Wetland-dominated landscapes influence carbon cycling through their potential to act as both carbon sinks and sources. Wetlands in low-relief landscapes have dynamic terrestrial-aquatic interfaces that change seasonally with variable surface water and groundwater levels. However, few studies have directly quantified dissolved organic matter (DOM) release and greenhouse gas (CO2, CH4) fluxes from wetland soils along terrestrial-aquatic interfaces as they are seasonally re-saturated by groundwater. To estimate groundwater-mediated soil DOM and gas fluxes, we performed laboratory simulations of vertical groundwater rise on intact soil cores collected from four Delmarva bay wetlands located in the Mid-Atlantic United States. At each wetland, one core was collected from within the wetland basin and the other from the transitional zone at the basin edge. Cores were re-saturated with groundwater over 15 days and then kept fully saturated for an additional 25 days. Source groundwater, soil porewater, and exfiltrated surface water samples were collected and analyzed for pH, ORP, DOM concentration, and DOM optical indices. In both the wetland and transition zone cores, porewater DOM concentrations increased over the wet up and were sustained during prolonged saturation. Optical indices shifted from recently produced, microbial-like signatures towards aromatic, terrestrial-like signatures. Fluxes of CO2 decreased as the duration of soil saturation increased and soil cores switched from CH4 sinks to sources upon full soil core saturation. Results indicate that groundwater rise sustains carbon mobilization from soils in wetland-dominated landscapes, emphasizing the need to understand how climate-driven changes to groundwater dynamics may affect carbon fluxes along terrestrial-aquatic interfaces.

Urban development normally occurs at the urban-rural interface, often in a spider-like appearance known as 'urban sprawl'. Mixed urban-rural watersheds are likely to experience hydrologic alterations such as increased peak flow and pollutant loads, further intensified by climate change. The implementation of low-impact development (LID) controls and best management practices (BMPs) offers a promising approach to improve watershed resilience. However, determining the optimal type, size, and placement of these measures remains challenging due to multiple objectives and constraints. We present a multi-objective simulation-optimization tool that integrates a coupled modeling framework with an evolutionary algorithm to optimize the performance of LID and BMP strategies. The simulation framework sequentially couples the Storm Water Management Model (SWMM) and the Soil and Water Assessment Tool Plus (SWAT+), and links to a cost estimation module to identify cost-effective stormwater control measures (SCMs) that balance peak flow reduction and runoff volume reduction. This tool was applied to the Stroubles Creek watershed in Montgomery County, Virginia, to optimize SCMs across a mixed urban-rural landscape. The tool generated a set of Pareto-optimal strategies that illustrate trade-offs among peak flow reduction, volume reduction, and implementation cost, helping stakeholders make informed decisions based on regulations, budgets, and practical constraints.

The fast pace of urban development and increasing intensity of precipitation events have made managing urban stormwater an increasingly difficult challenge. Hydrologic models are commonly used to predict flows and assess the performance of stormwater controls, often based on a hypothetical yet standardized design storm. The Storm Water Management Model (SWMM) is widely used for simulating runoff in urban watersheds. However, calibration of SWMM, as with all hydrologic models, is often plagued with issues such as subjectivity, and an abundance of model parameters, leading to delays and inefficiencies in model development and application. Further development of modeling and simulation tools to aid in design is critical in improving the function of stormwater management systems. To address these issues, we developed an integration of PySWMM (a Python wrapper (tool) for SWMM) and Pymoo (a Python package for multi-objective optimization) to automate the SWMM calibration process. The tool was tested using a case study urban watershed in Fredericksburg, VA. This tool can employ either a single-objective or multi-objective approach to calibrate a SWMM model by minimizing the error between prediction and observed values. This tool uses performance metrics including Nash-Sutcliffe Efficiency (NSE), Percent Bias (PBIAS), and Root Mean Square Error (RMSE) Standardized Ratio (RSR) for both single-event and long-term continuous rainfall-runoff processes. During multi-objective optimization calibration, the model achieved NSE, PBIAS, and RSR values of 0.73, 17.1, and 0.52, respectively; while the validation period recorded values of 0.86, 13.1, and 0.37, respectively. Additionally, in the single-objective optimization test case, the model yielded NSE values of 0.68 and 0.73 for the calibration and validation, respectively. The tool also supports parallelized optimization algorithms and utilizes Application Programming Interfaces (APIs) to dynamically update SWMM model parameters, accelerating both model execution and convergence. The tool successfully calibrated the SWMM model, delivering reliable results with suitable computational performance.

The fast-paced urbanisation has resulted in urban-rural transitional zones known as 'sprawl' that exhibit both urban and rural characteristics. This transformation significantly impacts water balance, leading to changes in surface runoff patterns in these mixed urban rural watersheds. The contrasting runoff generation patterns in urban and rural land uses pose significant challenges for accurately simulating runoff in these urban rural watersheds. To address these mixed watersheds, we developed an Integrated Environmental Modelling (IEM) approach to effectively represent complex hydrological behaviours in both urban and rural areas by integrating two widely used models: the Storm Water Management Model (SWMM) and the Soil and Water Assessment Tool Plus (SWAT+). The integrated model provides a means for coupling models, data storage, analysis, visualisation, and decision support systems. This framework links PYSWMM and PYSWAT+, offering automatic calibration of the integrated model in Python, which improves runoff simulation by considering distinct runoff generation patterns for each land use and the unique characteristics of each subcatchment. This study aims to improve our understanding of how runoff generation and streamflow behaviour vary across urban and rural areas by evaluating the performance of a coupled SWMM-SWAT+ model. A case study conducted in the urban-rural watershed of Stroubles Creek, Virginia, USA, demonstrated that the integrated model outperformed both standalone models in predicting streamflow during dry and wet periods. This study successfully shows that the SWMM-SWAT+ integration can effectively represent hydrological processes in mixed urban-rural watersheds, achieving higher accuracy than standalone models. The integrated model achieved higher accuracy than the standalone models, improving NSE from 0.51 (SWAT+) and 0.64 (SWMM) to 0.85, reducing RSR from 0.70 (SWAT+) and 0.60 (SWMM) to 0.39, and lowering PBIAS to 16.8%, compared to 37.87% (SWAT+) and -70.37% (SWMM), demonstrating its superior performance in streamflow simulation. These findings provide a practical and adaptable modelling framework for improving stormwater management, flood risk assessment, and sustainable water resources planning in transitional watersheds experiencing both urban and rural influences.

Communities increasingly face challenges from changing hydrological patterns caused by the combined effects of climate change and land use/land cover (LULC) change. However, the hydrological response of mixed land use watersheds to these combined effects remains poorly understood. To address this gap, we developed an automated platform to retrieve projected climate and LULC data and input them into the Storm Water Management Model (SWMM) and the Soil and Water Assessment Tool Plus (SWAT+). These models were coupled to assess the impacts of climate and LULC change on the Stroubles Creek watershed in Montgomery County, Virginia. Climate projections were obtained from CMIP6 and combined with LULC projections from the Integrated Climate and Land Use Scenarios (ICLUS) data source. The joint impacts of climate and LULC change were assessed over three 30-year periods, baseline (1981-2010), mid-century (2031-2060), and late-century (2071-2100), using projections from two Shared Socioeconomic Pathways (SSP245 and SSP585). Results indicate that temperatures are projected to increase under both scenarios in the mid- and late-century periods, with a maximum rise of nearly 9 °C by the late century under SSP585. The warming is most pronounced in winter, while spring and summer exhibit comparatively milder increases. Precipitation projections indicate a shift toward more intense rainfall events under most scenarios, with the exception of mid-century SSP585. In the mid-century SSP245 scenario, precipitation increases by up to 21.6 %. Expanding urban land use, together with these higher-intensity storms, leads to a sharp rise in urban peak flows, with 25-year flood magnitudes increasing by up to 100 % in the mid-century SSP245 scenario. In contrast, the decline in mean annual precipitation, coupled with the expansion of impervious surfaces, leads to substantial reductions in 7Q30 in urban areas, with decreases reaching nearly 45 % under the late-century SSP585 scenario. These findings underscore that urban areas are particularly vulnerable to the compounded effects of climate and land use change, facing amplified flood risks and reduced drought resilience compared to rural portions of the watershed.

There has been significant investment in stormwater control measures (SCM) to reduce erosion, filter pollutants, and mitigate peak storm flows within urban watersheds. SCMs have variable hydrologic connectivity to downstream waterbodies where SCMs may rapidly export water during storm events but dry up in-between events and these alternating wet/dry cycles influence the biogeochemical processes that occur in SCM soils. While the performance of SCMs has been evaluated for nutrient removal, less is known about the potential for mobilization of nutrients and dissolved organic matter (DOM) that accumulate in SCM soils. Because of the significant aquatic ecosystem and human health implications related to excess DOM and nutrients, further work is needed to understand how urban SCMs and wetland soils may be impacting downstream water quality. Water-soluble organic matter (WSOM) was extracted from SCM and urban wetland soils located in the Rappahannock River watershed, part of the larger Chesapeake Bay watershed in the Mid-Atlantic region, to assess the potential mobilization of DOM and nutrients from SCM soils. We found low quantities of readily released organic matter and nutrients regardless of SCM type. WSOM concentration and composition did not vary spatially within SCMs. However, SCM surface water had plant-like signatures and was more aromatic compared to WSOM, indicating that organic matter processing occurs as water moves through SCM soil media. Monthly sampling of SCM soils suggests WSOM and nutrient quantities peak when SCMs are dry. When accounting for spatial extent, SCMs likely serve as smaller potential sources of carbon to downstream aquatic ecosystems relative to larger naturally occurring urban wetlands. Exploring the potential soil-derived DOM in SCMs and urban wetlands furthers our knowledge of how urban systems influence DOM concentration and composition, while examining the performance of SCMs relative to natural soil systems.

Many states in the Eastern U.S. have limited water withdrawal regulations, posing significant risks to water supply management during periods of low flows. While these states require water withdrawal permits, exemptions for grandfathered withdrawals that allow unregulated access to surface water are common. Such permit exemptions present a challenge to water supply management, as full utilization of allowable withdrawals by permit-exempt users could pose risks to maintaining adequate water supplies for current and projected demand. This study used reported permit exemption data in Virginia to understand the extent, volume, and potential impact of permit-exempt withdrawals on 30- and 90-day low flows. The permit-exempt withdrawal values used in this study were obtained from Virginia Department of Environmental Quality. Maximum permit-exempt withdrawal volumes were significantly higher than projected future demands in permitted users. The impacts of these withdrawals on drought flows were compared with the impacts presented by climate change and demand growth. Widespread reduction in flows was observed with the "dry" future climate change scenario, while impacts were more localized in the exempt users and the demand growth scenarios. The impacts of exempt users exceeded the impact of climate change and demand growth scenarios in many regions during low-flow periods. Therefore, more comprehensive water planning, policy and research is needed to address the impact of permit exemptions.

Headwater wetlands are important sites for carbon storage and emissions. While local- and landscape-scale factors are known to influence wetland carbon biogeochemistry, the spatial and temporal heterogeneity of these factors limits our predictive understanding of wetland carbon dynamics. To address this issue, we examined relationships between carbon dioxide (CO2) and methane (CH4) concentrations with wetland hydrogeomorphology, water level, and biogeochemical conditions. We sampled water chemistry and dissolved gases (CO2 and CH4) and monitored continuous water level at 20 wetlands and co-located upland wells in the Delmarva Peninsula, Maryland, every 1–3 months for 2 years. We also obtained wetland hydrogeomorphologic metrics at maximum inundation (area, perimeter, and volume). Wetlands in our study were supersaturated with CO2 (mean = 315 μM) and CH4 (mean = 15 μM), highlighting their potential role as carbon sources to the atmosphere. Spatial and temporal variability in CO2 and CH4 concentrations was high, particularly for CH4, and both gases were more spatially variable than temporally. We found that groundwater is a potential source of CO2 in wetlands and CO2 decreases with increased water level. In contrast, CH4 concentrations appear to be related to substrate and nutrient availability and to drying patterns over a longer temporal scale. At the landscape scale, wetlands with higher perimeter:area ratios and wetlands with higher height above the nearest drainage had higher CO2 and CH4 concentrations. Understanding the variability of CO2 and CH4 in wetlands, and how these might change with changing environmental conditions and across different wetland types, is critical to understanding the current and future role of wetlands in the global carbon cycle.

Animal waste can contribute substantially to nutrient cycling and ecosystem productivity in many environments. However, little is known of the biogeochemical impact of animal excretion in wetland habitats. Here we investigate the effects of wood frog (Lithobates sylvaticus) tadpole aggregations on nutrient recycling, microbial metabolism and carbon cycling in geographically isolated wetlands. We used a paired mesocosm and field study approach that utilized measurements of tadpole excretion rates, microbial extracellular enzyme activities, and litter degradation. We found a strong relationship between tadpole development and nutrient excretion, demonstrating that ontological changes impact tadpole-mediated nutrient cycling in wetland habitats. Further, the interplay between population-level tadpole excretion and wetland hydrologic conditions increased ambient NH 4 + and PO 4 3 - concentrations by 56 and 14 times, respectively, compared to adjacent wetlands without tadpoles. Within our mesocosm study, microbes decreased extracellular enzyme production associated with nitrogen acquisition in response to the presence of tadpole-derived nitrogen. In addition to microbial metabolic responses, tadpole presence enhanced litter breakdown in both mesocosms and wetlands by 7% and 12%, respectively, in comparison to reference conditions. These results provide evidence for the functional and biogeochemical role of tadpole aggregations in wetland habitats, with important implications for ecosystem processes, biodiversity conservation, and ecosystem management.

Globally significant quantities of carbon (C), nitrogen (N), and phosphorus (P) enter freshwater reservoirs each year. These inputs can be buried in sediments, respired, taken up by organisms, emitted to the atmosphere, or exported downstream. While much is known about reservoir-scale biogeochemical processing, less is known about spatial and temporal variability of biogeochemistry within a reservoir along the continuum from inflowing streams to the dam. To address this gap, we examined longitudinal variability in surface water biogeochemistry (C, N, and P) in two small reservoirs throughout a thermally stratified season. We sampled total and dissolved fractions of C, N, and P, as well as chlorophyll-a from each reservoir’s major inflows to the dam. We found that heterogeneity in biogeochemical concentrations was greater over time than space. However, dissolved nutrient and organic carbon concentrations had high site-to-site variability within both reservoirs, potentially as a result of shifting biological activity or environmental conditions. When considering spatially explicit processing, we found that certain locations within the reservoir, most often the stream–reservoir interface, acted as “hotspots” of change in biogeochemical concentrations. Our study suggests that spatially explicit metrics of biogeochemical processing could help constrain the role of reservoirs in C, N, and P cycles in the landscape. Ultimately, our results highlight that biogeochemical heterogeneity in small reservoirs may be more variable over time than space, and that some sites within reservoirs play critically important roles in whole-ecosystem biogeochemical processing.

River flooding impacts human life and infrastructure, yet provides habitat and ecosystem services. Traditional flood control (e.g., levees, dams) reduces habitat and ecosystem services, and exacerbates flooding elsewhere. Floodplain restoration (i.e., bankfull floodplain reconnection and Stage 0) can also provide flood management, but has not been sufficiently evaluated for small frequent storms. We used 1D unsteady Hydrologic Engineering Center's River Analysis System to simulate small storms in a 5 km‐long, second‐order generic stream from the Chesapeake Bay watershed, and varied % channel restored (starting at the upstream end), restoration location, restoration bank height (distinguishes bankfull from Stage 0 restoration), and floodplain width/Manning's n . Stream restoration decreased (attenuated) peak flow up to 37% and increased floodplain exchange by up to 46%. Floodplain width and % channel restored had the largest impact on flood attenuation. The incremental effects of new restoration projects on flood attenuation were greatest when little prior restoration had occurred. By contrast, incremental effects on floodplain exchange were greatest in the presence of substantial prior restoration, setting up a tradeoff. A similar tradeoff was revealed between attenuation and exchange for project location, but not bank height or floodplain width. In particular, attenuation and exchange were always greater for Stage 0 than for bankfull floodplain restoration. Stage 0 thus may counteract human impacts such as urbanization.

Stream confluences are ubiquitous interfaces in freshwater networks and serve as junctions of previously independent landscapes. However, few studies have investigated how confluences influence the transport, mixing, and fate of organic matter (OM) and inorganic nutrients at the scale of river networks. To understand how network biogeochemical fluxes may be altered by confluences, we conducted two sampling campaigns at five confluences in summer and fall 2021 spanning the extent of a mixed land use stream network. We sampled the confluence mainstem and tributary reaches as well as throughout the mixing zone downstream. We predicted that biologically reactive solutes would mix non‐conservatively downstream of confluences and that alterations to downstream biogeochemistry would be driven by differences in chemistry and size of the tributary and upstream reaches. In our study, confluences were geomorphically distinct (e.g., wider, deeper, unique erosional, and depositional features) downstream compared to reaches upstream of the confluence. Dissolved OM and nutrients mixed non‐conservatively downstream of the five confluences. Biogeochemical patterns downstream of confluences were only partially explained by contributing reach chemistry and drainage area. We found that the relationship between geomorphic variability, water residence time, and microbial respiration differed between reaches upstream and downstream of confluences. The lack of explanatory power from network‐scale drivers suggests that non‐conservative mixing downstream of confluences may be driven by biogeochemical processes within the confluence mixing zone. The unique geomorphology, non‐conservative biogeochemistry, and ubiquity of confluences highlights a need to account for the distinct functional role of confluences in water resource management in freshwater networks.

Small impoundments are numerous throughout river corridors. Limited data on their size and outflow have made it difficult to assess how these smaller impoundments cumulatively impact streamflow. This study combined rainfall‐runoff data from the Chesapeake Bay Watershed Model with a routing framework to develop a hydrologic model capable of analyzing flow alteration induced by cumulative impoundment. Using standard design processes and satellite imagery, simulations of impoundment hydraulics were assembled for both small and large impoundments. Eleven of the 170 impoundments in the Difficult Run watershed were modeled to assess their cumulative impact on downstream flow from 1984 to 2005. Multiple simulations were analyzed to determine incremental effects. We found that flow alteration increased with impoundment density. Impoundments prolonged storm hydrographs, increasing median and baseflows, and decreasing peak streamflow downstream. Impoundment size and location impacted downstream flow alteration as headwater channels ran dry and evaporation from impoundments with high surface area to storage ratios decreased extreme low flows. Large reservoirs had a greater impact on median flows, as small ponds dominated low flow alteration. Including a greater fraction of the watershed’s 170 small impoundments may further increase flow alteration. These results suggest that small impoundments play a large role in determining water availability, particularly during droughts.

Understanding water consumption is an important component of water management. However, water consumption data are limited and consumption coefficients do not account for variability through time and across users. This study combines federally maintained discharge data with state-maintained withdrawal data at monthly time steps to estimate facility-level and spatially aggregated water consumption in Virginia between 2010 and 2016. We evaluate (1) the feasibility of using discharge and withdrawal datasets to estimate sub-annual water consumption, (2) how these consumption estimates vary depending on the level of spatial aggregation, and (3) what patterns of seasonality exist in consumption estimates. We find that a combined process of text matching and geospatial analysis is effective in matching facilities and yielding monthly time-series of water consumption. Our results suggest that median consumption in industrial (17%) and commercial (19%) facilities may be higher than median consumption coefficients in the literature (10%). Consumption estimates also demonstrated more variability across facilities and seasons than aggregate coefficients in the literature suggest. Combining this approach with institutional knowledge can assist in quantifying issues such as inter-basin transfers and infiltration that impact consumption estimates, ultimately allowing for more accurate accounts of water use and availability.

Preferential flow reduces water residence times and allows rapid transport of pollutants such as organic contaminants. Thus, preferential flow is considered to reduce the influence of soil matrix-solute interactions during solute transport. While this claim may be true when rainfall directly follows solute application, forcing rapid chemical and physical disequilibrium, it has been perpetuated as a general feature of solute transport-regardless of the magnitude preferential flow. A small number of studies have alternatively shown that preferential transport of strongly sorbing solutes is reduced when solutes have time to diffuse and equilibrate within the soil matrix. Here we expand this inference by allowing solute sorption equilibrium to occur and exploring how physiochemical properties affect solute transport across a vast range of preferential flow. We applied deuterium-labeled rainfall to field plots containing manure spiked with eight common antibiotics with a range of affinity for the soil after 7 days of equilibration with the soil matrix and quantified preferential flow and solute transport using 48 soil pore water samplers spread along a hillslope. Based on > 700 measurements, our data showed that solute transport to lysimeters was similar-regardless of antibiotic affinity for soil-when preferential flow represented less than 15% of the total water flow. When preferential flow exceeded 15%, however, concentrations were higher for compounds with relatively low affinity for soil. We provide evidence that (1) bypassing water flow can select for compounds that are more easily released from the soil matrix, and (2) this phenomenon becomes more evident as the magnitude of preferential flow increases. We argue that considering the natural spectrum preferential flow as an explanatory variable to gauge the influence of soil matrix-solute interactions may improve parsimonious transport models.

Freshwater harmful algal blooms (HABs), caused mostly by toxic cyanobacteria, produce a range of cyanotoxins that threaten the health of humans and domestic animals. Climate conditions and anthropogenic influences such as agricultural run-off can alter the onset and intensity of HABs. Little is known about the distribution and spread of freshwater HABs. Current sampling protocols in some lakes involve teams of researchers that collect samples by hand from a boat and/or from the shoreline. Water samples can be collected from the surface, from discrete-depth collections, and/or from depth-integrated intervals. These collections are often restricted to certain months of the year, and generally are only performed at a limited number of collection sites. In lakes with active HABs, surface samples are generally sufficient for HAB water quality assessments. We used a unique DrOne Water Sampling SystEm (DOWSE) to collect water samples from the surface of three different HABs in Ohio (Grand Lake St Marys, GLSM and Lake Erie) and Virginia (Lake Anna), United States in 2019. The DOWSE consisted of a 3D-printed sampling device tethered to a drone (uncrewed aerial system, or UAS), and was used to collect surface water samples at different distances (10–100 m) from the shore or from an anchored boat. One hundred and eighty water samples (40 at GLSM, 20 at Lake Erie, and 120 at Lake Anna) were collected and analyzed from 18 drone flights. Our methods included testing for cyanotoxins, phycocyanin, and nutrients from surface water samples. Mean concentrations of microcystins (MCs) in drone water samples were 15.00, 1.92, and 0.02 ppb for GLSM, Lake Erie, and Lake Anna, respectively. Lake Anna had low levels of anatoxin in nearly all (111/120) of the drone water samples. Mean concentrations of phycocyanin in drone water samples were 687, 38, and 62 ppb for GLSM, Lake Erie, and Lake Anna, respectively. High levels of total phosphorus were observed in the drone water samples from GLSM (mean of 0.34 mg/L) and Lake Erie (mean of 0.12 mg/L). Lake Anna had the highest variability of total phosphorus with concentrations that ranged from 0.01 mg/L to 0.21 mg/L, with a mean of 0.06 mg/L. Nitrate levels varied greatly across sites, inverse with bloom biomass, ranging from below detection to 3.64 mg/L, with highest mean values in Lake Erie followed by GLSM and Lake Anna, respectively. Drones offer a rapid, targeted collection of water samples from virtually anywhere on a lake with an active HAB without the need for a boat which can disturb the surrounding water. Drones are, however, limited in their ability to operate during inclement weather such as rain and heavy winds. Collectively, our results highlight numerous opportunities for drone-based water sampling technologies to track, predict, and respond to HABs in the future.

Hydrologic controls on carbon processing and export are a critical feature of wetland ecosystems. Hydrologic response to climate variability has important implications for carbon‐climate feedbacks, aquatic metabolism, and water quality. Little is known about how hydrologic processes along the terrestrial‐aquatic interface in low‐relief, depressional wetland catchments influence carbon dynamics, particularly regarding soil‐derived dissolved organic matter (DOM) transport and transformation. To understand the role of different soil horizons as potential sources of DOM to wetland systems, we measured water‐soluble organic matter (WSOM) concentration and composition in soils collected from upland to wetland transects at four Delmarva Bay wetlands in the eastern United States. Spectral metrics indicated that WSOM in shallow organic horizons had increased aromaticity, higher molecular weight, and plant‐like signatures. In contrast, WSOM from deeper, mineral horizons had lower aromaticity, lower molecular weights, and microbial‐like signatures. Organic soil horizons had the highest concentrations of WSOM, and WSOM decreased with increasing soil depth. WSOM concentrations also decreased from the upland to the wetland, suggesting that continuous soil saturation reduces WSOM concentrations. Despite wetland soils having lower WSOM, these horizons are thicker and continuously hydrologically connected to wetland surface and groundwater, leading to wetland soils representing the largest potential source of soil‐derived DOM to the Delmarva Bay wetland system. Knowledge of which soil horizons are most biogeochemically significant for DOM transport in wetland ecosystems will become increasingly important as climate change is expected to alter hydrologic regimes of wetland soils and their resulting carbon contributions from the landscape.

Urban developments can result in higher runoff and nutrient loadings transported to downstream receiving waterbodies. While much effort has been made recently inwatershed restoration in the U.S., a lack of recent runoff quality data limits the prediction capability of urban watershed models. The objectives of this study was to fill an existing information gap on how rainfall and land uses interact and affect such loadings. This study instrumented six coastal urban catchments, each dominated by a single land use. We measured total nitrogen (TN), total phosphorus (TP), total suspended solids (TSS), total Kjeldahl Nitrogen (TKN), ortho-P, and nitrate concentrations in runoff from 30 storm events over one year from six urban land uses, namely commercial, industrial, transportation, open space, low density residential, and high density residential. Results indicated that the median event mean concentrations (EMCs) for TSS, TP, and TN were 30 (19-34), 0.31 (0.26-0.31), and 0.94 (0.73-1.25) mg L-1, respectively. TSS EMCs from the open space and industrial land uses were significantly greater than other land uses; there were positive correlations between TN concentrations and imperviousness and between TP concentrations and turf coverage. Both the amount and intensity of rainfall positively influenced TSS concentrations in runoff regardless of land use. Using the collected data, this study developed a generic equation for predicting the loading of a pollutant as a function of rainfall depth. This equation was verified by comparing its predictionswith the simulations of a sufficiently-calibratedwater quality model in terms of TSS, TP, and TN loadings from various land uses in another coastal catchment for a period of ten years. Average TSS, TN, and TP loadings from the catchment were estimated to be 0.86, 0.03, and 0.01 kg ha(-1) cm(-1), respectively. (C) 2021 Elsevier B.V. All rights reserved.

Urbanization increases runoff, sediment, and nutrient loadings downstream, causing flooding, eutrophication, and harmful algal blooms. Stormwater control measures (SCMs) are used to address these concerns and are designed based on inflow loads. Thus, estimating nutrient and sediment loads is important for meeting restoration objectives. Pollutants accumulate on surfaces during dry periods, making Event Mean Concentration (EMC) a function of antecedent dry period (ADP). An EMC results from wash-off of accumulated pollutants from catchment surface during runoff events. However, several studies found little to no correlation between constituent concentrations in stormwater and ADP. The objective of this study is to verify this finding and discover which climatological or catchment characteristics most significantly affect stormwater quality. Stormwater quality data were obtained from the National Stormwater Quality Database (NSQD), which is the largest data repository of stormwater quality data in the U.S. Bayesian Network Structure Learner (BNSL) was used to assess the relationships between catchment characteristics, climatological information, and stormwater quality for selected land uses. Given the optimal BN structure, it was determined which parameters most affect stormwater quality EMCs. The results demonstrate that both catchment and rain characteristics affected stormwater quality EMCs. Among catchment characteristics, land use (LU) was the most important factor and catchment size was the least. Precipitation depth (P) and duration (D) affected Total Phosphorus (TP), Total Nitrogen (TN), and Total Suspended Solids (TSS). This indicated that it is likely that P and D had a greater influence on stormwater quality more than ADP. P, D, and ADP affected the dissolved constituents of TN (i.e. NO2-N/NO3-N) and TP (i.e. Ortho-P). Compared to other factors (i.e. P and D), the effect of ADP on TSS was negligible. Stormwater quality EMCs related to nitrogen were not affected by catchment slope (S). However, TSS and Ortho-P were influenced by S.