Prediction of algal bloom occurrence based on the naive Bayesian model considering satellite image pixel differences

Mu, Meng; Li, Yunmei; Bi, Shun; Lyu, Heng; Xu, Jie; Lei, Shaohua; Miao, Shihai; Zeng, Shuai; Zheng, Zhuo; Du, Chunyu

doi:10.1016/j.ecolind.2021.107416

Cited by 20 publications

(10 citation statements)

References 52 publications

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“…The development of many of the near‐term freshwater quality forecasts we analyzed was motivated by the need for freshwater ecosystem services in the face of increased ecosystem variability due to global change. Researchers identified increased variability in management‐relevant ecosystem variables such as water temperature (Carey et al, 2022; Thomas et al, 2020), distribution of freshwater fishes (Fraker et al, 2020), invasive species (Messager & Olden, 2018), and algal biomass (Liu et al, 2020; Mu et al, 2021; Page et al, 2018) as motivation for forecast development. In all cases, the stated motivation for anticipating increased variability was coupled with a desire to preemptively inform freshwater management and decision‐making.…”

Section: Resultsmentioning

confidence: 99%

Progress and opportunities in advancing near‐term forecasting of freshwater quality

Lofton

Howard

Thomas

et al. 2023

Global Change Biology

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Near‐term freshwater forecasts, defined as sub‐daily to decadal future predictions of a freshwater variable with quantified uncertainty, are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Shifting baselines in freshwater ecosystems due to land use and climate change prevent managers from relying on historical averages for predicting future conditions, necessitating near‐term forecasts to mitigate freshwater risks to human health and safety (e.g., flash floods, harmful algal blooms) and ecosystem services (e.g., water‐related recreation and tourism). To assess the current state of freshwater forecasting and identify opportunities for future progress, we synthesized freshwater forecasting papers published in the past 5 years. We found that freshwater forecasting is currently dominated by near‐term forecasts of water quantity and that near‐term water quality forecasts are fewer in number and in the early stages of development (i.e., non‐operational) despite their potential as important preemptive decision support tools. We contend that more freshwater quality forecasts are critically needed and that near‐term water quality forecasting is poised to make substantial advances based on examples of recent progress in forecasting methodology, workflows, and end‐user engagement. For example, current water quality forecasting systems can predict water temperature, dissolved oxygen, and algal bloom/toxin events 5 days ahead with reasonable accuracy. Continued progress in freshwater quality forecasting will be greatly accelerated by adapting tools and approaches from freshwater quantity forecasting (e.g., machine learning modeling methods). In addition, future development of effective operational freshwater quality forecasts will require substantive engagement of end users throughout the forecast process, funding, and training opportunities. Looking ahead, near‐term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management.

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Section: Resultsmentioning

confidence: 99%

Progress and opportunities in advancing near‐term forecasting of freshwater quality

Lofton

Howard

Thomas

et al. 2023

Global Change Biology

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“…While three studies presented near-term forecasts of phytoplankton-related variables in lakes, differences in their methodology precluded comparison. Two studies assessed their forecasts by converting the forecast to binary predictions (occurrence/non-occurrence of a bloom event; Mu et al, 2021) and exceedance/non-exceedance of a cyanobacterial toxin concentration threshold Liu et al, 2020), both of which reported better-than-chance skill at forecast horizons up to 5 -7 days ahead (Table 3). One additional study provided probabilistic forecasts of chlorophyll-a concentrations in two English lakes, with a reported RMSE of ~2.75 -5.25 mg m -3…”

Section: Water Quality Forecast Accuracy Is Usually Assessed But Comp...mentioning

confidence: 99%

“…2). Researchers identified increased variability in management-relevant ecosystem variables such as water temperature (Carey et al, 2022;Thomas, Figueiredo, et al, 2020), distribution of freshwater fishes (Fraker et al, 2020), invasive species (Messager & Olden, 2018), and algal biomass (Liu et al, 2020;Mu et al, 2021;Page et al, 2018) as motivation for forecast development. In all cases, the stated motivation for anticipating increased variability was coupled with a desire to preemptively inform freshwater management and decision-making.…”

Section: Water Quality Forecasts Are Motivated By Ecosystem Services ...mentioning

confidence: 99%

Progress and opportunities in advancing near-term forecasting of freshwater quality

Lofton

Howard

Thomas

et al. 2022

Preprint

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Near-term freshwater forecasts, defined as sub-daily to decadal future predictions of a freshwater variable with quantified uncertainty, are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Shifting baselines in freshwater ecosystems due to land use and climate change prevent managers from relying on historical averages for predicting future conditions, necessitating near-term forecasts to mitigate freshwater risks to human health and safety (e.g., flash floods, harmful algal blooms). To assess the current state of freshwater forecasting and identify opportunities for future progress, we synthesized freshwater forecasting papers published in the past five years. We found that freshwater forecasting is currently dominated by near-term forecasts of water quantity and that near-term water quality forecasts are fewer in number and in early stages of development (i.e., non-operational), despite their potential as important preemptive decision support tools. We contend that more freshwater quality forecasts are critically needed, and that near-term water quality forecasting is poised to make substantial advances based on examples of recent progress in forecasting methodology, workflows, and end user engagement. For example, current water quality forecasting systems can predict water temperature, dissolved oxygen, and algal bloom/toxin events five days ahead with reasonable accuracy. Continued progress in freshwater quality forecasting will be greatly accelerated by adapting tools and approaches from freshwater quantity forecasting (e.g., machine learning modeling methods). In addition, future development of effective operational freshwater quality forecasts necessitates substantive engagement of end users throughout the forecast process, funding, and training opportunities. Looking ahead, near-term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management.

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“…As a consequence, it is common to observe contamination of water bodies with heavy metals that are harmful to human and environmental health (Maggioni dos Santos et al, 2021). Moreover, the increasing occurrence of algal blooms, due to excessive inputs of phosphorus, have attracted worldwide attention, because they seriously affect aquatic life, local landscapes, tourism, and drinking water supplies (Duquesne et al, 2021;Mu et al, 2021). Lake Guaíba is a freshwater lake which is surrounded by the city of Porto Alegre (Fig.…”

Section: Introductionmentioning

confidence: 99%

Tributary contributions to sediment deposited in the Jacuí Delta, Southern Brazil

Tiecher

Ramon²,

Andrade³

et al. 2022

Journal of Great Lakes Research

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Prediction of algal bloom occurrence based on the naive Bayesian model considering satellite image pixel differences

Cited by 20 publications

References 52 publications

Progress and opportunities in advancing near‐term forecasting of freshwater quality

Progress and opportunities in advancing near‐term forecasting of freshwater quality

Progress and opportunities in advancing near-term forecasting of freshwater quality

Tributary contributions to sediment deposited in the Jacuí Delta, Southern Brazil

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