Green Infrastructure Practices Research Articles

BiodiverseCity St. Louis—An Initiative of the Missouri Botanical Garden

Botanical gardens are addressing urgent biodiversity issues through plant-based capacities including botanical research and data-sharing, conservation horticulture, ecological restoration, seed banking, and more. The Missouri Botanical Garden initiative BiodiverseCity St. Louis, led by the Garden’s sustainability division, adds broad community engagement to this mix. This work includes public and professional education, the demonstration and promotion of ecological landscaping and Green Infrastructure practices, citizen science programs, and coordinating communications for a regional network of partner organizations focused on biodiversity. Diverse activity engages businesses, local governments, elementary and secondary (K-12) schools, colleges, and community groups. Community biodiversity work at the Garden is informed by an institutional core of scientific rigor, provides opportunity for internal collaborations, and aligns with global strategies for plant conservation—to ground impactful local work. Missouri Botanical Garden’s experience offers a model for public gardens: leveraging modes of community engagement, in concert with diverse institutional strengths, to address biodiversity needs.

The Potential of Stormwater Management Strategies and Artificial Intelligence Modeling Tools to Improve Water Quality: A Review

AbstractStormwater management modeling tools have been utilized to enhance stormwater operating systems, assess modeling system efficiency, and evaluate the impacts of urban growth on stormwater runoff and water quality. This review explores the potential of stormwater management strategies and Artificial Intelligence modeling tools in enhancing water quality. The study focuses on evaluating stormwater modeling tools for planning and improving stormwater systems, assessing modeling efficiency, and understanding the impacts of new development on stormwater runoff and water quality. Various stormwater modeling tools are compared to aid in water management in urban and rural settings, which is crucial due to increasing storm intensity from climate change. The review debates the advantages and limitations of different modeling tools, particularly in modeling stormwater quantity and quality under different scenarios. It also examines tools used for predicting and analysing stormwater runoff during storm events in diverse locations. The assessment of modeling tools is centred on their support for Green Infrastructure (GI) practices, considering factors like modeling accuracy, data availability, and requirements. The study highlights the importance of these tools in managing water in urban areas and safeguarding water sources during stormwater events. Notably, the accuracy and efficacy of stormwater modeling tools are influenced by input data quality, calibration methods, and standardization metrics, with the widely used Stormwater Management Model (SWMM) being a common modeling tool.

Coalitional Game Theory for Stormwater Management and Green Infrastructure Practices

Coalitional Game Theory for Stormwater Management and Green Infrastructure Practices

Green Infrastructure Practices for Improving Urban Sustainability

Dünya nüfusunun 30 yıl içinde %70’inin kentlerde yaşayacağı ve kentsel alanların da üç kat artacağı öngörülmektedir. Nüfus artışı ile birlikte, dünyada giderek artan plansız kentleşme ve doğal kaynakların tüketimi, iklim değişikliği etkilerinin kent ekosistemleri üzerinde daha kalıcı hasarlar bırakacağı öngörülmektedir. Kentsel sürdürülebilirlik ekolojik, mekânsal, ekonomik ve sosyal sürdürülebilirliğin sağlanmasına bağlıdır. Bu kapsamda, yeşil altyapı sistemleri, hızla büyümekte olan kentleri iklim değişikliğine uyumlu sürdürülebilir kentler haline getirebilmek amacıyla benimsenmiş yapısal çözümlerden biridir. Yeşil altyapı sistemleri aracılığıyla kentlerin ekolojik ve sosyal problemlerine doğa tabanlı çözümler üretilirken, insanların doğaya olan erişimleri kolaylaştırılmakta ve uzun vadede ekonomik kazanımlar sağlanmaktadır. Bu çalışmada kentsel sürdürülebilirlik hedefi ve kentsel yeşil altyapı planlaması, çoklu fonksiyonellik, bağlantılık, entegrasyon, sosyal iletişim ve sürdürülebilirlik ilkeleri doğrultusunda farklı kıtalardaki beş kıyı kentinde sorgulanmaktadır.
 Bu çalışmada yeşil altyapı planlaması,çoklu fonksiyonellik, bağlantılılık, entegrasyon, sosyal iletişim ve sürdürülebilirlik ilkeleri doğrultusunda farklı kıtalardaki beş kıyı kentinde sorgulanmaktadır.Kentlerin benimsediği planlama stratejileri kapsamında uygulanan yeşil altyapı sistemleri arasındaki benzerlik ve farklılıklar doğrultusunda elde edilen kazanımlar, ilgili kentlerin yerel koşullarına göre değişim gösterebilmektedir. İrdelenen kent örneklerinde yeşil altyapı sistemleri uygulamalarından kısa, orta ve uzun vadede olumlu kazanımlar sağlanmıştır.

Determining social-psychological drivers of Texas Gulf Coast homeowners’ intention to implement private green infrastructure practices

Green infrastructure (GI) has been demonstrated to be an efficient flood mitigation measure and an effective approach for building community resilience, especially in the context of climate change. Drawing on Protection Motivation Theory, this study offers insight into the factors influencing residents' intention to implement individual GI practices by homeowners along the Texas Gulf Coast. The GI practices examined included the potential installation of (1) green roofs, (2) rain barrels, (3) rain gardens, (4) permeable pavement, and (5) tree protection and planting. Our findings revealed that homeowners expressed little interest in adopting GI practices owing to the lack of information, absence of incentives, and guidance on how to implement GI practices. Moreover, the findings from our modeling confirmed that perceptions of the effectiveness and cost of GI had the strongest influence on respondents’ intention to implement GI. Other significant indicators such as threat appraisal, reliance on public flood protection, perceived co-benefits, age, and the number of children varied with specific GI practices. These findings provide valuable information for city policymakers and planners in coastal regions concerning the promotion and development of GI that can meet the needs of their residents, provide the impetus for implementation, and in turn, contribute to community resilience.

Practical Tool for the Design and Cost Optimization of Permeable Pavements in the Planning Stage of Stormwater Management

To address issues created by increased stormwater runoff, there is growing interest in sustainable tools such as permeable pavement (PP), which is a green infrastructure (GI) practice. This paper outlines the development and application of a design tool called the “cost optimization tool for permeable pavements (COTPP).” This tool aims to help states, municipalities, and consultants design PPs using reliable hydrological and structural pavement design methods. The COTPP uses a cost optimization algorithm similar to a heuristic search that helps identify which combination of PPs, conventional pavement, and other GIs provides the most economic value. A sensitivity analysis was conducted using the tool, which consisted of designing the three main types of PP using varying design inputs and comparing the COTPP’s results to results from an existing design tool or guidelines. The average percent differences between the COTPP’s results and that of other methods were below 10% for the structural designs and around 15% for the hydrological designs. The differences were caused by the use of a safety factor in the hydrological design and other adjustments to design methods. It was concluded that the tool is reliable and can be confidently used by designers. The tool was then used for a representative case study site (PP parking lot) in which the actual design and cost estimates of on-site components were known. The COTPP was able to identify other design alternatives that helped reduce the actual construction cost of the existing parking lot from $305,918 to as low as $238,790.

Effects of watershed-scale green infrastructure retrofits on urban stormwater quality: A paired watershed study to quantify nutrient and sediment removal

Urban stormwater represents a substantial source of nutrients and sediment to aquatic ecosystems. Green infrastructure (GI), including bioretention and permeable pavement, is an increasingly utilized method to treat stormwater pollutants. Using soil and plants as natural filters, these systems are effective at the site scale, but little evidence exists regarding their performance at the watershed-scale. Blueprint Columbus is an effort by the City of Columbus, Ohio, USA to retrofit GI to eliminate sanitary sewer overflows and remove 20% of total suspended solids (TSS) from existing developed areas. Changes in water quality resulting from the combined effects of many GI practices installed in 11.5 and 47.8 ha treatment watersheds were quantified using a paired-watershed approach. Based on water quality data collected by automated samplers over a 3.5-year period, significant reductions in particulate and dissolved nutrients as well as sediment were observed following the installation of GI in both treatment watersheds compared to the control. Total nitrogen (TN), phosphorus (TP), and TSS concentrations decreased by 13.7–24.1%, 20.9–47.4%, and 61.6–67.7%, respectively. Runoff attenuation by GI contributed to pollutant load reductions of 24.0–25.4% (TN), 27.8–32.6% (TP), and 59.5–78.3% (TSS). Orthophosphate concentrations and loads increased in the watershed with bioretention only but significantly decreased in the treatment watershed with bioretention and permeable pavement. Reductions in TSS concentration were similar (within a margin of 5%) to the percent of the watershed imperviousness treated by GI. Results demonstrate that GI was effective in reducing runoff event mean concentrations and loads at the watershed-scale.

Convergence in Perceptions of Ecosystem Services Supports Green Infrastructure Decision-making in a Semi-arid City.

Effective management of cities using ecosystem services from green infrastructure (GI) requires explicit consideration of the linkages between provision of services and ecosystem service demands (i.e., governance priorities). Identification of stakeholder knowledge and objectives in GI decision-making contexts with respect to ecosystem services may improve urban planning; yet this information is rarely explicit in local contexts and cases. We address this gap by surveying environmental stakeholders and practitioners to investigate how perceptions of ecosystem services influence GI practice in Tucson, AZ. Results indicate that the semi-arid environment and urban design led to prioritizations that focus on water sustainability and urban heat mitigation. We found strong agreement in environmental perceptions between different management sectors. We observed matches (as well as mismatches) between the ecosystem service priorities and important environmental issues. Ecosystem services prioritization revealed a unique classification of ecosystem services that reflects stakeholder priorities. Our findings suggest the study of ecosystem services supply and demand can inform local urban management. These findings from a semi-arid city further suggest that understanding stakeholder knowledge, perceptions, and priorities should be important for cities in other regions where GI is being implemented as an environmental solution to provide ecosystem services.

Editorial: Special Issue on Smart and Green Infrastructures with Optimum Life Cycle Solutions

Abstract There are successful projects in many different countries using green infrastructure approaches to reduce imperviousness and preserve natural open space throughout a watershed and at the neighborhood scale, as well as adding green infrastructure practices at the site level. Intensive development of structures and the necessary supporting infrastructure is ongoing throughout the world. Although most of the urban areas are already densely settled with buildings above and below the ground, there is still a pressing need to construct new structures between or beneath the existing ones. In addition, topics such as recycling and warm mix asphalts are of interest for this special issue. This special issue on Smart and Green Infrastructures with Optimum Life Cycle Solutions in ASTM International’s Journal of Testing and Evaluation contains 27 papers. All papers in this special issue can provide a repository of the state-of-the-art research outcomes and state-of-the-practice case studies on smart and green infrastructures with optimum life cycle solutions. A wide range of topics are covered in this special issue, which advances the domain of smart and green infrastructures. The research topics in the issue include soil and rock, asphalt mixtures, asphalt mixtures, and fly ash as well as the innovative technologies for the application of novel materials in earthworks, accelerated infrastructure construction, and improvement of decision-making performance for infrastructures. This special issue offers a platform for sharing the latest results on the resiliency and green technologies of civil infrastructures. Typical topics include investigations related to civil infrastructures such as road construction, drainage system, tunnel project, and high fill slope. In addition, a number of civil and transportation materials related to geotechnical aspects of infrastructure are scientifically examined. This information should lead to more resilient infrastructure design, maintenance, and management. The rapid construction of urban infrastructure and transportation engineering facilitates the demand for green building materials and geotechnical materials. There are 11 papers involving building materials and geotechnical materials–related topics, including Gobi gravel soils (GGS), roller compacted concrete (RCC), fly ash, Montmorillonite Indian clay, and frozen soils. Among them, some novel materials have been testified and their engineering characteristics have been explored in four papers. Chen et al. studied the unconfined compressive strength of soils stabilized via gypsum-slag curing agent and cement. The authors developed the relationship between apparent porosity and unconfined compressive strength based on Python image processing method and concluded that the presence of the gypsum-slag hardening agent changes the microstructure and increases the unconfined compressive strength of the original soils. Wu and Li evaluated a novel high-performance solidified soil material from various perspectives including mechanical, water resistance, and antifrost performance. The authors noted that the 7 days unconfined compressive strength of this novel material had been enhanced by about 2 to 3 times compared with that of cement-stabilized aggregates. The results can offer some suggestions for the construction of a low-grade highway. The work of Le et al. focuses on the possibility of utilizing locally available soil in a lightweight foamed concrete mixture as an alternative sustainable solution. The authors observed that air foam content noticeably improves the self-leveling of backfill material, and it should be added lower than 20 % in order to ensure sufficient strength gain. To accurately quantify unfrozen water content in frozen soils, Ren et al. adopted the frequency domain reflectometry technique to measure the unfrozen water content of the prepared soil specimens. It was claimed that neither of the freeze-thaw cycles nor the freezing or thawing methods had significant impact on the measured soil-freezing characteristic curve. Regarding the improvement of concrete material performance, Au and Nam assessed the in situ and full-scale performance of recycled concrete aggregate (RCA), which is utilized as a pipe bedding and backfill material. Their research was based on both laboratory and field experiments and explored the exfiltration subdrainage performance of each RCA French drainage system. They demonstrated that RCA could be utilized as a subdrainage material and avoided a significant reduction in drainage system exfiltration performance compared with traditional materials (limestone). The work of Yao et al. extensively investigates the essential factors affecting pressure bleeding rate for high-strength concrete with good fluidity. Moreover, they suggested that some bleeding improvement measures and an appropriate mix ratio can obtain better performance for high-strength concrete. The work of Zhong et al. provides a comprehensive knowledge of the optimum workability of RCC. The authors reported the Vebe consistency decreased with the increase of the water-cement ratio. Furthermore, they found the optimal range of cement slurry surplus parameter was about 1.1 to 1.4 and the optimal range of cement mortar surplus parameter was about 1.2 to 1.6. An optimal sand ratio was also given, which had a prominent impact on RCC. To improve the engineering characteristics of expansive soil, Singh et al. utilized scanning electron microscope (SEM) and X-ray diffraction to study the mineralogical characteristics for both natural samples and reconstituted samples and investigated the different proportions of fly ash affecting the deformation behavior of expansive Montmorillonite Indian clay. Syed et al. used alkali-activated binder to enhance the subgrade strength characteristics of the expansive soil, and four types of fibers (polypropylene, glass, hemp, and coir fiber) are also selected to reinforce the expansive soil. Besides, the authors established a nonlinear regression model to predict the subgrade strength failure based on Monte Carlo simulation. They reported that the optimum dosages of fiber reinforcement and slag (or fly ash) are key factors for regulating the volumetric instability and tensile cracks of expansive soil. Lou et al. surveyed another modifier, superhydrophobic nano-SiO2, to improve the geotechnical characteristics of expansive soil. According to their laboratory test results, the optimum superhydrophobic nano-SiO2 content was 0.6 %. The study of Cai et al. focuses on improving the performance of impermeable bentonite to meet the requirements of low permeability, high chemical resistance, and strong adsorption performance. The authors explored the morphological changes and microstructure of raw bentonite and sodium polyacrylate (SPB) with various Cu2+ concentrations via SEM. They mentioned that the SPB could enhance the antiseepage ability and chemical resistance of bentonite as well as improve the adsorption of heavy metals. Topics related to recent developments in geotechnical engineering are discussed in three papers. Two are related to slope engineering stability, and the other one is related to underground construction. Wan et al. conducted a series of large-scale triaxial tests on GGS to investigate the influencing factors on its mechanical behavior, including coarse content, degree of compaction, and confining pressure. The authors evaluated the effects of slope angle and geotextiles on the safety factor. They also suggested the optimal value of slope angle and the optimum geotextiles reinforcement. The research of Xin et al. aims to study the characteristics and distribution of geological hazards along the pipeline. The authors conducted a case study on the basis of pipeline landslide hazard monitoring and data analysis technologies. They concluded that rainfall may cause concentrated stress and deformation of the pipeline, thereby causing a landslide. In a separate study, Jiang et al. performed a correlation analysis of rock mass properties and tunnel boring machine (TBM) parameters on the basis of the field data obtained from the Yin-song headrace tunnel in China. The authors built a statistical prediction model to perform the prediction of penetration rate through multivariate linear regression analysis, which can provide some constructive suggestions on the low life cycle cost of a TBM. Maintenance, rehabilitation, structural health, life cycle management, remediation techniques, safety assessment, and pavement management decision-making are other areas covered in this special issue and are discussed in five research articles. Chen et al. analyzed pavement maintenance and rehabilitation (M&R) activities by introducing belief function theory, which proposed a precise and straightforward method to assist engineers in conducting M&R decision-making. The research of Steyn and Broekman proposed a novel framework based on Digital Twins technology. By integrating the environmental monitoring, physical, surface temperature, and management data, the authors provide references for assisting the maintenance of roads. Qiu et al. established a numerical model of a typical subgrade structure under the action of a snowdrift by including in the scope of the influence of a typical roadbed structure. The authors conducted numerical simulations by computational fluid dynamics method to testify the influence of the motion characteristics of snow particles on the flow field. Yuan et al. gave a new perspective to monitor the structural health of infrastructure through introducing the digital zenith tube, which was evolved on the basis of the astrogeodetic and photogrammetric theory. Omar et al. evaluated the influence of the in situ precontamination moisture content on the performance of fine-grained soil contaminated with various levels of used engine oil. The authors reported that knowledge of site moisture levels before contamination is vital to assess the influence of contamination by the engine oil. Eight papers in this special issue are related to the design life, resilient modulus measurement, pavement construction, subbase, and bridges. The work by Zhong et al. studies the design methods for the mix ratio of RCC during the construction process of the Qinglian highway rehabilitation project. In order to find out the optimal value of the mix ratio, the orthogonal test method was adopted. An optimal amount of cement was given by the authors, which can reduce the occurrence of road distresses on the premise of meeting the strength requirements. These results may combine the practical project with a mixture ratio design and use the indicators recommended in the design process. The work of Yang focuses on the correction of piston friction before conducting a resilient modulus test by utilizing an external load cell. The author assessed the effects of piston friction on the resilient modulus of residual lateritic soils compacted at optimum moisture content and built the correction procedures based on test findings. Lai et al. emphasized bridging the gap between the difference in laboratory and field compaction and developing a quick and economical method for the quality control of backfills. They designed a rotary compactor and a miniature dynamic cone penetrometer to compact the soil samples with different water contents. The study by Tapase et al. works on the perfection of the analysis and design process for flexible pavement by considering a variety of materials to be used in different layers of pavement. The authors demonstrated the method by depicting the design charts under the consideration of comprehensive factors with various natures, which may exhibit a more ecofriendly and economic framework. Focusing on dealing with the rutting of asphalt pavement, Zhang et al. explored a new antirutting asphalt mixture that contains seven different materials. In addition, the authors demonstrated that the Chinese rutting test was more suitable for high-modulus asphalt mixture, and improving the high temperature stability of the asphalt mixture can slow down the attenuation of the antishipping property. Huang et al. designed and molded four types of asphalt mortar specimens with different aggregates to investigate the influence of limestone, basalt, diabase, and steel slag on the road performance of asphalt mortar. They noted that basalt asphalt mortar exhibited the best comprehensive pavement performance. The work by Ashfaq et al. focuses on assessing the unconfined compressive strength characteristics of lime and gypsum-treated coal gangue. The authors utilized target reliability-based design optimization to assess the optimal amounts of lime and gypsum content for the satisfactory performance of pavements. Moreover, for accelerated bridge construction, the study of Xiang et al. focuses on the varyingly grout aged specimens and performed laboratory tests to analyze the interior failure modes of specimens by industrial computed tomography detecting technology. The authors proposed a numerical model related to grout age and the stress-slip. Last but not least, we would like to sincerely thank the reviewers for their thoughtful comments and efforts toward improving the scientific quality of articles in this special issue. This special issue is expected to play an essential role in advancing the boundary of geotechnical engineering, which can support decisions regarding the optimal management and maintenance of civil infrastructures to provide a smarter and greener life cycle solution for geotechnical engineering practitioners.

Citizens’ preferences on green infrastructure practices and their enhancement in Portland, Oregon

Green infrastructure (GI) has been gaining increasing attention due to its efficiency in controlling and purifying urban stormwater runoff, creating environmental amenities, and biodiversity conservation. Nevertheless, the existing knowledge of people's preferences for GI is not yet sufficient for evidence-based policymaking for enhancing GI. This study analyzes citizens' perceptions of the relative importance of six GI practices and estimates their willingness to pay (WTP) to enhance them. To this end, the study applies two types of stated preference methods (best-worst scaling and contingent valuation) to citizen survey data collected in Portland, Oregon. We found that GI practices that are more likely to lead to private benefits (e.g., rain barrels, urban trees) received relatively higher ratings, whereas the ratings of practices that do not offer such benefits (e.g., bioswales, rain gardens) were relatively lower. However, the diversity of preferences was large, as the relative importance varied widely among respondents. Heterogeneous preferences were also found in terms of citizens' WTP for hypothetical GI enhancement. Our comparison of uniform and variable payment schemes revealed that variable payment outperformed uniform payment because of the significant variation in citizens' WTP. The difference was large when the annual household payment was small.

Tracking geomorphic changes after suburban development with a high density of green stormwater infrastructure practices in Montgomery County, Maryland

Stream morphology is affected by changes on the surrounding landscape. Understanding the effects of urbanization on stream morphology is a critical factor for land managers to maintain and improve vulnerable stream corridors in urbanizing landscapes. Stormwater practices are used in urban landscapes to manage runoff volumes and peak flows, potentially mitigating alterations to the flow regime that drive changes in channel morphology. However, there remains a paucity of long-term studies assessing watershed-scale relationships between urbanization and effects on stream morphology where green stormwater infrastructure exists in high densities. This paper evaluates the geomorphic changes across four headwater catchments in the Chesapeake Bay Watershed over the course of >10 yr and relates these changes to urban development. Annual cross-sectional surveys conducted from 2002 to 2019 in one forested catchment, one agricultural catchment, and two treatment catchments were used to understand the relationship between urbanization and changes in stream morphology. Six cross-sectional geomorphic metrics were calculated and compared with development timelines and high flow events. A channel evolution model was then used to understand the status of morphologic stability at sites within the study. Results suggest downstream environments in developing areas are more impacted during early phases of suburban construction. Channel change during construction could be a result of sediment and erosion control efforts' limitations on preventing and controlling overland sediment mobilization or of increased discharge causing widening and thus bank-derived sediment to move to the streambed. Results demonstrate that geomorphic metrics are highly variable within a small area and are not always accurate representations of broader landscape changes but rather of the more localized environment at a specific stream segment. Despite a high density of stormwater management facilities in urban catchments, substantial alterations to cross sections were found at multiple locations in each catchment including the controls.

A Bayesian modeling framework to predict stormwater pollutant reduction in bioretention media

Bioretention is a green stormwater infrastructure practice that has been shown to reduce some of the harmful effects of urban stormwater on downstream receiving waters. Typically, media used for bioretention consist of high percentages of sand to realize high hydraulic conductivities and smaller percentages of soil or organic materials to improve the retention of stormwater pollutants. The objectives of this study were to evaluate four bioretention media mixes that differed in sand, compost, and water treatment residuals content and to predict pollutant removal based on realistic stormwater concentrations using Bayesian statistics. Pollutants of interest were chemical oxygen demand, ammonia, nitrite, nitrate, total Kjeldahl nitrogen, as well as total and dissolved forms of phosphorus, copper, lead, and zinc. Water quality data were collected for eleven storms, and cumulative rainfall after construction was used as a measure for the media age. The data were evaluated for the probability to observe pollutant reduction and for the probability to observe high-performance reduction (HPR) with a minimum pollutant reduction of 60%. The chemical oxygen demand had a probability for reduction of P = 0.09 and HPR of P = 0.00, resulting in pollutant export in the majority of storms. HPR reduction goals were met for total lead, zinc, and copper, and reduction probabilities were generally P > 0.5 for all total and dissolved metals. Age and media composition affected phosphorus and nitrogen removal, with increased pollutant retention observed as the media aged. Lower compost percentages resulted in less nutrient export. This probabilistic model of realistic stormwater concentrations in combination with bioretention pollutant removal experiments results in a holistic view of credible pollutant outflow concentrations that can be used by stormwater managers to alleviate the effects of stormwater on surface water quality.

Seasonal Hydroclimatic and Soil Biogeochemical Drivers of N and P Availability in a Constructed Stormwater Wetland

Constructed stormwater wetlands are green stormwater infrastructure (GSI) practices with potential to treat stormwater nutrient pollution. GSI nutrient removal performance is controlled by GSI soil nutrient cycles, which depend on soil hydrologic and biogeochemical conditions. The objective of this study was to characterize spatial and temporal patterns in soil dissolved nutrients, and their relationships with soil conditions, at a constructed stormwater wetland in Milwaukee, Wisconsin. Ion exchange membranes were used to measure soil nutrient availability, which was combined with precipitation, air and soil temperature, soil moisture, and soil oxygen data. Nitrate was intermittent: 17% and 25% of the study period accounted for 50% and 67% of the total nitrate availability in the Upland and Lowland, respectively. Time-series data suggest this intermittency resulted from summertime N mineralization. Orthophosphate was higher in the well-aerated Upland than in the periodically anoxic Lowland with a larger contributing area. Regression results indicate that relationships between nutrient availability and environmental drivers depended on the nutrient and landscape position. Modeling spatiotemporal variability of GSI soil nutrient dynamics may improve system performance and prediction.

Quantifying the stormwater runoff volume reduction benefits of urban street tree canopy

Trees in the urban right-of-way areas have increasingly been considered part of a suite of green infrastructure practices used to manage stormwater runoff. A paired-catchment experimental design (with street tree removal as the treatment) was used to assess how street trees affect major hydrologic fluxes in a typical residential stormwater collection and conveyance network. The treatment consisted of removing 29 green ash (Fraxinus pennsylvanica) and two Norway maple (Acer platanoides) street trees from a medium-density residential area. Tree removal resulted in an estimated 198 m3 increase in surface runoff volume compared to the control catchment over the course of the study. This increase accounted for 4% of the total measured runoff after trees were removed. Despite significant changes to runoff volume (p ≤ 0.10), peak discharge was generally not affected by tree removal. On a per-tree basis, 66 L of rainfall per m2 of canopy was lost that would have otherwise been intercepted and stored. Runoff volume reduction benefit was estimated at 6376 L per tree. These values experimentally document per-capita retention services rendered by trees over a growing season with 42 storm events. These values are within the range reported by previous studies, which largely relied on simulation. This study provides catchment scale evidence that reducing stormwater runoff is one of many ecosystem services provided by street trees. This study quantifies these services, based on site conditions and a mix of deciduous species, and serves to improve our ability to account for this important yet otherwise poorly constrained hydrologic service. Engineers, city planners, urban foresters, and others involved with the management of urban stormwater can use this information to better understand tradeoffs involved in using green infrastructure to reduce urban runoff burden.

Statistical modelling of hydrological performance in a suite of green infrastructure practices.

Statistical modelling procedures (feature selection in conjunction with multiple linear regressions) were applied to determine the performance of a suite of stormwater green infrastructures (GIs) installed at the Belknap Campus of the University of Louisville. Two separate multiple linear regression models (MLRMs) were developed and calibrated to estimate the reductions of the flow regime parameters (flow volume and peak flow rates) within the down-gradient combined sewer system (CSS). The developed MLRMs showed that wet-weather-related CSS flow was mitigated post implementation of the stormwater GIs. At the down-gradient combined sewer flow-monitoring site, the average reduction rates of flow volume and the peak flow were estimated to be 22 and 63% per rainfall event, respectively. Unlike the black-box nature of most machine-learning techniques, the MLRM has the advantage of showing the unique statistical relationship between the rainfall features and the investigated CSS flow parameters. The results from this study indicate that proper statistic modelling can be applied effectively to evaluate the hydrological performance of stormwater management practices when lacking instrumentation and having limited drainage or sewer information.

GIS-based air quality modelling: spatial prediction of PM10 for Selangor State, Malaysia using machine learning algorithms.

Rapid urbanization has caused severe deterioration of air quality globally, leading to increased hospitalization and premature deaths. Therefore, accurate prediction of air quality is crucial for mitigation planning to support urban sustainability and resilience. Although some studies have predicted air pollutants such as particulate matter (PM) using machine learning algorithms (MLAs), there is a paucity of studies on spatial hazard assessment with respect to the air quality index (AQI). Incorporating PM in AQI studies is crucial because of its easily inhalable micro-size which has adverse impacts on ecology, environment, and human health. Accurate and timely prediction of the air quality index can ensure adequate intervention to aid air quality management. Therefore, this study undertakes a spatial hazard assessment of the air quality index using particulate matter with a diameter of 10 μm or lesser (PM10) in Selangor, Malaysia, by developing four machine learning models: eXtreme Gradient Boosting (XGBoost), random forest (RF), K-nearest neighbour (KNN), and Naive Bayes (NB). Spatially processed data such as NDVI, SAVI, BU, LST, Ws, slope, elevation, and road density was used for the modelling. The model was trained with 70% of the dataset, while 30% was used for cross-validation. Results showed that XGBoost has the highest overall accuracy and precision of 0.989 and 0.995, followed by random forest (0.989, 0.993), K-nearest neighbour (0.987, 0.984), and Naive Bayes (0.917, 0.922), respectively. The spatial air quality maps were generated by integrating the geographical information system (GIS) with the four MLAs, which correlated with Malaysia's air pollution index. The maps indicate that air quality in Selangor is satisfactory and posed no threats to health. Nevertheless, the two algorithms with the best performance (XGBoost and RF) indicate that a high percentage of the air quality is moderate. The study concludes that successful air pollution management policies such as green infrastructure practice, improvement of energy efficiency, and restrictions on heavy-duty vehicles can be adopted in Selangor and other Southeast Asian cities to prevent deterioration of air quality in the future.

The Impacts of Climate Change and Porous Pavements on Combined Sewer Overflows: A Case Study of the City of Buffalo, New York, USA

Combined sewer overflows (CSOs) release pollutants collected in urban runoff into local waterways, impacting both aquatic life and human health. The impact of climate change on precipitation may result in an increase in the frequency and magnitude of heavy precipitation events, with a corresponding increase in CSO discharges. The installation of Green Infrastructure (GI) such as Porous Pavements (PP) is a resilient approach to mitigate CSO events. However, an understanding of the impact of climate change on CSO events and the effectiveness of GI practices is crucial for designing sustainable urban stormwater management systems. Using the Storm Water Management Model (SWMM), the performance of PP as a CSO abatement strategy was studied for the city of Buffalo, New York, USA. This paper used the Intensity-Duration-Frequency (IDF) curves for current (1970–1999) and future (2070–2099) design rainfall scenarios, with four rainfall durations (1, 6, 12, and 24 hours) and four return periods (2, 10, 50, and 100 years). The simulation results show that (1) current 100-year events generate CSO volumes similar to predicted 50-year events; (2) CSO volumes could increase by 11–73% in 2070–2099 compared to 1970–1999 when no GI intervention is performed; and (3) the installation of PP can reduce 2–31% of future CSO volume. This case study demonstrates the regional CSO challenges posed by climate change and supports the use of GI as a mitigation strategy.

Green infrastructure influences soil health: Biological divergence one year after installation

Global threats to soils remain one of the greatest concerns and challenges of the 21st century. Built landscapes have profound local and global effects because they create urban heat islands, increase habitat fragmentation, and reduce biological diversity. Additionally, impervious surfaces alter natural watersheds and reduce infiltration increasing runoff that leads to erosion and soil degradation. To combat these effects, green infrastructure (GI) practices, like water harvesting rain gardens, are implemented in the Southwest United States to restore natural ecological function, yet little is known about how GI impacts soil health. Soil health can be measured using indicators that include physical, chemical, and biological characteristics that support ecosystem processes. This study aimed to evaluate changes in water holding capacity, bulk density, pH, electrical conductivity, Gibbs free energy, species richness and Shannon diversity in response to rain gardens that received different inputs (frequency and amount) and sources of harvested water (rain, municipal, greywater) one year after installation. We hypothesized that soil health indicators in GI diverge from the unaltered control treatment one year following installation. Although physical and chemical indicators were comparatively less sensitive to GI treatments than biological indicators, they varied within treatments after one year of GI management (pH increased: H = 36.37; p-value = 0.00; electrical conductivity decreased: H = 33.94; p-value = 0.00). Overall, we observed significantly higher soil microbial diversity (F = 4.29; p-value = 0.015) and richness (F = 4.02; p-value = 0.019) in surface soils in GI treatments after one year of management. Our findings suggest GI practices enhanced soil biological health which may lead to positive feedbacks that assist gradual changes in the abiotic environment thus enhancing soil health over time. These findings have broad implications for effectively assessing the success of GI management practices over short time periods using soil biological health indicators.

Multi-Objective Model-Based Assessment of Green-Grey Infrastructures for Urban Flood Mitigation

This paper presents the performance quantification of different green-grey infrastructures, including rainfall-runoff and infiltration processes, on the overland flow and its connection with a sewer system. The present study suggests three main components to form the structure of the proposed model-based assessment. The first two components provide the optimal number of green infrastructure (GI) practices allocated in an urban catchment and optimal grey infrastructures, such as pipe and storage tank sizing. The third component evaluates selected combined green-grey infrastructures based on rainfall-runoff and infiltration computation in a 2D model domain. This framework was applied in an urban catchment in Dhaka City (Bangladesh) where different green-grey infrastructures were evaluated in relation to flood damage and investment costs. These practices implemented separately have an impact on the reduction of damage and investment costs. However, their combination has been shown to be the best action to follow. Finally, it was proved that including rainfall-runoff and infiltration processes, along with the representation of GI within a 2D model domain, enhances the analysis of the optimal combination of infrastructures, which in turn allows the drainage system to be assessed holistically.

Hydrological Modeling of Green Infrastructure to Quantify Its Effect on Flood Mitigation and Water Availability in the High School Watershed in Tucson, AZ

Green Infrastructure (GI) practices are being implemented in numerous cities to tackle stormwater management issues and achieve co-benefits such as mitigating heat island effects and air pollution, as well as water augmentation, health, and economic benefits. Tucson, Arizona is a fast-growing city in the semiarid region of the southwest United States and provides a unique landscape in terms of urban hydrology and stormwater management, where stormwater is routed along the streets to the nearest ephemeral washes. Local organizations have implemented various GI practices, such as curb cuts, traffic chicanes, roof runoff harvesting, and retention basins, to capture the excess runoff and utilize it on-site. This study models the 3.31 km2 High School watershed in central Tucson using the Automated Geospatial Watershed Assessment (AGWA) tool and the Kinematic Runoff and Erosion (KINEROS2) model. Each parcel in the watershed was individually represented using the KINEROS2 Urban element to simulate small-scale flow-on/flow-off processes. Seven different configurations of GI implementation were simulated using design storms, and we stochastically generated 20 years of precipitation data to understand the effects of GI implementation on flood mitigation and long-term water availability, respectively. The design storm analysis indicates that the configuration designed to mimic the current level of GI implementation, which includes 175 on-street basins and 37 roof runoff harvesting cisterns, has minimum (<2%) influence on runoff volume. Furthermore, the analysis showed that the current level of GI implementation caused an increase (<1%) in peak flows at the watershed outlet but predicted reduced on-street accumulated volumes (>25%) and increased water availability via GI capture and infiltration. When the GI implementation was increased by a factor of two and five, a larger reduction of peak flow (<8% and <22%, respectively) and volume (<3% and <8%, respectively) was simulated at the watershed outlet. The 20-year analysis showed that parcels with roof runoff harvesting cisterns were able to meet their landscape irrigation demands throughout the year, except for the dry months of May and June. Additionally, stormwater captured and infiltrated by the on-street basins could support xeric vegetation for most of the year, except June, where the water demand exceeded volume of water infiltrated in the basins. The current level of GI implementation in the High School watershed may not have significant large-scale impacts, but it provides numerous benefits at the parcel, street, and small neighborhood scales.