Grantee Research Project Results
Final Report: Temporal and Spatial Optimization of Existing and Emerging Nutrient Management Technologies and Practices for Control of Harmful Algal Blooms
EPA Grant Number: R840090Title: Temporal and Spatial Optimization of Existing and Emerging Nutrient Management Technologies and Practices for Control of Harmful Algal Blooms
Investigators: Zhang, Qiong , Mihelcic, James R. , Ergas, Sarina , Arias, Mauricio , Charkhgard, Hadi , Rains, Mark , Nachabe, Mahmood
Institution: University of South Florida
EPA Project Officer: Ludwig-Monty, Sarah
Project Period: September 1, 2020 through August 31, 2023 (Extended to August 31, 2024)
Project Amount: $1,000,000
RFA: Approaches to Reduce Nutrient Loadings for Harmful Algal Blooms Management (2020) RFA Text | Recipients Lists
Research Category: Harmful Algal Blooms , Water
Objective:
The overall goal of this project was to optimize the implementation of nutrient treatment technologies and management practices guided directly by the ecological response of the watershed for effective Harmful Algal Bloom (HAB) control. The project objectives were to 1) develop a holistic assessment framework for evaluating existing and emerging nutrient management technologies/strategies, 2) create an innovation road map for supporting the scale-up of promising emerging technologies, and 3) integrate hydro-ecological models of temporal algae production with nutrient management optimization models. The project will provide decision-makers with a tool to implement the most appropriate suite of nutrient management strategies temporally and spatially for HAB control.
Summary/Accomplishments (Outputs/Outcomes):
The project successfully progressed as planned, maintaining its original goals and objectives throughout the implementation period. The project focused on four key tasks-- (a) Development of a Holistic Assessment Framework for Evaluation of Nutrient Management Technologies and Practices, (b) Selecting, Testing, and Scaling Up Emerging Technologies, (c) Development of an Integrated Modeling Platform to Predict Nutrient Load Reduction and Algae Production, (d) Creating a Decision Support Framework to Optimize Implementation of Nutrient Management Technologies and Practices--and achieved significant milestones in each area. The team included one research assistant professor, one postdoctoral fellow, six PhD students, and two master's students. Stakeholder engagement was a priority, with regular meetings held with the entire stakeholder group and subcommittees for individual tasks to receive feedback and ensure collaboration over the four years. The important outputs/outcomes from the project during the four years are as follows:
Task 1: Development of a Holistic Assessment Framework for Evaluation of Nutrient Management Technologies and Practices.
The research team successfully developed a comprehensive framework alongside a spreadsheet assessment tool to evaluate nutrient management technologies and practices. Additionally, an Excel-based database containing data for various best management practices (BMPs) was created.
- The assessment framework was developed through a systematic literature review and an iterative refining process involving stakeholder engagement. Systematic literature reviews and stakeholder feedback identified ten key indicators covering technological, environmental, economic, social-ecological, and managerial criteria. The framework employed a weighted sum multi-criteria analysis with realistic weighting schemes. Stakeholders can also vary the weightings of different indicators based on their preferences.
- An Excel-based database was created, containing data on nutrient removal and costs for 45 BMPs. Performance data for BMPs were collected from literature and state-wide project reports, ensuring quality assurance.
- A spreadsheet assessment tool with visual outputs was created for evaluation of nutrient management technologies and practices. Challenges related to data limitations were addressed by allowing users to prioritize critical indicators, simplifying data collection without compromising evaluation accuracy.
Task 2: Selecting, Testing, and Scaling Up Emerging Technologies.
The research team tested and evaluated three different emerging technologies and produced a draft roadmap for scaling up emerging technologies. The task also focused on capacity building and knowledge transfer, engaging stakeholders from diverse sectors, including state agencies, county utilities, water management districts, academic institutions, and consultants, through multiple meetings.
- Technology 1-- Adsorbent-Amended Reactive Aquatic Barriers. Nine phosphorus-sorbing materials (PSMs) were screened, four were tested for phosphate removal in column studies, and one material was tested in field-scale aquatic barrier studies. Results indicated that drinking water treatment (DWT) residuals were particularly effective due to their high phosphate adsorption capacity at low concentrations. Mixing DWT residuals with coarse sand enhanced hydraulic conductivity. Field studies highlighted channel morphology shifts and short-circuiting in sandy soils, suggesting that reactive barriers may be better suited for hardened grey/concrete infrastructure.
- Technology 2 -- Biochar-Enhanced Bioretention Systems. Bioretention systems with biochar in both the unsaturated zone and the internal water storage zone (IWSZ) achieved higher nutrient removal from nursery runoff compared to systems with biochar only in the unsaturated zone. Tracer studies demonstrated that biochar's microporosity extended pollutant residence time, reduced short-circuiting, and enhanced denitrification. Lower hydraulic loading rates (HLRs) improved nitrate reduction, but phosphate reduction remained unaffected. Higher outlet heights allowed more time for denitrification. However, adding Muhly grass did not significantly improve nutrient removal, likely due to the short growth period and residual fertilizer in plant roots.
- Technology 3 -- Hybrid Adsorption Biological Treatment Systems for Onsite Wastewater Treatment. Incorporation of zeolite and biochar into drainfield materials is expected to improve nitrogen removal from septic tank effluent by: 1) capturing ammonia, allowing more time for nitrification, and 2) providing conditions that enhance denitrification. Despite delays in material procurement and partner collaboration, adsorbent-amended and control systems of In-Ground Hybrid Adsorption Biological Treatment System (HABiTS) were constructed, tracer studies were completed, and initial testing with real wastewater is ongoing.
- Draft Roadmap for Emerging Technology Scale-up. A draft roadmap for emerging technology scale-up was created by involving partners from regulatory agencies, academia, and industry. The primary focus of the roadmap was onsite wastewater treatment systems (OWTS) technology scale-up and commercialization. The roadmap involves a step-by-step process designed to address technical, regulatory, and commercialization challenges.
Task 3: Development of an Integrated Modeling Platform to Predict Nutrient Load Reduction and Algae Production.
The research team recalibrated the Watershed Assessment Model (WAM) to reflect recent hydroclimatic conditions in the Lake Okeechobee watershed. The project delivered the first open-source model of hydrodynamics and water quality for Lake Okeechobee. It also provided watershed-wide estimates of BMP optimization impacts on nutrient load reduction and algae production.
- A model of the six northern sub-watersheds of Lake Okeechobee was calibrated/validated for water discharge and nitrogen (N)/phosphorous (P) loads for the period of 1995-2018. The hydrological and hydrodynamic components of the model are acceptable with Nash-Sutcliffe (NS) coefficient > 0.5.
- A model of the Lake Okeechobee has been completely developed and calibrated/validated using Delft3d. A number of 'what-if' scenarios have been analyzed to assess potential management strategies. The most effective way to control HABs is by reducing both nitrogen and phosphorus.
- Different BMP implementation scenarios in the six sub-watersheds were evaluated. The project demonstrated that the current placement of BMPs has not been adequate and that even the widespread use of current technologies and practices for nutrient control in the watershed would not be enough to meet the target of Lake Okeechobee's total maximum daily load (TMDL).
- The effect of future land use land cover (LULC) changes (2070) on flows and nutrient loads in the Lake Okeechobee watershed was investigated. The results demonstrated that the transition from natural or agricultural to urban lands will increase nutrient loads at the watershed scale.
Task 4: Creating a Decision Support Framework to Optimize Implementation of Nutrient Management Technologies and Practices.
The research team developed a robust multi-objective optimization model for HAB control via nutrient management decisions using quality-assured data from Tasks 1-3.
- A custom-built optimization tool, AquNutriOpt, was developed and can be downloaded from GitHub (https://github.com/Ashim-Khanal/AquaNutriOpt). The tool was validated through scenario testing in various sub-watersheds, demonstrating alignment between simulated and optimized phosphorus reduction results. The framework provides actionable insights for BMP and treatment technology (TT) implementation to reduce nutrient loads in the Lake Okeechobee watershed.
Conclusions:
Overall, the project delivered a comprehensive set of tools and models for nutrient management that will enable stakeholders to holistically evaluate nutrient management technologies and practices and strategically optimize the implementation of the technologies and practices for effective HAB control.
Journal Articles on this Report : 8 Displayed | Download in RIS Format
| Other project views: | All 25 publications | 9 publications in selected types | All 9 journal articles |
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Dang T, Arias M, Tarabih O, Phlips E, Ergas S, Rains M, Zhang Q. Modeling temporal and spatial variations of biogeochemical processes in a large subtropical lake:Assessing alternative solutions to algal blooms in Lake Okeechobee, Florida. Journal of Hydrology-Regional Studies 2023;47(101441). |
R840090 (2022) R840090 (Final) |
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Hua J, Cooper R, Cornejo P, Ergas S, Zhang Q. A holistic sustainability assessment framework for evaluating strategies to prevent nutrient pollution. Sustainability 2024;16(12). |
R840090 (2023) R840090 (Final) |
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Tarabih O, Dang T, Paudel R, Arias M. Lake operation optimization of nutrient exports:Application of phosphorus control in the largest subtropical lake in the United States. Environmental Modeling & Software 2023;160(105603). |
R840090 (2021) R840090 (Final) |
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Khanal A, Mahmoodian V, Tarabih OM, Hua J, Arias ME, Zhang Q, Charkhgard H. AquaNutriOpt:optimizing nutrients for controlling harmful algal blooms in Python—a case study of Lake Okeechobee. Environmental Modelling & Software 2024:106025. |
R840090 (2023) R840090 (Final) |
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Tarabih OM, Arias ME, Santos AL, Hua J, Cooper RZ, Khanal A, Dang TD, Khare YP, Charkhgard H, Rains MC, Zhang Q. Effects of the spatial distribution of best management practices for watershed wide nutrient load reduction. Ecological Engineering 2024;201:107211. |
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Cooper RZ, Ergas SJ, Nachabe M. Multi-decadal nutrient management and trends in two catchments of Lake Okeechobee. Resources 2024;13(2):28. |
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Santos AL, Tarabih OM, Arias ME, Rains MC, Zhang Q. Effects of future land use variability on nutrient loads in a fast‐urbanizing landscape. JAWRA Journal of the American Water Resources Association 2025;61(2):e70009. |
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Khanal A, Tarabih OM, Arias ME, Zhang Q, Charkhgard H. AquaNutriOpt II:A multi-period bi-objective nutrient optimization python tool for controlling harmful algal blooms-a case study of Lake Okeechobee. Environmental Modelling & Software 2025:106428. |
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Supplemental Keywords:
Algal blooms, sustainability assessment framework, emerging technologies, watershed modeling, lake modeling, BMP optimizationRelevant Websites:
Progress and Final Reports:
Original AbstractThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.