Ten‐Year Hindcast Assessment of an Improved Probabilistic Forecast System for Cyanotoxin (Microcystins) Risk Level in Lake Erie
Abstract Toxic harmful algal blooms produce public health hazards in freshwater systems around the world. There is a need for forecast systems that can mitigate risk of public exposure to toxins. We improved an approach to predict the spatially and temporally resolved probability of microcystins (MC...
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| Format: | Article |
| Language: | English |
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Wiley
2025-04-01
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| Series: | Water Resources Research |
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| Online Access: | https://doi.org/10.1029/2024WR038952 |
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| author | Qianqian Liu Mark D. Rowe Richard P. Stumpf Reagan Errera Casey Godwin Justin D. Chaffin Eric J. Anderson Tongyao Pu |
| author_facet | Qianqian Liu Mark D. Rowe Richard P. Stumpf Reagan Errera Casey Godwin Justin D. Chaffin Eric J. Anderson Tongyao Pu |
| author_sort | Qianqian Liu |
| collection | DOAJ |
| description | Abstract Toxic harmful algal blooms produce public health hazards in freshwater systems around the world. There is a need for forecast systems that can mitigate risk of public exposure to toxins. We improved an approach to predict the spatially and temporally resolved probability of microcystins (MCs) exceeding a threshold level (6 μg L−1) in western Lake Erie. This approach combines a 5‐day chlorophyll‐a forecast model, a weekly updated regression model predicting MCs from chlorophyll‐a, and an empirical relationship between predicted MCs and observed probability of MCs exceeding the threshold calibrated over a hindcast period. We included additional years in the database for calibration and assessment, applied an empirical bias adjustment to the Moderate Resolution Imaging Spectroradiometer for consistency with Sentinel‐3 satellite imagery, and applied a robust Siegel regression method. Cross‐validation showed reasonable skill over regions including surface water, public water system plant intake sites, and bottom waters. The forecast also presented useful skill when assessed against two intensive sampling events of Microcystis blooms in western Lake Erie in 2018 and 2019. Our results provide a comprehensive assessment of a novel method to forecast MC risk, which may be recalibrated and applied to other systems affected by toxic cyanobacterial blooms, where a similar relationship exists between chlorophyll and toxin concentrations at toxin levels relevant to advisory levels. |
| format | Article |
| id | doaj-art-ec82d65699554d61862ad0b6669f2e44 |
| institution | OA Journals |
| issn | 0043-1397 1944-7973 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Water Resources Research |
| spelling | doaj-art-ec82d65699554d61862ad0b6669f2e442025-08-20T02:09:25ZengWileyWater Resources Research0043-13971944-79732025-04-01614n/an/a10.1029/2024WR038952Ten‐Year Hindcast Assessment of an Improved Probabilistic Forecast System for Cyanotoxin (Microcystins) Risk Level in Lake ErieQianqian Liu0Mark D. Rowe1Richard P. Stumpf2Reagan Errera3Casey Godwin4Justin D. Chaffin5Eric J. Anderson6Tongyao Pu7Department of Physics and Physical Oceanography University of North Carolina Wilmington Wilmington NC USAGreat Lakes Environmental Research Laboratory National Oceanic and Atmospheric Administration Ann Arbor MI USANational Centers for Coastal Ocean Science National Oceanic and Atmospheric Administration Silver Spring MD USAGreat Lakes Environmental Research Laboratory National Oceanic and Atmospheric Administration Ann Arbor MI USACooperative Institute for Great Lakes Research University of Michigan Ann Arbor MI USAStone Laboratory and Ohio Sea Grant The Ohio State University Put‐In‐Bay OH USACivil and Environmental Engineering Colorado School of Mines Golden CO USACooperative Institute for Great Lakes Research University of Michigan Ann Arbor MI USAAbstract Toxic harmful algal blooms produce public health hazards in freshwater systems around the world. There is a need for forecast systems that can mitigate risk of public exposure to toxins. We improved an approach to predict the spatially and temporally resolved probability of microcystins (MCs) exceeding a threshold level (6 μg L−1) in western Lake Erie. This approach combines a 5‐day chlorophyll‐a forecast model, a weekly updated regression model predicting MCs from chlorophyll‐a, and an empirical relationship between predicted MCs and observed probability of MCs exceeding the threshold calibrated over a hindcast period. We included additional years in the database for calibration and assessment, applied an empirical bias adjustment to the Moderate Resolution Imaging Spectroradiometer for consistency with Sentinel‐3 satellite imagery, and applied a robust Siegel regression method. Cross‐validation showed reasonable skill over regions including surface water, public water system plant intake sites, and bottom waters. The forecast also presented useful skill when assessed against two intensive sampling events of Microcystis blooms in western Lake Erie in 2018 and 2019. Our results provide a comprehensive assessment of a novel method to forecast MC risk, which may be recalibrated and applied to other systems affected by toxic cyanobacterial blooms, where a similar relationship exists between chlorophyll and toxin concentrations at toxin levels relevant to advisory levels.https://doi.org/10.1029/2024WR038952Lake Eriecyanobacterial harmful algal bloommicrocystinsprobabilistic forecastcross‐validationskill assessment |
| spellingShingle | Qianqian Liu Mark D. Rowe Richard P. Stumpf Reagan Errera Casey Godwin Justin D. Chaffin Eric J. Anderson Tongyao Pu Ten‐Year Hindcast Assessment of an Improved Probabilistic Forecast System for Cyanotoxin (Microcystins) Risk Level in Lake Erie Water Resources Research Lake Erie cyanobacterial harmful algal bloom microcystins probabilistic forecast cross‐validation skill assessment |
| title | Ten‐Year Hindcast Assessment of an Improved Probabilistic Forecast System for Cyanotoxin (Microcystins) Risk Level in Lake Erie |
| title_full | Ten‐Year Hindcast Assessment of an Improved Probabilistic Forecast System for Cyanotoxin (Microcystins) Risk Level in Lake Erie |
| title_fullStr | Ten‐Year Hindcast Assessment of an Improved Probabilistic Forecast System for Cyanotoxin (Microcystins) Risk Level in Lake Erie |
| title_full_unstemmed | Ten‐Year Hindcast Assessment of an Improved Probabilistic Forecast System for Cyanotoxin (Microcystins) Risk Level in Lake Erie |
| title_short | Ten‐Year Hindcast Assessment of an Improved Probabilistic Forecast System for Cyanotoxin (Microcystins) Risk Level in Lake Erie |
| title_sort | ten year hindcast assessment of an improved probabilistic forecast system for cyanotoxin microcystins risk level in lake erie |
| topic | Lake Erie cyanobacterial harmful algal bloom microcystins probabilistic forecast cross‐validation skill assessment |
| url | https://doi.org/10.1029/2024WR038952 |
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