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

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.

2019 ◽  
Vol 45 (3) ◽  
pp. 490-507 ◽  
Author(s):  
Michael J. Sayers ◽  
Karl R. Bosse ◽  
Robert A. Shuchman ◽  
Steven A. Ruberg ◽  
Gary L. Fahnenstiel ◽  
...  

2018 ◽  
Vol 61 (1) ◽  
pp. 223-232 ◽  
Author(s):  
Lindsay A. Pease ◽  
Norman R. Fausey ◽  
Jay F. Martin ◽  
Larry C. Brown

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.


2020 ◽  
Vol 96 (4) ◽  
pp. 510-530
Author(s):  
Hongxing Liu ◽  
Wendong Zhang ◽  
Elena Irwin ◽  
Jeffrey Kast ◽  
Noel Aloysius ◽  
...  

2005 ◽  
Vol 31 ◽  
pp. 45-63 ◽  
Author(s):  
Sheridan K. Haack ◽  
Brian P. Neff ◽  
Donald O. Rosenberry ◽  
Jacqueline F. Savino ◽  
Scott C. Lundstrom

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

2021 ◽  
Vol 3 ◽  
Author(s):  
Samuel A. Miller ◽  
Steve W. Lyon

Artificial subsurface (tile) drainage is used in many agricultural areas where soils have naturally poor drainage to increase crop yield and field trafficability. Studies at the field scale indicate that tile drains disproportionately export large soluble reactive phosphorus (SRP) and nitrate loads to downstream waterbodies relative to other surface and subsurface runoff pathways, but knowledge gaps remain understanding the impact of tile drainage to nutrient export at watershed scales. The Western Lake Erie Basin is susceptible to summertime eutrophic conditions driven by non-point source nutrient pollution due to a shallow mean water depth and land use dominated by agriculture. The purpose of this study is to analyze the impact of tile drainage on downstream discharge, nutrient concentrations, and nutrient loads for 16 watersheds that drain to the Western Lake Erie Basin. Daily discharge and nutrient concentrations were summarized annually and during the main nutrient loading period (March–July) for 2 years representing normal nutrient loading period precipitation (2018) and above normal precipitation (2019). Results indicate positive correlations between watershed tile drainage percentage and runoff metrics during 2019, but no relationship during 2018. Additionally, SRP concentration and load were positively correlated to watershed tile drainage percentage in 2019, but not in 2018. Watershed tile drainage percentage was correlated with nitrate concentration and load for both years. The SRP concentration-discharge relationships suggested relatively weak, chemodynamic behavior, implying a slight enriching effect where SRP concentrations were greater at higher stream discharge conditions during both years. In contrast, nitrate concentration-discharge relationships suggested strong, enriching chemodynamic behavior during 2018, but chemostatic behavior during 2019. The difference in SRP and nitrate export patterns in the 2 years analyzed highlights the importance of implementing appropriate best management practices that target specific nutrients and treat primary delivery pathways to effectively improve downstream aquatic health conditions.


2017 ◽  
Vol 1 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Ramiro Berardo ◽  
Francesca Formica ◽  
Jeffrey Reutter ◽  
Ajay Singh

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.


2021 ◽  
Vol 11 (14) ◽  
pp. 6529
Author(s):  
Qi Wang ◽  
Song Wang

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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