Catchment legacies and time lags: a parsimonious watershed model to predict the effects of legacy storage on nitrogen export

Contrasting nitrogen transport patterns in subtropical basins revealed by combined multiple isotopic analyzes and hydrological simulations

Although enhancing the knowledge of nitrogen (N) dynamics in aquatic systems is crucial for basin N management, there is still a lack of theories on the patterns of basin N sources and transport because of the intricate influence of human activities, climatic conditions, landscape patterns, and topography on the trajectory of basin N. To shed new light on the patterns of basin N sources and transport in the Chinese subtropical monsoon region, this study provides a comprehensive approach combining multiple isotopes and hydrological model based on monthly records of hydro-chemistry and isotopes (18O-NO3- /15N-NO-3 and 18O-H2O /2H-H2O) for river water, groundwater and rainfall in three basins over multiple years. Our observations of hydro-chemistry showed that fluvial N levels in highly urbanized basins (3.05 ± 1.42 mg·L-1) were the highest and were characterized by higher levels in the dry season. In the agricultural basin, fluvial N levels in February and March were approximately 1.9 times higher than those in the other months. The fluvial N load was higher in agricultural basins (0.624-0.728 T N km -2 y -1) than in urban basins (0.558 T N km -2 y -1), primarily because of variations in sewage treatment rates and fertilizer application. In highly urbanized basin, manure and sewage (46.9 %) were the dominant sources of fluvial N, which were discharged into rivers after treatment. In the plain agricultural basin, a substantial portion of diffused residential sewage leaches into aquifers and is stored. In the hilly agro-forest mixed basin, the high baseflow coefficient (75.8 %) and the key role of groundwater N, mainly from soil N (27.3 %), chemical fertilizers (20.2 %), manure and sewage (46.6 %), to fluvial N (26.5 %) indicated that a high proportion of the N sources leached into the aquifer and were then transported to rivers. For the first time, this study integrated multiple methods to substantiate the proposed typical patterns of N sources and transport within the basins. These findings have significant implications for tailored basin-specific N management strategies.

Determining the likelihood and cost of detecting reductions of nitrate‑nitrogen concentrations in groundwater across New Zealand

Nitrate‑nitrogen (NO3-N) is a contaminant of concern in groundwater worldwide. Stakeholders need information on the ability to detect changes in NO3-N concentrations to prove that land management practices are meeting water quality aims. We created a database of quarterly to monthly NO3-N measurements in 948 sites across New Zealand; 186 of those sites had mean residence time (MRT) data. New Zealand has set a target of sufficient land use mitigations in the next 30 years to ensure steady state surface water concentrations do not exceed 2.4 mg L-1. Here we assess whether the current monitoring network could identify the impacts of these mitigations, assuming that the mitigations are successfully implemented at the source. Only 41 % of the network could detect statistically significant reductions with the current standard quarterly sampling after 30 years of monitoring. The percentage of sites increased to 60 % with increased monitoring frequency (often weekly) but this required a 100-300 % increase in monitoring costs. However, policy makers and stakeholders typically require information on policy and mitigation effectiveness within 5-10 years. Detection within 5-10 years was very unlikely (0-20 % of sites) regardless of the sampling frequency. Importantly, these analyses include the impacts of groundwater lag and temporal dispersion on the likelihood of detecting change, ignoring these impacts, incorrectly, yields a much higher likelihood of detecting reductions. We conclude that the current monitoring network is unlikely to be fit for the purpose of detecting NO3-N reductions within practical timeframes or budgets. Furthermore, we conclude that lag and temporal dispersion effects must be included in detection power calculations; we therefore recommend that MRT data is regularly collected. We also provide a python package to enable easy detection power calculations with lag and temporal dispersion impacts, thereby supporting the development of robust change-detection monitoring networks.

Routine stream monitoring data enables the unravelling of hydrological pathways and transfers of agricultural contaminants through catchments

Catchment-scale understanding of water and contaminant fluxes through all pathways is essential to address land use and climate change impacts on freshwater. However, few options exist to obtain this understanding for the many catchments worldwide for which streamflow and low-frequency water chemistry, but little other data exists. We applied the Bayesian chemistry-assisted hydrograph separation and load partitioning model (BACH) to 47 catchments with widely differing characteristics. As BACH relies on concentration differences between pathways, chemodynamic behaviour of a water constituent indicates its likely suitability as tracer. Typical tracers (e.g. silica, chloride) were unavailable, but Electrical Conductivity and a few monitored nutrients proved chemodynamic in most catchments. Using one of two tracer combinations (Total Nitrogen + Electrical Conductivity, Total Nitrogen + Total Phosphorus) allowed in 85 % of the catchments to estimate streamflow contributions by near-surface (NS), shallow groundwater (SGW), and deep groundwater (DGW) pathways and pathway-specific tracer concentrations and yields with acceptable confidence. In 46 catchments, at least two pathways contributed ≥20 % of the streamflow, and all three ≥20 % in 12 catchments, cautioning against the notion of a single 'dominant' pathway. In contrast to hydrometric hydrograph separation, BACH allows differentiation between 'young' (NS + SGW) and 'old' (DGW) water, which is crucial for the understanding of pollution in catchments with strong temporal gradients in land use intensity. Consistent with generally increasing land use intensity, and groundwater denitrification occurring in some catchments, Total Nitrogen (TN) concentrations were in most catchments higher in NS and SGW compared to DGW. In most catchments, the greatest fraction of the TN yield was conveyed by SGW (≈ 40-90 %). Exceptions were wet and hilly catchments under bush, where the NS transferred most of the very low yields, and three young volcanic catchments where the DGW transferred the majority of the yield due to particularly high DGW flow contributions.

Wetland Flowpaths Mediate Nitrogen and Phosphorus Concentrations across the Upper Mississippi River Basin

Eutrophication, harmful algal blooms, and human health impacts are critical environmental challenges resulting from excess nitrogen and phosphorus in surface waters. Yet we have limited information regarding how wetland characteristics mediate water quality across watershed scales. We developed a large, novel set of spatial variables characterizing hydrological flowpaths from wetlands to streams, that is, "wetland hydrological transport variables," to explore how wetlands statistically explain the variability in total nitrogen (TN) and total phosphorus (TP) concentrations across the Upper Mississippi River Basin (UMRB) in the United States. We found that wetland flowpath variables improved landscape-to-aquatic nutrient multilinear regression models (from R2 = 0.89 to 0.91 for TN; R2 = 0.53 to 0.84 for TP) and provided insights into potential processes governing how wetlands influence watershed-scale TN and TP concentrations. Specifically, flowpath variables describing flow-attenuating environments, for example, subsurface transport compared to overland flowpaths, were related to lower TN and TP concentrations. Frequent hydrological connections from wetlands to streams were also linked to low TP concentrations, which likely suggests a nutrient source limitation in some areas of the UMRB. Consideration of wetland flowpaths could inform management and conservation activities designed to reduce nutrient export to downstream waters.

Advances in Catchment Science, Hydrochemistry, and Aquatic Ecology Enabled by High-Frequency Water Quality Measurements

High-frequency water quality measurements in streams and rivers have expanded in scope and sophistication during the last two decades. Existing technology allows in situ automated measurements of water quality constituents, including both solutes and particulates, at unprecedented frequencies from seconds to subdaily sampling intervals. This detailed chemical information can be combined with measurements of hydrological and biogeochemical processes, bringing new insights into the sources, transport pathways, and transformation processes of solutes and particulates in complex catchments and along the aquatic continuum. Here, we summarize established and emerging high-frequency water quality technologies, outline key high-frequency hydrochemical data sets, and review scientific advances in key focus areas enabled by the rapid development of high-frequency water quality measurements in streams and rivers. Finally, we discuss future directions and challenges for using high-frequency water quality measurements to bridge scientific and management gaps by promoting a holistic understanding of freshwater systems and catchment status, health, and function.

Advancing Watershed Legacy Nitrogen Modeling to Improve Global Water Quality

Despite widespread implementation of watershed nitrogen reduction programs across the globe, nitrogen levels in many surface waters remain high. Watershed legacy nitrogen storage, i.e., the long-term retention of nitrogen in soils and groundwater, is one of several explanations for this lack of progress. However scientists and water managers are ill-equipped to estimate how legacy nitrogen moderates in-stream nitrogen responses to land conservation practices, largely because modeling tools and associated long-term monitoring approaches to answering these questions remain inadequate. We demonstrate the need for improved watershed models to simulate legacy nitrogen processes and offer modeling solutions to support long-term nitrogen-based sustainable land management across the globe.

Impacts of soil, climate, and phenology on retention of dissolved agricultural nutrients by permanent-cover buffers

Nutrient losses from farms affects environmental and human health, but retention by riparian buffers can vary by nutrient identity, flow path, soil texture, seasonality, and buffer width. On conventional farms with corn, we test the relationships between levels of dissolved nitrogen (N) and phosphorus (P) in downslope surface-water, and flow paths relating to porewater in soils (to 40 cm deep), groundwater of the saturated zone (to 2.5 m deep), soil nutrient pools, and changes in plant biomass and tissue quality by season. We found that the major drivers of surface-water nutrients were multi-factor and nutrient-specific, variously relating to soil, climate, vegetation uptake, and tiling on clay soils. N retention was best explained by soil type, with 10 times more surface-water N in the sand versus clay setting, despite identical fertilization rates on corn. P retention was best explained by precipitation and time of year. Vegetation uptake was strongest for shallow-soil porewater, and was greatest in buffers where root biomass was 20 times greater by weight. We were unable to detect any impact of vegetative uptake on groundwater nutrients. Overall, peak nutrient inputs to surface-water were in early summer, fall, and winter - all times when plant uptake is low. Buffers appear to be a necessary component of nutrient capture on farms, but insufficient unless partnered with measures that reduce nutrient flows at times when plants are inactive.

A Dynamic Modeling Approach to Estimate Nitrogen Loading in Coastal Bays on Cape Cod, Massachusetts, USA

Solving estuarine water quality problems on Cape Cod, Massachusetts, or elsewhere, is difficult. Nitrogen from septic systems takes years to decades to travel by groundwater to estuaries, depending on local hydrogeology, meaning that nitrogen loading in future years may exceed current conditions. We created a dynamic nitrogen model of Cape Cod’s 54 estuaries to better understand 1. how past and present conditions, including legacy nitrogen in groundwater, influence future nitrogen loading, and 2. how different development and nitrogen abatement scenarios could have additional effects. We find that 43 of 54 estuaries are not in equilibrium with current watershed nitrogen loading levels; this increases to 52 of 54 under a buildout scenario. Watersheds contain up to 1000 tons of legacy nitrogen in groundwater; yet, we find that a rapid investment in source control successfully reduces nitrogen loading, revealing a wide range of potential outcomes that depend ultimately on the resources and attention invested in the problem.

Examining Relationships Between Groundwater Nitrate Concentrations in Drinking Water and Landscape Characteristics to Understand Health Risks

Nitrate ingested from drinking water has been linked to adverse health outcomes (e.g., cancer, birth defects) at levels as low as ∼2 mg/L NO₃-N, far below the regulatory limits of 10 mg/L. In many areas, groundwater is a common drinking water source and may contain elevated nitrate, but limited data on the patterns and concentrations are available. Using an extensive regulatory data set of over 100,000 nitrate drinking water well samples, we developed new maps of groundwater nitrate concentrations from 76,724 wells in Michigan's Lower Peninsula, USA for the 2006-2015 period. Kriging, a geostatistical method, was used to interpolate concentrations and quantify probability of exceeding relevant thresholds (>0.4 [common detection limit], >2 mg/L NO₃-N). We summarized this probability in small watersheds (∼80 km²) to identify correlated variables using the machine learning method classification and regression trees (CARTs). We found 79% of wells had concentrations below the detection limit in this analysis (<0.4 mg/L NO₃-N). In the shallow aquifer (focus of study), 13% of wells exceeded 2 mg/L NO₃-N and 2% exceeded the EPA maximum contaminant level of 10 mg/L. CART explained 40%-45% of variation in each model and identified three categories of critical correlated variables: source (high agricultural nitrogen inputs), vulnerable soil conditions (low soil organic carbon and high hydraulic conductivity), and transport mechanisms (high aquifer recharge). These findings add to the body of literature seeking to identify communities at risk of elevated nitrate and study associated adverse health outcomes.

Agricultural phosphorus surplus trajectories for Ontario, Canada (1961-2016), and erosional export risk

Management strategies aimed at reducing nutrient enrichment of surface waters may be hampered by nutrient legacies that have accumulated in the landscape. Here, we apply the Net Anthropogenic Phosphorus Input (NAPI) model to reconstruct the historical phosphorus (P) input trajectories for the province of Ontario, which encompasses the Canadian portion of the drainage basin of the Laurentian Great Lakes (LGL). NAPI considers P inputs from detergent, human and livestock waste, fertilizer inputs, and P outputs by crop uptake. During the entire time period considered, from 1961 to 2016, Ontario experienced positive annual NAPI values. Despite a generally downward NAPI trend since the late 1970s, the lower LGL, especially Lake Erie, continue to be plagued by algal blooms. When comparing NAPI results and river monitoring data for the period 2003 to 2013, P discharged by Canadian rivers into Lake Erie only accounts for 12.5% of the NAPI supplied to the watersheds' agricultural areas. Thus, over 85% of the agricultural NAPI is retained in the watersheds where it contributes to a growing P legacy, primarily as soil P. The slow release of legacy P therefore represents a long-term risk to the recovery of the lake. To help mitigate this risk, we present a methodology to spatially map out the source areas with the greatest potential of erosional export of legacy soil P to surface waters. These areas should be prioritized in soil conservation efforts.

Nitrogen legacies in anthropogenic landscapes: a case study in the Mondego Basin in Portugal

Nitrogen (N) legacies have built up in anthropogenic landscapes over decades of agricultural intensification, and these legacies lead to time lags in water quality change measurable even beyond the moment of application of N. It is important to understand these legacies to quantify the relationship between N inputs and N concentrations in streams and implement best management practices for water quality improvement; however, little is known about the magnitude of legacies in various landscape elements like soils and groundwater. Here, we have used the ELEMeNT (Exploration of Long-tErM Nutrient Trajectories) model to explore the buildup and depletion of N legacies over a 216-year period, across the Mondego River Basin, a 6645-km2 watershed in Portugal, where human interventions have considerably changed the characteristics of the basin to prevent floods and improve farming conditions in recent decades. The results show that the increase in the amount of inorganic fertilizer applied was the main driver for the anthropogenic N loads in the watershed from 1950 until the beginning of the 1990s. The N inputs have been decreasing since then, but N loads in the river did not document any decrease till the 1990s; after which there was a decline. This time lag between the N inputs to the watershed and the N loads in the river (about two decades) is a function of accumulation of N legacy.

A hillslope-scale aquifer-model to determine past agricultural legacy and future nitrate concentrations in rivers

The long-term fate of agricultural nitrate depends on rapid subsurface transfer, denitrification and storage in aquifers. Quantifying these processes remains an issue due to time varying subsurface contribution, unknown aquifer storage and heterogeneous denitrification potential. Here, we develop a parsimonious modelling approach that uses long-term discharge and river nitrate concentration time-series combined with groundwater age data determined from chlorofluorocarbons in springs and boreholes. To leverage their informational content, we use a Boussinesq-type equivalent hillslope model to capture the dynamics of aquifer flows and evolving surface and subsurface contribution to rivers. Nitrate transport was modelled with a depth-resolved high-order finite-difference method and denitrification by a first-order law. We applied the method to three heavily nitrate loaded catchments of a crystalline temperate region of France (Brittany). We found that mean water transit time ranged 10-32 years and Damköhler ratio (transit time/denitrification time) ranged 0.12-0.55, leading to limited denitrification in the aquifer (10-20%). The long-term trajectory of nitrate concentration in rivers appears determined by flows stratification in the aquifer. The results suggest that autotrophic denitrification is controlled by the accessibility of reduced minerals which occurs at the base of the aquifer where flows decrease. One interpretation is that denitrification might be an interfacial process in zones that are weathered enough to transmit flows and not too weathered to have remaining accessible reduced minerals. Consequently, denitrification would not be controlled by the total aquifer volume and related mean transit time but by the proximity of the active weathered interface with the water table. This should be confirmed by complementary studies to which the developed methodology might be further deployed.

What do we need to predict groundwater nitrate recovery trajectories?

Nitrate contamination affects many of the Earth's aquifers and surface waters. Large-scale predictions of groundwater nitrate trends normally require the characterization of multiple anthropic and natural factors. To assess different approaches for upscaling estimates of nitrate recovery, we tested the influence of hydrological, historical, and biological factors on predictions of future nitrate concentration in aquifers. We tested the factors with a rich hydrogeological dataset from a fractured bedrock catchment in western France (Brittany). A sensitivity analysis performed on a calibrated model of groundwater flow, denitrification, and nitrogen inputs revealed that trends in nitrate concentration can effectively be approximated with a limited number of key parameters. The total mass of nitrate that entered the aquifer since the beginning of the industrial period needs to be characterized, but the shape of the historical nitrogen input time series can be largely simplified without substantially altering the predictions. Aquifer flow and transport processes can be represented by the mean and standard deviation of the residence time distribution, offering a tractable tool to make reasonable predictions at watershed to regional scales. Apparent sensitivity to denitrification rate was primarily attributable to time lags in oxygen depletion, meaning that denitrification can be simplified to an on/off process, defined only by the time needed for nitrate to reach the hypoxic reactive layer. Obtaining these key parameters at large scales is still challenging with currently available information, but the results are promising regarding our future ability to predict nitrate concentration with integrated monitoring and modeling approaches.

Three decades of regulation of agricultural nitrogen losses: Experiences from the Danish Agricultural Monitoring Program

Excess nitrogen (N) losses from intensive agricultural production are a world-wide problem causing eutrophication in vulnerable aquatic ecosystems such as estuaries. Therefore, Denmark as one of the most intensively farmed countries in the world has enforced mandatory regulations on agricultural production since the late 1980s. We demonstrate the outcome of the regulations imposed on agriculture by analyzing decadal trends in nitrate (NO₃^-) concentrations and loads in streams using 29 years of detailed monitoring data and survey information on agricultural practices at field level from five intensively cultivated headwater catchments. The analysis includes the importance of four main drivers (climate, land use, agricultural practices, and biogeophysical properties of catchments), each divided into different factors that may influence stream NO₃^- loads during three subperiods defined by the time of introduction of different mitigation measures: i) 1990-1998, ii) 1999-2007, and iii) 2008-2018. Significant correlations with annual flow-weighted stream NO₃^- concentrations and/or loads were found for factors representing all of the four main drivers including precipitation, large scale climate fluctuations, runoff, previous year's runoff, baseflow index, number of annual frost days, agricultural area, livestock density, field N surplus, catch crop cover, manure storage capacity, method and time of manure spreading, and time of soil tillage. Changes in the four drivers were reflected by the load-runoff (L-Q) relationships for each of the three subperiods within each of the five headwater catchments. The five catchments experienced large but catchment-specific downward shifts in the L-Q relationship attributable to changes in land use and agricultural management within the catchments. The documented large downward shifts in NO₃^- loads demonstrated for the five catchments (30-52%) as a consequence of mandatory regulation over a period of nearly three decades are a unique example of how agriculture can reduce its environmental impact.

The implications of lag times between nitrate leaching losses and riverine loads for water quality policy

Understanding the lag time between land management and impacts on riverine nitrate–nitrogen (N) loads is critical to understand when action to mitigate nitrate–N leaching losses from the soil profile may start improving water quality. These lags occur due to leaching of nitrate–N through the subsurface (soil and groundwater). Actions to mitigate nitrate–N losses have been mandated in New Zealand policy to start showing improvements in water quality within five years. We estimated annual rates of nitrate–N leaching and annual nitrate–N loads for 77 river catchments from 1990 to 2018. Lag times between these losses and riverine loads were determined for 34 catchments but could not be determined in other catchments because they exhibited little change in nitrate–N leaching losses or loads. Lag times varied from 1 to 12 years according to factors like catchment size (Strahler stream order and altitude) and slope. For eight catchments where additional isotope and modelling data were available, the mean transit time for surface water at baseflow to pass through the catchment was on average 2.1 years less than, and never greater than, the mean lag time for nitrate–N, inferring our lag time estimates were robust. The median lag time for nitrate–N across the 34 catchments was 4.5 years, meaning that nearly half of these catchments wouldn’t exhibit decreases in nitrate–N because of practice change within the five years outlined in policy.

Groundwater inflow in rivers as a controlling factor to surface water nitrate concentrations and impact of groundwater age distribution on response times for remediation strategies

Diffuse groundwater contamination by intense fertilizer use is a widespread problem in most of the agricultural regions in West-Europe and in many other countries worldwide. As a result elevated nitrate concentrations in groundwater are found, and as groundwater is the source of baseflow into rivers and streams, also surface waters show increased nitrate levels. Flanders in the north of Belgium is no exception and despite restrictions on the fertilizer use and remediation practices initiated in the mid-1990s, and still ongoing, in many stream monitoring points, peak concentrations are measured above the 50 mg/l criterium. In many monitoring stations there is apparently a long delay between the start of the restrictions and effect on water quality. Often this delay is related to high concentrations in the groundwater inflow and long residence and travel times of groundwater feeding the streams. To better understand this behavior and estimate response times a tool was developed that incorporates the main water flows in a typical catchment and considers the effects of varying groundwater ages. This tool is conceived as a parsimonious lumped parameter model, simple and easy enough to be used by many people but still capturing the main mechanisms end processes. In this paper the tool is explained and it is applied on two testcases in Flanders to show its performance.

Context is Everything: Interacting Inputs and Landscape Characteristics Control Stream Nitrogen

To understand the environmental and anthropogenic drivers of stream nitrogen (N) concentrations across the conterminous US, we combined summer low-flow data from 4997 streams with watershed information across three survey periods (2000-2014) of the US EPA's National Rivers and Streams Assessment. Watershed N inputs explained 51% of the variation in log-transformed stream total N (TN) concentrations. Both N source and input rates influenced stream NO3/TN ratios and N concentrations. Streams dominated by oxidized N forms (NO3/TN ratio > 0.50) were more strongly responsive to the N input rate compared to streams dominated by other N forms. NO3 proportional contribution increased with N inputs, supporting N saturation-enhanced NO3 export to aquatic ecosystems. By combining information about N inputs with climatic and landscape factors, random forest models of stream N concentrations explained 70, 58, and 60% of the spatial variation in stream concentrations of TN, dissolved inorganic N, and total organic N, respectively. The strength and direction of relationships between watershed drivers and stream N concentrations and forms varied with N input intensity. Model results for high N input watersheds not only indicated potential contributions from contaminated groundwater to high stream N concentrations but also the mitigating role of wetlands.

The Shallow and Deep Hypothesis: Subsurface Vertical Chemical Contrasts Shape Nitrate Export Patterns from Different Land Uses

Eutrophication has threatened water resources worldwide, yet mechanistic understanding on controls of nutrient export remains elusive. This work tests the shallow and deep hypothesis: subsurface vertical chemical contrasts regulate nitrate export patterns under different land use conditions. We synthesized data from 228 watersheds and used reactive transport modeling (500 simulations) under broad land use, climate, and geology conditions. Data synthesis indicated that human perturbation has amplified chemical contrasts in shallow water (e.g., soil water) versus deep waters (e.g., groundwater), inducing primarily flushing patterns (concentrations increase with streamflow) in agriculture lands and dilution patterns (concentrations decrease with streamflow) in urban watersheds. Results revealed a quantitative relationship between export patterns and shallow-versus-deep concentration contrasts, underscoring the often-overlooked role of nutrient distribution over depth. Results challenge the commonly held perception that legacy stores in agricultural lands induce chemostasis where concentrations vary negligibly with streamflow. They suggest that nitrate concentrations from agricultural lands will escalate during large hydrological events, which can exacerbate nutrient export problems as flooding events intensify in the future climate.

Best Management Practices for Diffuse Nutrient Pollution: Wicked Problems Across Urban and Agricultural Watersheds

Extensive time and financial resources have been dedicated to address nonpoint sources of nitrogen and phosphorus in watersheds. Despite these efforts, many watersheds have not seen substantial improvement in water quality. The objective of this study is to review the literature and investigate key factors affecting the lack of improvement in nutrient levels in waterways in urban and agricultural regions. From 94 studies identified in the academic literature, we found that, although 60% of studies found improvements in water quality after implementation of Best Management Practices (BMPs) within the watershed, these studies were mostly modeling studies rather than field monitoring studies. For studies that were unable to find improvements in water quality after the implementation of BMPs, the lack of improvement was attributed to lack of knowledge about BMP functioning, lag times, nonoptimal placement and distribution of BMPs in the watershed, postimplementation BMP failure, and socio-political and economic challenges. We refer to these limiting factors as known unknowns. We also acknowledge the existence of unknown unknowns that hinder further improvement in BMP effectiveness and suggest that machine learning, approaches from the field of business and operations management, and long-term convergent studies could be used to resolve these unknown unknowns.

The role of groundwater discharge fluxes on Si:P ratios in a major tributary to Lake Erie

Groundwater discharge can be a major source of nutrients to river systems. Although quantification of groundwater nitrate loading to streams is common, the dependence of surface water silicon (Si) and phosphorus (P) concentrations on groundwater sources has rarely been determined. Additionally, the ability of groundwater discharge to drive surface water Si:P ratios has not been contextualized relative to riverine inputs or in-stream transformations. In this study, we quantify the seasonal dynamics of Si and P cycles in the Grand River (GR) watershed, the largest Canadian watershed draining into Lake Erie, to test our hypothesis that regions of Si-rich groundwater discharge increase surface water Si:P ratios. Historically, both the GR and Lake Erie have been considered stoichiometrically P-limited, where the molar Si:P ratio is greater than the ~16:1 phytoplankton uptake ratio. However, recent trends suggest that eastern Lake Erie may be approaching Si-limitation. We sampled groundwater and surface water for dissolved and reactive particulate Si as well as total dissolved P for 12months within and downstream of a 50-km reach of high groundwater discharge. Our results indicate that groundwater Si:P ratios are lower than the corresponding surface water and that groundwater is a significant source of bioavailable P to surface water. Despite these observations, the watershed remains P-limited for the majority of the year, with localized periods of Si-limitation. We further find that groundwater Si:P ratios are a relatively minor driver of surface water Si:P, but that the magnitude of Si and P loads from groundwater represent a large proportion of the overall fluxes to Lake Erie.

Legacy nitrogen may prevent achievement of water quality goals in the Gulf of Mexico

In August 2017, the Gulf of Mexico’s hypoxic zone was declared to be the largest ever measured. It has been estimated that a 60% decrease in watershed nitrogen (N) loading may be necessary to adequately reduce eutrophication in the Gulf. However, to date there has been no rigorous assessment of the effect of N legacies on achieving water quality goals. In this study, we show that even if agricultural N use became 100% efficient, it would take decades to meet target N loads due to legacy N within the Mississippi River basin. Our results suggest that both long-term commitment and large-scale changes in agricultural management practices will be necessary to decrease Mississippi N loads and to meet current goals for reducing the size of the Gulf hypoxic zone.

Tomography of anthropogenic nitrate contribution along a mesoscale river

Elevated nitrate concentrations are a thread for water supply and ecological integrity in surface water. Nitrate fluxes obtained by standard monitoring protocols at the catchment outlet strongly integrate spatially and temporally variable processes such as mobilization and turnover. Consequently, inference of dominant nitrate sources is often problematic and challenging in terms of effective river management and prioritization of measures. Here, we combine a spatially highly resolved assessment of nitrate concentration and fluxes along a mesoscale catchment with four years of monitoring data at two representative sites. The catchment is characterized by a strong land use gradient from pristine headwaters to lowland sub-catchments with intense agricultural land use and wastewater sources. We use nitrate concentrations in combination with hydrograph separation and isotopic fingerprinting methods to characterize and quantify nitrate source contribution. The hydrological analysis revealed a clear dominance of base flow during both campaigns. However, the absolute amounts of discharge differed considerably from one another (outlet: 1.42m³s^-1 in 2014, 0.43m³s^-1 in 2015). Nitrate concentrations are generally low in the pristine headwaters (<3mgL^-1) and increase downstream (15 to 16mgL^-1) due to the contribution of agricultural and wastewater sources. While the agricultural contribution did not vary in terms of nitrate concentration and isotopic signature between the years, the wastewater contribution strongly increased with decreasing discharge. Wastewater-borne nitrate load in the entire catchment ranged between 19% (2014) and 39% (2015). Long-term monitoring of nitrate concentration and isotopic composition in two sub-catchment exhibits a good agreement with findings from spatially monitoring. In both datasets, isotopic composition indicates that denitrification plays only a minor role. The spatially highly resolved monitoring approach helped to pinpoint hot spots of nitrate inputs into the stream while the long-term information allowed to place results into the context of intra-annual variability.

Integrated climate-chemical indicators of diffuse pollution from land to water

Management of agricultural diffuse pollution to water remains a challenge and is influenced by the complex interactions of rainfall-runoff pathways, soil and nutrient management, agricultural landscape heterogeneity and biogeochemical cycling in receiving water bodies. Amplified cycles of weather can also influence nutrient loss to water although they are less considered in policy reviews. Here, we present the development of climate-chemical indicators of diffuse pollution in highly monitored catchments in Western Europe. Specifically, we investigated the influences and relationships between weather processes amplified by the North Atlantic Oscillation during a sharp upward trend (2010–2016) and the patterns of diffuse nitrate and phosphorus pollution in rivers. On an annual scale, we found correlations between local catchment-scale nutrient concentrations in rivers and the influence of larger, oceanic-scale climate patterns defined by the intensity of the North Atlantic Oscillation. These influences were catchment-specific showing positive, negative or no correlation according to a typology. Upward trends in these decadal oscillations may override positive benefits of local management in some years or indicate greater benefits in other years. Developing integrated climate-chemical indicators into catchment monitoring indicators will provide a new and important contribution to water quality management objectives.

A review on effectiveness of best management practices in improving hydrology and water quality: Needs and opportunities

Best management practices (BMPs) have been widely used to address hydrology and water quality issues in both agricultural and urban areas. Increasing numbers of BMPs have been studied in research projects and implemented in watershed management projects, but a gap remains in quantifying their effectiveness through time. In this paper, we review the current knowledge about BMP efficiencies, which indicates that most empirical studies have focused on short-term efficiencies, while few have explored long-term efficiencies. Most simulation efforts that consider BMPs assume constant performance irrespective of ages of the practices, generally based on anticipated maintenance activities or the expected performance over the life of the BMP(s). However, efficiencies of BMPs likely change over time irrespective of maintenance due to factors such as degradation of structures and accumulation of pollutants. Generally, the impacts of BMPs implemented in water quality protection programs at watershed levels have not been as rapid or large as expected, possibly due to overly high expectations for practice long-term efficiency, with BMPs even being sources of pollutants under some conditions and during some time periods. The review of available datasets reveals that current data are limited regarding both short-term and long-term BMP efficiency. Based on this review, this paper provides suggestions regarding needs and opportunities. Existing practice efficiency data need to be compiled. New data on BMP efficiencies that consider important factors, such as maintenance activities, also need to be collected. Then, the existing and new data need to be analyzed. Further research is needed to create a framework, as well as modeling approaches built on the framework, to simulate changes in BMP efficiencies with time. The research community needs to work together in addressing these needs and opportunities, which will assist decision makers in formulating better decisions regarding BMP implementation in watershed management projects.

Ensemble modeling informs hypoxia management in the northern Gulf of Mexico

A large region of low-dissolved-oxygen bottom waters (hypoxia) forms nearly every summer in the northern Gulf of Mexico because of nutrient inputs from the Mississippi River Basin and water column stratification. Policymakers developed goals to reduce the area of hypoxic extent because of its ecological, economic, and commercial fisheries impacts. However, the goals remain elusive after 30 y of research and monitoring and 15 y of goal-setting and assessment because there has been little change in river nitrogen concentrations. An intergovernmental Task Force recently extended to 2035 the deadline for achieving the goal of a 5,000-km2 5-y average hypoxic zone and set an interim load target of a 20% reduction of the spring nitrogen loading from the Mississippi River by 2025 as part of their adaptive management process. The Task Force has asked modelers to reassess the loading reduction required to achieve the 2035 goal and to determine the effect of the 20% interim load reduction. Here, we address both questions using a probabilistic ensemble of four substantially different hypoxia models. Our results indicate that, under typical weather conditions, a 59% reduction in Mississippi River nitrogen load is required to reduce hypoxic area to 5,000 km2 The interim goal of a 20% load reduction is expected to produce an 18% reduction in hypoxic area over the long term. However, due to substantial interannual variability, a 25% load reduction is required before there is 95% certainty of observing any hypoxic area reduction between consecutive 5-y assessment periods.

Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales

Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern U.S. region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern U.S. region, leading to weak relationships between drivers and stoichiometry. Our results suggest ecological context mediates controls on lake nutrients and stoichiometry. Predicting stoichiometry was generally more difficult than predicting nutrient concentrations, but human activity may decouple N and P, leading to better prediction of N:P stoichiometry in regions with high anthropogenic activity.

Water quality trend and change-point analyses using integration of locally weighted polynomial regression and segmented regression

Trend and change-point analyses of water quality time series data have important implications for pollution control and environmental decision-making. This paper developed a new approach to assess trends and change-points of water quality parameters by integrating locally weighted polynomial regression (LWPR) and segmented regression (SegReg). Firstly, LWPR was used to pretreat the original water quality data into a smoothed time series to represent the long-term trend of water quality. Then, SegReg was used to identify the long-term trends and change-points of the smoothed time series. Finally, statistical tests were applied to determine the significance of the long-term trends and change-points. The efficacy of this approach was validated using a 10-year record of total nitrogen (TN) and chemical oxygen demand (COD_Mn) from Shanxi Reservoir watershed in eastern China. Results showed that this approach was straightforward and reliable for assessment of long-term trends and change-points on irregular water quality datasets. The reliability was verified by statistical tests and practical considerations for Shanxi Reservoir watershed. The newly developed integrated LWPR-SegReg approach is not only limited to the assessment of trends and change-points of water quality parameters but also has a broad application to other fields with long-term time series records.

Watershed-scale impacts of stormwater green infrastructure on hydrology, nutrient fluxes, and combined sewer overflows in the mid-Atlantic region

Stormwater green infrastructure (SGI), including rain gardens, detention ponds, bioswales, and green roofs, is being implemented in cities across the globe to reduce flooding, combined sewer overflows, and pollutant transport to streams and rivers. Despite the increasing use of urban SGI, few studies have quantified the cumulative effects of multiple SGI projects on hydrology and water quality at the watershed scale. To assess the effects of SGI, Washington, DC, Montgomery County, MD, and Baltimore County, MD, were selected based on the availability of data on SGI, water quality, and stream flow. The cumulative impact of SGI was evaluated over space and time by comparing watersheds with and without SGI, and by assessing how long-term changes in SGI impact hydrologic and water quality metrics over time. Most Mid-Atlantic municipalities have a goal of achieving 10-20% of the landscape drain runoff through SGI by 2030. Of these areas, Washington, DC currently has the greatest amount of SGI (12.7% of the landscape drained through SGI), while Baltimore County has the lowest (7.9%). When controlling for watersheds size and percent impervious surface cover, watersheds with greater amounts of SGI have less flashy hydrology, with 44% lower peak runoff, 26% less frequent runoff events, and 26% less variable runoff. Watersheds with more SGI also show 44% less NO3(-) and 48% less total nitrogen exports compared to watersheds with minimal SGI. There was no significant reduction in phosphorus exports or combined sewer overflows in watersheds with greater SGI. When comparing individual watersheds over time, increases in SGI corresponded to non-significant reductions in hydrologic flashiness compared to watersheds with no change in SGI. While the implementation of SGI is somewhat in its infancy in some regions, cities are beginning to have a scale of SGI where there are statistically significant differences in hydrologic patterns and water quality.