Near-term forecasts of NEON lakes reveal gradients of environmental predictability across the U.S.

et al. 2023

Global Change Biology

Self 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) 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.

Section: Discussion and Synthesis: Opportunities To Advance Near‐term...mentioning

confidence: 99%

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

confidence: 99%

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

Lofton

Howard

et al. 2023

Global Change Biology

Self Cite

“…All data analyzed in this manuscript are published and publicly available at Thomas et al (2022a). This submission used novel code, which is provided in Thomas et al (2022b,c).…”

Section: Data Availability Statementmentioning

confidence: 99%

“…This submission used novel code, which is provided in Thomas et al . (2022b,c). The analysis is executable as a Binder at: https://mybinder.org/v2/zenodo/10.5281/zenodo.6267616/?urlpath=rstudio, with Binder instructions available in WebPanel 1.…”

Section: Data Availability Statementmentioning

confidence: 99%

Near‐term forecasts of NEON lakes reveal gradients of environmental predictability across the US

Frontiers in Ecol & Environ

McClure

Moore

et al. 2023

Self Cite

The US National Ecological Observatory Network's (NEON's) standardized monitoring program provides an unprecedented opportunity for comparing the predictability of ecosystems. To harness the power of NEON data for examining environmental predictability, we scaled a near-term, iterative, water temperature forecasting system to all six NEON lakes in the conterminous US. We generated 1-day-ahead to 35-days-ahead forecasts using a process-based hydrodynamic model that was updated with observations as they became available. Among lakes, forecasts were more accurate than a null model up to 35-days-ahead, with an aggregated 1-day-ahead root-mean square error (RMSE) of 0.61°C and a 35-days-ahead RMSE of 2.17°C. Water temperature forecast accuracy was positively associated with lake depth and water clarity, and negatively associated with fetch and catchment size. The results of our analysis suggest that lake characteristics interact with weather to control the predictability of thermal structure. Our work provides some of the first probabilistic forecasts of NEON sites and a framework for examining continental-scale predictability.

“…Development of forecasts of a single target variable at many sites with different environmental conditions can also provide insight on the intrinsic predictability of water quality and the utility of forecasting for water quality management across ecosystems. Initiatives such as the National Ecological Observatory Network (NEON) Ecological Forecasting Challenge (Thomas, Boettiger, et al, 2021), which solicits participants to submit forecasts for multiple sites using standardized data collected by NEON and assesses them for accuracy, are a starting point to compare predictability across ecosystems and model types (e.g., Thomas et al, 2022).…”

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

confidence: 99%

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

Lofton

Howard

et al. 2022

Preprint

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.