Doctoral Dissertation Research: Characterizing Spatial Patterns of River Morphology and Hydraulics: Remote Mapping and Geostatistical Modeling of a Dynamic Fluvial System

河道及其输送的水和泥沙之间的非线性相互作用导致在一系列空间和时间尺度上的广泛的过程和形成。提取这种复杂性的尝试长期以来一直受到天然河流中不均匀条件的阻碍，以及河道形态的双重作用，既是水流和泥沙输送过程的结果，也是对其的控制。同样，强调断面平均预测的传统方法没有解决河段内和河段之间的深度和流速的二维空间变化，尽管它们在河道形态和泥沙输送之间的关系中发挥了基础作用。由于难以以足够精确和经济的方式测量河道和滩涂地形，阻碍了对这些重要相互作用进行表征和建模的努力。这项博士论文研究的目标是：开发遥感和地统计学方法来描述河流形态和水力学的空间模式；将这些技术应用于黄石国家公园的一个原始流域；并将观测到的地形和水流模式与泥沙输送和河道变化联系起来。这项研究产生的技术创新包括一种灵活的、以物理为基础的河流遥感方法，以及一种专门的地统计学框架，用于改进河道形态的表示和对河段尺度空间结构的定量描述。该项目的现场部分包括详细的地形测量和在一定流量范围内对几个河流河段的水流深度、流速和床沙粒度的空间分布测量。为了为这些密集的现场提供背景资料，将使用1949年至2004年期间的一系列遥感数据绘制水深变化图，记录河道平面和谷底土地覆盖的变化，并估计沉积物的长期转移速率。该项目将引入一种新的、明显的空间视角，使地貌学理论超越对单个横断面平均深度和速度的一维预测，转向对这些水力变量的变异性和空间模式的参数建模。开发的技术还将有助于在更大范围的尺度上检查河道形态和泥沙输送之间的关系。这些工具将对河流恢复特别有用，在河流恢复中，有效的监测和适应性管理对项目的成功至关重要，但往往受到甚至难以收集基本现场数据的困难，以及缺乏客观标准来评估实现诸如“地貌复杂性增加”等模糊目标的进展。

Non-linear interactions among river channels and the water and sediment they convey result in a broad spectrum of process and form across a range of spatial and temporal scales. Attempts to distill this complexity have long been stymied by the non-uniform conditions found in natural rivers and by the dual role of channel morphology as both a consequence of and a control on flow and sediment transport processes. Similarly, traditional approaches emphasizing the prediction of cross-sectional averages have not addressed two-dimensional spatial variations of depth and velocity within and among reaches, despite their fundamental role in the relationship between channel morphology and sediment transport. Efforts to characterize and model these important interactions have been hindered by the difficulty of measuring channel and floodplain topography with sufficient precision and economy. The goals of this doctoral dissertation research are to: develop remote sensing and geostatistical methods for characterizing spatial patterns of river morphology and hydraulics; apply these techniques to a pristine watershed in Yellowstone National Park; and relate the observed patterns of topography and flow to sediment transport and channel change. The technical innovations resulting from this study include a flexible, physics-based approach to remote sensing of rivers and a specialized geostatistical framework for obtaining improved representations of channel form and quantitative descriptions of reach-scale spatial structure. The field component of the project involves detailed topographic surveys and spatially distributed measurements of flow depth and velocity and bed material grain size in several stream reaches at a range of discharges. To provide context for these intensive field sites, a time series of remotely sensed data spanning the period from 1949 to 2004 will be used to map variations in water depth, document changes in channel planform and valley floor land cover, and estimate long-term rates of sediment transfer. This project will introduce a new, distinctly spatial perspective that will allow geomorphic theory to move beyond one-dimensional prediction of mean depths and velocities for individual cross-sections to parametric modeling of the variability and spatial pattern of these hydraulic quantities. The techniques developed will also facilitate examination of the relationship between channel morphology and sediment transport across an expanded range of scales. These tools will be particularly useful for river restoration, where effective monitoring and adaptive management are critical to project success but are often compromised by the difficulty of collecting even basic field data and by the lack of objective criteria for assessing progress toward such nebulous goals as "increased geomorphic complexity.'"