Grantee Research Project Results
2023 Progress 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 Period Covered by this Report: September 1, 2022 through August 31,2023
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 is to optimize the implementation of nutrient treatment technologies and management practices guided directly by the ecological response of the watershed for effective Harmful Algal Blooms (HABs) control. The project objectives are 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 temporally and spatially implement the most appropriate suite of nutrient management strategies for HAB control.
Progress Summary:
During this reporting period, we organized several meetings with a subcommittee of the stakeholder group for individual tasks to receive feedbacks. Four tasks were planned and have been carried out as planned for Year 3. The progresses made in each task were summarized as following: (Task 1) -- The assessment framework has been finalized with ten indicators covering technological, environmental, economic, social-ecological, and managerial criteria. The finalized framework with the realistic weighting schemes have been applied for evaluating ten best management practices (BMPs) and compared with the South Florida Water Management District (SFWMD) framework to demonstrate the robustness of BMP selection and inform implementation space. The cost effectiveness of spatial allocation of BMP has been investigated for the Upper Kissimmee and Taylor Creek/Nubbins Slough sub-watersheds. Life cycle assessment (LCA) and life cycle cost analysis (LCCA) of varied onsite sewage treatment and disposal systems (OSTDS) across different scales is in progress; (Task 2) -- Preliminary testing and pilot-scale experiments have been carried out to test several new technologies such as biochar-based adsorption barrier or biochar-amended bioretention system, and novel In-ground Hybrid Adsorption Biological Treatment System (HABiTS) prototype is under development. These activities have been done in partnership with a utility (the City of Lakeland), a technology vender (Mackworth-Enviro), Southern Water and Soil LLC (Greg Mayfield) and GeoMatrix Systems, LLC (David Potts). The experiences gained in Task 2 will be used to develop a roadmap for implementation of new technologies; (Task 3) -- The effects of different BMP spatial allocation scenarios in the Watershed on nutrient exports to Lake Okeechobee has been investigated. The optimization outputs from Task 4 has been simulated for all of the six subwatersheds through water assessment model (WAM) to validate the optimal BMP distributions. The effects of the future 2070 Land Use Land Cover (LULC) changes on flows, and nutrient loads in the Watershed have been evaluated using WAM; (Task 4) --The team successfully developed AquaNutriOpt, a user-friendly open-source Python package designed to address a complex combinatorial optimization problem aimed at optimizing nutrient management for controlling harmful algal blooms. Utilizing a novel integer programming model, the package can handle diverse user inputs, automatically converting them into an optimization model and solving it to identify optimal Best Management Practices and Treatment Technologies. All research activities are following the approved Quality Assurance Project Plan (QAPP).
Some important outcomes from the project are: (1) The BMP evaluation results using the developed assessment framework are robust with built-in uncertainty analysis considering realistic range of indicator weightings. The developed framework is also flexible considering only dominant indicators when available data is limited; (2) The analysis of the varied BMP spatial allocation scenarios showed that targeting the top 10% TN nutrient loading in the Upper Kissimmee sub-watershed is the most cost-effective implementation plan; (3) The pilot scale bioretention systems have achieved significant inorganic-N removal from the plant nursery runoff but less TP removal; (4) The placement of BMP today has not been adequate and even the widespread use of current technologies and practices for nutrient control in the watershed would not be enough to meet the target Lake Okeechobee's total maximum daily load (TMDL); (5) Both nitrogen and phosphorus play a critical role on algal blooms, but algae blooms are more responsive to inorganic nitrogen; (6) The transition from natural or agricultural to urban lands will lead to increased nutrient loads at the watershed scale; (7) The optimization model and its associated open-source Python package are available for public use.
Future Activities:
The planned activities include: (1) finalize the the design of the spreadsheet tool for technology/practice evaluation; (2) complete the BMP spatial allocation study and LCA&LCCA of OSTDS; (3) finalize the design and start the operation of the bench-scale novel In-ground HABiTS treating household wastewater; (4) develop a roadmap for scaling up emerging technology with selected examples; (5) focus on scenarios of BMP configuration and their effects on algal blooms; (6) modify the underlying optimization model to incorporate data from multiple time periods during the optimization process and test the methodology generating optimal trade-offs for two specified nutrients (e.g., Phosphorus and Nitrogen) across various potential budget scenarios; (7) release AquaNutriOpt Version 2 for public use.
Journal Articles on this Report : 3 Displayed | Download in RIS Format
| Other project views: | All 25 publications | 9 publications in selected types | All 9 journal articles |
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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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Richardsoin N, Luangphairin N, Bhattacharjee A, Nachabe M, Ergas S. Nursery Runoff Treatment by Novel Biochar-Amended Bioretention Systems. WATER 2025;14(3):330. |
R840090 (2023) |
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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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Supplemental Keywords:
algal blooms, sustainability assessment framework, emerging technologies, watershed modeling, lake modeling, BMP optimizationProgress 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.