square kilometer as compared with the traditional watershed on an annual basis. Our research provides planners a valuable model to prioritize watersheds for BMP design based on model results or in optimizing BMP selection.

Influence of land development on stormwater runoff from a mixed land use and land cover catchment

Mitigating for the negative impacts of stormwater runoff is becoming a concern due to increased land development. Understanding how land development influences stormwater runoff is essential for sustainably managing water resources. In recent years, aggregate low impact development-best management practices (LID-BMPs) have been implemented to reduce the negative impacts of stormwater runoff on receiving water bodies. This study used an integrated approach to determine the influence of land development and assess the ecological benefits of four aggregate LID-BMPs in stormwater runoff from a mixed land use and land cover (LULC) catchment with ongoing land development. It used data from 2011 to 2015 that monitored 41 storm events and monthly LULC, and a Personalized Computer Storm Water Management Model (PCSWMM). The four aggregate LID-BMPs are: ecological (S1), utilizing pervious covers (S2), and multi-control (S3) and (S4). These LID-BMPs were designed and distributed in the study area based on catchment characteristics, cost, and effectiveness. PCSWMM was used to simulate the monitored storm events from 2014 (calibration: R2 and NSE>0.5; RMSE <11) and 2015 (validation: R2 and NSE>0.5; RMSE <12). For continuous simulation and analyzing LID-BMPs scenarios, the five-year (2011 to 2015) stormwater runoff data and LULC change patterns (only 2015 for LID-BMPs) were used. Results show that the expansion of bare land and impervious cover, soil alteration, and high amount of precipitation influenced the stormwater runoff variability during different phases of land development. The four aggregate LID-BMPs reduced runoff volume (34%–61%), peak flow (6%–19%), and pollutant concentrations (53%–83%). The results of this study, in addition to supporting local LULC planning and land development activities, also could be applied to input data for empirical modeling, and designing sustainable stormwater management guidelines and monitoring strategies.

Indicator and Pathogen Removal by Low Impact Development Best Management Practices

Microbial contamination in urban stormwater is one of the most widespread and challenging water quality issues in developed countries. Low impact development (LID) best management practices (BMPs) restore pre-urban hydrology by treating and/or harvesting urban runoff and stormwater, and can be designed to remove many contaminants including pathogens. One particular type of LID BMP, stormwater biofilters (i.e., vegetated media filters, also known as bioinfiltration, bioretention, or rain gardens), is becoming increasingly popular in urban environments due to its multiple co-benefits (e.g., improved hydrology, water quality, local climate and aesthetics). However, increased understanding of the factors influencing microbial removal in biofilters is needed to effectively design and implement biofilters for microbial water quality improvement. This paper aims to provide a holistic view of microbial removal in biofilter systems, and reviews the effects of various design choices such as filter media, vegetation, infauna, submerged zones, and hydraulic retention time on microbial removal. Limitations in current knowledge and recommendations for future research are also discussed.

Redox Dynamics and Oxygen Reduction Rates of Infiltrating Urban Stormwater beneath Low Impact Development (LID)

Low impact development (LID) best management practices (BMPs) collect, infiltrate, and treat stormwater runoff, and increase recharge to aquifers. Understanding the controls on reduction/oxidation (redox) conditions within LID BMPs is important for groundwater management because outflow from some LID BMPs can recharge aquifers and affect groundwater quality. Here we evaluate redox conditions of urban stormwater runoff in a LID infiltration trench in San Francisco, California, and quantify the relation between water saturation (%) and temperature (◦C) and resulting dissolved oxygen (DO) concentrations, redox dynamics, and O2 reduction rates. The DO fluctuations ha ve an inverse response to the duration of saturation of the trench. Anoxic (&lt;0.5 mg/L) conditions often occurred within hours of stormwater events and persisted from a few hours to two days, which indicate that microbial respiration can be a limiting factor for DO. Temperature of stormwater runoff was not a statistically significant control on DO. The estimated O2 reduction rate is 0.003mg·L-1·min-1, which is two to five orders of magnitude higher than in groundwater from previous studies. Higher rates of O2 reduction are a function of the more toxic and organic-rich stormwater runoff that drives faster microbial O2 reduction. Our findings have important implications for the design of infiltration trenches and other LID BMPs to achieve desired redox conditions for infiltrating stormwater toward minimizing groundwater contamination.

Multiobjective, Socioeconomic, Boundary-Emanating, Nearest Distance Algorithm for Stormwater Low-Impact BMP Selection and Placement

AbstractStormwater low-impact development (LID) has become an important method for the reduction of stormwater runoff emanating from impervious surfaces to local water bodies. The extra runoff from human-made impervious surfaces overloads water bodies with polluted runoff. Since many LID best management practices (BMPs) exist, and many areas have multiple subcatchments, it is important to carefully select which BMPs to place in each subcatchment and its placement in order to minimize cost, but also to give the highest chance of owner BMP maintenance. LID BMPs are often constructed on private land and maintenance can be at the owner’s expense and, therefore, not guaranteed. A new algorithm, entitled multi-objective, socio-economic, boundary-emanating, nearest distance (MOSEBEND), that is easily used by practitioners is introduced and demonstrated here for a road in a community showing that the algorithm allows the selection of the set of BMPs on the various subcatchments with the lowest cost, highest runof...

LID-BMPs planning for urban runoff control and the case study in China

Low Impact Development Best Management Practices (LID-BMPs) have in recent years received much recognition as cost-effective measures for mitigating urban runoff impacts. In the present paper, a procedure for LID-BMPs planning and analysis using a comprehensive decision support tool was proposed. A case study was conducted to the planning of an LID-BMPs implementation effort at a college campus in Foshan, Guangdong Province, China. By examining information obtained, potential LID-BMPs were first selected. SUSTAIN was then used to analyze four runoff control scenarios, namely: pre-development scenario; basic scenario (existing campus development plan without BMP control); Scenario 1 (least-cost BMPs implementation); and, Scenario 2 (maximized BMPs performance). A sensitivity analysis was also performed to assess the impact of the hydrologic and water quality parameters. The optimal solution for each of the two LID-BMPs scenarios was obtained by using the non-dominated sorting genetic algorithm-II (NSGA-II). Finally, the cost-effectiveness of the LID-BMPs implementation scenarios was examined by determining the incremental cost for a unit improvement of control.

Urban recharge beneath low impact development and effects of climate variability and change

[1] Understanding low impact development (LID) planning and best management practices (BMPs) effects on recharge is important because of the increasing use of LID BMPs to reduce storm water runoff and improve surface-water quality. LID BMPs are microscale, decentralized management techniques such as vegetated systems, pervious pavement, and infiltration trenches to capture, reduce, filter, and slow storm water runoff. Some BMPs may enhance recharge, which has often been considered a secondary management benefit. Here we report results of a field and HYDRUS-2D modeling study in San Francisco, California, USA to quantify urban recharge rates, volumes, and efficiency beneath a LID BMP infiltration trench and irrigated lawn considering historical El Nino/Southern Oscillation (ENSO) variability and future climate change using simulated precipitation from the Geophysical Fluid Dynamic Laboratory (GFDL) A1F1 climate scenario. We find that in situ and modeling methods are complementary, particularly for simulating historical and future recharge scenarios, and the in situ data are critical for accurately estimating recharge under current conditions. Observed (2011–2012) and future (2099–2100) recharge rates beneath the infiltration trench (1750–3710 mm yr−1) were an order of magnitude greater than beneath the irrigated lawn (130–730 mm yr−1). Beneath the infiltration trench, recharge rates ranged from 1390 to 5840 mm yr−1 and averaged 3410 mm yr−1 for El Nino years (1954–2012) and from 1540 to 3330 mm yr−1 and averaged 2430 mm yr−1 for La Nina years. We demonstrate a clear benefit for recharge and local groundwater resources using LID BMPs.

Development of a multi-criteria index ranking system for urban runoff best management practices (BMPs) selection

Low impact development best management practices (LID-BMPs) are considered to be cost-effective measures for mitigating the water quantity and quality impact of urban runoff. Currently, there are many types of LID-BMPs, and each type has its own intrinsic technical and/or economical characteristics and limitations for implementation. The selection of the most appropriate BMP type(s) for a specific installation site is therefore a very important planning step. In the present study, a multi-criteria selection index system (MCIS) for LID-BMP planning was developed. The selection indexes include 12 first-level indices and 26 second-level indices which reflect the specific installation site characteristics pertaining to site suitability, runoff control performance, and economics of implementation. A mechanism for ranking the BMPs was devised. First, each individual second-level index was assigned a numeric value that was based on site characteristics and information on LID-BMPs. The quantified indices were normalized and then integrated to obtain the score for each of the first-level index. The final evaluation scores of each LID-BMP were then calculated based on the scores for the first-level indices. Finally, the appropriate BMP types for a specific installation site were determined according to the rank of the final evaluation scores. In order to facilitate the application of the MCIS BMP ranking system, the computational process has been coded into a software program, BMPSELEC. A case study demonstrating the MCIS methodology, using an LID-BMP implementation planning at a college campus in Foshan, Guangdong Province, is presented.

Planning of LID–BMPs for urban runoff control: The case of Beijing Olympic Village

In this paper, a planning analysis of implementing low impact development (LID) type of stormwater best management practices (BMPs) for urban runoff control is presented. The Beijing Olympic Village (BOV) residential area in China was used as a case study. The original BOV stormwater system incorporated some LID BMPs such as porous pavements, green roofs and rainwater cisterns. After the 2008 Olympics, the BOV was converted to a residential complex and some stormwater facilities were modified for landscaping purposes. The performance of the original stormwater management system at the BOV residential area was first evaluated by using the model BMPDSS. BMPDSS is a best management practice (BMP) planning and analysis tool, which is capable of simulating BMP performance and optimizing BMP placement and design. The Storm Water Management Model (SWMM) was used to simulate pipe network hydraulics for the BOV. The present study then examined the performance associated with the BMP modifications for landscaping purposes, and then further BMP modifications designed for enhancing runoff control capabilities of the system. Using the 2008 rainfall data for Beijing, peak flow rate and runoff volume reductions under the three scenarios were calculated by using the coupled SWMM–BMPDSS framework and compared. Optimization analysis for BMP design aimed at achieving either maximum runoff control or total minimum system cost was then conducted. The results were used to form recommendations to the Beijing authorities for modifying the present stormwater management system in order to achieve more runoff control benefits.