Hydrologic closure relationships at different levels of hillslope model complexity

例如，为了限制污染物向水资源的排放，水和土地管理有赖于对山坡和集水区地下水流和溶质运移的准确模型预测。这些尺度上的问题源于地下属性的未知异质性和流动和传输动力学的简化表示。在水文模型中，这些简化需要在时间和空间上变化的闭合关系(代表聚集的小尺度物理)。地下有限的测量能力和山坡及以上的困难实验阻碍了寻找这些封闭关系，而这些关系是更好的水和土地管理政策所必需的。这个项目旨在发现这些封闭关系的性质，并将朝着直接从山坡尺度上更好地理解迈出重要的一步。这个项目将在一个山坡尺度的实验系统中检查封闭关系，并探索其对现实世界集水区的普适性。山坡尺度研究将利用亚利桑那大学生物圈2号的景观演变天文台(LEO)山坡的非凡测量能力。最近在利奥山坡进行的试验收集的数据将被用来寻找和解释两个不同水平的模型复杂性的时间变化的闭合关系：(I)系统尺度的闭合关系，例如通过时间分布和蓄流关系；以及(Ii)混合三维山坡水文模型(H3D)基于过程的耦合非饱和和饱和区的表示。该项目将结合最近的方法学进展，即(1)确定过境时间分布和储排关系的基于数据的新办法，(2)数据同化和(3)机器学习方法，对封闭关系，例如它们的时间变异性及其与其他水文变量的联系，获得新的见解。转移到现实世界的案例将在装备齐全的零级基础上进行测试。这一裁决反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Water and land management, for example to limit the discharge of pollutants into water resources, relies on accurate model predictions of subsurface water flow and solute transport at scales of hillslopes and catchments. Issues at these scales arise from unknown heterogeneity of subsurface properties and simplified representation of the flow and transport dynamics. Within hydrologic models these simplifications require closure relationships (representing the aggregated small-scale physics) that vary in time and space. Limited measurement capabilities in the subsurface and difficult experimentation at the hillslope scale and beyond hamper the search for these closure relationships, that are needed for better water and land management policies. This project aims at discovering the nature of these closure relationships and will make an important step towards an improved understanding directly at the hillslope scale. This project will examine the closure relationships in a hillslope scale experimental system and explore its generalizability to real-world catchments. The hillslope scale study will take advantage of the exceptional measurement capability of the Landscape Evolution Observatory (LEO) hillslopes at Biosphere 2, The University of Arizona. Data collected from recent experiments at the LEO hillslopes will be utilized to find and explain temporally changing closure relationships for two different levels of model complexity: (i) the system-scale closure relationships, e.g., transit time distributions and the storage-discharge relationship, and (ii) the simplified process-based representation of coupled unsaturated and saturated zone of the hybrid-3D hillslope hydrological model (h3D). The project will gain novel insights into the closure relationships, e.g., their temporal variability and their connection to other hydrologic variables, by combining recent methodological advances, namely (i) new data-based approaches to determine transit time distributions and the storage-discharge relationship, (ii) data assimilation, and (iii) machine learning methods. The transfer to real-world cases will be tested on a well-equipped zero-order basin.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.