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

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.

Short-term Lake Erie algal bloom prediction by classification and regression models

The recent outbreaks of harmful algal blooms in the western Lake Erie Basin (WLEB) have drawn tremendous attention to bloom prediction for better control and management. Many weekly to annual bloom prediction models have been reported, but they only employ small datasets, have limited types of input features, build linear regression or probabilistic models, or require complex process-based computations. To address these limitations, we conducted a comprehensive literature review, complied a large dataset containing chlorophyll-a index (from 2002 to 2019) as the output and a novel combination of riverine (the Maumee & Detroit Rivers) and meteorological (WLEB) features as the input, and built machine learning-based classification and regression models for 10-d scale bloom predictions. By analyzing the feature importance, we identified 8 most important features for the HAB control, including nitrogen loads, time, water levels, soluble reactive phosphorus load, and solar irradiance. Here, both long- and short-term nitrogen loads were for the first time considered in HAB models for Lake Erie. Based on these features, the 2-, 3-, and 4-level random forest classification models achieved an accuracy of 89.6%, 77.0%, and 66.7%, respectively, and the regression model achieved an R² value of 0.69. In addition, long-short term memory (LSTM) was implemented to predict temporal trends of four short-term features (N, solar irradiance, and two water levels) and achieved the Nash-Sutcliffe efficiency of 0.12-0.97. Feeding the LSTM model predictions for these features into the 2-level classification model reached an accuracy of 86.0% for predicting the HABs in 2017-2018, suggesting that we can provide short-term HAB forecasts even when the feature values are not available.

Influence of sampling frequency and estimation method on phosphorus load uncertainty in the Western Lake Erie Basin, Ohio, USA

Accurate estimates of nutrient loads are necessary to identify critical source areas and quantify the impact of management practices on pollutant export. Previous studies have investigated nutrient load estimate uncertainty, but they often focus on nutrient loads estimated using an interpolation method for large-scale watersheds with short-term datasets. The study objective was to quantify uncertainty in soluble reactive phosphorus (SRP), total phosphorus (TP), and suspended solids (SS) load estimates from two small (<103 km2) agricultural watersheds in the western Lake Erie Basin resulting from different sampling frequencies. Each watershed had high temporal resolution datasets of discharge (15 min) and nutrient concentration (1 to 3 samples per day) collected over a 30-year period (1990-2020). Firstly, SRP, TP, and SS loads were calculated using the high temporal resolution datasets, which was assumed as "true loads". Secondly, the high temporal concentration data were decomposed to semiweekly, weekly, biweekly, and monthly sampling and annual loads were estimated using four common load estimation methods to assess the effect of sampling frequency and load estimation method on load estimate error. Across the four different methods, the composite method had the lowest relative root mean square and absolute bias, but the rectangular interpolation method was the most precise. However, even with semiweekly sampling, the composite method resulted in an unacceptable level of precision (average imprecision = 39 %), while the interpolation method resulted in an unacceptable bias (average absolute bias = 16 %). Because neither method could provide acceptable accuracy and precision at the lowest decrease in sampling (e.t. semiweekly sampling), continued daily sampling is recommended in these watersheds.

Modeling and assessing water and nutrient balances in a tile-drained agricultural watershed in the U.S. Corn Belt

Identifying the key processes and primary sources of water and nutrient losses is essential for water quantity and quality management in watersheds. This is especially true in the U.S. Corn Belt, which has been recognized as the primary region contributing nutrient loads to the Great Lakes and the Gulf of Mexico. A SWAT (Soil and Water Assessment Tool) model simulation was set up in an agricultural watershed with about 50% tile drainage area in the U.S. Corn Belt to study the water and nutrient balance components for the whole watershed and the corn-soybean rotation system. The SWAT model was improved to consider additional nitrogen and phosphorus loss paths from the soil. The model was comprehensively calibrated and validated for simulating monthly stream flow, total suspended solids (TSS), nutrient loads (including total Kjeldahl nitrogen (TKN), nitrate and nitrite nitrogen (NO_x-N), total phosphorus (TP) and orthophosphate phosphorus (orthoP)), actual evapotranspiration (ET_a), leaf area index (LAI) and annual crop yields in the watershed from 2011 to 2019. Results showed the model performance was very good for simulating the stream flow, TSS and ET_a, and acceptable for nutrient loads, LAI and crop yields. ET_a, surface runoff, lateral soil flow, tile drainage and percolation respectively accounted for 65%, 15%, 2%, 8% and 9% of the precipitation. Fertilizer was the main source of nitrogen and phosphorus input to the watershed, and harvested crops were the main paths removing nutrients. Surface runoff, tile drainage and percolation each contributed about 30% of total nitrogen losses to water, with surface runoff being dominated by organic nitrogen while tile drainage and percolation were dominated by nitrate nitrogen. Phosphorus losses were mainly through surface runoff, which resulted in 66% of the total losses and was dominated by organic phosphorus and soluble phosphorus. Representing about 49% of the watershed area, the corn-soybean rotation system contributed 83% and 88% of the total nitrogen and phosphorus inputs, respectively, to the watershed, as well as 64% and 46% of the nitrogen and phosphorus losses to the water system, respectively. The non-growing season (October to the next April) was identified as the critical period resulting in water and nutrient losses due to low evapotranspiration and plant uptake. Targeted management strategies for reducing nutrient loads in key hydrological paths were suggested.

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.

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.

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.

Water quality prospective in Twenty First Century: Status of water quality in major river basins, contemporary strategies and impediments: A review

Water quality improvement is one of the top priorities in the global agenda endorsed by United Nation. In this review manuscript, a holistic view of water quality degradation such as concerned pollutants, source of pollution, and its consequences in major river basins around the globe (at least 1 from each continent and a total of 16 basins) is presented. Additionally, nine contemporary techniques such as field scale evaluation, watershed scale evaluation, strategies to identify critical source areas, optimization strategies for placement of best management practices (BMPs), social component in watershed modeling, machine learning algorithms to address water quality problems in complex natural systems concomitant with spatial heterogeneity, establishing a total maximum daily loads (TMDLs), remote sensing in monitoring water quality, and developing water quality index are discussed. Next, the existing barriers to improve water quality are classified into primary and secondary impediments. A detail discussion of three primary impediments (climate change, urbanization and industrial activities, and agriculture) and ten secondary impediments (availability of water quality data, complexity of system, lack of skilled person, environmental legislation, fragmented mandate, limitation in resources, environmental awareness, resistance to change, alteration of nutrient ratio by river damming, and emerging pollutants) are illustrated. Finally, considering all the existing knowledge gaps pertaining to contemporary strategies, a future direction of water quality research is outlined to significantly improve the water quality around the globe.

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.

Less Agricultural Phosphorus Applied in 2019 Led to Less Dissolved Phosphorus Transported to Lake Erie

Extreme precipitation events affect water quantity and quality in various regions of the world. Heavy precipitation in 2019 resulted in a record high area of unplanted agricultural fields in the U.S. and especially in the Maumee River Watershed (MRW). March-July phosphorus (P) loads from the MRW drive harmful algal bloom (HAB) severity in Lake Erie; hence changes in management that influence P export can ultimately affect HAB severity. In this study, we found that the 2019 dissolved reactive P (DRP) load from March-July was 29% lower than predicted, while the particulate P (PP) load was similar to the predicted value. Furthermore, the reduced DRP load resulted in a less severe HAB than predicted based on discharge volume. The 29% reduction in DRP loss in the MRW occurred with a 62% reduction in applied P, emphasizing the strong influence of recently applied P and subsequent incidental P losses on watershed P loading. Other possible contributing factors to this reduced load include lower precipitation intensity, altered tillage practices, and effects of fallow soils, but more data is needed to assess their importance. We recommend conservation practices focusing on P application techniques and timing and improving resiliency against extreme precipitation events.

Uncertainty analysis of the performance of a management system for achieving phosphorus load reduction to surface waters

The recent re-eutrophication of Lake Erie suggests an inadequate phosphorus management system that results in excessive loads to the lake. In response, governments in Canada and the U.S. have issued a new policy objective: 40% reductions in total phosphorus (TP) and dissolved reactive phosphorus (DRP) loads relative to 2008. The International Organization for Standardization (ISO) 31000 is a risk management standard. One of its analytical tools is the ISO 31010:2009 Bowtie Risk Analysis Tool, a tool that structures the cause-effect-impact pathway of risk but lacks the ability to capture the probability of reducing risk associated with different management systems. Here, we combined the Bowtie Risk Analysis Tool with a Bayesian belief network model to analyze the probability of different agricultural management systems of best management practices (BMPs) to achieve the 40% reductions in TP and DRP loads using different adoption rates. The commonly used soil conservation BMPs (e.g., reduced tillage) have a low probability of reducing TP and DRP to achieve the policy objective; while it can achieve the TP load reduction objective at increased adoptions rates >40%, it does not achieve the DRP load reduction objective, and in fact has the unintended consequence of increasing DRP loads. If decision makers continue to rely on soil conservation BMPs, the trade-offs between meeting objectives of different forms of phosphorus will require deciding whether the management priority is to achieve 40% load reduction objectives or to prevent further increases in DRP loads, the identified culprit causing the repeated algal blooms. In contrast, TP- and DRP-effective BMPS had higher probabilities of achieving the policy objective, especially at increased adoption rates >20%. The integration of Bayesian belief networks with the ISO risk management standard allows decision makers to determine the most probable outcomes of their management decisions, and to track and prepare for less probable outcomes, thereby decreasing the risk of failing to achieve policy objectives.

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.

Lake Huron's Phosphorus Contributions to the St. Clair-Detroit River Great Lakes Connecting Channel

The United States and Canada called for a 40% load reduction of total phosphorus from 2008 levels entering the western and central basins of Lake Erie to achieve a 6000 MTA target and help reduce its central basin hypoxia. The Detroit River is a significant source of total phosphorus to Lake Erie; it in turn has been reported to receive up to 58% of its load from Lake Huron when accounting for resuspended sediment loads previously unmonitored at the lake outlet. Key open questions are where does this additional load originate, what drives its variability, and how often does it occur. We used a hydrodynamic model, satellite images of resuspension events and ice cover, wave hindcasts, and continuous turbidity measurements at the outlet of Lake Huron to determine where in Lake Huron the undetected load originates and what drives its variability. We show that the additional sediment load, and likely phosphorus, is from wave-induced Lake Huron sediment resuspension, primarily within 30 km of the southeastern shore. When the flow is from southwest or down the center of the lake, the resuspended sediment is not detected at Canada's sampling station at the head of the St. Clair River.

A SWAT-based optimization tool for obtaining cost-effective strategies for agricultural conservation practice implementation at watershed scales

To address the harmful algal blooms problem in Lake Erie, one solution is to determine the most cost-effective strategies for implementing agricultural best management practices (BMPs) in the Maumee River watershed. An optimization tool, which combines multi-objective optimization algorithms, SWAT (Soil and Water Assessment Tool), and a computational efficient framework, was created to optimally identify agricultural BMPs at watershed scales. The optimization tool was demonstrated in the Matson Ditch watershed, an agricultural watershed in the Maumee River basin considering critical areas (25% of the watershed with the greatest pollutant loadings per area) and the entire watershed. The initial implementation of BMPs with low expenditures greatly reduced pollutant loadings; beyond certain levels of pollutant reductions, additional expenditures resulted in less significant reductions in pollutant loadings. Compared to optimization for the entire watershed, optimization in critical areas can greatly reduce computational time and obtain similar optimization results for initial reductions in pollutant loadings, which were 10% for Dissolved Reactive Phosphorus (DRP) and 38% for Total Phosphorus (TP); however, for greater reductions in pollutant loadings, critical area optimization was less cost-effective. With the target of simultaneously reducing March-July DRP/TP losses by 40%, the optimized scenario that reduced DRP losses by 40% was found to reduce 51.1% of TP; however, the optimized scenario that reduced TP losses by 40% can only decrease 11.3% of DRP. The optimization tool can help stakeholders identify optimal types, quantities, and spatial locations of BMPs that can maximize reductions in pollutant loadings with the lowest BMP costs.

Assessment of hydrology and nutrient losses in a changing climate in a subsurface-drained watershed

Studies assessing the impact of subsurface drains on hydrology and nutrient yield in a changing climate are limited, specifically for Western Lake Erie Basin. This study aimed to evaluate the impact of changing climate on hydro-climatology and nutrient loadings in agricultural subsurface-drained areas on a watershed in northeastern Indiana. The study was conducted using a hydrologic model - the Soil and Water Assessment Tool (SWAT) - under two different greenhouse gas emission scenarios (RCP 4.5 and RCP 8.5). Based on analysis, annual subsurface drain flow totals could increase by 70% with respect to the baseline by the end of the 21st century. Surface runoff could increase by 10 to 140% and changes are expected to be greater under RCP 8.5. Soluble phosphorus yield over the basin in a year via subsurface drains could decrease by 30 to 60% under either emission scenarios. Annual total soluble phosphorus yield (soluble phosphorus loading to stream) from subsurface drains and surface runoff could vary from 0.041 to 0.058 kg/ha under RCP 4.5 and 0.035 to 0.064 kg/ha under RCP 8.5 by the end of the 21st century while the values from the baseline model were 0.051 kg/ha. This was attributable to the fact that future climate could have a greater increase in surface runoff than subsurface drain flow based on analysis of the different climate scenarios. Outputs from individual climate model data rather than ensembles provided a band of influence of watershed responses, while outputs from different timelines provided details for evaluating management practice suitability with respect to anticipated differences in climate. Results provide valuable information for stakeholders and policy makers for planning management practices to protect water quality.

The Latitudes, Attitudes, and Platitudes of Watershed Phosphorus Management in North America

Phosphorus (P) plays a crucial role in agriculture as a primary fertilizer nutrient-and as a cause of the eutrophication of surface waters. Despite decades of efforts to keep P on agricultural fields and reduce losses to waterways, frequent algal blooms persist, triggering not only ecological disruption but also economic, social, and political consequences. We investigate historical and persistent factors affecting agricultural P mitigation in a transect of major watersheds across North America: Lake Winnipeg, Lake Erie, the Chesapeake Bay, and Lake Okeechobee/Everglades. These water bodies span 26 degrees of latitude, from the cold climate of central Canada to the subtropics of the southeastern United States. These water bodies and their associated watersheds have tracked trajectories of P mitigation that manifest remarkable similarities, and all have faced challenges in the application of science to agricultural management that continue to this day. An evolution of knowledge and experience in watershed P mitigation calls into question uniform solutions as well as efforts to transfer strategies from other arenas. As a result, there is a need to admit to shortcomings of past approaches, plotting a future for watershed P mitigation that accepts the sometimes two-sided nature of Hennig Brandt's "Devil's Element."

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.

Reliable Future Climatic Projections for Sustainable Hydro-Meteorological Assessments in the Western Lake Erie Basin

Modeling efforts to simulate hydrologic processes under different climate conditions rely on accurate input data. Among other inaccuracies, errors in climate projections can lead to incorrect decisions. This study aimed to develop a reliable climate (precipitation and temperature) database for the Western Lake Erie Basin for the 21st century. Two statistically downscaled bias-corrected sources of climate projections (GDO: Global Downscaled Climate and Hydrology Projections and MACA: Multivariate Adaptive Constructed Analogs) were tested for their effectiveness in simulating historic climate (1966–2005) using ground-based station data from the National Climatic Data Center. MACA was found to have less bias than GDO and was better at simulating selected climate indices; thus, its climate projections were subsequently tested with different bias correction methods including the power transformation method, variance scaling of temperature, and Stochastic Weather Generators. The power transformation method outperformed the other methods and was used in bias corrections for 2006 to 2099. From the analysis, mean daily precipitation values were expected to remain more or less the same under both RCP (Representative Concentration Pathway) 4.5 and RCP 8.5 scenarios, ranging between 2.4 mm and 3.2 mm, while standard deviations were expected to increase, pointing to a rescaling of the distribution. Maximum one-day precipitation was expected to increase and could vary between 120 and 650 mm across the basin, while the number of wet days could potentially increase under the effects of RCP 4.5 and RCP 8.5. Both mean maximum and mean minimum daily air temperatures were expected to increase by up to 5.0 °C across the basin, while absolute maximum and minimum values could increase by more than 10 °C. The number of days in which precipitation could potentially fall as snow was expected to decrease, as was the annual number of days for optimal corn growth, although an earlier start to the growing season could be expected. Results from this study were very useful in creating a reliable climate database for the entire Western Lake Erie Basin (WLEB), which can be used for hydrologic, water resources, and other applications in the basin. The resulting climate database is published and accessible through the Purdue University Research Repository (Mehan et al., 2019), which is an open-access repository.

Evaluation of constraints to water quality improvements in the Western Lake Erie Basin

Severe environmental and health impacts have been experienced in the Western Lake Erie Basin (WLEB) because of eutrophication and associated proliferation of harmful algae blooms. Efforts to improve water quality within the WLEB have been on-going for several decades. However, water quality improvements in the basin have not been realized as anticipated. In this study, factors affecting water quality within the WLEB were evaluated with a view to differentiating their impacts and informing further assessments in the basin. Over the long-term (1966-2015) and basin-wide, total annual precipitation increased significantly by about 2.4 mm/year while mean monthly streamflows also increased during the same period although the increase was not significant (p = 0.36). There was, however, a significant increase in spring streamflows during this period (p = 0.003). Patterns in water quality parameters showed significant reductions in total suspended solids (TSS) (p < 0.001) and total phosphorus (TP) (p = 0.018) while soluble reactive phosphorus (SRP) increased significantly (p < 0.001), and in particular from about 1995. Results of near-term (2005-2015) analysis showed a non-significant (p = 0.262) reduction in TSS concentrations of about 0.25 mg/L/year. TP concentrations did not vary substantially during the same period while a 0.11 mg/L/year increase in nitrate and a 0.001 mg/L/year increase in SRP were observed, with increases in nitrates being significant (p = 0.013). TP and SRP concentrations, however, remained high within the basin with daily values ranging between 0.03 and 1.84 mg/L and less than 0.002-0.52 mg/L, respectively. Basin-wide, both spring precipitation and spring streamflows increased significantly during the period 2005-2015 (p < 0.001). Overall, no substantial changes in land use were observed, suggesting that water quality responses might be attributable to management. Based on recent data, corn acreage in the basin and fertilizer applied to corn increased by 33% and 10% respectively. Combined Sewer Overflows (CSOs) and impoundments were also important factors due to their prevalence in the basin. Based on the analysis, changes in agricultural management, increase in spring precipitation, CSOs, legacy phosphorus, and the presence of dams were thought to present constraints to water quality improvements despite conservation efforts within the basin.

Ecosystem services in the Great Lakes

A comprehensive inventory of ecosystem services across the entire Great Lakes basin is currently lacking and is needed to make informed management decisions. A greater appreciation and understanding of ecosystem services, including both use and non-use services, may have avoided misguided resource management decisions in the past that have resulted in legacies inherited by future generations. Given the interest in ecosystem services and lack of a coherent approach to addressing this topic in the Great Lakes, a summit was convened involving 28 experts working on various aspects of ecosystem services in the Great Lakes. The invited attendees spanned a variety of social and natural sciences. Given the unique status of the Great Lakes as the world's largest collective repository of surface freshwater, and the numerous stressors threatening this valuable resource, timing was propitious to examine ecosystem services. Several themes and recommendations emerged from the summit. There was general consensus that 1) a comprehensive inventory of ecosystem services throughout the Great Lakes is a desirable goal but would require considerable resources; 2) more spatially and temporally intensive data are needed to overcome our data gaps, but the arrangement of data networks and observatories must be well-coordinated; 3) trade-offs must be considered as part of ecosystem services analyses; and 4) formation of a Great Lakes Institute for Ecosystem Services, to provide a hub for research, meetings, and training is desirable. Several challenges also emerged during the summit, which are discussed in the paper.

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.