Progress and opportunities in advancing near‐term forecasting of freshwater quality
Progress and opportunities in advancing near‐term forecasting of freshwater quality
复制标题
推进淡水水质近期预报的进展和机遇
DOI：
10.1111/gcb.16590
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发表时间：
2023-01
影响因子：
11.6
通讯作者：
M. Lofton;Dexter W. Howard;R. Q. Thomas;C. Carey
中科院分区：
文献类型：
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作者：
M. Lofton;Dexter W. Howard;R. Q. Thomas;C. Carey
由于淡水生态系统由于全球变化而表现出更大的变异性，因此迫切需要近期淡水预测，即对具有量化不确定性的淡水变量的次日至十年的未来预测。由于土地利用和气候变化，淡水生态系统的基线发生了变化，管理人员无法依靠历史平均值来预测未来条件，因此需要进行近期预测，以减轻淡水对人类健康和安全的风险（例如，山洪暴发、有害藻华）和生态系统服务（例如，与水有关的娱乐和旅游）。为了评估淡水预测的现状并确定未来进展的机会，我们综合了过去5年发表的淡水预测论文。我们发现，淡水预测目前主要是对水量的短期预测，而近期水质预测的数量较少，而且还处于发展的早期阶段（即非操作性），尽管它们有潜力成为重要的先发制人的决策支持工具。我们认为，更多的淡水质量预测是迫切需要的，基于最近预测方法、工作流程和最终用户参与方面的进展，近期水质预测有望取得实质性进展。例如，目前的水质预报系统可以提前5天以合理的精度预测水温、溶解氧和藻华/毒素事件。通过适应淡水数量预测的工具和方法（如机器学习建模方法），将大大加快淡水质量预测的持续进展。此外，未来发展有效的可操作的淡水质量预测将需要最终用户在整个预测过程、资金和培训机会的实质性参与。展望未来，面对全球变化带来的变异性和风险增加，近期预测为淡水管理提供了一个充满希望的未来，我们鼓励淡水科学界将预测方法纳入水质研究和管理。
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.