Ag retailers and water quality solutions for the Western Lake Erie Basin

Crops & Soils ◽  
2014 ◽  
Vol 47 (5) ◽  
pp. 14-16
Author(s):  
Kip Studer ◽  
Jane Petzoldt ◽  
Mark Adelsperger ◽  
Thomas Green
Keyword(s):  
Water Quality ◽  
Lake Erie ◽  
Western Lake ◽  
Western Lake Erie

scholarly journals Spatial and temporal variability of inherent and apparent optical properties in western Lake Erie: Implications for water quality remote sensing

2019 ◽  
Vol 45 (3) ◽  
pp. 490-507 ◽  
Author(s):  
Michael J. Sayers ◽  
Karl R. Bosse ◽  
Robert A. Shuchman ◽  
Steven A. Ruberg ◽  
Gary L. Fahnenstiel ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Optical Properties ◽  
Temporal Variability ◽  
Lake Erie ◽  
Spatial And Temporal Variability ◽  
Western Lake ◽  
Western Lake Erie

Weather, Landscape, and Management Effects on Nitrate and Soluble Phosphorus Concentrations in Subsurface Drainage in the Western Lake Erie Basin

2018 ◽  
Vol 61 (1) ◽  
pp. 223-232 ◽  
Author(s):  
Lindsay A. Pease ◽  
Norman R. Fausey ◽  
Jay F. Martin ◽  
Larry C. Brown
Keyword(s):  
Water Quality ◽  
Lake Erie ◽  
Subsurface Drainage ◽  
Quality Data ◽  
P Loss ◽  
Western Lake ◽  
Soluble Phosphorus ◽  
Management Factors ◽  
Soluble P ◽  
Western Lake Erie

Abstract. Subsurface drainage, while an important and necessary agricultural production practice in the Midwest, contributes nitrate (NO3-N) and soluble phosphorus (P) to surface waters. Eutrophication (i.e., excessive enrichment of surface water by NO3-N and soluble P) supports harmful algal blooms in receiving waters. The magnitude of NO3-N and soluble P loss in subsurface drainage varies greatly by landscape, weather, and field management factors. This study evaluated both the relative and combined impacts of these factors on observed NO3-N and soluble P concentrations in subsurface drainage water in the Western Lake Erie Basin watershed. Water quality data from multiple drainage outlet sites in northwest Ohio provided evidence that the primary management factors affecting NO3-N and soluble P loss were the amount and time of fertilizer application. Results strongly support following Tri-State fertilizer recommendations and 4R nutrient stewardship principles to reduce the risk of NO3-N and soluble P loss. Results also provided evidence of NO3-N and soluble P transport to subsurface drains via different pathways. Due to differences in NO3-N and soluble P transport through the soil profile (via baseflow and preferential flow, respectively), management approaches taken to reduce one nutrient may exacerbate losses of the other. Further research is needed to address potential changes in field hydrology (and consequently the in-field transport of soluble nutrients) from different types of agricultural best management practices (BMPs) and to evaluate optimal stacking of BMPs to achieve reductions in both NO3-N and soluble P loss. Controlled drainage has a high potential for stacking with other BMPs because it is primarily a physical discharge and load reduction practice. Keywords: Agriculture, Eutrophication, Nutrient transport, Regression analysis, Water quality.

An Evaluation of Effects of Groundwater Exchange on Nearshore Habitats and Water Quality of Western Lake Erie

2005 ◽  
Vol 31 ◽  
pp. 45-63 ◽  
Author(s):  
Sheridan K. Haack ◽  
Brian P. Neff ◽  
Donald O. Rosenberry ◽  
Jacqueline F. Savino ◽  
Scott C. Lundstrom
Keyword(s):  
Water Quality ◽  
Lake Erie ◽  
Western Lake ◽  
Groundwater Exchange ◽  
Western Lake Erie

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

2018 ◽  
Vol 205 ◽  
pp. 85-98 ◽  
Author(s):  
Lawrence Sekaluvu ◽  
Lefei Zhang ◽  
Margaret Gitau
Keyword(s):  
Water Quality ◽  
Lake Erie ◽  
Quality Improvements ◽  
Western Lake ◽  
Western Lake Erie

scholarly journals Multi-Year Simulation of Western Lake Erie Hydrodynamics and Biogeochemistry to Evaluate Nutrient Management Scenarios

2021 ◽  
Vol 13 (14) ◽  
pp. 7516
Author(s):  
Qi Wang ◽  
Leon Boegman
Keyword(s):  
Water Quality ◽  
Best Management Practices ◽  
Lake Erie ◽  
Water Levels ◽  
Management Scenarios ◽  
Biogeochemical Models ◽  
Western Lake ◽  
Mean Square Errors ◽  
Western Lake Erie ◽  
Total P

During the 1970s, harmful cyanobacteria (HFCB) were common occurrences in western Lake Erie. Remediation strategies reduced total P loads and bloom frequency; however, HFCB have reoccurred since the mid-1990s under increased system stress from climate change. Given these concurrent changes in nutrient loading and climate forcing, there is a need to develop management tools to investigate historical changes in the lake and predict future water quality. Herein, we applied coupled one-dimensional hydrodynamic and biogeochemical models (GLM–AED) to reproduce water quality conditions of western Lake Erie from 1979 through 2015, thereby removing the obstacle of setting and scaling initial conditions in management scenarios. The physical forcing was derived from surface buoys, airports, and land-based stations. Nutrient loads were reconstructed from historical monitoring data. The root-mean-square errors between simulations and observations for water levels (0.36 m), surface water temperature (2.5 °C), and concentrations of total P (0.01 mg L−1), PO4 (0.01 mg L−1), NH4 (0.03 mg L−1), NO3 (0.68 mg L−1), total chlorophyll a (18.74 μg L−1), chlorophytes (3.94 μg L−1), cyanobacteria (12.44 μg L−1), diatoms (3.17 μg L−1), and cryptophytes (3.18 μg L−1) were minimized using model-independent parameter estimation, and were within literature ranges from single year three-dimensional simulations. A sensitivity analysis shows that 40% reductions of total P and dissolved reactive P loads would have been necessary to bring blooms under the mild threshold (9600 MTA cyanobacteria biomass) during recent years (2005–2015), consistent with the Annex 4 recommendation. However, these would not likely be achieved by applying best management practices in the Maumee River watershed.

Impact of Land Use Activities in the Maumee River Watershed on Harmful Algal Blooms in Lake Erie

2017 ◽  
Vol 1 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Ramiro Berardo ◽  
Francesca Formica ◽  
Jeffrey Reutter ◽  
Ajay Singh
Keyword(s):  
Water Quality ◽  
Undergraduate Students ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Lake Erie ◽  
Ecological Stability ◽  
Urban Centers ◽  
River Watershed ◽  
Western Lake ◽  
Western Lake Erie

One of the focal events motivating the passage of the Clean Water Act in 1972 was the decline of water quality in Lake Erie, which was originally linked to insufficient treatment of wastewater in some of the biggest adjacent urban centers. The passing of the CWA and the adoption of the Great Lakes Water Quality Agreement in the early 1970s contributed to the quick improvement of water quality in the two ensuing decades, but the 1990s saw the return of water quality problems, indicated by the return of algal blooms to Western Lake Erie. Algal blooms typically occur when excess nutrients are produced by mixture of agricultural and urban practices, and they may threaten ecological stability and public health for millions dependent on the lake for drinking water, tourism, and fisheries. In this case study, we explore the relationship between human behavior and water quality impairments that lead to harmful algal blooms (HABs) in the Western Lake Erie Basin (WLEB), and in particular, the Maumee River Watershed. The case is designed to be taught in eight class meetings to an audience of upper-level undergraduate students, and has been tested in the classroom in consecutive semesters starting in the fall of 2015.

scholarly journals A Predictive Model of Chlorophyll a in Western Lake Erie Based on Artificial Neural Network

2021 ◽  
Vol 11 (14) ◽  
pp. 6529
Author(s):  
Qi Wang ◽  
Song Wang
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Artificial Neural Network ◽  
Chlorophyll A ◽  
Lake Erie ◽  
Ann Model ◽  
Meteorological Forcing ◽  
Chl A ◽  
Western Lake ◽  
Western Lake Erie

The reoccurrence of algal blooms in western Lake Erie (WLE) since the mid-1990s, under increased system stress from climate change and excessive nutrients, has shown the need for developing management tools to predict water quality. In this study, process-based model GLM-AED (General Lake Model-Aquatic Ecosystem Dynamics) and statistical model ANN (artificial neural network) were developed with meteorological forcing derived from surface buoys, airports, and land-based stations and historical monitoring nutrients, to predict water quality in WLE from 2002 to 2015. GLM-AED was calibrated with observed water temperature and chlorophyll a (Chl-a) from 2002 to 2015. For ANN, during the training period (2002–2010), the inputs included meteorological forcing and nutrient concentrations, and the target was Chl-a simulated by calibrated GLM-AED due to the lack of continuously daily measured Chl-a concentrations. During the testing period (2011–2015), the predicted Chl-a concentrations were compared with the observations. The results showed that the ANN model has higher accuracy with lower Chl-a RMSE and MAE values than GLM-AED during 2011 and 2015. Lastly, we applied the established ANN model to predict the future 10-year water quality of WLE, which showed that the probability of adverse health effects would be moderate, so more intense water resources management should be implemented.

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