Ensemble forecasting applied to the field of hydrology is currently an established area of research embracing a broad spectrum of operational situations. This work catalogs the various pathways of ensemble streamflow forecasting based on an exhaustive review of more than 700 studies over the last 40 years. We focus on the advanced state of the art in the model-based (dynamical) ensemble forecasting approaches. Ensemble streamflow prediction systems are categorized into three leading classes: statistics-based streamflow prediction systems, climatology-based ensemble streamflow prediction systems and numerical weather prediction-based hydrological ensemble prediction systems. For each ensemble approach, technical information, as well as details about its strengths and weaknesses, are provided based on a critical review of the studies listed. Through this literature review, the performance and uncertainty associated with the ensemble forecasting systems are underlined from both operational and scientific viewpoints. Finally, the remaining key challenges and prospective future research directions are presented, notably through hybrid dynamical - statistical learning approaches, which obviously present new challenges to be overcome in order to allow the successful employment of ensemble streamflow forecasting systems in the next decades. Targeting students, researchers and practitioners, this review provides a detailed perspective on the major features of an increasingly important area of hydrological forecasting.

中文翻译：

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生成集合流预测：过去 40 年的方法和途径回顾

应用于水文领域的集合预报目前是一个既定的研究领域，涵盖了广泛的业务情况。这项工作基于对过去 40 年中 700 多项研究的详尽回顾，对集合流预测的各种途径进行了编目。我们专注于基于模型的（动态）集合预测方法的先进技术。集合流预测系统分为三大类：基于统计的流预测系统、基于气候学的集合流预测系统和基于数值天气预报的水文集合预测系统。对于每一种集成方法，技术信息以及有关其优缺点的详细信息都是根据对所列研究的严格审查提供的。通过这篇文献综述，从操作和科学的角度强调了与集合预报系统相关的性能和不确定性。最后，提出了剩余的关键挑战和未来的前瞻性研究方向，特别是通过混合动力-统计学习方法，这显然提出了需要克服的新挑战，以便在未来几十年成功使用集合流预测系统。本综述针对学生、研究人员和从业人员，详细介绍了水文预测日益重要的领域的主要特征。提出了剩余的关键挑战和未来的前瞻性研究方向，特别是通过混合动力-统计学习方法，这显然提出了需要克服的新挑战，以便在未来几十年成功使用集合流预测系统。本综述针对学生、研究人员和从业人员，详细介绍了水文预测日益重要的领域的主要特征。提出了剩余的关键挑战和未来的前瞻性研究方向，特别是通过混合动力-统计学习方法，这显然提出了需要克服的新挑战，以便在未来几十年成功使用集合流预测系统。本综述针对学生、研究人员和从业人员，详细介绍了水文预测日益重要的领域的主要特征。