Effective freshwater management depends on understanding how human activities and geological processes influence streamflow dynamics. Urbanization disrupts natural hydrological processes, altering both stormflow and baseflow. Karst watersheds, characterized by complex and heterogeneous surface-groundwater interactions, pose unique challenges for predicting the impacts of urban development on streamflow. This study investigates how urbanization and karst groundwater interactions influence streamflow variability in a mixed land-use watershed within the Ridge and Valley Province of central Pennsylvania. We analyzed 24 years (2000-2024) of streamflow data from 14 monitoring stations spanning gradients in urbanization (10%-90% developed land) and karst geology. Streamflow metrics including flow duration curves, baseflow index, Richards-Baker flashiness index, master recession curve slopes, and low-flow trends, were used to assess land use and groundwater controls. Urbanization increased stream flashiness, steepened recession rates, and decreased the proportion of base flow. Streams with the highest levels of development exhibited most sensitivity to further increases in urban land cover. In contrast, streams with substantial groundwater inputs exhibited more stable baseflows and were less sensitive to drought conditions. Stormwater infiltration and wastewater recycling supported low-flow regimes, partially offsetting development effects, whereas recent growth combined with groundwater withdrawals led to reduced low flows in some areas. These findings highlight the need to account for hydrological complexity and groundwater recharge when managing water resources in increasingly urbanized karst watersheds.

Despite increased understanding and adoption of nature-based solutions (NBSs) within urban and coastal areas, large-scale NBS for fluvial flood mitigation remain challenging to study and implement. A stronger evidence base is needed to identify critical research gaps and to best inform the design and deployment of NBS on the watershed scale. We synthesize evidence of the performance and co-benefits of NBS for fluvial flood mitigation based on a systematic review of 131 peer-reviewed papers worldwide, developing an Ecosystem Focus Type (EFT) to compare flood mitigation across large-scale NBS. While we find that NBS can mitigate fluvial floods across all EFTs, our study also highlights that inconsistencies in measurement methods, a dearth of empirical case studies, and large variability in reported values limit generalization and comparison across NBS. Co-benefits for fluvial flood NBS are numerous, but few are quantified, and study methods vary with regard to specific NBS. Social benefits of NBS, including benefits to communities most in need of support, are infrequently part of these studies. There is a clear need to develop common design and performance standards for large-scale NBS and for guidance on which measures are key to consider and monitor for flood mitigation and co-benefits. The success of large-scale NBS for fluvial flood mitigation will depend on research and practice guided by transdisciplinary systems thinking approaches that can deliver evidence-based, community-driven outcomes.

The importance of subsurface water dynamics, such as water storage and flow partitioning, is well recognised. Yet, our understanding of their drivers and links to streamflow generation has remained elusive, especially in small headwater streams that are often data-limited but crucial for downstream water quantity and quality. Large-scale analyses have focused on streamflow characteristics across rivers with varying drainage areas, often overlooking the subsurface water dynamics that shape streamflow behaviour. Here we ask the question: What are the climate and landscape characteristics that regulate subsurface dynamic storage, flow path partitioning, and dynamics of streamflow generation in headwater streams? To answer this question, we used streamflow data and a widely-used hydrological model (HBV) for 15 headwater catchments across the contiguous United States. Results show that climate characteristics such as aridity and precipitation phase (snow or rain) and land attributes such as topography and soil texture are key drivers of streamflow generation dynamics. In particular, steeper slopes generally promoted more streamflow, regardless of aridity. Streams in flat, rainy sites (< 30% precipitation as snow) with finer soils exhibited flashier regimes than those in snowy sites (> 30% precipitation as snow) or sites with coarse soils and deeper flow paths. In snowy sites, less weathered, thinner soils promoted shallower flow paths such that discharge was more sensitive to changes in storage, but snow dampened streamflow flashiness overall. Results here indicate that land characteristics such as steepness and soil texture modify subsurface water storage and shallow and deep flow partitioning, ultimately regulating streamflow response to climate forcing. As climate change increases uncertainty in water availability, understanding the interacting climate and landscape features that regulate streamflow will be essential to predict hydrological shifts in headwater catchments and improve water resources management.

Lined bioretention basins can be an optimal solution for urban stormwater runoff problems in regions with karst geology or high-density urban environments. In this study, inflows and outflows of a lined bioretention basin in central Pennsylvania were monitored for a year from June 2020 to June 2021. These data were used to generate hydrologic performance metrics, such as peak flow ratio, peak delay ratio, and runoff reduction. The basin displayed an impressive capacity in total volumetric runoff reduction, achieving an overall efficiency of 94%. This exceptional performance was primarily attributed to the basin's effectiveness in capturing and managing smaller storm events. The basin's performance declined when dealing with larger and more intense rainfall events, with a decrease in runoff reduction to as low as 64%. There was excellent control of peak outflow rates from the basin, with nearly 97% of events meeting the target peak flow reduction threshold. The basin did not perform well in delaying its peak outflow, which is likely due to the location of an underdrain very close to the inlet. When evaluating contributions to runoff reduction, the total evapotranspiration, overflow, and storage could not match this reduction volume, indicating leakage and exfiltration from the system. Although there are potential sources of error in this water budget, this indicates possible issues with the integrity of the basin's lining and the importance of proper construction and maintenance. Overall, this study demonstrates the hydrologic benefits that lined bioretention basins can provide but also highlights important monitoring and design considerations. For monitoring, this includes the challenge of closing the water budget and assessing liner leakage. For design, this includes the need to ensure liner integrity and appropriately place underdrains for increased peak flow delay.

Climate change-related risk mitigation is typically addressed using cost-benefit analysis that evaluates mitigation strategies against a wide range of simulated scenarios and identifies a static policy to be implemented, without considering future observations. Due to the substantial uncertainties inherent in climate projections, this identified policy will likely be sub-optimal with respect to the actual climate trajectory that evolves in time. In this work, we thus formulate climate risk management as a dynamic decision-making problem based on Markov Decision Processes (MDPs) and Partially Observable MDPs (POMDPs), taking real-time data into account for evaluating the evolving conditions and related model uncertainties, in order to select the best possible life-cycle actions in time, with global optimality guarantees for the formulated optimization problem. The framework is developed for coastal adaptation applications, considering a wide variety of possible action types, including various forms of nature-based infrastructure. Related environmental impacts of carbon emissions and uptake are also incorporated, and social cost of carbon implications are discussed, together with several future directions and supported features. Climate change-related risk mitigation for infrastructure systems often requires adaptation. A computational framework for optimal decision-making under uncertainty based on dynamically changing conditions observed in time is developed in response.

Internal water storage (IWS) is gaining interest as a design element in stormwater control measures. It is implemented via an upturned elbow or elevated underdrain to create a subsurface storage zone with saturated conditions conducive to nitrogen removal via denitrification. However, IWS can potentially alter emissions of microbially produced greenhouse gases due to changes in subsurface redox conditions. These greenhouse gases include carbon dioxide, methane, and nitrous oxide. We investigated these biogeochemical dynamics using mesocosms mimicking free draining, IWS, and fully saturated stormwater treatment basins. In a series of simulated storm events, we quantified nitrogen removal, dissolved gas concentrations in the outflow, and surface soil emissions of greenhouse gases. IWS and fully saturated mesocosms had the best nitrate reduction, although fully saturated mesocosms exported other forms of nitrogen. Regarding greenhouse gas emissions, fully saturated mesocosms had the highest methane concentrations in outflow water and higher overall greenhouse gas fluxes from the soil surface compared with IWS. Free draining mesocosms sometimes had significantly higher nitrous oxide emissions, particularly after induced drought periods. These results suggest that stormwater basins with IWS have the potential to enhance nitrogen removal while minimizing biological greenhouse gas emissions compared with other stormwater basin drainage configurations.

As climate change impacts accelerate, the characteristics (frequency, depth, intensity) of rainfall events are expected to become more intense and volatile. This study seeks to use historical data to examine stormwater control measures' (SCMs') ability to remove common pollutants during high intensity/depth storm events. This study examines bioretention and grassed swales, due to their prevalence within stormwater systems, varying susceptibility to scour, and depth of data available. Pollutant and rainfall depth data was extracted from the International Stormwater Best Management Practice (BMP) Database. Percent removal as a function of rainfall depth was then calculated. Findings suggest that assumed correlations between pollutants could be inaccurate under expected conditions. Findings also suggest that scour becomes concerning in SCMs that do not contain standing water or have a ponding depth to still water. Future work includes further analyzing assumed correlations between pollutants, expanding SCM types to further investigate effects of scour, and exploring percent removal as related to rainfall intensity.

As solar energy becomes a cheap source of renewable energy, the number of major utility-scale ground solar panel installations, often called 'solar farms,' are growing. With these solar farms often covering hundreds of acres, there is potential for impacts on natural hydrologic processes, including runoff generation and erosion. There is still limited research in this area, and best management practices to address these impacts are variable and not well understood. To fill this gap, we conducted a field investigation of soil moisture patterns, solar radiation, and vegetation at two solar farms in central Pennsylvania, USA that are representative of the complex terrain in the region (e.g., high or variable slopes). Both solar farms also included engineered infiltration basins or trenches that were investigated. Analysis of soil moisture patterns reveals redistribution of water relative to panels, with dripline soil moisture 19 % higher than the reference, and underpanel moisture 25 % lower than the reference, on average at both solar farms over a year. There are also the greatest periods of saturation and runoff generation at the panel driplines. However, an open interspace between panel rows and existing infiltration basins and trenches are playing a critical role in managing runoff. Micrometeorological monitoring indicates reduced evapotranspiration (ET) under panels, with potential underpanel ET 37-67 % lower in summer, and minimal difference in winter. However, a survey of vegetation revealed almost complete ground coverage under panels, which is critical for supporting infiltration and reducing erosion. As solar farms expand to meet important renewable energy goals, it is essential that care be taken to design the landscape to minimize runoff generation and erosion. This work demonstrates that healthy vegetation and well-draining soils can help manage runoff on solar farms; where necessary on more challenging landscapes, engineered stormwater controls can manage any unmitigated runoff.

Abstract Although the importance of dynamic water storage and flowpath partitioning on discharge behavior has been well recognized within the critical zone community, there is still little consensus surrounding the question, “ How do climate factors from above and land characteristics from below dictate dynamic storage, flowpath partitioning, and ultimately regulate hydrological dynamics?” Answers to this question have been hindered by limited and inconsistent spatio-temporal data and arduous-to-measure subsurface data. Here we aim to answer this question above by using a semi-distributed hydrological model (HBV model) to simulate and understand the dynamics of water storage, groundwater flowpaths, and discharge in 15 headwater catchments across the contiguous United States. Results show that topography, precipitation falling as snow, and catchment soil texture all influence catchment dynamic storage, storage-discharge sensitivity, flowpath partitioning, and discharge flashiness. Flat, rain-dominated sites (< 30% precipitation as snow) with finer soils exhibited flashier discharge regimes than catchments with coarse soils and/or significant snowfall (>30% precipitation as snow). Rain-dominated sites with clay soils (indicative of chemical weathering) showed lower dynamic storage and discharge that was more sensitive to changes in dynamic storage than rainy sites with coarse soils. Steep, snowy sites with coarse soils (more mechanical weathering) had lowest dynamic storage and deep groundwater fed discharge that was less sensitive to changes in dynamic storage than fine-soil snowy or rainy catchments. These results highlight aridity and precipitation (snow versus rain) as the dominant climate controls from above and topography and soil texture as the dominant land controls from below. The study challenges the traditional view that climate controls water balance while subsurface structure dictates subsurface flow path. Rather, it shows that climate and land characteristics jointly regulate water balance, groundwater flowpath partitioning, and discharge responses. These findings have important implication for the projection of the future of water resources, especially as climate change and human activities continue to intensify.

Climate change is projected to alter rainfall patterns in many parts of the US and around the world, highlighting the importance of stormwater management systems within resiliency efforts. Stormwater systems typically are designed based on historical rainfall records with the assumption of climate stationarity. This assumption is no longer valid for many locations, leaving a gap in the knowledge about how to ensure that these systems will meet the desired level of service over their design life. Researchers and practitioners have begun exploring how to incorporate future climate scenarios into the design of stormwater systems to maintain the current level of function well into the future. Despite this, uncertainty remains about how to manage cloudburst events, the water quality implications of climate change, and how to incorporate uncertainty in climate model outputs into engineering designs. In the absence of unifying design criteria for incorporating climate change into infrastructure design, communities have begun to form their strategies, from updating intensity-duration-frequency curves to characterizing rainfall based solely on "recent" historical data. As the debate continues regarding how to best protect communities against uncertain future weather patterns, a set of critical considerations has emerged. There is a dire need to explicitly define what resiliency means for stormwater management systems under a climate change paradigm to allow for clear design criteria that incorporate uncertainty and can achieve favorable outcomes at the system scale. There also is ample opportunity to develop new approaches and technologies that allow communities to optimize their infrastructure in terms of water management and an array of other ecosystem services. Thus, despite the current and future challenges of climate change, opportunities exist to develop the next generation of stormwater management systems that serve as multifunctional community assets.

The study compared the life cycle environmental impacts of three coastal flood management strategies: grey infrastructure (levee), green–grey infrastructure (levee and oyster reef), and a do-nothing scenario, considering the flood damage of a single flooding event in the absence of protection infrastructure. A case study was adopted from a New Orleans, Louisiana residential area to facilitate the comparison. Hazus software, design guidelines, reports, existing projects, and literature were utilized as foreground data for modelling materials. A process-based life cycle assessment was used to assess environmental impacts. The life cycle environmental impacts included global warming, ozone depletion, acidification, eutrophication, smog formation, resource depletion, ecotoxicity, and various human health effects. The ecoinvent database was used for the selected life cycle unit processes. The mean results show green–grey infrastructure as the most promising strategy across most impact categories, reducing 47% of the greenhouse gas (GHG) emissions compared to the do-nothing strategy. Compared to grey infrastructure, green–grey infrastructure mitigates 13%–15% of the environmental impacts while providing equivalent flood protection. A flooding event with a 100-year recurrence interval in the study area is estimated at 34 million kg of CO _2 equivalent per kilometre of shoreline, while grey and green–grey infrastructure mitigating such flooding is estimated to be 21 and 18 million kg, respectively. This study reinforced that coastal flooding environmental impacts are primarily caused by rebuilding damaged houses, especially concrete and structural timber replacement, accounting for 90% of GHG emissions, with only 10% associated with flood debris waste treatment. The asphalt cover of the levee was identified as the primary contributor to environmental impacts in grey infrastructure, accounting for over 75% of GHG emissions during construction. We found that there is an important interplay between grey and green infrastructure and optimizing their designs can offer solutions to sustainable coastal flood protection.

Sodium chloride (NaCl) deicers contaminate bioretention and influence effluent water quality, the effects of which are not yet fully understood. We tested this by constructing 48 mesocosms in a greenhouse, each having Panicum virgatum, Eutrochium purpureum, or no vegetation; having an internal water storage (IWS) zone or not; and being exposed to high or low NaCl doses in the late winters of 2022 and 2023. Synthetic stormwater was applied and effluent was monitored through May 2023 with an end-of-experiment analysis of soil and plant biomass for nitrogen, phosphorus, copper, zinc, and total suspended solids (TSS). Average effluent loads increased in spring, after NaCl application, for total phosphorus (+61%), copper (+61%), zinc (+88%), and TSS (+66%). These four analytes recovered by summer, with average annual percent removals >85%. Vegetation and IWS reduced annual phosphorus (by -33 and -70%, respectively) and copper (by -24 and -40%) loads, while higher NaCl concentrations increased annual phosphorus (+107%), copper (+22%), and TSS (+51%) loads. Nitrogen removal was not linked with NaCl but was dependent upon the presence of IWS or vegetation. Post-NaCl effluent spikes pose seasonal risks to aquatic ecosystems, emphasizing the need for active maintenance, redundant removal mechanisms, and minimized exposure to NaCl.

Since the 1987 Clean Water Act Section 319 amendment, the US Government has required and funded the development of nonpoint source pollution programs with about $5 billion dollars. Despite these expenditures, nonpoint source pollution from urban watersheds is still a significant cause of impaired waters in the United States. Urban stormwater management has rapidly evolved over recent decades with decision-making made at a local or city scale. To address the need for a better understanding of how stormwater management has been implemented in different cities, we used stormwater control measure (SCM) network data from 23 US cities and assessed what physical, climatic, socioeconomic, and/or regulatory explanatory variables, if any, are related to SCM assemblages at the municipal scale. Spearman’s correlation and Wilcoxon rank-sum tests were used to investigate relationships between explanatory variables and SCM types and assemblages of SCMs in each city. The results from these analyses showed that for the cities assessed, physical explanatory variables (e.g. impervious percentage and depth to water table) explained the greatest portion of variability in SCM assemblages. Additionally, it was found that cities with combined sewers favored filters, swales and strips, and infiltrators over basins, and cities that are under consent decrees with the Environmental Protection Agency tended to include filters more frequently in their SCM inventories. Future work can build on the SCM assemblages used in this study and their explanatory variables to better understand the differences and drivers of differences in SCM effectiveness across cities, improve watershed modeling, and investigate city- and watershed-scale impacts of SCM assemblages.

ADVERTISEMENT RETURN TO ISSUEPREVViewpointNEXTThe Greatest Opportunity for Green Stormwater Infrastructure Is to Advance Environmental JusticeGregory H. LeFevre*Gregory H. LeFevreDepartment of Civil and Environmental Engineering and IIHR─Hydroscience & Engineering, University of Iowa, Iowa City, Iowa 52242, United States*[email protected]More by Gregory H. LeFevreView Biographyhttps://orcid.org/0000-0002-7746-0297, Marccus D. Hendricks*Marccus D. HendricksSchool of Architecture, Planning & Preservation, University of Maryland, College Park, Maryland 20742, United States*[email protected]More by Marccus D. HendricksView Biography, Maya E. Carrasquillo*Maya E. CarrasquilloDepartment of Civil & Environmental Engineering, University of California─Berkeley, Berkeley, California 94720, United States*[email protected]More by Maya E. CarrasquilloView Biography, Lauren E. McPhillips*Lauren E. McPhillipsDepartment of Civil and Environmental Engineering and Department of Agricultural and Biological Engineering, The Pennsylvania State University, University Park, Pennsylvania 16802, United States*[email protected]More by Lauren E. McPhillipsView Biographyhttps://orcid.org/0000-0002-4990-7979, Brandon K. Winfrey*Brandon K. WinfreyDepartment of Civil Engineering, Monash University, Clayton, Victoria 3800, Australia*[email protected]More by Brandon K. WinfreyView Biography, and James R. Mihelcic*James R. MihelcicDepartment of Civil & Environmental Engineering, University of South Florida, Tampa, Florida 33620, United States*[email protected]More by James R. MihelcicView Biographyhttps://orcid.org/0000-0002-1736-9264Cite this: Environ. Sci. Technol. 2023, 57, 48, 19088–19093Publication Date (Web):November 18, 2023Publication History Received28 August 2023Published online18 November 2023Published inissue 5 December 2023https://pubs.acs.org/doi/10.1021/acs.est.3c07062https://doi.org/10.1021/acs.est.3c07062article-commentaryACS PublicationsCopyright © 2023 American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views2108Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (7 MB) Get e-AlertscloseSUBJECTS:Climate,Environmental science,Groundwaters,Impurities,Water treatment Get e-Alerts

Green stormwater infrastructure (GSI) is adopted to reduce the impact of stormwater on urban flooding and water quality issues. This study assessed the performance of GSI, like bioretention basins, in accumulating metals. Twenty one GSI basins were considered for this study, which were located in New York and Pennsylvania, USA. Shallow (0-5 cm) soil samples were collected from each site at inlet, pool, and adjacent reference locations. The study analyzed 3 base cations (Ca, Mg, Na) and 6 metals (Cd, Cr, Cu, Ni, Pb, and Zn), some of which are toxic to ecosystem and human health. The accumulation of cations/metals at the inlet and pool differed between the selected basins. However, accumulation was consistently higher at the inlet or the pool of the basin as compared to the reference location. Contrary to prior research, this study did not find significant accumulation with age, suggesting that other factors such as site characteristics (e.g., loading rate) might be confounding. GSI basins that receive water only from parking lots or parking lots and building roofs combined showed higher metals and Na accumulation as compared to the basins that received stormwater only from building roofs. Cu, Mg and Zn accumulation showed a positive relationship with the organic matter content in soil, indicating likely sorption of metals on organic matter. Ca and Cu accumulation was greater in GSI basins with larger drainage areas. A negative relationship between Cu and Na implies that Na loading from de-icers may reduce Cu retention. Overall, the study found that the GSI basins are successfully accumulating metals and some base cations, with highest accumulation at the inlet. Additionally, this study provided evidence of GSI effectiveness in accumulating metals using a more cost efficient and time averaged approach compared to traditional means of stormwater inflow and outflow monitoring.

Flooding is a natural hazard that touches nearly all facets of the globe and is expected to become more frequent and intensified due to climate and land-use change. However, flooding does not impact all individuals equally. Therefore, understanding how flooding impacts distribute across populations of different socioeconomic and demographic backgrounds is vital. One approach to reducing flood risk on people is using indicators, such as social vulnerability indices and flood exposure metrics, to inform decision-making for flood risk management. However, such indicators can face the scale and zonal effect produced by the Modifiable Areal Unit Problem (MAUP). This study investigates how the U.S. Census block group, tract, and county scale selection impacts social vulnerability and flood exposure outcomes within coastal Virginia, USA. Here we show how (1) scale selection can obstruct our understanding of drivers of vulnerability, (2) increasingly aggregated scales significantly undercount highly vulnerable populations, and (3) hotspot clusters of social vulnerability and flood exposure can identify variable priority areas for current and future flood risk reduction. Study results present considerations about using such indicators, given the real-life consequences that can occur due to the MAUP. The results of this work warrant understanding the implications of scale selection on research methodological approaches and what this means for practitioners and policymakers that utilize such information to help guide flood mitigation strategies.

Various climate change effects pose increasing risks to the nation's infrastructure. Available methodologies address the risk-management problem primarily through cost-benefit analysis frameworks, which evaluate a comprehensive set of protection strategies against a wide range of simulated possible future scenarios. However, due to the substantial climate model uncertainties present over the future planning horizon, such strategies can often lead to less informed policies that might be optimal in an average sense, over the mean of anticipated future scenarios, but cannot offer adaptive solutions based on the actual climate effects evolving in time. To address these limitations, in this research, climate risk mitigation is instead formulated as a decision-making problem within a closed-loop stochastic control-based framework using Markov decision processes (MDP), taking real-time data into account, for evaluating the evolving conditions, and selecting the best possible, most informed life-cycle actions in time. Although broadly applicable, the merit of the framework will be illustrated through coastal risk mitigation against storm surge and sea-level rise in an idealized coastal city setting.

Green stormwater infrastructure (GSI) can provide multiple benefits in addition to stormwater management. However, there is a need to improve GSI siting to ensure these benefits are realized. We present a planning algorithm that hones in on ‘sweet spots’ of GSI implementation that are hydrologically optimal, feasible, and provide more equitable access to the benefits of GSI. We apply this approach in Lancaster, a city in Pennsylvania, US, with multiple stormwater-related challenges. To identify sweet spots, we first leveraged available spatial data to derive maps of five key criteria, including hydrology, vegetation, property ownership, sewer system type, and social vulnerability. We then normalized each layer and combined them using two different weighting schemes, including an ‘Even Weights’ and a ‘People’s Choice’ scenario based on a choice experiment embedded in a community survey. The survey indicated a preference for prioritizing the hydrology and sewer system criteria. Sweet spots for GSI implementation under each scenario were mapped based on the 90th percentile of the final combined key criteria layers. Comparisons between the two weighting schemes indicated a 73% overlap in sweet spot locations. We also found a small percentage (16%) of existing GSI in Lancaster overlapped with the sweet spots, indicating an opportunity to target future GSI implementation in the remaining sweet spots. Despite being demonstrated in a specific city, this relatively simple approach leveraging widely available spatial data can be applied and customized elsewhere and help improve future GSI siting methods.

Nature-based solutions (NBS) are key for managing water resources, as well as providing many other benefits. While traditionally "gray" highly engineered strategies have been used to manage water in urban areas, we articulate the role that NBS can play in managing water related to flooding, drought, and water quality challenges. Specifically, NBS for water can range from hybrid ecological-technological features explicitly engineered to manage stormwater to other designed or intact natural features such as wetlands or parks that may provide water management as a co-benefit. Criteria are reviewed for choosing the best NBS for the intended goal(s), and we showcase several case examples of NBS for water resilience from around the world. Remaining knowledge gaps for NBS for water implementation include space challenges, changes in performance over time, and incorporation of NBS that are not explicitly engineered for water management into existing management and regulatory frameworks.