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.

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.

Modified APEX model for Simulating Macropore Phosphorus Contributions to Tile Drains.

The contribution of macropore flow to phosphorus (P) loadings in tile-drained agricultural landscapes remains poorly understood at the field scale, despite the recognized deleterious impacts of contaminant transport via macropore pathways. A new subroutine that couples existing matrix-excess and matrix-desiccation macropore flow theory and a modified P routine is implemented in the Agricultural Policy Environmental eXtender (APEX) model. The original and modified formulation were applied and evaluated for a case study in a poorly drained field in Western Ohio with 31 months of surface and subsurface monitoring data. Results highlighted that a macropore subroutine in APEX improved edge-of-field discharge calibration and validation for both tile and total discharge from satisfactory and good, respectively, to very good and improved dissolved reactive P load calibration and validation statistics for tile P loads from unsatisfactory to very good. Output from the calibrated macropore simulations suggested median annual matrix-desiccation macropore flow contributions of 48% and P load contributions of 43%, with the majority of loading occurring in winter and spring. While somewhat counterintuitive, the prominence of matrix-desiccation macropore flow during seasons with less cracking reflects the importance of coupled development of macropore pathways and adequate supply of the macropore flow source. The innovative features of the model allow for assessments of annual macropore P contributions to tile drainage and has the potential to inform P site assessment tools.

Vertical Stratification of Soil Phosphorus as a Concern for Dissolved Phosphorus Runoff in the Lake Erie Basin.

During the re-eutrophication of Lake Erie, dissolved reactive phosphorus (DRP) loading and concentrations to the lake have nearly doubled, while particulate phosphorus (PP) has remained relatively constant. One potential cause of increased DRP concentrations is P stratification, or the buildup of soil-test P (STP) in the upper soil layer (<5 cm). Stratification often accompanies no-till and mulch-till practices that reduce erosion and PP loading, practices that have been widely implemented throughout the Lake Erie Basin. To evaluate the extent of P stratification in the Sandusky Watershed, certified crop advisors were enlisted to collect stratified soil samples (0-5 or 0-2.5 cm) alongside their normal agronomic samples (0-20 cm) ( = 1758 fields). The mean STP level in the upper 2.5 cm was 55% higher than the mean of agronomic samples used for fertilizer recommendations. The amounts of stratification were highly variable and did not correlate with agronomic STPs (Spearman's = 0.039, = 0.178). Agronomic STP in 70% of the fields was within the buildup or maintenance ranges for corn ( L.) and soybeans [ (L.) Merr.] (0-46 mg kg Mehlich-3 P). The cumulative risks for DRP runoff from the large number of fields in the buildup and maintenance ranges exceeded the risks from fields above those ranges. Reducing stratification by a one-time soil inversion has the potential for larger and quicker reductions in DRP runoff risk than practices related to drawing down agronomic STP levels. Periodic soil inversion and mixing, targeted by stratified STP data, should be considered a viable practice to reduce DRP loading to Lake Erie.

Edge-Of-Field Evaluation of the Ohio Phosphorus Risk Index.

The Phosphorus Index (PI) has been the cornerstone for phosphorus (P)-based management and planning over the past twenty years, yet field-scale evaluation of many state PIs has been limited. In this study, P loads measured in surface runoff and tile discharge from 40 agricultural fields in Ohio with prevailing management practices were used to evaluate the Ohio PI. Annual P loads were highly variable among fields (dissolved reactive P: 0.03-4.51 kg ha, total P: 0.03-6.88 kg ha). Both measured annual dissolved reactive P ( = 0.36, < 0.001) and total P ( = 0.25, < 0.001) loads were significantly related to Ohio PI score. The relationship between measured load and PI score substantially improved when averaged annual field values were used (dissolved reactive P: = 0.71, total P: = 0.73), indicating that the Ohio PI should be utilized to evaluate average annual risk of P loss, rather than as an annual risk tool. Comparison between the Ohio PI and other established local and national metrics resulted in large differences in potential P management recommendations for the monitored fields. In the near term, revision of Ohio PI risk categories and management recommendations using local P loading thresholds is needed. To meet the minimum criteria for state PI tools, future research efforts should focus on using measured field data (i) to incorporate new input factors (i.e., P application timing and leaching potential) into the Ohio PI, and (ii) to calibrate and validate the Ohio PI to provide better P risk assessments and management recommendations.

Increased Soluble Phosphorus Loads to Lake Erie: Unintended Consequences of Conservation Practices?

Cumulative daily load time series show that the early 2000s marked a step-change increase in riverine soluble reactive phosphorus (SRP) loads entering the Western Lake Erie Basin from three major tributaries: the Maumee, Sandusky, and Raisin Rivers. These elevated SRP loads have been sustained over the last 12 yr. Empirical regression models were used to estimate the contributions from (i) increased runoff from changing weather and precipitation patterns and (ii) increased SRP delivery (the combined effects of increased source availability and/or increased transport efficiency of labile phosphorus [P] fractions). Approximately 65% of the SRP load increase after 2002 was attributable to increased SRP delivery, with higher runoff volumes accounting for the remaining 35%. Increased SRP delivery occurred concomitantly with declining watershed P budgets. However, within these watersheds, there have been long-term, largescale changes in land management: reduced tillage to minimize erosion and particulate P loss, and increased tile drainage to improve field operations and profitability. These practices can inadvertently increase labile P fractions at the soil surface and transmission of soluble P via subsurface drainage. Our findings suggest that changes in agricultural practices, including some conservation practices designed to reduce erosion and particulate P transport, may have had unintended, cumulative, and converging impacts contributing to the increased SRP loads, reaching a critical threshold around 2002.

Long-term and seasonal trend decomposition of Maumee River nutrient inputs to western Lake Erie.

Cyanobacterial blooms in western Lake Erie have recently garnered widespread attention. Current evidence indicates that a major source of the nutrients that fuel these blooms is the Maumee River. We applied a seasonal trend decomposition technique to examine long-term and seasonal changes in Maumee River discharge and nutrient concentrations and loads. Our results indicate similar long-term increases in both regional precipitation and Maumee River discharge (1975-2013), although changes in the seasonal cycles are less pronounced. Total and dissolved phosphorus concentrations declined from the 1970s into the 1990s; since then, total phosphorus concentrations have been relatively stable, while dissolved phosphorus concentrations have increased. However, both total and dissolved phosphorus loads have increased since the 1990s because of the Maumee River discharge increases. Total nitrogen and nitrate concentrations and loads exhibited patterns that were almost the reverse of those of phosphorus, with increases into the 1990s and decreases since then. Seasonal changes in concentrations and loads were also apparent with increases since approximately 1990 in March phosphorus concentrations and loads. These documented changes in phosphorus, nitrogen, and suspended solids likely reflect changing land-use practices. Knowledge of these patterns should facilitate efforts to better manage ongoing eutrophication problems in western Lake Erie.

Analysis of spatiotemporal variation in dissolved organic carbon concentrations for streams with cropland-dominated watersheds.

It remains a challenge to understand how dissolved organic carbon (DOC) is cycled from farmlands to rivers due to the complex interaction between farming practices, the baseflow hydrology of predominantly flat lowlands, and seasonal environmental influences such as snowpack. To address this, field DOC concentrations were measured monthly throughout the year at sub-basin scales across the Chippewa River Watershed, which falls within the Corn Belt of the Midwestern United States. These DOC dynamics in stream water from croplands were benchmarked against the data sampled from hilly forested areas in the Connecticut River Watershed. The Soil Water Assessment Tool (SWAT) simulation was applied to provide potential predictive variables associated with daily baseflow. Our study outlines a framework using the combination of primary field data, hydrological modeling, and knowledge-based reclassification of Land Use/Land Cover (LULC) data to analyze the viability of modeling the spatial and temporal variations of cropland stream DOC concentrations. Calibration of the SWAT model resulted in the overall daily Nash-Sutcliffe model efficiency coefficient (NSE) of 0.67 and the corresponding R2 = 0.89. Our main results show: 1) baseflow DOC concentrations from croplands were substantially higher throughout the year relative to other landcover areas, especially for spring runoff/snowmelt scenarios, 2) an empirical analysis explained ~82 % of the spatial gradient of annual mean observed DOC concentrations, and 3) with the addition of hydrological simulated variables, a linear model explained ~81 % of monthly and 54 % of daily variations of observed DOC concentrations for cropland sub-basins. Our study identified key factors regulating the spatiotemporal DOC concentrations in cropland streamflow; the contribution here promotes to strengthen future analytical models that link watershed characteristics to carbon cycling processes in a large freshwater ecosystem.

Crop growth, hydrology, and water quality dynamics in agricultural fields across the Western Lake Erie Basin: Multi-site verification of the Nutrient Tracking Tool (NTT).

Agricultural field- and watershed-scale water quality models are used to assess the potential impact of management practices to reduce nutrient and sediment exports. However, observed data are often not available to calibrate and verify these models. Three years of data from the U.S. Department of Agriculture-Agricultural Research Service's 12 paired edge-of-field sites in northwest Ohio were used to calibrate and validate the Nutrient Tracking Tool. The goal of this study was to identify a single optimal parameter set for the Nutrient Tracking Tool in simulating annual crop yields, water balance, and nutrient loads across the Western Lake Erie Basin. A multi-site and multi-objective auto-calibration subroutine was developed in R to perform model calibration across the edge-of-field sites. The statistical metrics and evaluation criteria used in comparing the simulated results with the observed data were: Cohen's D Effect Size (Cohen's D < 0.20) and Percent bias (PBIAS ± 10% for crop yields, subsurface (tile) discharge, and surface runoff and ± 25% for dissolved reactive phosphorus (DRP) and nitrate­nitrogen (nitrate-N) in tile discharge, and DRP, particulate phosphorus, and nitrate-N in surface runoff). In both calibration and validation, the Cohen's D and PBIAS for annual crop yields, tile discharge, surface runoff, DRP, particulate P, and nitrate-N showed that the average simulated results were similar to the average observed values for each variable. The calibrated model simulated well the annual averages of crop yields, flows, and nutrient losses across fields. The tile drainage and phosphorus transport subroutines in the Nutrient Tracking Tool should be further improved to better simulate the dynamics of discharge and phosphorus transport through subsurface drainage. Stakeholders can use the verified model to evaluate the effectiveness of conservation practices in improving the water quality across the Western Lake Erie Basin.

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.

The re-eutrophication of Lake Erie: Harmful algal blooms and hypoxia.

Lake Erie supplies drinking water to more than 11 million consumers, processes millions of gallons of wastewater, provides important species habitat and supports a substantial industrial sector, with >$50 billion annual income to tourism, recreational boating, shipping, fisheries, and other industries. These and other key ecosystem services are currently threatened by an excess supply of nutrients, manifested in particular by increases in the magnitude and extent of harmful planktonic and benthic algal blooms (HABs) and hypoxia. Widespread concern for this important international waterbody has been manifested in a strong focus of scientific and public material on the subject, and commitments for Canada-US remedial actions in recent agreements among Federal, Provincial and State agencies. This review provides a retrospective synthesis of past and current nutrient inputs, impairments by planktonic and benthic HABs and hypoxia, modelling and Best Management Practices in the Lake Erie basin. The results demonstrate that phosphorus reduction is of primary importance, but the effects of climate, nitrogen and other factors should also be considered in the context of adaptive management. Actions to reduce nutrient levels by targeted Best Management Practices will likely need to be tailored for soil types, topography, and farming practices.