Evaluating the longevity of in-stream phosphorus legacies: A downstream cascade of recovery following point source remediation.

In-stream phosphorus (P) legacies cause lags between upstream remediation and downstream load reductions. However, the length of these lags is largely unknown, especially for long stream distances. As a result, lag time estimates at the large-watershed scale have been abstract and sometimes understated. Here, we leverage a large area watershed model with newly improved in-stream P simulation (SWAT+P.R&R) to evaluate the magnitude, longevity, and spatial cascade of legacy P remobilization in a U.S. corn belt watershed. Our results illustrate the "spiraling recovery" of P loads after a hypothetical point source remediation, where locations further downstream take longer to recover to baseline load levels. At the watershed outlet, in-stream legacy P contributions are equivalent to 30% of the baseline average annual P loads for three years after remediation. In-stream legacies do not approach exhaustion (95% remobilized) until at least 9 years after remediation. In hypothetical weather scenarios beginning with dry years, legacy contributions persist even longer. These findings (1) suggest that in-stream legacies could impact P loads for years to decades in large river basins, (2) support explicit accounting for spatial scale in future studies of in-stream legacies, and (3) provide concerning implications for water quality recovery in large river basins.

River Basin Simulations Reveal Wide-Ranging Wetland-Mediated Nitrate Reductions.

River basin-scale wetland restoration and creation is a primary management option for mitigating nitrogen-based water quality challenges. However, the magnitude of nitrogen reduction that will result from adding wetlands across large river basins is uncertain, partly because the areal extent, location, and physical and functional characteristics of the wetlands are unknown. We simulated over 3600 wetland restoration scenarios across the ∼450,000 km2 Upper Mississippi River Basin (UMRB) depicting varied assumptions for wetland areal extent, physical and functional characteristics, and placement strategy. These simulations indicated that restoring wetlands will reduce local nitrate yields and nitrate loads at the UMRB outlet. However, the projected magnitude of nitrate reduction varied widely across disparate scenario assumptions─e.g., restoring 4500 km2 of wetlands (i.e., 1% of UMRB area) decreased mean annual nitrate loads at the UMRB outlet between 3 and 42%. Higher magnitude nitrate reductions correlated with best-case assumptions, particularly for characteristics controlling nitrate loading rates to the wetlands. These results show that simplified claims about basin-scale wetland-mediated water quality improvements discount the breadth of possible wetland impacts across disparate wetland physical and functional conditions and highlight a need for greater clarity regarding the likelihood of these conditions at river basin scales.

Representing soil health practice effects on soil properties and nutrient loss in a watershed-scale hydrologic model.

Watershed-scale hydrologic models are commonly used to assess the water quality effects of agricultural conservation practices that improve soil health (e.g., cover crops and no-till). However, models rarely account for how these practices (i.e., soil health practices) affect soil physical and functional properties such as water holding capacity and soil aggregate stability, which may, in turn, affect water quality. We introduce a method to represent changes in soil physical and functional properties caused by soil health practices in the Soil and Water Assessment Tool (SWAT) model. We used the SWAT model's default representation of winter cover crops and no-till and modified soil descriptive parameters to depict soil health practice effects on soil properties. We assumed that the soil health practices would increase soil organic carbon (SOC), a principal indicator of soil health, by 0.01 g C g-1 of soil and then estimated changes in other soil properties (e.g., water holding capacity) using SOC-based predictive equations and preceding literature. Results indicated that our soil property modifications had statistically significant effects on simulated hydrology and nutrient loss, though outputs were more substantially affected by the model's default representation of cover crops and no-till. Results also indicated that soil health practices can reduce nitrogen and total phosphorus loss but may increase dissolved reactive phosphorus loss. Our representation of soil health practices provides a more complete estimate of practice efficacy but underscores a need for additional observational data to verify results and guide further model improvements.

Effect of alfalfa on subsurface (tile) nitrogen and phosphorus loss in Ohio, USA.

Growing annual crops such as corn (Zea mays L.) can lead to considerable nutrient losses through subsurface drainage in agricultural fields, posing a serious threat to surface water quality in the midwestern United States. Perennial crops have the potential to reduce these nutrient losses. However, more comprehensive data are needed on the nutrient loss effect of perennial crops. We examined the effect of alfalfa (Medicago sativa L.) on nitrate-nitrogen (NO3 - -N), total nitrogen (TN), dissolved reactive phosphorus (DRP), and total phosphorus (TP) in subsurface drainage using a before-after-control-impact (BACI) experimental design with one control field (with annual crops) and one impact field (with alfalfa) each on two farms (Sites A and B) located in northwestern Ohio. The "Before" period (prior to planting alfalfa at the impact field) extended for 4 yr (2013-2017) at Site A and 6 yr (2011-2017) at Site B; the "After" period extended for an additional 2 yr at both sites. Reductions in the mean monthly discharge and loads of NO3 - -N, TN, DRP, and TP were significant at Site A, whereas the only significant change at site B was a reduction in the mean monthly TP load. Significant reductions in NO3 - -N loads were observed during spring and winter at Site A. In addition, alfalfa reduced the variability of discharge and nutrient loads through subsurface drainage at both sites. Our findings suggest that introducing alfalfa into annual crop rotations has the potential to reduce subsurface nutrient loads and increase the resiliency of agricultural systems.

Assessing the Accuracy of Farmers' Nutrient Loss Risk Perceptions.

Use of nutrient management practices to reduce nutrient loss from agriculture and its associated water quality consequences, including hypoxia and eutrophication, is widely encouraged. However, little is known about which factors influence farmers' risk perceptions associated with nutrient loss, and thus possibly influence their decisions to adopt such practices. To determine which factors were associated with relative "accuracy" of nutrient loss-associated risk perceptions, specific farm field management information was used as inputs to a Soil and Water Assessment Tool model of the study watershed to produce water quality outputs for each modeled farm field. This information was paired with farmers' risk perceptions associated with nutrient loss on their farm to assess relative "accuracy" of each farmer's perceptions compared to the rest of the farmers in the study. We then investigated characteristics of the farm and farmer that are associated with comparative "overprediction" and "underprediction" of risk, and found that characteristics of the individual (conservation identity, prior conservation practice adoption, efficacy beliefs, and perceived seriousness of the consequences of nutrient loss) are more important in determining whether farmers are likely to "overpredict" or "underpredict" risk than is the objective (modeled) vulnerability of their land to nutrient loss.

Evaluating the efficacy of targeting options for conservation practice adoption on watershed-scale phosphorus reductions.

Conservation identities of farmers in the Maumee River watershed, derived from farmer surveys, were embedded into a SWAT watershed model. This was done to improve the representation of the heterogeneity among farmers in the decision-making process related to the adoption of conservation practices. Modeled farm operations, created with near field-level Hydrologic Response Units (HRUs) within the SWAT model, were assigned a modeled primary operator. Modeled primary operators held unique conservation identities driven by their spatial location within the watershed. Five pathways of targeting the adoption of subsurface placement of phosphorus and buffer strips to HRUs within the watershed were assessed. Targeting pathways included targeting by HRU-level phosphorus losses, conservation identity of model operators, a hybrid approach combining HRU-level phosphorus losses and conservation identity of the model primary operator managing the HRU, and a proxy measure for random placement throughout the watershed. Targeting the placement of subsurface phosphorus application to all agricultural HRUs resulted in the greatest reduction in total phosphorus losses (32%) versus buffer strips (23%). For both conservation practices, targeting by HRU-level total phosphorus losses resulted in the most efficient rate of phosphorus reduction as measured by the ratio of phosphorus reduction to conservation practice adoption rates. The hybrid targeting approach closely resembled targeting by phosphorus losses, indicating near optimal results can be obtained even when constraining adoption by farmer characteristics. These results indicate that by developing management strategies based on a combination of field-level information and human-operator characteristics, a more efficient use of limited resources can be used while achieving near-maximal environmental benefits as compared to managing environmental outcomes solely based on field-level information.

Uncertainty in critical source area predictions from watershed-scale hydrologic models.

Watershed-scale hydrologic models are frequently used to inform conservation and restoration efforts by identifying critical source areas (CSAs; alternatively 'hotspots'), defined as areas that export relatively greater quantities of nutrients and sediment. The CSAs can then be prioritized or 'targeted' for conservation and restoration to ensure efficient use of limited resources. However, CSA simulations from watershed-scale hydrologic models may be uncertain and it is critical that the extent and implications of this uncertainty be conveyed to stakeholders and decision makers. We used an ensemble of four independently developed Soil and Water Assessment Tool (SWAT) models and a SPAtially Referenced Regression On Watershed attributes (SPARROW) model to simulate CSA locations for flow, phosphorus, nitrogen, and sediment within the ~17,000-km2 Maumee River watershed at the HUC-12 scale. We then assessed uncertainty in CSA simulations determined as the variation in CSA locations across the models. Our application of an ensemble of models - differing with respect to inputs, structure, and parameterization - facilitated an improved accounting of CSA prediction uncertainty. We found that the models agreed on the location of a subset of CSAs, and that these locations may be targeted with relative confidence. However, models more often disagreed on CSA locations. On average, only 16%-46% of HUC-12 subwatersheds simulated as a CSA by one model were also simulated as a CSA by a different model. Our work shows that simulated CSA locations are highly uncertain and may vary substantially across models. Hence, while models may be useful in informing conservation and restoration planning, their application to identify CSA locations would benefit from comprehensive uncertainty analyses to avoid inefficient use of limited resources.

Simulating internal watershed processes using multiple SWAT models.

The need for effective water quality models to help guide management and policy, and extend monitoring information, is at the forefront of recent discussions related to watershed management. These models are often calibrated and validated at the basin outlet, which ensures that models are capable of evaluating basin scale hydrology and water quality. However, there is a need to understand where these models succeed or fail with respect to internal process representation, as these watershed-scale models are used to inform management practices and mitigation strategies upstream. We evaluated an ensemble of models-each calibrated to in-stream observations at the basin outlet-against discharge and nutrient observations at the farm field scale to determine the extent to which these models capture field-scale dynamics. While all models performed well at the watershed outlet, upstream performance varied. Models tended to over-predict discharge through surface runoff and subsurface drainage, while under-predicting phosphorus loading through subsurface drainage and nitrogen loading through surface runoff. Our study suggests that while models may be applied to predict impacts of management at the basin scale, care should be taken in applying the models to evaluate field-scale management and processes in the absence of data that can be incorporated at that scale, even with the use of multiple models.

Evaluating management options to reduce Lake Erie algal blooms using an ensemble of watershed models.

Reducing harmful algal blooms in Lake Erie, situated between the United States and Canada, requires implementing best management practices to decrease nutrient loading from upstream sources. Bi-national water quality targets have been set for total and dissolved phosphorus loads, with the ultimate goal of reaching these targets in 9-out-of-10 years. Row crop agriculture dominates the land use in the Western Lake Erie Basin thus requiring efforts to mitigate nutrient loads from agricultural systems. To determine the types and extent of agricultural management practices needed to reach the water quality goals, we used five independently developed Soil and Water Assessment Tool models to evaluate the effects of 18 management scenarios over a 10-year period on nutrient export. Guidance from a stakeholder group was provided throughout the project, and resulted in improved data, development of realistic scenarios, and expanded outreach. Subsurface placement of phosphorus fertilizers, cover crops, riparian buffers, and wetlands were among the most effective management options. But, only in one realistic scenario did a majority (3/5) of the models predict that the total phosphorus loading target would be met in 9-out-of-10 years. Further, the dissolved phosphorus loading target was predicted to meet the 9-out-of-10-year goal by only one model and only in three scenarios. In all scenarios evaluated, the 9-out-of-10-year goal was not met based on the average of model predictions. Ensemble modeling revealed general agreement about the effects of several practices although some scenarios resulted in a wide range of uncertainty. Overall, our results demonstrate that there are multiple pathways to approach the established water quality goals, but greater adoption rates of practices than those tested here will likely be needed to attain the management targets.

Bias correction of climate model outputs influences watershed model nutrient load predictions.

Waterbodies around the world experience problems associated with elevated phosphorus (P) and nitrogen (N) loads. While vital for ecosystem functioning, when present in excess amounts these nutrients can impair water quality and create symptoms of eutrophication, including harmful algal blooms. Under a changing climate, nutrient loads are likely to change. While climate models can serve as inputs to watershed models, the climate models often do not adequately represent the distribution of observed data, generating uncertainties that can be addressed to some degree with bias correction. However, the impacts of bias correction on nutrient models are not well understood. This study compares 4 univariate and 3 multivariate bias correction methods, which correct precipitation and temperature variables from 4 climate models in the historical (1980-1999) and mid-century future (2046-2065) time periods. These variables served as inputs to a calibrated Soil and Water Assessment Tool (SWAT) model of Lake Erie's Maumee River watershed. We compared the performance of SWAT outputs driven with climate model outputs that were bias-corrected (BC) and not bias-corrected (no-BC) for dissolved reactive P, total P, and total N. Results based on graphical comparisons and goodness of fit metrics showed that the choice of BC method impacts both the direction of change and magnitude of nutrient loads and hydrological processes. While the Delta method performed best, it should be used with caution since it considers historical variable relationships as the basis for predictions, which may not hold true under future climate. Quantile Delta Mapping (QDM) and Multivariate Bias Correction N-dimensional probability density function transform (MBCn) BC methods also performed well and work well for non-stationary climate scenarios. Furthermore, results suggest that February-July cumulative load in the Maumee basin is likely to decrease in the mid-century as runoff and snowfall decrease, and evapotranspiration increases with warming temperatures.

Source contribution to phosphorus loads from the Maumee River watershed to Lake Erie.

Coastal eutrophication is a leading cause of degraded water quality around the world. Identifying the sources and their relative contributions to impaired downstream water quality is an important step in developing management plans to address water quality concerns. Recent mass-balance studies of Total Phosphorus (TP) loads of the Maumee River watershed highlight the considerable phosphorus contributions of non-point sources, including agricultural sources, degrading regional downstream water quality. This analysis builds upon these mass-balance studies by using the Soil and Water Assessment Tool to simulate the movement of phosphorus from manure, inorganic fertilizer, point sources, and soil sources, and respective loads of TP and Dissolved Reactive Phosphorus (DRP). This yields a more explicit estimation of source contribution from the watershed. Model simulations indicate that inorganic fertilizers contribute a greater proportion of TP (45% compared to 8%) and DRP (58% compared to 12%) discharged from the watershed than manure sources in the March-July period, the season driving harmful algal blooms. Although inorganic fertilizers contributed a greater mass of TP and DRP than manure sources, the two sources had similar average delivery fractions of TP (2.7% for inorganic fertilizers vs. 3.0% for manure sources) as well as DRP (0.7% for inorganic fertilizers vs. 1.2% for manure sources). Point sources contributed similar proportions of TP (5%) and DRP (12%) discharged in March-July as manure sources. Soil sources of phosphorus contributed over 40% of the March-July TP load and 20% of the March-July DRP load from the watershed to Lake Erie. Reductions of manures and inorganic fertilizers corresponded to a greater proportion of phosphorus delivered from soil sources of phosphorus, indicating that legacy phosphorus in soils may need to be a focus of management efforts to reach nutrient load reduction goals. In agricultural watersheds aground the world, including the Maumee River watershed, upstream nutrient management should not focus solely on an individual nutrient source; rather a comprehensive approach involving numerous sources should be undertaken.

Quantifying uncertainty cascading from climate, watershed, and lake models in harmful algal bloom predictions.

In response to increased harmful algal blooms (HABs), hypoxia, and nearshore algae growth in Lake Erie, the United States and Canada agreed to phosphorus load reduction targets. While the load targets were guided by an ensemble of models, none of them considered the effects of climate change. Some watershed models developed to guide load reduction strategies have simulated climate effects, but without extending the resulting loads or their uncertainties to HAB projections. In this study, we integrated an ensemble of four climate models, three watershed models, and four HAB models. Nutrient loads and HAB predictions were generated for historical (1985-1999), current (2002-2017), and mid-21st-century (2051-2065) periods. For the current and historical periods, modeled loads and HABs are comparable to observations but exhibit less interannual variability. Our results show that climate impacts on watershed processes are likely to lead to reductions in future loading, assuming land use and watershed management practices are unchanged. This reduction in load should help reduce the magnitude of future HABs, although increases in lake temperature could mitigate that decrease. Using Monte-Carlo analysis to attribute sources of uncertainty from this cascade of models, we show that the uncertainty associated with each model is significant, and that improvements in all three are needed to build confidence in future projections.

The hydrologic model as a source of nutrient loading uncertainty in a future climate.

Hydrologic models are applied increasingly with climate projections to provide insights into future hydrologic conditions. However, both hydrologic models and climate models can produce a wide range of predictions based on model inputs, assumptions, and structure. To characterize a range of future predictions, it is common to use multiple climate models to drive hydrologic models, yet it is less common to also use a suite of hydrologic models. It is also common for hydrologic models to report riverine discharge and assume that nutrient loading will follow similar patterns, but this may not be the case. In this study, we characterized uncertainty from both climate models and hydrologic models in predicting riverine discharge and nutrient loading. Six climate models drawn from the Coupled Model Intercomparison Project Phase 5 ensemble were used to drive five independently developed and calibrated Soil and Water Assessment Tool models to assess hydrology and nutrient loadings for mid-century (2046-2065) in the Maumee River Watershed,the largest watershedsdraining to the Laurentian Great Lakes. Under those conditions, there was no clear agreement on the direction of change in future nutrient loadings or discharge. Analysis of variance demonstrated that variation among climate models was the dominant source of uncertainty in predicting future total discharge, tile discharge (i.e. subsurface drainage), evapotranspiration, and total nitrogen loading, while hydrologic models were the main source of uncertainty in predicted surface runoff and phosphorus loadings. This innovative study quantifies the importance of hydrologic model in the prediction of riverine nutrient loadings under a future climate.

Climate Change and Nutrient Loading in the Western Lake Erie Basin: Warming Can Counteract a Wetter Future.

In the past 20 years, Lake Erie has experienced a resurgence of harmful algal blooms and hypoxia driven by increased nutrient loading from its agriculturally dominated watersheds. The increase in phosphorus loading, specifically the dissolved reactive portion, has been attributed to a combination of changing climate and agricultural management. While many management practices and strategies have been identified to reduce phosphorus loads, the impacts of future climate remain uncertain. This is particularly the case for the Great Lakes region because many global climate models do not accurately represent the land-lake interactions that govern regional climate. For this study, we used midcentury (2046-2065) climate projections from one global model and four regional dynamically downscaled models as drivers for the Soil and Water Assessment Tool configured for the Maumee River watershed, the source of almost 50% of Lake Erie's Western Basin phosphorus load. Our findings suggest that future warming may lead to less nutrient runoff due to increased evapotranspiration and decreased snowfall, despite projected moderate increases in intensity and overall amount of precipitation. Results highlight the benefits of considering multiple environmental drivers in determining the fate of nutrients in the environment and demonstrate a need to improve approaches for climate change assessment using watershed models.

Engaging Stakeholders To Define Feasible and Desirable Agricultural Conservation in Western Lake Erie Watersheds.

Widespread adoption of agricultural conservation measures in Lake Erie's Maumee River watershed may be required to reduce phosphorus loading that drives harmful algal blooms and hypoxia. We engaged agricultural and conservation stakeholders through a survey and workshops to determine which conservation practices to evaluate. We investigated feasible and desirable conservation practices using the Soil and Water Assessment Tool calibrated for streamflow, sediment, and nutrient loading near the Maumee River outlet. We found subsurface placement of phosphorus applications to be the individual practice most influential on March-July dissolved reactive phosphorus (DRP) loading from row croplands. Perennial cover crops and vegetated filter strips were most effective for reducing seasonal total phosphorus (TP) loading. We found that practices effective for reducing TP and DRP load were not always mutually beneficial, culminating in trade-offs among multiple Lake Erie phosphorus management goals. Adoption of practices at levels considered feasible to stakeholders led to nearly reaching TP targets for western Lake Erie on average years; however, adoption of practices at a rate that goes beyond what is currently considered feasible will likely be required to reach the DRP target.

Evaluating the Impact of Legacy P and Agricultural Conservation Practices on Nutrient Loads from the Maumee River Watershed.

The recent resurgence of hypoxia and harmful algal blooms in Lake Erie, driven substantially by phosphorus loads from agriculture, have led the United States and Canada to begin developing plans to meet new phosphorus load targets. To provide insight into which agricultural management options could help reach these targets, we tested alternative agricultural-land-use and land-management scenarios on phosphorus loads to Lake Erie. These scenarios highlight certain constraints on phosphorus load reductions from changes in the Maumee River Watershed (MRW), which contributes roughly half of the phosphorus load to the lake's western basin. We evaluate the effects on phosphorus loads under nutrient management strategies, reduction of fertilizer applications, employing vegetative buffers, and implementing widespread cover crops and alternative cropping changes. Results indicate that even if fertilizer application ceased, it may take years to see desired decreases in phosphorus loads, especially if we experience greater spring precipitation or snowmelt. Scenarios also indicate that widespread conversions to perennial crops that may be used for biofuel production are capable of substantially reducing phosphorus loads. This work demonstrates that a combination of legacy phosphorus, land management, land use, and climate should all be considered when seeking phosphorus-loading solutions.

An in-depth examination of farmers' perceptions of targeting conservation practices.

Watershed managers have largely embraced targeting of agricultural conservation as a way to manage strategically non-point source pollution from agricultural lands. However, while targeting of particular watersheds is not uncommon, targeting farms and fields within a specific watershed has lagged. In this work, we employed a qualitative approach, using farmer interviews in west-central Indiana to better understand their views on targeting. Interviews focused on adoption of conservation practices on farmers' lands and identified their views on targeting, disproportionality, and monetary incentives. Results show consistent support for the targeting approach, despite dramatic differences in farmers' views of land stewardship, in their views about disproportionality of water quality impacts, and in their trust in conservation programming. While the theoretical concept of targeting was palatable to all participants, many raised concerns about its practical implementation, pointing to the need for flexibility when applying targeting solutions and revealing misgivings about the government agencies that perform targeting.