Scaling-up Stakeholder Engagement Efforts to Inform Better Communication &amp; Uptake of NOAA Great Lakes Ice Forecast Information

Fujisaki‐Manome, Ayumi; Gill, Devin; Channell, Kimberly; Graves, Victoria; Jagannathan, Kripa; Anderson, Eric; Lemos, M.C.

doi:10.7302/4389

Cited by 2 publications

(7 citation statements)

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“…Near-term forecasts comprise a wide range of time scales (e.g., daily, weekly, seasonal, decadal), each of which is likely associated with different end-user goals and decisions. For example, a ship captain may be most interested in lake ice conditions over the next several hours to days when deciding whether to embark (Fujisaki-Manome et al, 2022), while a reservoir manager may look multiple months ahead when planning water releases downstream (Jackson-Blake et al, 2022;Turner et al, 2020). We observed a relative dearth of near-term freshwater quality forecasts at multi-month (seasonal) time scales (but see Mercado-Bettín et al, 2021;Figure 6), highlighting an opportunity for the development of additional forecasts at this horizon.…”

Section: More Forecasts Using Diverse Modeling Approaches Over Multip...mentioning

confidence: 92%

“…Near-term forecasts of future ecosystem conditions enable preemptive interventions, allowing natural resource decision-makers to prevent or mitigate risk (e.g., Berthet et al, 2016;Fujisaki-Manome et al, 2022). Among ecosystems, near-term forecasts of freshwater ecosystems (i.e., lakes, rivers, wetlands) may be particularly valuable, as freshwaters have been more negatively impacted by human activities and global change than terrestrial or marine ecosystems (Albert et al, 2021;Moorhouse & Macdonald, 2015), necessitating new approaches for their management.…”

Section: Introductionmentioning

confidence: 99%

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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: More Forecasts Using Diverse Modeling Approaches Over Multip...mentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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

Lofton

Howard

Thomas

et al. 2023

Global Change Biology

View full text Add to dashboard Cite

show abstract

“…1; Dietze, 2017), which includes: engagement of end users; coordination of the forecasting team; model, infrastructure, and workflow development; data collection; uncertainty quantification; data assimilation (Table 1); forecast generation; forecast assessment; and dissemination to end users. Ideally, targeted freshwater forecast end users (e.g., managers, natural resource decision-makers) are engaged at the beginning of the forecast process to identify: 1) first, whether a forecast would assist in achieving end user goals; 2) if yes, then which forecasted variables are needed; and 3) the frequency and method of forecast dissemination (e.g., Berthet et al, 2016;Fujisaki-Manome et al, 2022;Gerst et al, 2020; Fig. 1 Step A).…”

Section: Overview Of the Near-term Iterative Forecasting Cyclementioning

confidence: 99%

“…multiple time horizons is needed to ensure maximum forecast utility for end users. Different end user decisions are made at different time scales; for example, a ship captain may be most interested in lake ice conditions over the next several hours to days when deciding whether to embark(Fujisaki-Manome et al, 2022), while a reservoir manager may look multiple months ahead when planning water releases downstream(Jackson-Blake et al, 2022;Turner et al, 2020). We observed a relative dearth of near-term freshwater quality forecasts at multimonth/seasonal timescales (but seeMercado-Bettín et al, 2021; Fig.…”

mentioning

confidence: 93%

“…1; Dietze, 2017), are increasingly being developed to understand and predict the future of ecosystems (Lewis et al, 2022). Forecasts of future ecosystem conditions enable preemptive management, enabling decision-makers to prevent or mitigate risk (e.g., Berthet et al, 2016;Fujisaki-Manome et al, 2022). Among ecosystems, forecasts of freshwater ecosystems (i.e., lakes, rivers, wetlands) may be particularly valuable, as freshwaters have been more negatively impacted by human activities and global change than terrestrial or marine ecosystems (Albert et al, 2021;Moorhouse & Macdonald, 2015), necessitating new approaches for their management.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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

Lofton

Howard

Thomas

et al. 2022

Preprint

View full text Add to dashboard Cite

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.

show abstract

Scaling-up Stakeholder Engagement Efforts to Inform Better Communication & Uptake of NOAA Great Lakes Ice Forecast Information

Cited by 2 publications

References 0 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

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