Measuring and modelling hydrological parameter fields: strategies for sampling and integrating fine-scale surface and subsurface data in a spatial simulation framework

很好地认识到在水文系统中测量细尺度空间异质性或斑块的重要性和难度，特别是对于像湿地这样的复杂系统。我的研究计划的目标是a)通过b)湿地地下水力传导场的开发和确定方法的例子，揭示野外采样策略与其描述空间复杂水文系统的有效性之间的关系。这项拟议的研究将使用“混合模式”方法，将理论模拟实验与实验室和现场调查紧密结合起来，以推动参数发现模型。这项工作将混合使用实地数据采集系统、地球空间和地球物理综合工具以及我的研究小组在过去三年中开发的建模框架。我将开发从探地雷达信号中估计电导率场和水力传导场的方法，在‘沙箱’实验室环境中以及在Fletcher Fen和Point Pelee Marsh进行验证。除了该计划的面向领域的方面，我将使用模拟实验来评估采样策略和不同的测量方法对我们表征湿地系统的能力的影响。这些研究使用从我们的现场数据中提取的空间、时间和测量误差分布的估计，从我们的生态COSM模拟框架中实施的典型水文模型中得出具有不同程度测量不确定性的数据集。预计这项研究将揭示数据采样模式与自然系统中运行的过程之间的基本空间和时间相互作用。这项工作将导致许多应用开发，包括描述湿地的新的非侵入性方法，以及更好地量化复杂自然系统的采样设计方法。

The importance and the difficulty of measuring fine-scale spatial heterogeneity or 'patchiness' in hydrological systems is well recognized, especially for complex systems like wetlands. The goal of my research program is to a) uncover the relationship between field sampling strategies and their effectiveness for describing spatially complex hydrological systems, by example of b) developing and methods to determine subsurface hydraulic conductivity fields in wetlands. The proposed study will use a 'mixed-mode' approach, tightly integrating theoretical simulation experiments with lab and field investigations to drive parameter discovery models. The work will use a mixture of field data acquisition systems, geospatial and geophysical integration tools, and modelling frameworks developed by my research group over the past three years. I will develop methods to estimate electrical and hydraulic conductivity fields from GPR signals, validated in a 'sandbox' lab environment and in Fletcher Fen and Point Pelee Marsh. Parallel to the field-oriented aspects of the program, I will use simulation experiments to evaluate the effects that sampling strategies and varied measurement methods have on our ability to characterize wetland systems. These investigations use estimates of spatial, temporal, and measurement error distributions drawn from our field data to derive datasets with varying degrees of measurement uncertainty from representative hydrologic models implemented in our ECO-COSM simulation framework. The research is expected to reveal important insights into the fundamental spatial and temporal interactions between patterns of data sampling and the processes operative in natural systems. The work will lead to many applied developments including new, non-invasive methods for describing wetlands and sampling design methods that better quantify complex natural systems.