Nature‐based solutions for water‐resource challenges require advances in the science of ecohydrology. Current understanding is limited by a shortage of observations and theories that can further our capability to synthesize complex processes across scales ranging from submillimetres to tens of kilometres. Recent developments in environmental sensing, data, and modelling have the potential to drive rapid improvements in ecohydrological understanding. After briefly reviewing advances in sensor technologies, this paper highlights how improved measurements and modelling can be applied to enhance understanding of the following ecohydrological examples: interception and canopy processes, root uptake and critical zone processes, and up‐scaled effects of land use on streamflow. Novel and improved sensors will enable new questions and experiments, while machine learning and empirical methods provide additional opportunities to advance science. The synergy resulting from the convergence of these parallel developments will provide new insight into ecohydrological processes and thereby help identify nature‐based solutions to address water‐resource challenges in the 21st century.

中文翻译：

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推进21世纪的生态水文学：机遇的融合

基于自然的水资源挑战解决方案需要生态水文学的进步。当前的理解受到缺乏观测和理论的局限，这些观测和理论可以进一步增强我们在亚毫米到几十公里范围内综合复杂过程的能力。环境感测，数据和模型的最新发展有潜力推动生态水文认识的迅速改善。在简要回顾了传感器技术的进展之后，本文重点介绍了如何应用改进的测量和建模方法来加深对以下生态水文实例的理解：拦截和冠层过程，根系吸收和临界区过程，以及土地利用对河流流量的放大影响。新颖且经过改进的传感器将带来新的问题和实验，机器学习和经验方法为推进科学提供了更多机会。这些并行发展的融合所产生的协同作用将提供对生态水文学过程的新见解，从而有助于确定基于自然界的解决方案，以应对21世纪的水资源挑战。