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The severe drought in California (2012-2016) generated significant public and government concern. State and local watering regulations were enacted to reduce residential and commercial water-use during the droughts. This study presents a comparison of residential runoff volumes before and after local landscape irrigation regulations were enacted during the droughts of 2008 and 2012-2016. Each sampling site (Folsom 1 and Folsom 2) was a storm drain outfall that drained a low-density residential catchment in the City of Folsom. Dry season runoff measured at the sampling sites represents neighborhood outdoor water waste, mainly from landscape irrigation. During the drought of 2012-2016, median runoff flows were significantly reduced after local landscape irrigation regulations were enacted. The daily runoff pattern was also highly influenced by regulation, with reductions of daily peak runoff flows on 4-5 days in a week after watering regulations were enacted. The number of peak flow events in the daily runoff pattern were reduced during this period. In addition, a significant reduction in mean runoff volume occurred. Based on these results, the watering regulations enacted by the City of Folsom had a positive effect on reducing urban runoff from residential neighborhoods during the dry season. As the results are from monitoring sites in a relatively small geographical area, further work should evaluate reductions in irrigation runoff from other California locations to determine if this is a localized phenomenon.

Stormwater ponds manage urban runoff and mitigate storm-event flooding. Stormwater ponds also offer various secondary advantages such as filtering pollutants, providing a habitat for wildlife, and adding recreational value and access to green spaces to communities. However, stormwater pond features and their potential to offer secondary benefits can vary based on the initial construction and the ongoing maintenance practices. This study developed an assessment tool for evaluating stormwater ponds' expected functioning for secondary benefits, including potential for pollutant filtering by shoreline vegetation, safety, and access by people for activities like walking or wildlife viewing. We used the tool to compare stormwater ponds in East Tampa and Riverview, Florida, communities with contrasting socioeconomic backgrounds. The overall pond functioning was consistent between both communities; however, several distinctions emerged between specific pond attributes. Suburban ponds exhibited narrower buffer zones, lower bank stability, and less lighting. Conversely, ponds in the lower-income East Tampa had lower accessibility due to a higher number of fences, more litter, and inferior water appearance. This study uncovered a need for consideration of stormwater pond secondary benefits in both communities and an untapped potential to transform stormwater ponds into vibrant green spaces. Highlights: Stormwater ponds offer secondary ecological and social benefits, varying by initial construction and upkeep practices. Differences in pond features were noted between inner-city and suburban communities, indicating areas for improvement. There is potential to enhance stormwater ponds as green spaces in all communities, irrespective of socioeconomic status. [ABSTRACT FROM AUTHOR]

Climate and land use changes have a significant impact on the runoff generation process in urban environments, and these effects could get worse in the future. The combined contributions of these changes have increased the risk of flooding. Therefore, there is a need for integrated modeling to better understand the runoff variability, especially in small urban catchments. To quantify and separate the effects of land-use changes and climate change on the hydrological response of urban catchments with a distributed hydrological model (Storm Water Management Model, SWMM), this study introduces a new integrated approach based on the Machine Learning based land use change modeler and climate change scenarios under CMIP6. Based on supervised classification and land use change model analysis, accumulated impervious area increase from 22% (in 2023) to 33% (in 2060) was observed in the study area. Furthermore, integrating this projected increase in imperviousness with future climate change into SWMM by considering three different scenarios i.e., S1 (Climate Change), S2 (Combined Land Use and Climate Change), and S3 (Land use Change) resulted that climate change could cause an increase in runoff from 13.2% to 18.3% in peak runoff and the contribution of land use could range from 9.1% to 18.6%. Similarly, in response to the coupled effects of climate and land-use change, the runoff would likely change from 24.53% to 39.66%. Conclusively, the study showed that despite climate change, intensive urban development by the substitution of impervious surfaces could also have a severe impact on the microclimate and hydrology of small catchments. Lastly, this study could provide a way forward for the future planning and management of water resources in small catchments which could be extended to larger catchments. [ABSTRACT FROM AUTHOR]

Previous studies have proven the efficiency of LID practices in mitigating surface runoff in urban watersheds; however, the impact of their placement strategy over the urban drainage system, under continuous temporal hydrological simulation, has not been explored yet. This study simulated, under continuous time scale, five LID practices and four LID placement strategies (downstream, center, upstream and uniformly) on the drainage system of the Universidade Federal de Lavras urban area, in the state of Minas Gerais, Brazil. Under the conditions analyzed, it was found that there were no significant statistical differences between the efficiency of the different LID practices, individually or combined, within the same placement strategy. The uniform placement strategy proved to be more efficient, but in soils with higher Ksat values, other strategies showed better results. Therefore, it was found that soil Ksat is a parameter that should be carefully analyzed for LID practices implementation. [ABSTRACT FROM AUTHOR]

The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In this study, we aimed to find appropriate evapotranspiration and parameter optimization schemes for HYDRUS-1D, a commonly used modeling tool for green roofs. Comparative studies of this sort in the context of green roof runoff modeling have not been conducted previously and are important in guiding users to overcome the difficulties of choosing the right numerical schemes for an accurate prediction of runoff from a green roof. As a study site, the Portland Building Ecoroof in Portland, Oregon, USA, was chosen, as green roof configurations and observed data for climate and runoff were available. From the simulation results of the runoff volume, the Blaney–Criddle method, which was considered an alternative, was found to be appropriate for calculating evapotranspiration from a green roof (R2 = 0.82) relative to the Hargreaves method built in HYDRUS-1D (R2 = 0.46). In addition, this study showed that the optimization method using the harmony search algorithm, which was proposed as an alternative optimizer, was better (R2 = 0.95) than that of the HYDRUS-1D's own optimization module (R2 = 0.82) in calibrating HYDRUS-1D for green roof runoff. The findings are thought to be useful in guiding modelers who are considering using HYDRUS-1D for green roof runoff simulations. [ABSTRACT FROM AUTHOR]

This study brings a systematic review that evaluated 43 articles on Nature-Based Solutions (NBS) applied to stormwater management in urban areas. This review aims to establish a reference on NBS effectively applied and whose environmental, social, and economic benefits have been duly discussed. The results address 13 NBS techniques/methodologies implemented and their ecosystem benefits. Our findings suggest that the multifunctional nature of NBS makes it challenging to categorize environmental services and social benefits since there are multiple interactions and scales among the various benefits of NBS. Most studies have made greater efforts in approaches that use modeling, test benches, and/or laboratory facilities. However, although they work well for their purposes, there is no guarantee that the benefits will be maintained when applied on a full scale. We concluded that only a few studies scientifically evaluated the performance of installed NBS infrastructures, almost all in developed countries. [ABSTRACT FROM AUTHOR]

Because low-impact development (LID) infrastructures are effective in capturing and utilizing urban stormwater runoff, real-time control (RTC) strategies can be viewed as soft infrastructures, offering an additional suite of opportunities to improve the stormwater drainage system performance. However, there is a paucity of analyses that disentangle the contributing sources of performance enhancement in these joint hard–soft stormwater infrastructures. This study evaluated the stormwater system performance with integrated LID infrastructures, in-sewer storage capacity, and RTC strategies. Our results showed that LID infrastructures play a major role in mitigating the flow peaks and high volumes, whereas adding RTC to the storage unit and in-sewer flow control mostly improves the performance under relatively small rainfall events, e.g., those with a 3-year return period. The critical contribution of RTC is realized by utilizing storage units as much as possible during the rainfall event. A downstream storage unit that is too close to the outfall may not be suitable for RTC application together with in-sewer capacity utilization. In the present case, the combination of a midstream storage unit and upstream control site at branch pipes worked better than those at other locations. The results suggest that the integration of LID and RTC on a simulation-system level can enhance the reduction of the peak runoff and total discharged volume only if the storage site and control locations are selected carefully. [ABSTRACT FROM AUTHOR]

The acceleration of urbanization has disrupted natural water cycles, resulting in increased impervious urban surfaces and non-point source pollution from stormwater runoff. Addressing urban stormwater recharge has become crucial. This study introduces a novel silica sand-based permeable filtration material, investigating its surface characteristics, pore structure, permeability, and pollutant interception capabilities. The results demonstrate that hydrophilic binder coating modification of the permeable surface sand aggregate, combined with hydrophilic inorganic additives, having a porous structure with an average pore size of less than 50 μm and a porosity between 15% and 35%, significantly enhances surface hydrophilicity, achieving a permeation rate of up to 6.8 mL/(min·cm²). Moreover, it shows exceptional filtration and anti-clogging properties, achieving over 98% suspended solids interception and strong resistance to fouling. Dynamic biofilm formation experiments using simulated rain and domestic wastewater explore biofilm morphology and function on silica sand filtration well surfaces. Mature biofilms sustain COD removal efficiency exceeding 70%, with levels consistently below 50 mg/L, NH4+ decreasing to 2 mg N/L, and total nitrogen maintained below 10 mg N/L. The system features anoxic, anoxic, and aerobic zones, fostering synergistic organic matter and nitrogen removal by diverse microorganisms, enhancing pollutant mitigation. Silica sand-based permeable filtration material effectively mitigates urban stormwater runoff pollutants—suspended solids, organic matter, and nitrogen—offering an innovative solution for sponge city development and rainwater resource management. [ABSTRACT FROM AUTHOR]

Because of its low‐lying location, urbanization, and inadequate infrastructure, Jakarta (Indonesia) has experienced an increase in annual flooding events, rising from an average of five significant floods per year in the 1990s to over 20 annually (2010–2020). With climate change exacerbating extreme weather events, Jakarta encounters escalating risks of flooding. Although the recurrent flooding is exacerbated by non‐point source (NPS) of pollution such as urban runoff and agricultural discharge that contribute to 40% of total pollutants leading to flood‐related issues in Jakarta, none has investigated this research gap. To reflect its novelty, this work explores the implications of climate change on the annual flooding in Jakarta by focusing on NPS and analyzes their impacts from social perspectives. This work also underscores the implications of flooding on livelihoods, health, and social cohesion in Jakarta. Focus group discussion with affected residents was used to shed light on the coping strategies employed in response to recurrent floods, ranging from community‐based initiatives to reliance on informal networks. The empirical findings show that the implications of flooding extend beyond physical damages. Displacement of communities, loss of livelihoods, disruption of essential services, and increased health risks are among the social impacts experienced by local residents. Vulnerable populations, including low‐income communities residing in informal settlements, bear their consequences. Economic losses from flooding amount to USD 500 million annually, impacting over 1 million residents. However, recent interventions have led to a 15% reduction in peak flood levels and a 20% reduction in flood duration in affected areas. Community resilience has also improved, with a 25% increase in flood insurance coverage and a 20% rise in community response initiatives. Overall, this study highlights that climate change exacerbates annual flooding in Jakarta, significantly impacting vulnerable communities through NPS pollution. Addressing the challenges requires integrated approaches combining effective pollution control, resilient infrastructure, and community engagement to mitigate social and long‐term environmental impacts. Practitioner Points: Climate‐induced flooding disproportionately affects vulnerable communities in Jakarta.Non‐point source pollution from urban runoff contributes to the severity of flooding in Jakarta.Waterborne diseases, disruption of livelihoods, and reduced access to clean water are major concerns identified in the study.The study highlights the importance of community‐based adaptation strategies to mitigate the impact of flooding and pollution. [ABSTRACT FROM AUTHOR]

Urban parks in Vietnam are undergoing expansion plans, yet the actual area is dwindling, attributed to limited ecosystem services and inadequate public engagement. This study addressed the dual challenge of shrinking green spaces and the need for enhanced ecosystem services in urban areas. We aimed to devise strategies to bolster ecosystem service development through a comprehensive survey of park users and an analysis of the impact of green areas on ecosystem service quality. Specifically, we surveyed 400 residents to gauge perceptions, attitudes, and insights regarding park ecosystem services. Additionally, we assessed the importance of urban green spaces through various indicators (pH,DO,TSS,COD,N–NH4+,N–NO2−,N–NO3−,P–PO43−) in surface runoff samples, both with and without vegetation, during five rainfall events. The findings reveal a limited understanding of park ecosystem services among the populace, reflected in their minimal willingness to pay for such services. Moreover, the study uncovers significant differences in the impacts of parks on sustainable urban drainage, as evidenced by contrasting qualities of rainwater samples processed through green areas versus typical stormwater runoff. These results underscore the need for targeted interventions to raise awareness and improve ecosystem services in urban parks, which is pivotal for sustainable urban development. This case study from Vietnam contributes both theoretically and practically by highlighting the crucial role of public awareness and engagement in enhancing ecosystem services in urban landscapes. Practical Applications: Our study illuminates the crucial role of nature-based solutions in enhancing ecosystem services within urban environments, as exemplified by Gia Dinh and Tao Dan Parks in Ho Chi Minh City, Vietnam. This research is particularly valuable for urban developers, park management, and city planners because it underscores the potential of urban parks to contribute significantly to environmental sustainability and public well-being. We found that the public's awareness and valuation of the parks' ecosystem services are key to their willingness to support and fund park improvements. Therefore, educational programs aimed at increasing understanding of the benefits provided by these green spaces could lead to greater community involvement and investment in their maintenance and development. For policymakers, our findings suggest that investing in the ecological aspects of urban parks can pay off in terms of both enhanced environmental quality and increased public usage and enjoyment. Additionally, the implementation of sustainable drainage systems within these parks not only mitigates urban flooding but also improves the quality of urban runoff, presenting a compelling case for integrating similar nature-based solutions in urban planning initiatives. By presenting clear, real-world examples from Gia Dinh and Tao Dan Parks, our study provides a framework for other cities looking to link ecosystem services with urban development. The insights gained here can guide the transformation of urban green spaces into multifunctional areas that support biodiversity, provide recreational opportunities, and serve as cornerstones for sustainable city living. [ABSTRACT FROM AUTHOR]

When using runoff infiltration devices to remove nitrogen and phosphorus pollutants from urban runoff, the quality of the effluent is affected by the length of dry spells between rain events. This study presents a novel analysis of how these dry periods impact the device's effectiveness in removing pollutants and the resulting biological succession within the filter. Our analysis examines nitrogen and phosphorus removal in a rainwater filtration context, providing new insights into how dry period duration influences infiltration system performance. The results indicate that biological processes have a significant impact on reducing total nitrogen (TN) and total phosphorus (TP) contents under different drying periods. A 3-day drying period is most effective for reducing TN through biological processes, while a 7-day period is best for TP reduction. This suggests that moderately extending the drying period improves TP removal efficiency but does not enhance TN removal. The dominant bacterial phylum responsible for denitrification and phosphorus removal is Proteobacteria, with Pseudomonas and Acinetobacter as the leading genera. As the drying period lengthens, the dominant genera shift from Pseudomonas to Massilia. At a 3-day drying period, denitrification primarily occurs through Pseudomonas on the surfaces of maifanite and zeolite. At a 7-day dry-out period, Acinetobacter is mainly responsible for phosphate removal on maifanite surfaces. However, after a 14-day dry-out period, both biomass and bioactivity of Pseudomonas and Acinetobacter decrease, leading to reduced efficiency in removing nitrogen and phosphorus pollutants from runoff infiltration devices. These results aid in developing runoff infiltration devices for specific scenarios and offer crucial guidance for regulating runoff pollution control technologies. [ABSTRACT FROM AUTHOR]

Hawassa is a rapidly developing city in Lake Hawassa watershed of Ethiopia. Analyzing the effect of land cover dynamics on surface runoff remains imperative to adaptive urban stormwater management. This study quantified spatial variation of land cover and sensitivity of stormwater management response. Historical 30 years of daily annual rainfall, three satellite imageries, DEM, and hydrological soil group data were analyzed. A statistical‐based combined approach of geospatial techniques and Soil Conservation Service‐Curve Number (SCS‐CN) model was employed. CN and surface runoff depth for the delineated urban watersheds were determined. The result revealed that the built‐up area increased by 30.9 km2, where the rate varies spatially. The variation of impervious land cover explains 58.6% of change in CN with coefficient of 0.352. While CN is inversely correlated with agricultural and vegetation land cover variations. The finding suggests CN explains 96.78% of the change in surface runoff with a significant correlation coefficient of 3.91. The proposed integrated model approach justifies the potential to reorganize the relationship between the spatial effect of land cover variation on surface runoff at the urban watersheds. Thus, suitable local‐specific solutions can be devised for effective management of flood risk and optimize the drainage system of urban areas. [ABSTRACT FROM AUTHOR]

Implementing rain garden (RG) designs is widespread worldwide to reduce peak flow rates, promote stormwater infiltration, and treat pollutants. However, inadequate RG design degrades its hydrological behaviour, requiring the development and validation of an appropriate hydrological model for the design and analysis of structures. This study aimed to improve a hydrological infiltration model based on Darcy's law by taking into account the height of the water column (HWC) at the surface of the RG and the filtration coefficients of soil materials. The model was tested by simulating the hydrological characteristics of a rain garden based on a single rain event of critical intensity (36 mm/h). Using the validated model, design curves were obtained that predict the performance of the RG as a function of the main design parameters of the structure: water column height, ratio of catchment area to structure area, layer thickness, and soil filtration coefficient. The hydrological efficiency of the RG was evaluated in terms of the time of complete saturation, filling of the structure with water, and determining the change in HWC caused by changes in the parameters. The filtration coefficient and thickness of the upper and intermediate infiltration layers of the RG are the main parameters that affect the depth of saturation of the layers of the structure and the HWC on the surface. The model is not very sensitive to the model parameters related to the lower gravel layer. If the top layer's thickness increases by 10 cm, it takes longer to fill the structure with water, and the HWC on the surface reaches 0.341 m. The rain garden's performance improves when the filtration coefficient of the top layer is 7.0 cm/h. Complete saturation and filling of the structure with rainwater do not occur within 7200 s, and the water column reaches a height of 0.342 m at this filtration coefficient. However, the rain garden's effectiveness decreases if the filtration coefficient of the upper and intermediate layers exceeds 15 cm/h and 25 cm/h, respectively, or if the catchment area to RG area ratio decreases to values below 15. The modelling results confirm that considering the HWC in RG hydrological models is essential for designing structures to minimise the risk of overflow during intense rainfall events. [ABSTRACT FROM AUTHOR]

Urban runoff appears to be a pathway for transferring new emerging pollutants from land-based sources to the aquatic environment. This paper aimed to identify and describe the groups of pollutants present in rainwater surface runoff as well as their mixture with wastewater in the combined sewer system from urbanized catchments and to determine the correlations between these pollutants. Four leading groups of new emerging pollutants have been identified that may be present in rainwater and municipal wastewater mixtures. The samples were tested for microplastics, phthalic acid esters, pesticides, and polycyclic aromatic hydrocarbons as well as basic parameters. The pilot site was Słupsk (northwestern Poland). We conducted nine sampling campaigns at three points. The results of the present study revealed that (i) polycyclic aromatic hydrocarbons were not present in the tested samples; (ii) the selected organochlorine pesticides were detected during one campaign in the dry season and therefore were not of critical importance; (iii) out of the 11 analyzed phthalic acid esters, five selected substances released from commonly used plastic products were present; and (iv) the number of microplastics contained in the tested samples ranged from 1,400 to 14,036 pcs/L and even occurred during pure rainfall. [ABSTRACT FROM AUTHOR]

Nitrogen and phosphorous compounds are significant pollutants in urban stormwater runoff. In this study, three lab-scale bioretention cells, namely a control reactor CM, and reactors M1 and M2 containing Scrap Iron Filings (SIF) with granulated brick (M1) and pumice pellets (M2), respectively, were used to evaluate the simultaneous removal of nitrate, nitrite, ammonia, total nitrogen, phosphorous, and COD using simulated runoff. Under unsaturated conditions, M1 with the ZVI-brick combination removed 91.37% TP, while M2 with the ZVI-pumice combination removed 89.76% TP. Under saturated conditions, M2 removed 72.02% TN, and M1 removed 66.1% TN. It was found that the presence of saturation zones benefitted TN removal which can be attributed to the creation of anoxic conditions within saturation zones, which favoured denitrification, as well as the prolongation of influent retention and reaction time, while it hindered TP removal. TP removal percentages for CM, M1, and M2 declined from 86.77%, 91.37%, and 89.76% in unsaturated conditions to 63.99%, 83.67%, and 71.74% in saturated conditions due to the propensity of soil-bound P to leach in anoxic environments. The media amendments were further characterized using Scanning Electron Microscopy (SEM) and X Ray Diffraction analysis (XRD), as well as adsorption and leaching tests. Significantly, the highest pollutant leaching was observed in the assessed conditions for CM, underscoring the usefulness of including media like ZVI, brick powder, and pumice pellets. This incorporation not only heightened the effectiveness of pollutant removal but also fortified their retention in potential future stormwater events. In consideration of this, M1 emerged as the preferred design option, as its non-leaching characteristics were verified through flushing with distilled water after post-stormwater influent loading cycles when compared to traditional designs. [ABSTRACT FROM AUTHOR]

Stormwater 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. [ABSTRACT FROM AUTHOR]

The complex topography and inherent nonlinearity affiliated with influential hydrological processes of urban catchments, coupled with limited availability of measured data, limits the prediction accuracy of conventional models. Artificial Neural Network models (ANNs) have displayed commendable progress in recognising and simulating highly complex, non-linear associations allied with input-output variables, with limited comprehension of the underlying physical processes. Therefore, this paper investigates the effectiveness and accuracy of ANN models, in estimating the urban catchment runoff, employing minimal and commonly available hydrological data variables – rainfall and upstream catchment flow data, employing two powerful supervised-learning-algorithms, Bayesian-Regularization (BR) and Levenberg-Marquardt (LM). Gardiners Creek catchment, encompassed in Melbourne, Australia, with more than thirty years of quality-checked rainfall and streamflow data was chosen as the study location. Two significant storm events that transpired within the last fifteen years - the 4th of February 2011 and the 6th of November 2018, were nominated for calibration and validation of the ANN model. The study results advocate that the use of the LM-ANN model stipulates accurate estimates of the historical storm events, with a stronger correlation and lower generalisation error, in contrast to the BR-ANN model, while the integration of upstream catchment flow alongside rainfall, vindicate for their collective impact upon the dynamics of the flow being spawned at the downstream catchment locations, significantly enhancing the model performance and providing a more cost-effective and near-realistic modelling approach that can be considered for application in studies of urban catchment responses, with limited data availability. [ABSTRACT FROM AUTHOR]

Initiatives to repurpose vacant lots to improve people's well-being are increasing worldwide. Still, little is known about how distinct plant communities influence the provision of ecosystem services in vacant lots. To bridge this gap, we investigated associations in vacant lots between land-cover type, plant diversity (both taxonomic and functional), and composition with soil organic carbon and hydraulic conductivity which are indicators of carbon storage and stormwater runoff control. We sampled plant communities, soil organic carbon, and hydraulic conductivity across 50 sites, three plots per site, in the Greater Quebec City Area, Canada. The sites comprised five land-cover types: lawn, bare soil, low- and high-density herbaceous vegetation, and sparse trees. Soil organic carbon was lowest in bare soil lots, while the lowest hydraulic conductivity was found in lots with sparse trees and high-density herbaceous vegetation. Soil organic carbon was positively correlated with forb and total plant cover, but negatively correlated with functional dispersion. Hydraulic conductivity was positively correlated with taproot frequency and functional dispersion of three traits (lifespan, specific leaf area, and reproductive modes), but negatively correlated with grass and total plant cover. This research highlights the associations between plant functional traits and groups with soil characteristics, uncovering patterns that might be overlooked if only land-cover was considered, such as higher carbon storage and hydraulic conductivity associated with forb-rich meadows with high taproot frequency. We advocate for a trait-focused approach in vacant lot revitalization, particularly when the goal is to enhance local levels of soil-based ecosystem services. [ABSTRACT FROM AUTHOR]

Abstract Urban runoff appears to be a pathway for transferring new emerging pollutants from land-based sources to the aquatic environment. This paper aimed to identify and describe the groups of pollutants present in rainwater surface runoff as well as their mixture with wastewater in the combined sewer system from urbanized catchments and to determine the correlations between these pollutants. Four leading groups of new emerging pollutants have been identified that may be present in rainwater and municipal wastewater mixtures. The samples were tested for microplastics, phthalic acid esters, pesticides, and polycyclic aromatic hydrocarbons as well as basic parameters. The pilot site was Słupsk (northwestern Poland). We conducted nine sampling campaigns at three points. The results of the present study revealed that (i) polycyclic aromatic hydrocarbons were not present in the tested samples; (ii) the selected organochlorine pesticides were detected during one campaign in the dry season and therefore were not of critical importance; (iii) out of the 11 analyzed phthalic acid esters, five selected substances released from commonly used plastic products were present; and (iv) the number of microplastics contained in the tested samples ranged from 1,400 to 14,036 pcs/L and even occurred during pure rainfall.

While green infrastructures (GIs) are used to address urban flooding and stormwater runoff and enhance sustainability, their implementation faces challenges such as limited funding and competing priorities. Existing studies generally focused on specific/individual GI practices, potentially overlooking the broader benefits or values of comprehensive GI plans that generally are interconnected networks of multiple GI practices. Thus, this paper developed an agent-based model to offer municipalities, planners, and decision makers a structured and systematic modeling approach to: (1) simulate the dynamic nature of GI implementation plans across spatial and temporal dimensions; (2) capture the interplay among regulations that govern GI plans; and (3) conduct scenario and sensitivity analyses to gain deeper insights into the various characteristics of GI plans under different scenarios. The proposed model considered different economic values of GI plans, including stormwater management, carbon sequestration, pollutant removal, energy cost savings, and increased property value, as well as the social values, such as the positive impact on nearby residents/communities. In addition, the developed model considered the following six GI practices: green roofs, rain gardens, community gardens, bioswales, permeable playgrounds, and permeable pavements. These GI practices were modeled across five submodels: school greening, private property greening, park greening, right-of-way property greening, and public housing properties greening. Scenario analysis was conducted to investigate the effect of financial limitations (i.e., funding priorities) on the model's behavior under two scenarios. Finally, the developed model was statistically validated. The results showed that increasing the number of GIs does not guarantee an increase in their economic value, but rather the implementation of GIs should be well planned according to a priority plan. The findings also provided valuable insights into the importance of considering physical and institutional limitations. This paper contributes a practical workflow for evaluating the costs and benefits of GI programs. [ABSTRACT FROM AUTHOR]

This research examined heavy metals distribution and potential environmental impact in seven locations along the Bhavnagar coast in Gujarat, India. The study used several analyses, including hierarchical cluster analysis (HCA), principal component analysis (PCA), and correlation analysis to investigate the harmful heavy metals present in the area. To evaluate the possible risk of Cd, Pb, Cr, Zn, Co, Cu, Ni, Mn, and Fe to the marine environment, pollution indices such as contamination factors (Cf), enrichment factor (Ef), geo-accumulation index (Igeo), ecological risk factor (Er), ecological risk index (RI) and sediment quality guidelines (SQGs) applied. Based on the results, the mean concentration of heavy metals was ranked in the following order (mg/kg): Fe (561.4) > Mn (58.9) > Cr (42) > Zn (12.5) > Pb (8.2) > Ni (7) > Cu (5.2) > Co (2.7) > Cd (.3). Compared to the pre-monsoon and post-monsoon seasons, the results showed a diluting impact on heavy metal concentrations during the monsoon season. The spatial distribution of the heavy metals indicated that the geogenic source and anthropogenic source were the primary contributors to pollution in the studied region. Principal component analysis suggests that Cd, Pb, Co and Cr may have come from shipbreaking activities, municipal discharge and industrial operations. Cf, Igeo, and Ef demonstrated no pollution to moderate pollution, with a maximum contribution of Cd, and the coastal sediment poses a minimal ecological risk for all heavy metals investigated. Shipbreaking, urban runoff, salt-marine, and agricultural runoff release toxic metals into the coastal environment. In conclusion, the information obtained from this geochemical characterization could be valuable to policymakers and stakeholders in developing effective management measures for the Bhavnagar coastal region, Gulf of Khambhat, Gujarat, India. [ABSTRACT FROM AUTHOR]

To accurately figure out how much pollution comes from urban surface runoff and take steps to protect receiving water, we needed to fully understand how road-deposited sediments (RDS) wash off. Our research indicates that particles smaller than 100 μm imparted 59–73% of the wash-off load. Two instances of natural rainfall reduced the aggregate RDS mass by approximately 27–36%. On days without rain, the RDS particle shrank in size, but it became heavier after a downpour. The results showed that the source restricted the tiny particles washed off of RDS, while transport generally restricted the heavier particles washed off. We used 39 artificial rainfall events with different particle sizes to confirm our results on RDS wash-off. When compared to the heavier particles, tiny particles have a greater wash-off percentage, and when it comes to describing the wash-off mechanism, Fw values offer an inventive and insightful assessment. It has been assessed that tiny particles were source-restricted and this mechanism occurred during the initial stage, but heavier particles were transport-restricted and it occurred during the late stage. HIGHLIGHTS Natural rain reduces road-deposited sediment (RDS) by 27–36%, highlighting rainfall's cleansing effect on urban surfaces.; On rain-free days, RDS particles shrink, becoming heavier after downpours, revealing the dynamic interplay between rainfall and particle behavior in urban runoff.;

An expansion of impervious surfaces in urban areas leads to increases of nutrient loads discharged with the surface runoff to receivers. A study of a different density of urban development impact on total nitrogen (TN) and phosphorus (TP) loads from the city of Lublin (eastern Poland) with the use of the SWAT (Soil & Water Assessment Tool) model was performed. To distinguish between areas with high and low density of urban development (UHD and ULD), a special analysis of hydrological parameters has been proposed. Moreover, to investigate the impact of climate change, four variant scenarios were taken into account, combining the RCP (representative concentration pathway) 4.5 and 8.5 forecasts and the adopted time horizons (2026–2035 and 2046–2055). The results showed a much higher share of TN and TP from UHD compared to ULD (86%—32 022 kg/year and 89%—2574 kg/year, respectively). In addition, the variant scenarios showed that the forecasted increase in precipitation and temperature will result in increased loads of nutrients from UHD and ULD up to 30%. Furthermore, the current increase of inhabitant number, due to the Ukrainian war migration and the common tendency to convert agricultural land to residential areas, could contribute to further expansion of UHD and ULD areas and an additional increase of nutrient loads. [ABSTRACT FROM AUTHOR]

The growing processes of urban expansion have led to changes in the biochemical and physical properties of the hydrological systems in watersheds, not only by altering the hydrological conditions of the territory, but also by introducing pollutants into water bodies. Thus, diffuse pollution from stormwater runoff is considered one of the main causes of water quality degradation in receiving waters in urban areas, especially in rainy regions such as the South American tropics, where urban development and management processes are generally poorly planned. This article presents the results of an evaluation of the relationship between land use and runoff water quality, taking into account different rainfall characteristics. Sampling was carried out in Medellín, Colombia, in areas with different land uses. Basic water quality parameters and some sources of urban pollution were studied. The results showed that parameters such as total suspended solids have a high variability, especially in the residential area, which makes it difficult to control the activities carried out there. The highest levels of pollution were found in the industrial area, where the presence of covers with very low or no permeability and the increase in anthropic activity cause a strong alteration in the quality of runoff water. These results open the door to question the impact of land use on the chemical composition of rainwater and promote a better understanding of surface runoff water pollution processes, thus providing a complete vision of the interactions in an urban ecosystem, establishing a key tool for water management in urban watersheds. [ABSTRACT FROM AUTHOR]

The Grand River watershed is the largest catchment in southern Ontario. The river's northern and southern sections are influenced by agriculture, whereas central regions receive wastewater effluent and urban runoff. To characterize in-river microbial communities, as they relate to spatial and environmental factors, we conducted two same-day sampling events along the entire 300 km length of the river, representing contrasting flow seasons (high flow spring melt and low flow end of summer). Through high-throughput sequencing of 16S rRNA genes, we assessed the relationship between river microbiota and spatial and physicochemical variables. Flow season had a greater impact on communities than spatial or diel effects and profiles diverged with distance between sites under both flow conditions, but low-flow profiles exhibited higher beta diversity. High-flow profiles showed greater species richness and increased presence of soil and sediment taxa, which may relate to increased input from terrestrial sources. Total suspended solids, dissolved inorganic carbon, and distance from headwaters significantly explained microbial community variation during the low-flow event, whereas conductivity, sulfate, and nitrite were significant explanatory factors for spring melt. This study establishes a baseline for the Grand River's microbial community, serving as a foundation for modeling the microbiology of anthropogenically impacted freshwater systems affected by lotic processes. [ABSTRACT FROM AUTHOR]

Understanding rainfall intensity in different regions, especially in the context of climate changes, is crucial for designing hydraulic structures like urban runoff collection systems. Therefore, a comprehensive examination of three variables, including daily and annual rainfall and the maximum intensity of short-term rainfall, is essential due to variations in the amount and temporal distribution of rainfall. In many regions, extreme rainfall intensities may not have been recorded, necessitating the estimation of maximum rainfall with durations less than 24 h by leveraging the correlation between maximum 24-h rainfall and annual rainfall. As precipitation is a multi-variable phenomenon with interdependent variables, employing multi-variable analysis provides a more accurate interpretation than single-variable analysis. To achieve this, this study utilized five copula functions from the symmetric Archimedean copula family to analyze the dependence structure between variables. The data for all three precipitation variables from the Isfahan synoptic station, representing the Central Plateau region of Iran, were collected over a 53-year period (1967–2020).Subsequently, the best marginal distribution functions were fitted to the variables. Then, using the maximum likelihood method and goodness of fit tests, the copula parameters and the best bivariate and trivariate copula functions were estimated respectively. Finally, the probabilities and periods of joint (AND and OR) and conditional returns of two and three variables were calculated and illustrated. Comparing the results of the bivariate and three-variables (maximum intensity of rainfall in short-term, maximum daily rainfall and average total annual rainfall) return periods, it was concluded that the three-variable conditional return period provides higher reliability for the long-term design of infrastructures. [ABSTRACT FROM AUTHOR]

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Urban flooding can differ significantly from rural flooding due to the influence of rapidly changing land use and rainfall patterns on runoff in urban areas. Consequently, understanding and managing urban flooding necessitate a comprehensive grasp of these influential factors. This study focuses on assessing the impact of land use and rainfall changes on runoff and flood resilience in urban areas of Chennai, India, utilizing the InVEST-UFRM model. The research includes an evaluation of flood risk and potential damage to building infrastructure, examining 14 sub-basins within the study area with diverse land use and rainfall depths for 2015, 2020, and 2025. Observed rainfall and land use data were employed for 2015 and 2020, while future rainfall data relied on Global Circulation Models (GCMs) of the Coupled Model Inter-comparison Project-6 (CMIP6) outputs and QGIS MOLUSCE plugin predicted land use for 2025. The study identified that the change in land use had a more significant impact on runoff than the temporal change in rainfall amount. Notably, the reduction of water bodies in the study area emerged as a major contributing factor to excessive runoff. The estimated maximum potential damage to built infrastructure in the study area reached approximately 10 billion USD. This research provides valuable insights into urban flood resilience and the impact of land use and rainfall changes and proposes effective measures for flood adaptation and mitigation. The study findings can serve as essential tools for urban planners in an effective management of urban floods in similar regions as investigated here. [ABSTRACT FROM AUTHOR]

This study investigated the level of dissolved heavy metals in the water of Longhu Lake and focused on the speciation, mobility, and risks of heavy metals (Cr, Mn, Ni, Cu, Zn, As, Cd, and Pb) in sediment. The levels of heavy metals in the water were found to be below the thresholds set by the Chinese safe drinking water standard. The highest average percentages of Cr, Ni, Zn, and As were bound with residual fractions, while Pb and Cu were bound with reducible fractions. Additionally, the highest percentage of Cd and Mn was bound to the acid-soluble fraction in the sediment. These findings suggest that Cd, Mn, Pb, and Cu likely originated from anthropogenic sources in the lake. There was a strong correlation between total organic carbon (TOC) and metal fractions in the sediment, indicating that TOC may play a role in transporting heavy metal fractions. Risk assessment code values for Cd and Mn indicated higher risks and mobility, while Ni, Cu, and Zn showed medium risks and mobility for aquatic biota. To mitigate heavy metal contamination, it is recommended to improve monitoring and regulation of urban runoff and inlet areas. [ABSTRACT FROM AUTHOR]

The Storm Water Management Model (SWMM) is a hydrological model for simulating and predicting runoff. Although powerful, SWMM can be computationally demanding. Therefore, we develop machine learning (ML) models to approximate the behavior of SWMM and expedite the task of predicting runoff. We perform a case study for the First Creek watershed in Knoxville, Tennessee, USA. We train ML models using rainfall data and subcatchment characteristics and apply feature engineering and clustering to objectively compare the outputs from SWMM and ML models. The results show that random forests can predict runoff volume accurately, with a Mean Absolute Error (MAE) of 0.006 (0.001) ${10^6}$ 10 6 gallons, where predictions are made almost instantaneously. Hence, our proposed ML-based approach can accurately predict runoff while greatly reducing computational requirements, filling a critical need in the field. [ABSTRACT FROM AUTHOR]

While green roofs have gained widespread popularity as a measure to detain and retain runoff in urban areas, their performance during extreme events is not well studied. In this study 15 years of runoff and precipitation observations from a small extensive green roof in Norway are analysed. GEV‐distributions were fitted to the annual max values for precipitation and runoff in order to develop intensity‐duration‐frequency (IDF) and runoff‐duration‐frequency (RDF) data. Using the IDF and RDF data a total of 31 extreme events were identified (containing precipitation or runoff values with return period greater than 2 years for one or more durations). While nearly all extreme runoff events were caused by extreme precipitation, only 69% of the extreme precipitation events resulted in extreme runoff. The assumption of 1:1 equivalency of return periods did not hold true, and deviations were mainly explained by variations in substrate water content prior to the extreme event. Moreover, in 50% of the events, the runoff duration with the greatest return period was shorter than the precipitation duration with the greatest return period. Hence, the results indicate that the use of design storms to predict runoff from green roofs may be inappropriate. The potential of having IDF and RDF data available was demonstrated by the development of simple empirical equations, which ensure conservations of both return period and duration. To generate reliable green roof RDF data, future research should prioritize evaluating various continuous models with the aim of accurately describing extreme events. [ABSTRACT FROM AUTHOR]

Urban floods caused by extreme rainstorm events have increased in recent decades, particularly in concave-down bridge zones. To simulate urban flooding processes accurately, an integrated urban flood model (IUFM) was constructed by coupling a distributed urban surface runoff model based on the cellular automata framework (CA-DUSRM), a widely used pipe convergence module in the storm water management model (SWMM), with an inundation module that describes the overflow expansion process associated with terrain and land-cover. The IUFM was used in a case study of the Anhua Bridge (a typical concave-down overpass) study area in Beijing, China. The spatial-temporal variations in flood depth modeled by the IUFM were verified to be reliable by comparison with actual measurements and other simulations. The validated IUFM was used to obtain temporal variations in flood range, depth, and volume under four rainstorm scenarios (return periods of 3-year, 10-year, 50-year, and 100-year). The results showed that the surface runoff process, overflow from drainage networks, and overflow expansion process could affect the flooding status by changing the composition and spatial configuration of pervious or impervious patches, drainage capacity, and underlying surface characteristics (such as terrain and land-cover). Overall, although the simulation results from the IUFM contain uncertainties from the model structures and inputs, the IUFM is an effective tool that can provide accurate and timely information to prevent and control urban flood disasters and provide decision-making support for long-term storm water management and sponge city construction. [ABSTRACT FROM AUTHOR]

This study investigated how nitrogen and dissolved organic matter (DOM) from stormwater runoff and rainfall support the growth of Karenia brevis and Pyrodinium bahamense. Excitation–emission matrix spectroscopy coupled with parallel factor analysis tracked changes in the optical properties of DOM in each bioassay, revealing greater reactivity of terrestrial humic-like DOM. Significant increases in cell yield and specific growth rates were observed upon additions of runoff for both species, with significant increases in specific growth rates upon the addition of a 2 in simulated rain event for P. bahamense only. By hour 48, 100% of the dissolved organic nitrogen (DON) in each treatment was utilized by P. bahamense, and by hour 72, over 50% of the DON was utilized by K. brevis. The percentage of bioavailable dissolved organic carbon (DOC) was greater for P. bahamense compared to K. brevis, suggesting a greater affinity for DOC compounds by P. bahamense. However, the bioavailability of DOM for each species could be owed to distinct chemical characteristics of labile DOM conveyed from each site. This study demonstrates that stormwater runoff and rainfall are both sources of labile DOM and DON for K. brevis and P. bahamense, which has implications for blooms of these species in Tampa Bay waters. [ABSTRACT FROM AUTHOR]

A sponge city is an established urban stormwater management approach that effectively reduces urban runoff and pollutant discharges. In order to plan and design, estimate costs, and evaluate the performance of urban sponge city systems, it is essential to calculate the storage scale. In this context, a sponge city storage scale and calculation method based on a multifactor spatial overlay was designed, utilising the starting area of the Dafeng Hi-tech Development Zone in Yancheng City, China, as an illustrative example. The indicators for assessing the impact of sponge city systems on river plain networks are constructed based on four aspects: land planning, building density, water surface rate and green space rate. The relative importance of each indicator was determined based on the necessity of controlling runoff from land parcels and the appropriateness of facility construction. The annual runoff control rate of the 39 low-impact development control units in the study area was calculated using ArcGIS through multifactor spatial overlay mapping and weighting. The results showed that (1) the Geographic Information System (GIS)overlay technology can effectively assist in the decomposition of LID scales; (2) data can be derived, including the design storage volume and other basic control scale indicators for each unit. The study results are expected to serve as a reference for the preparation of special low-impact development plans in the river plain network area of China and the promotion of the construction of a sustainable blue–green system in the city. [ABSTRACT FROM AUTHOR]

Rain gardens are used to solve urban problems related to the negative impact of stormwater. (1) Scientific contributions from different countries provide general guidelines for the design and operation of rain gardens in different geographical areas. Given the small spatial scale of rain gardens, the use of existing infiltration models often leads to design errors. (2) The purpose of this paper is to develop a hydrological model by introducing a system of equations that extends the ability to calculate the rate, flow rate and time of saturation of layers with moisture and rainwater leakage from the rain garden system. (3) The results obtained allow us to describe the dynamic processes of passage and saturation of layers of the rain garden at a certain point in time, which extends the ability to calculate the flow rate. It was established that the smaller the area of the rain garden compared to the area of the catchment basin, the faster it reaches its full saturation. Increasing the thickness of the rain garden layers allows for an increase in the efficiency of water retention at a lower value of the area ratio. (4) The practical significance of the results obtained is especially important for the correct description of hydrodynamics in the system and determining the optimal conditions for the effective functioning and management of the rain garden structure for any climatic region. [ABSTRACT FROM AUTHOR]

Urban runoff is acidic in nature and mainly consists of heavy metals and sediments. In this study, the pervious concrete samples were cured in a CO2-rich environment and their performance under runoff conditions was evaluated by passing different solutions containing clay particles, heavy metal ions, and acid species. The compressive strength of these samples was reduced by up to 14% when they were cured in water instead of a CO2 environment. Heavy metal ions, including lead and zinc, in the simulated runoff were adsorbed in these pervious concrete samples by up to 96% and 80% at the end of the experiment, but the acid species in this runoff could leach calcium ions from the cement components during passage. Clay particles in the runoff were trapped in the flow channels of samples, which marginally reduced the percolation rate by up to 14%. Concrete carbonation reduced the release of calcium ions under runoff conditions, and zinc removal was relatively lower because of the nonavailability of hydroxyl sites in the interconnected pore structure. The weight and strength losses in the carbonated concrete samples were relatively lower at the end of the acid storage experiment, suggesting that CO2 curing reduces cement degradation in aggressive chemicals. The SEM and tomography images revealed the degraded microstructure, while the XRD results provided data on the mineralogical changes. CO2 curing improves the strength gain and service life of pervious concrete in runoff environments. [ABSTRACT FROM AUTHOR]

Flow regimes are increasingly impacted by more extreme natural hazards of droughts and floods as a result of climate change, compounded by anthropogenic influences in both urban and intensively managed rural catchments. However, the characteristics of sustainable flow regimes that are needed to maintain or restore hydrologic, biogeochemical and ecological function under rapid global change remain unclear and contested. We conducted an inter-comparison of two streams in the Berlin-Brandenburg region of NE Germany, which are both mesoscale sub-catchments of the River Spree; an intermittent rural agricultural stream (the Demnitzer Millcreek) and a heavily anthropogenically impacted urban stream (the Panke). Through tracer-based analyses using stable water isotopes, we identified the dominant physical processes (runoff sources, flowpaths and age characteristics) sustaining streamflow over multiple years (2018–2023), including three major drought years (2018–20, 2021–22). In the urban stream, low flows are regulated through artificially increased baseflow from treated waste water effluent (by up to 80 %), whilst storm drainage drives rapid, transient high flow and runoff responses (up to 80 %) to intense convective summer rainfall. The intermittent groundwater-dominated rural stream experienced extended no-flow periods during drought years (⁓ 60 % of the year), and only moderate storm runoff coefficients (<10 %) in winter along near-surface flows paths after heavy rainfall. In both streams, groundwater dominance with young water influence prevails, with low water ages in the urban stream (<10 %) despite significant urban runoff, and higher ones in the rural stream (⁓15 %). Urban cover resulted in mean transit time of ⁓4 years compared to arable land with ⁓3 years, highlighting the interlinkages of landuse and catchment properties on catchment transit times. Understanding seasonal and interannual variability in streamflow generation through a tracer-based hydrological template, has potential for assessing the impacts of natural hazards on the sustainability of future baseflow management, including wider water quality and ecological implications across anthropogenically impacted environments. [ABSTRACT FROM AUTHOR]

Understanding the diagenetic processes of organic matter (OM) within mangrove forests is essential to grasp ecosystem dynamics and exchanges with adjacent ecosystems. This study investigated the influence of urban runoff on leaf litter degradation in a New Caledonian mangrove forest, subjected to urban rainwater for over 50 years. Focusing on Avicennia marina and Rhizophora stylosa , our objectives were to determine factors affecting leaf litter degradation, assess urban runoff effects on decay rates and element concentrations, and understand OM changes at the molecular level. Litterbags containing senescent leaves placed on the mangrove floor were collected after 7, 14, 28, 56, and 72 days. C and N along with their stable isotopes were evaluated during degradation as well as lignin and neutral carbohydrates contents. Despite lower initial N content, R. stylosa exhibited faster degradation (t 1/2 of 36 ± 3 and 28 ± 2 days) than A. marina (t 1/2 of 43 ± 9 and 33 ± 4 days), emphasizing the critical role of species position within the mangrove forest regarding tidal immersion. Urban runoff, submerging the urban site, intensified leaf litter degradation, influencing both mass loss and molecular changes in OM. After 72 days of leaf litter degradation, the loss of rhamnose and glucose was more pronounced at the control site (13 % and 75 % for rhamnose and 46 % and 53 % for glucose for A. marina and R. stylosa , respectively) compared to the urban site. The study also exposed molecular tendencies during mangrove leaf litter degradation. The content of ferulic acid in the leaf litter decreased at all stands after 72 days of degradation (between −25 % and −58 %), while total syringyl phenols increased (between + 64 % and + 232 %). This research exposed the global implications of urban runoff, indicating accelerated leaf litter degradation in mangrove forests, potentially disrupting C sequestration dynamics and threatening ecosystem services. [ABSTRACT FROM AUTHOR]

Numerous organic chemicals exist within aquatic environments, yet effectively screening and prioritizing them is a huge challenge. This study provides a comprehensive investigation into the ecological dynamics of the North Oconee River within Athens-Clarke County, Georgia, with a specific focus on the distribution of 33 identified compounds, including a prominent pesticide. The research, conducted in the riverine ecosystems proximal to the Firefly trail, employs advanced analytical techniques to elucidate potential contamination sources arising from agricultural and urban runoff. Intriguingly, the study reveals North Oconee River near the Firefly Trail as a notable site for heightened pesticide contamination, warranting a meticulous exploration of its origins. Furthermore, the investigation unveils the intricate microbial degradation processes of malathion within the North Oconee River, elucidating the pivotal role played by microbial activity in river water. The detection of degradant byproducts prompts the considerations of bioavailability and toxicity, associating potential implications for the river's overall ecological health. Ongoing research endeavors to precisely quantify environmental risks and unravel indigenous microbial degradation pathways, presenting pivotal contributions to the scientific community's understanding of complex riverine ecosystems. This research serves as a foundational piece in informing sustainable environmental management practices and emphasizes the urgency of comprehensive stewardship in safeguarding aquatic ecosystems. [ABSTRACT FROM AUTHOR]

The massive use of antibiotics has led to the escalation of microbial resistance in aquatic environment, resulting in an increasing concern regarding antibiotic resistance genes (ARGs), posing a serious threat to ecological safety and human health. In this study, surface water samples were collected at eight sampling sites along the Yangtze River Estuary. The seasonal and spatial distribution patterns of 10 antibiotics and target genes in two major classes (sulfonamides and tetracyclines) were analyzed. The findings indicated a high prevalence of sulfonamide and tetracycline resistance genes along the Yangtze River Estuary. Kruskal–Wallis analysis revealed significant seasonal variations in the abundance of all target genes. The accumulation of antibiotic resistance genes in the coastal area of the Yangtze River Estuary can be attributed to the influence of urban instream runoff and the discharge of effluents from wastewater treatment plants. ANISOM analysis indicated significant seasonal differences in the microbial community structure. VPA showed that environmental factors contribute the most to ARG variation. PLS-PM demonstrate that environmental factors and microbial communities pose direct effect to ARG variation. Analysis of driving factors influencing ARGs in this study may shed new insights into the mechanism of the maintenance and propagation of ARGs. [ABSTRACT FROM AUTHOR]

This study investigates the heavy metals (HMs) and other constituents in Lake Tana around the Gulf of Bahir Dar City. The water sample was collected from areas receiving drainage water and a reference sample was collected from areas away from the urban impact, both during dry and wet seasons. Pollution sources and levels were determined using pollution indices and GIS spatial analyses. All in situ parameters were in the recommended range of the USEPA aquatic and WHO drinking water guidelines. The level of dissolved P was recorded between 0.03 and 0.9 mg/l and the level of N-NO3 ranged from 0.05 to 1.01 mg/l indicating that the limits were above USEPA aquatic criteria. The HMs varied from 0.08 to 2.85 mg/l for Cu, 0.10 to 1.60 mg/l for Fe, 0.04 to 0.22 mg/l for Cr, and Mn was below detection. Cr and Fe were above the aquatic and drinking water guideline limit. Spatially, pollution was more significant in areas receiving drainage. Also, except Cu and Fe, other parameters were higher in the rainy season indicating storm runoff pollution. The overall pollution indices of water quality status, such as water quality index 63, heavy metal pollution index 3.1, and nutrient pollution index 4.7, indicated the quality level of water to be alarming. Therefore, comprehensive regulatory and waste management practices are needed. HIGHLIGHTS This research is a first study evaluating the heavy metals (HMs) in Lake Tana.; Both HMs (Cr and Fe) and nutrients (N and P) exceeded the aquatic limit.; GIS spatial analysis shows that concentration is at a high level in urban drainage discharge area.; HMs and nutrients are at high levels in the rainy season.; The calculated pollution indices such as WQI, HPI, and NPI indicated the water quality of the lake to be alarming.;

Introduction and GoalDue to the large volume of human and commercial activities, one of the most important goals of infrastructure is to collect and transfer urban runoff, control floods and prevent flooding in cities. To correctly estimate the runoff and characteristics of hydrological units and channels, it is important to use appropriate hydrological and water models. Considering the importance of this topic, this research was conducted with the aim of estimating the urban runoff of the Malayer to determine the potential flooding points using a storm water management model (SWMM).Material and MethodsOn the basis of available technical reports, the area of the sub-watersheds, nodes and main channels of the city were first determined. Flow direction and slope of the area was determined using a digital elevation model and 11 sub-watersheds were identified. In addition, 11 nodes were determined, regardless of the initial water depth and water level. Using the daily rainfall data of the Malayer synoptic station during the 1992–2020 statistical period, a nine-hour rainfall with a return period of 2 years was calculated and entered into the model. The geometrical shape of the channels was an open rectangle and the flow trend in the channels was determined using the kinetic wave method. The size of the maximum flow of water through the channels was calculated using the relationship between the cross-section of the flow and the speed of the flow a 9-hour the rainfall with a return period of 2 years. To calibrate the model, the variables of percentage of impervious areas, pond storage and roughness coefficient of impervious areas were used in the change range of the allowed modification range. In order to evaluate the model, Nash-Sutcliffe efficiency coefficient and the root mean square error were used.Results and DiscussionThe results showed that after optimizing the sizes of the variables, the Nash-Sutcliffe efficiency coefficient and the root mean square error were 0.73 and 0.02, respectively. Of the total rainfall of 14.54 mm, 5.53 mm was related to infiltration losses, 7.55 mm was related to surface runoff, and 1.45 mm was related to pond storage. The results showed that the sub-watersheds that were in the north of the city and overlooking the heights and leading to node number 10 had more volume and drainage and it is necessary to revise the design and expansion of the channels in this area. In addition, the sub-watersheds of the western part of the city (sub-watersheds no. 4) and the southwestern part (sub-watersheds no. 8) had the highest and lowest flood potential of 0.651 and 0.547, respectively.Conclusion and SuggestionIn this research, the results showed that almost half of the city would be affected by flood risks in the event of rains. Therefore, the current drainage network does not have the necessary efficiency to discharge urban runoff in the northern part of the city, and it is necessary to determine the optimal dimensions of the channels. Because the eastern elevations of the studied area are snow-covered and considering the geology of the area, in future research, models capable of calculating the runoff caused by snow melting should be used.

Introduction Urban flooding is caused by the lack of capacity of the harvesting channel network and occurs when the amount of precipitation exceeds the network's capacity. One of the two main factors contributing to the aggravation of damage caused by urban floods is population growth and the expansion of urbanization, and the second factor is heavy rainfall caused by climate change, which plays an essential role in intensifying and accelerating the hydrological cycle and may change the amount and frequency of precipitation. This factor affects the probability of flooding, runoff volume, and peak flow. It is more visible in arid and semi-arid areas where rainfall usually occurs briefly but with high intensity. Urban flooding is a growing threat to urban infrastructure and public health, posing significant challenges to urban resilience and sustainability. One of the urban infrastructures that is of great importance is the runoff collection network. The increase of impervious surfaces wear and tear on the network. changes in the rainfall pattern due to climate change have increased the occurrence of urban floods and raised the importance of network redesign to minimize the system vulnerability. Materials and Methods In this research, the runoff harvesting network of ten districts of Tehran Municipality was redesigned and optimized. This area, with a population of 327,000 people, is located in the relatively dense fabric of the Tehran metropolis, and its area is 807 ha. Simulating the runoff collection network and checking the performance of the network by two indicators of vulnerability and reliability requires an accurate model with great details. For this purpose, in this research, SWMM version 5.1 software was used to simulate the runoff collection network. The study area was divided into 285 sub-basins to simulate the sub-channels in better detail. Then, information such as slope, area, and percentage of impervious space was introduced through ArcMap software version 10.3.1 as information under the watersheds. The sub-watershed width parameter was calculated by dividing the sub-watershed area by its most significant length using Q-GIS software and applied to the sub-basins. The LARS-WG model has also been used for the exponential micro-scale output of climate models. To simulate the network in the current or present situation, the historical precipitation information of the Mehrabad synoptic station was used, and to affect the network in future conditions, the precipitation information of the climate models of the sixth climate change report was used. Among the predictions of climate models, the most incremental changes in threshold precipitation were selected as a pessimistic scenario, and a system redesign was done to reduce vulnerability under this scenario. Results and Discussion This study was conducted to assess the performance of Tehran municipality's runoff collection network under current and future conditions. The SWMM hydraulic model was employed to simulate the network under various rainfall scenarios. Current conditions revealed a total runoff volume of 45.9, 51.14, and 59.7 thousand m3 for return periods of 2, 5, and 10 years, respectively. This runoff volume resulted in a vulnerability increase from 10.4 to 12.2% and a reliability reduction from 97.5 to 95.8%. To evaluate the network's performance under future climate change scenarios, the SWMM model was used with data from the IPCC sixth assessment report. Among the top five climate models, the one with the highest precipitation was selected as the pessimistic scenario. Simulation results under future conditions indicated a significant runoff volume increase, reaching 64.04 and 72.18 thousand m3 in 5- and 10-year return periods, respectively. This increase corresponded to vulnerability indices of 12.7 and 13.9% and reliability indices of 95.3 and 94.3% for the same return periods. To enhance the network's resilience, a genetic algorithm-based optimization approach was employed. Cost, reliability, and vulnerability index were considered optimization objectives with specific weighting functions. The algorithm converged to an optimal design solution in the 168th iteration, resulting in a 7.6% vulnerability reduction and a 98.1% reliability enhancement. Conclusion The vulnerability index in the return periods of 5 and 10 years is equal to 12.7 % and 13.9 %, respectively, and the reliability index is equal to 95.3 % and 94.3 %. After checking the network in its current state and future conditions, an optimal network redesign was done to improve system performance in both current and future conditions. For this purpose, the genetic algorithm was used for optimization, and the objective function consisting of cost, vulnerability index, and reliability index and the importance weights of each, were defined. Then, MATLAB software did the optimal network redesign by connecting the simulator and optimizer model. The results showed that in the 168th iteration, the algorithm reached its final answer of 0.3, which remained constant until the 300th iteration. Also, the optimal redesign has reduced network vulnerability by 7.6% and increased reliability by 98.1%. This research showed that with an optimal redesign and solving the current network problems, the system's ability to face future climate change threats could also be increased. Of course, spending the least money to achieve the best result was one of the main goals of this research. In future studies, it is recommended to use low-impact development tools along with optimal redesign to fix defects and improve the performance of the runoff collection network.

To reduce the dependence on natural aggregates and to improve the utilization of solid waste, travertine waste cutting stone pieces were used as aggregate to produce travertine pervious concrete (TPC). This paper focuses on the effect of various factors, including contact time, travertine replacement rate, cement amount used, contact area and competitive adsorption on the removal of Cd2+, Cu2+ and Pb2+ by TPC and travertine under the rapid method and immersion method. The results showed that the contact time between TPC and heavy metal solution directly affects the adsorption capacity. The removal rates of Cd2+, Cu2+ and Pb2+ (95.28–100.00 %) with the immersion method are greatly higher than that under the rapid method (only 12.38–27.45 %). Encased in cement paste, travertine aggregates in pervious concrete can only remove 1.52–4.80 % of heavy metal ions. As the main adsorbent for heavy metal ions, the cement paste reported in this study can remove almost all heavy metal ions in the solution under the long-term leaching tests. Furthermore, the travertine itself with porosity and high CaO also has a higher ability to remove heavy metals and its removal capacity was also directly affected by the contact area. Under the influence of ternary competitive mechanism, the adsorption capacity of TPC is Pb2+ > Cd2+ > Cu2+. Finally, a laboratory-scale TPC pavement (TPCP) with a rainfall system was built. The 72.17–96.23 % urban runoff could be removed by TPCP in one hour, and the removal rates of TPCP for Cd2+, Cu2+ and Pb2+ all exceeded 96.0 % within 30 minutes, demonstrating environmental friendliness.

Natural stormwater treatment systems (NTS) are built ecosystems designed to capture and treat stormwater runoff via natural processes. Although NTS design typically targets water services, the biological communities associated with NTS (i.e., plants, animals, and microbes) can provide non-targeted functions that can result in ecosystem services, such as biodiversity, pollination, and climate regulation, or in some cases disservices. Additional co-benefits of NTS include recreation, education and outreach opportunities, and aesthetic value. A review of NTS ecosystem services and co-benefits is provided with specific examples from Los Angeles County, highlighting the need for ecosystem services indicators, standard measurements, and monitoring. As NTS become globally widespread, best practices must include the ability to holistically assess NTS performance in ways that extend beyond water treatment services. Three models are presented that can be used to evaluate NTS performance. Such information can be important in advancing NTS design, choosing spatial placement, and making choices between NTS and more traditional stormwater treatment options.

Urban areas produce large amounts of stormwater runoff due to vast areas of impervious surfaces. Stormwater inlets, or catch basins, are commonly used for collecting and directing stormwater runoff away from streets and sidewalks. The conveyances used to direct flow to surface waters may be part of a municipal separate storm sewer systems (MS4s). Typically, MS4s redirect runoff without providing a means for removing harmful pollutants. These pollutants are then often discharged directly into local lakes, rivers, and streams, potentially harming native aquatic ecosystems. Post-construction stormwater practices are commonly used to treat runoff from urban areas by reducing the total runoff volume, lowering peak flow rates, and/or removing harmful pollutants from runoff. However, some post construction stormwater practices require large footprints, construction, and maintenance. Catch basin inserts (CBIs) are one type of post-construction best management practice that are installed within existing catch basins and require no additional land use while still providing a means for removing pollutants from stormwater runoff before entering the MS4. However, limited data is available to demonstrate the expected performance of various CBIs to ensure that these practices meet the pollutant removal standards set forth by the US Environmental Protection Agency (USEPA). The objective of this study was to evaluate the sediment removal capabilities of eight different proprietary CBI products for potential use as a post-construction stormwater practice for Department of Transportation projects. Results indicate that only two basket-type CBIs met the 80% sediment retention benchmark established for the study. While not surpassing the benchmark, three bag-type CBIs did achieve more than 70% sediment retention. The remaining three CBIs (one basket-type, one bag-type, and one cartridge type) fell notably short of the performance benchmark. [ABSTRACT FROM AUTHOR]