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