Predicting Cyanobacterial Harmful Algal Blooms (CyanoHABs) in a Regulated River Using a Revised EFDC Model
نویسندگان
چکیده
Cyanobacterial Harmful Algal Blooms (CyanoHABs) produce toxins and odors in public water bodies drinking water. Current process-based models predict algal blooms by modeling chlorophyll-a concentrations. However, concentrations represent all algae hence, a method for predicting the proportion of harmful cyanobacteria is required. We proposed technique to based on source codes Environmental Fluid Dynamics Code from National Institute Research. A graphical user interface was developed generate information about general quality which subsequently used model Predictive performed Hapcheon-Changnyeong Weir–Changnyeong-Haman Weir section Nakdong River, South Korea, May October 2019, season CyanoHABs predominantly occur. To evaluate success rate model, detailed five-step classification levels proposed. The results demonstrated high prediction accuracy (62%) cyanobacteria. For management CyanoHABs, rather than chlorophyll-a, should be as index, allow direct inference their cell densities (cells/mL). may help improve existing Algae Alert System Korea.
منابع مشابه
Occurrence of Cyanobacterial Harmful Algal Blooms Workgroup report.
Appreciation is given to all those whose efforts made the production of this book possible. Thanks are due to the editors, Anthony Fristachi, US Environmental Protection Agency, Office of Research and Development, Cincinnati, Ohio and Jim Sinclair, PhD, US Environmental Protection Agency. Thanks are also due to Dr. Jeffrey Johansen of John Carroll University for his review and revisions to the ...
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ژورنال
عنوان ژورنال: Water
سال: 2021
ISSN: ['2073-4441']
DOI: https://doi.org/10.3390/w13040439