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This study investigates the combined impacts of climate change and agricultural conservation on the magnitude and uncertainty of nutrient loadings in the Maumee River Watershed, the second-largest watershed of the Laurentian Great Lakes. Two scenarios — baseline agricultural management and increased agricultural conservation — were assessed using an ensemble of five Soil and Water Assessment Tools driven by six climate models. The increased conservation scenario included raising conservation adoption rates from a baseline of existing conservation practices to feasible rates in the near future based on farmer surveys. This increased adoption of winter cover crops on 6%–10% to 60% of cultivated cropland; subsurface placement of phosphorus fertilizers on 35%–60% to 68% of cultivated cropland; and buffer strips intercepting runoff from 29%–34% to 50% of cultivated cropland. Increased conservation resulted in statistically significant (p ≤ 0.05) reductions in annual loads of total phosphorus (41%), dissolved reactive phosphorus (18%), and total nitrogen (14%) under the highest emission climate scenario (RCP 8.5). While nutrient loads decreased with increased conservation relative to baseline management for all watershed models, different conclusions on the true effectiveness of conservation under climate change may be drawn if only one watershed model was used.

Food, energy, and water (FEW) sectors are inextricably linked, making one sector vulnerable to disruptions in another. Interactions between FEW systems, viral pandemics, and human health have not been widely studied. We mined scientific and news/media articles for causal relations among FEW and COVID-19 variables and qualitatively characterized system dynamics. Food systems promoted the emergence and spread of COVID-19, leading to illness and death. Major supply-side breakdowns were avoided (likely due to low morbidity/mortality among working-age people). However, COVID-19 and physical distancing disrupted labor and capital inputs and stressed supply chains, while creating economic insecurity among the already vulnerable poor. This led to demand-side FEW insecurities, in turn increasing susceptibility to COVID-19 among people with many comorbidities. COVID-19 revealed trade-offs such as allocation of water to hygiene versus to food production and disease burden avoided by physical distancing versus disease burden from increased FEW insecurities. News/media articles suggest great public interest in FEW insecurities triggered by COVID-19 interventions among individuals with low COVID-19 case-fatality rates. There is virtually no quantitative analysis of any of these trade-offs or feedbacks. Enhanced quantitative FEW and health models are urgently needed as future pandemics are likely and may have greater morbidity and mortality than COVID-19.

Background Large rivers are ecological treasures with high human value, but most have experienced decades of degradation from industrial and municipal sewage, row-crop agricultural practices, and hydrologic alteration. We reviewed published analyses of long-term fish diversity publications from three intensively managed large river ecosystems to demonstrate the conservation potential of large river ecosystems. Results We show how the incorporation of recent advances in river concepts will allow a better understanding of river ecosystem functioning and conservation. Lastly, we focus on the Wabash River ecosystem based on high conservation value and provide a list of actions to maintain and support the ecosystem. In the Wabash River, there were originally 66 species of freshwater mussels, but now only 30 species with reproducing populations remain. Although there were multiple stressors over the last century, the largest change in Wabash River fish biodiversity was associated with rapid increases in municipal nutrient loading and invasive bigheaded carps. Conclusions Like similarly neglected large river systems worldwide, the Wabash River has a surprising amount of ecological resilience and recovery. For instance, of the 151 native fish species found in the 1800s, only three species have experienced local extinctions, making the modern assemblage more intact than many comparable rivers in the Mississippi River basin. However, not all the changes are positive or support the idea of recovery. Primary production underpins the productivity of these ecosystems, and the Wabash River phytoplankton assemblages shifted from high-quality green algae in the 1970s to lower less nutritional blue-green algae as nutrient and invasive species have recently increased. Our recommendations for the Wabash River and other altered rivers include the restoration of natural hydrology for the mainstem and tributaries, nutrient reductions, mechanisms to restore historical hydrologic patterns, additional sediment controls, and improved local hydraulics.

Hurricanes that damage lives and property can also impact pollutant sources and trigger poor water quality. Yet, these water quality impacts that affect both human and natural communities are difficult to quantify. We developed an operational remote sensing-based hurricane flood extent mapping method, examined potential water quality implications of two "500-year" hurricanes in 2016 and 2018, and identified options to increase social-ecological resilience in North Carolina. Flooding detected with synthetic aperture radar (91% accuracy) extended beyond state-mapped hazard zones. Furthermore, the legal floodplain underestimated impacts for communities with higher proportions of older adults, disabilities, unemployment, and mobile homes, as well as for headwater streams with restricted elevation gradients. Pollution sources were repeatedly affected, including ∼55% of wastewater treatment plant capacity and swine operations that generate ∼500 M tons/y manure. We identified ∼4.8 million km

Despite the global push for a circular water and nutrient economy, the United States still lags in recycling and reusing valuable waste streams. The reuse of waste streams could result in more sustainable agricultural practices by reducing water withdrawals in stressed environments and nutrient inputs to eutrophication-impacted ecosystems. However, microbial risks are a key barrier to reuse. We identify research and regulatory gaps through a systematic review of quantitative microbial risk assessments (QMRAs) and regulations for biosolids, manure, and human source-separated urine. We propose a cohesive path forward to improve upon existing QMRA approaches, to combine QMRA with other risk frameworks, and to develop integrated monitoring and control strategies by incorporating molecular biology tools. The application of a farm-to-fork risk-based approach that considers the combined use of waste streams is needed to develop comprehensive best management practices, treatment recommendations, and microbial quality criteria that promote food safety while advancing agricultural sustainability.

As a result of increased harmful algal blooms and hypoxia in Lake Erie, the US and Canada revised their phosphorus loading targets under the 2012 Great Lakes Water Quality Agreement. The focus of this paper is the Detroit River and its watershed, a source of 25% of the total phosphorus (TP) load to Lake Erie. Its load declined 37% since 1998, due chiefly to improvements at the regional Great Lakes Water Authority Water Resource Recovery Facility (WRRF) in Detroit and phosphorus sequestered by zebra and quagga mussels in Lake Huron. In addition to the 54% of the load from Lake Huron, nonpoint sources contribute 57% of the TP load and 50% of the dissolved reactive phosphorus load, with the remaining balance from point sources. After Lake Huron, the largest source is the WRRF, which has already reduced its load by over 40%. Currently, loads from Lake Huron and further reductions from the WRRF are not part of the reduction strategy, therefore remaining watershed sources will need to decline by 72% to meet the Water Quality Agreement target - a daunting challenge. Because other urban sources are very small, most of the reduction would have to come from agriculturally-dominated lands. The most effective way to reduce those loads is to apply combinations of practices like cover crops, buffer strips, wetlands, and applying fertilizer below the soil surface on the lands with the highest phosphorus losses. However, our simulations suggest even extensive conservation on those lands may not be enough.

In 2015, 48 permitted Confined Animal Feeding Operations (CAFOs) housed approximately 90% of poultry and 20% of swine and cattle within the Ohio portion of the Maumee River watershed. Recently, concerns about the impact CAFOs may have on nutrient loading in the watershed have been raised. In this study, we used manure management plans and inspection reports obtained from the Ohio Department of Agriculture Division of Livestock Environmental Permitting (ODA-DLEP) to assess how these CAFOs managed their manure for the years 2014 and 2015. A majority of liquid manure was applied between April and October, closely matching the amount of liquid manure planned to be applied during this period. Approximately 79% of the acres under control of the CAFOs that received manure had Bray P1 soil test phosphorus values below 50 ppm. The average distance between a swine CAFO’s livestock holding barn to the fields they control that can receive manure was 1.43 miles while for cattle CAFOs this distance was 1.91 miles. Approximately 78% of manure phosphorus generated on CAFOs was planned to be transferred through Distribution and Utilization, a process in which ownership of manure changes hands, including virtually all solid poultry manure phosphorus. While publicly available data show that, in general, CAFOs in the region are adhering to their state-approved permits, a knowledge gap regarding the management of approximately 80% of manure phosphorus exists due to manure transferred through Distribution and Utilization and manure produced from non-permitted livestock operations.

Nutrient loading from nonpoint sources has degraded water quality in large water bodies globally. The water quality of Lake Erie, the most productive of the Laurentian Great Lakes bordering the United States and Canada, is influenced by phosphorus loads from the Detroit River that drains an almost 19,000 km 2 international watershed. We used the Soil and Water Assessment Tool (SWAT) to evaluate a range of management practices to potentially reduce total phosphorus (TP) and dissolved reactive phosphorus (DRP) loads. Scenarios included both single practices and bundles of multiple practices. Single practice scenarios included fertilizer rate reduction (Rate) and sub-surface placement (PL), filter strips (FL), grassed waterways, cover crops (CC), wetlands (WT), controlled drainage, and changes in tillage practices. Bundle scenarios included combinations of Rate, PL, FL, CC, and WT with three adoption strategies: application on all applicable areas, on 55% of randomly selected applicable areas, and on 55% of high phosphorus yielding applicable areas. Results showed that among the single practice scenarios, FL, WT, PL, CC, and Rate performed well in reducing both TP and DRP loss from agricultural dominated sub-watersheds. Over all, the CC, FL, WT bundle performed best, followed by the CC, PL, WT bundle, reducing the load up to 80% and 70%, respectively, with 100% implementation. However, targeting high phosphorus yielding areas performed nearly as well as 100% implementation. Results from this work suggest that there are potential pathways for phosphorus load reduction, but extensive implementation of multiple practices is required.

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.

Concentrated Animal Feeding Operations (CAFOs) have arisen and expanded in the U.S. and globally to address efficiencies in livestock production. CAFOs tend to cluster in space for logistical purposes. Efficient distribution of concentrated manures produced by these operations is often not economically feasible, which may lead to accumulation on land near CAFOs, potentially resulting in local environmental changes. Moreover, as CAFOs are established or expand, they may need more lands to apply their manures, likely driving land use changes even after their establishment. Studies have yet to investigate these spatiotemporal impacts of CAFOs. We investigated whether the presence of regulated liquid waste CAFOs is associated with land use change over time and space as well as degraded environmental conditions surrounding those facilities. We used MODIS (Moderate Resolution Imaging Spectrometer) images from 2000 to 2018 to examine these questions in Michigan and North Carolina- states with varied CAFO establishment histories. We found that cropland extent increased while savanna and forest decreased near CAFOs. Similar observations did not occur outside of areas influenced by CAFOs. We also found evidence of environmental degradation, including decreased evapotranspiration and increased day and nighttime land surface temperatures in North Carolina. This study advances our understanding of environmental impacts surrounding CAFOs. Our findings can support policy changes and highlight the need to better understand these globally increasing entities.

Air carries a diverse load of particulate microscopic biological matter in suspension, either aerosolized or aggregated with dust particles, the aerobiome, which is dispersed by winds from sources to sinks. The aerobiome is known to contain microbes, including pathogens, as well as debris or small-sized propagules from plants and animals, but its variability and composition has not been studied comprehensibly. To gain a dynamic insight into the aerobiome existing over a mixed-use dryland setting, we conducted a biologically comprehensive, year-long survey of its composition and dynamics for particles less than 10 μm in diameter based on quantitative analyses of DNA content coupled to genomic sequencing. Airborne biological loads were more dependent on seasonal events than on meteorological conditions and only weakly correlated with dust loads. Core aerobiome species could be understood as a mixture of high elevation (e.g. Microbacteriaceae, Micrococcaceae, Deinococci), and local plant and soil sources (e.g. Sphingomonas, Streptomyces, Acinetobacter). Despite the mixed used of the land surrounding the sampling site, taxa that contributed to high load events were largely traceable to proximal agricultural practices like cotton and livestock farming. This included not only the predominance of specific crop plant signals over those of native vegetation, but also that of their pathogens (bacterial, viral and eukaryotic). Faecal bacterial loads were also seasonally important, possibly sourced in intensive animal husbandry or manure fertilization activity, and this microbial load was enriched in tetracycline resistance genes. The presence of the native opportunistic pathogen, Coccidioides spp., by contrast, was detected only with highly sensitive techniques, and only rarely. We conclude that agricultural activity exerts a much stronger influence that the native vegetation as a mass loss factor to the land system and as an input to dryland aerobiomes, including in the dispersal of plant, animal and human pathogens and their genetic resistance characteristics.

Urban agriculture offers the opportunity to provide fresh, local food to urban communities. However, urban agriculture can only be successfully embedded in urban areas if consumers perceive urban farming positively and accept urban farms in their community. Success of urban agriculture is rooted in positive perception of those living close by, and the perception strongly affects acceptance of farming within individuals' direct proximity. This research investigates perception and acceptance of urban agriculture through a qualitative, exploratory field study with N = 19 residents from a major metropolitan area in the southwest U.S. Specifically, in this exploratory research we implement the method of concept mapping testing its use in the field of Agroecology and Ecosystem Services. In the concept mapping procedure, respondents are free to write down all the associations that come to mind when presented with a stimulus, such as, “urban farming.” When applying concept mapping, participants are asked to recall associations and then directly link them to each other displaying their knowledge structure, i.e., perception. Data were analyzed using content analysis and semantic network analysis. Consumers' perception of urban farming is related to the following categories: environment, society, economy, and food and attributes. The number of positive associations is much higher than the number of negative associations signaling that consumers would be likely to accept farming close to where they live. Furthermore, our findings show that individuals' perceptions can differ greatly in terms of what they associate with urban farming and how they evaluate it. While some only think of a few things, others have well-developed knowledge structures. Overall, investigating consumers' perception helps designing strategies for the successful adoption of urban farming.

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.

Hurricanes that cause damage to lives and property are often accompanied by poor water quality that threatens the health of human communities and aquatic species. North Carolina has experienced 3 d...

Freshwater provisioning (FWP) is a critical ecosystem service that is highly affected by climate change/variability as well as land use/land management. Agricultural best management practices (BMPs) are implemented to mitigate the adverse impacts of intensive agricultural production on flow and water quality, thus can potentially protect and improve FWP services. Many studies have assessed BMP effectiveness for improving hydrology/water quality, however the impact of climate changes on BMP effectiveness for protecting FWP is poorly understood. In this study, changes in FWP under 5 BMPs and 6 projected climate change/variability scenarios, were quantified. The Soil and Water Assessment Tool was used to quantify FWP services for baseline (1975–2004) and future climates (2021–2050). We then assessed the climate change impacts on BMP effectiveness for 13 watersheds in the Upper Mississippi River Basin. The results indicated that all 5 BMP scenarios behaved similarly under the historical and future climates, generally resulting in improved FWP services compared to the baseline agricultural management. The combined BMPs was the most effective way to enhance FWP. No-tillage and cover crops performed well in improving FWP in agriculturally-dominated watersheds, while filter strips and grassed waterways had high effectiveness in non-agriculturally dominated watersheds. Results for the climate scenarios indicate that 5 BMPs under future climate were still effective compared to baseline. The increased precipitation and rising temperatures generally improved BMP effectiveness in maintaining and improving FWP services, due to increased freshwater availability under the projected future climate.

Sophisticated methods for uncertainty quantification have been proposed for overcoming the pitfalls of simple statistical inference in hydrology. The implementation of such methods is conceptually and computationally challenging, however, especially for large-scale models. Here, we explore whether there are circumstances in which simple approaches, such as least squares, produce comparably accurate and reliable predictions. We do so using three case studies, with two involving a small sewer catchment with limited calibration data, and one an agricultural river basin with rich calibration data. We also review additional published case studies. We find that least squares performs similarly to more sophisticated approaches such as a Bayesian autoregressive error model in terms of both accuracy and reliability if calibration periods are long or if the input data and the model have minimal bias. Overall, we find that, when mindfully applied, simple statistical methods such as least squares can still be useful for uncertainty quantification.

Over the past few decades, there has been a nationwide trend away from small livestock farms and toward large Concentrated Animal Feeding Operations (CAFOs). This shift results in concentrated manure production and introduces potential problems associated with its disposal. We analyzed data from 13 permitted CAFOs in southeastern Michigan, including 1187 occurrences of manure application from 12 of the CAFOs with available field-level data. CAFOs applied excess manure nutrients to cropland by applying to fields with soil phosphorus test levels >50 ppm (42% of all cases), applying to soybeans (7% of all cases), over-estimating crop yields in calculating plant nutrient requirements (67% of all cases), and applying beyond what is allowed by state permits (26% of all cases). This represents significant potential for redistribution of manure nutrients. The total amount of manure from all instances of over-application could be redistributed to fertilize over 4775 ha (11,800 acres) per year. Significant barriers to redistribution of manure exist, however, including cost, land availability, crop and soil need, transport logistics, and farmers' reluctance to use manure instead of inorganic fertilizer due to its variable composition. These findings are relevant to the harmful algal bloom and hypoxia issues in Lake Erie, which are driven by excess nutrients, and can be used to better inform science, modeling, and policy in the region.

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.

In response to degraded water quality, federal policy makers in the US and Canada called for a 40% reduction in phosphorus (P) loads to Lake Erie, and state and provincial policy makers in the Great Lakes region set a load-reduction target for the year 2025. Here, we configured five separate SWAT (US Department of Agriculture's Soil and Water Assessment Tool) models to assess load reduction strategies for the agriculturally dominated Maumee River watershed, the largest P source contributing to toxic algal blooms in Lake Erie. Although several potential pathways may achieve the target loads, our results show that any successful pathway will require large-scale implementation of multiple practices. For example, one successful pathway involved targeting 50% of row cropland that has the highest P loss in the watershed with a combination of three practices: subsurface application of P fertilizers, planting cereal rye as a winter cover crop, and installing buffer strips. Achieving these levels of implementation will require local, state/provincial, and federal agencies to collaborate with the private sector to set shared implementation goals and to demand innovation and honest assessments of water quality-related programs, policies, and partnerships.

Pay-for-performance (PFP) is a relatively new approach to agricultural conservation that attaches an incentive payment to quantified reductions in nutrient runoff from a participating farm. Similar to a payment for ecosystem services approach, PFP lends itself to providing incentives for the most beneficial practices at the field level. To date, PFP conservation in the U.S. has only been applied in small pilot programs. Because monitoring conservation performance for each field enrolled in a program would be cost-prohibitive, field-level modeling can provide cost-effective estimates of anticipated improvements in nutrient runoff. We developed a PFP system that uses a unique application of one of the leading agricultural models, the USDA’s Soil and Water Assessment Tool, to evaluate the nutrient load reductions of potential farm practice changes based on field-level agronomic and management data. The initial phase of the project focused on simulating individual fields in the River Raisin watershed in southeastern Michigan. Here we present development of the modeling approach and results from the pilot year, 2015-2016. These results stress that (1) there is variability in practice effectiveness both within and between farms, and thus there is not one “best practice” for all farms, (2) conservation decisions are made most effectively at the scale of the farm field rather than the sub-watershed or watershed level, and (3) detailed, field-level management information is needed to accurately model and manage on-farm nutrient loadings. Keywords: Agricultural conservation, Pay-for-performance, Phosphorus, River Raisin, SWAT, Western basin of Lake Erie.

Background Several studies have reported environmental disparities regarding exposure to concentrated animal feeding operations (CAFOs). Public health implications of environmental justice from the intensive livestock industry are of great concern in North Carolina (NC), USA, a state with a large number and extensive history of CAFOs. Objectives We examined disparities by exposure to CAFOs using several environmental justice metrics and considering potentially vulnerable subpopulations. Methods We obtained data on permitted animal facilities from NC Department of Environmental Quality (DEQ). Using ZIP code level variables from the 2010 Census, we evaluated environmental disparities by eight environmental justice metrics (i.e., percentage of Non-Hispanic White, Non-Hispanic Black, or Hispanic; percentage living below the poverty level; median household income; percentage with education less than high school diploma; racial residential isolation (RI) for Non-Hispanic Black; and educational residential isolation (ERI) for population without college degree). We applied two approaches to assign CAFOs exposure for each ZIP code: (1) a count method based on the number of CAFOs within ZIP code; and (2) a buffer method based on the area-weighted number of CAFOs using a 15 km buffer. Results Spatial distributions of CAFOs exposure generally showed similar patterns between the two exposure methods. However, some ZIP codes had different estimated CAFOs exposure for the different approaches, with higher exposure when using the buffer method. Our findings indicate that CAFOs are located disproportionately in communities with higher percentage of minorities and in low-income communities. Distributions of environmental justice metrics generally showed similar patterns for both exposure methods, however starker disparities were observed using a buffer method. Conclusions Our findings of the disproportionate location of CAFOs provide evidence of environmental disparities with respect to race and socioeconomic status in NC and have implications for future studies of environmental and health impacts of CAFOs.

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.

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.

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.

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.

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.

Predicting flood risk is important for climate change adaptation. We quantify fluvial flood risk due to changing climate in a mixed-use watershed in Michigan, USA. We apply two approaches to project future climate change: an ensemble of temperature and precipitation perturbations on the historical record and an ensemble of global and regional climate models. We incorporate climate projections into the Soil and Water Assessment Tool (SWAT) to estimate daily streamflow, then quantify flood risk using indices related to flood probability, duration, magnitude, and frequency. Results indicate rising temperatures may counteract small increases in precipitation, likely due to increased evapotranspiration. Climate model data without bias correction used in SWAT produced reasonable future streamflow changes—similar to the perturbation of historical climate—therefore retaining the predicted change in the flood frequency distribution. This work advances the application of climate models in SWAT for flood risk evaluation at watershed scales.

With the high demand for freshwater and its vital role in sustaining multiple ecosystem services, it is important to quantify and evaluate freshwater provisioning for various services (e.g., drinking, fisheries, recreation). Research on ecosystem services has increased recently, though relatively fewer studies apply a data driven approach to quantify freshwater provisioning for different ecosystem services. In this study, freshwater provisioning was quantified annually from 1995 to 2013 for 13 watersheds in the Upper Mississippi River Basin (UMRB). Results showed that the annual freshwater provision indices for all watersheds were less than one indicating that freshwater provisioning is diminished in the UMRB. The concentrations of sediment and nutrients (total nitrogen, and total phosphorus) are the most sensitive factors that impact freshwater provisioning in the UMRB. A significant linear relationship was observed between precipitation and freshwater provisioning index. During wet periods freshwater provisioning generally decreased in the study watersheds, primarily because of relatively high concentrations and loads of sediment and nutrients delivered from nonpoint sources. Results from this study may provide an insight, as well as an example of a data-driven approach to enhance freshwater provisioning for different ecosystem services and to develop a sustainable and integrated watershed management approach for the UMRB.

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.

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.

The increasing number of citizen science projects around the world brings the need to evaluate the effectiveness of these projects and to show the applicability of the data they collect. This research describes the Wabash River Sampling Blitz, a volunteer water-quality monitoring program in Central Indiana developed by the Wabash River Enhancement Corporation (WREC). Results indicate that field test strips for nitrate+nitrite-N read by volunteers generally agree with lab-determined values. Orthophosphate results are less transferable owing to low observed concentrations, although the field test strip values from unfiltered samples consistently over-predicted the lab values. Hierarchical cluster analysis (HCA) applied to volunteer-collected data groups sampling sites into meaningful management clusters that can help to identify water-quality priorities across the watershed as a proof of concept for watershed managers. Results of the HCA provide an opportunity for WREC to target future programs, education, and activities by analyzing the data collected by citizen scientists. Overall this study demonstrates how citizen science water quality data can be validated and applied in subsequent watershed management strategies.

We present a comparison of two ecohydrologic models commonly used for planning land management to assess the production of hydrologic ecosystem services: the Soil and Water Assessment Tool (SWAT) and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) annual water yield model. We compare these two models at two distinct sites in the US: the Wildcat Creek Watershed in Indiana and the Upper Upatoi Creek Watershed in Georgia. The InVEST and SWAT models provide similar estimates of the spatial distribution of water yield in Wildcat Creek, but very different estimates of the spatial distribution of water yield in Upper Upatoi Creek. The InVEST model may do a poor job estimating the spatial distribution of water yield in the Upper Upatoi Creek Watershed because baseflow provides a significant portion of the site’s total water yield, which means that storage dynamics which are not modeled by InVEST may be important. We also compare the ability of these two models, as well as one newly developed set of ecosystem service indices, to deliver useful guidance for land management decisions focused on providing hydrologic ecosystem services in three particular decision contexts: environmental flow ecosystem services, ecosystem services for potable water supply, and ecosystem services for rainfed irrigation. We present a simple framework for selecting models or indices to evaluate hydrologic ecosystem services as a way to formalize where models deliver useful guidance.