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

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dc.contributor.authorLofton, Mary E.en
dc.contributor.authorHoward, Dexter W.en
dc.contributor.authorThomas, R. Quinnen
dc.contributor.authorCarey, Cayelan C.en
dc.date.accessioned2024-01-17T14:36:46Zen
dc.date.available2024-01-17T14:36:46Zen
dc.date.issued2023-04en
dc.description.abstractNear-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.en
dc.description.versionPublished versionen
dc.format.extentPages 1691-1714en
dc.format.extent24 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1111/gcb.16590en
dc.identifier.eissn1365-2486en
dc.identifier.issn1354-1013en
dc.identifier.issue7en
dc.identifier.orcidThomas, Robert [0000-0003-1282-7825]en
dc.identifier.orcidCarey, Cayelan [0000-0001-8835-4476]en
dc.identifier.pmid36622168en
dc.identifier.urihttps://hdl.handle.net/10919/117378en
dc.identifier.volume29en
dc.language.isoenen
dc.publisherWileyen
dc.relation.urihttps://www.ncbi.nlm.nih.gov/pubmed/36622168en
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectaquatic ecosystem modelingen
dc.subjectdata assimilationen
dc.subjectecological forecastingen
dc.subjectfreshwater managementen
dc.subjecthindcasten
dc.subjecthydrological forecastingen
dc.subjectnear-term iterative forecasting cycleen
dc.subjectuncertaintyen
dc.subjectwater qualityen
dc.subjectwater quantityen
dc.subject.meshHumansen
dc.subject.meshUncertaintyen
dc.subject.meshEcosystemen
dc.subject.meshTemperatureen
dc.subject.meshFresh Wateren
dc.subject.meshForecastingen
dc.subject.meshWater Qualityen
dc.titleProgress and opportunities in advancing near-term forecasting of freshwater qualityen
dc.title.serialGlobal Change Biologyen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherJournalen
dcterms.dateAccepted2022-11-23en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Scienceen
pubs.organisational-group/Virginia Tech/Science/Biological Sciencesen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Science/COS T&R Facultyen

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