Collaborative Research: Understanding the Hydrologic Implications of Landscape Structure and Climate -- Towards a Unifying Framework of Watershed Similarity

合作研究：了解景观结构和气候的水文影响——建立流域相似性的统一框架

• 批准号: 0635770
• 负责人: Peter Troch
• 金额: $ 15.88万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-03-15 至 2011-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0635770&HistoricalAwards=false
• 关键词: Collaborative; Research; Understanding; Hydrologic; Implications

To what extents do landscape structure and climate control watershed hydrologic response? Understanding this relationship is necessary to develop a watershed classification system that can help to build low-dimensional and falsifiable hydrologic models and more reliably predict the response of ungauged basins. We propose to develop and test a unifying similarity theory of watershed hydrology based on dimensionless indices that capture both the internal structure of landscapes (geomorphology, pedology and vegetation patterns) and prevailing climate characteristics. The innovation of the research lies in the fact that we will (i) apply bottom-up as well as top-down dimensional analyses to observations from a large number of U.S. watersheds in various climate regions, and (ii) regionalize these similarity measures in an uncertainty framework to derive constraints on hydrologic behavior in ungauged basins. This unifying similarity theory of watershed hydrology will enhance our fundamental understanding of landscape functioning in the hydrological cycle and will promote the development of techniques that permit an integrated analysis of water budgets at the watershed scale, as well as of the effects of ecosystem disturbance and land use change. The main research hypothesis is that advancement in understanding watershed-scale hydrologic response is possible by focusing on the geomorphologic and ecologic controls on hydrological processes of landscapes. The ultimate proposal objective is to improve our fundamental understanding of flow processes at the watershed-scale. Constructing such a novel similarity theory of watershed hydrology, including an associated suite of models, will provide new insights into the hydrologic driving mechanisms at a wide range of space and time scales. Understanding the required level of complexity of hydrologic models directly links our proposal to current questions of the operational forecasting community in the United States. The proposal includes graduate training in advanced hydrologic modeling and synthesis in a collaborative research environment across three different departments at three different institutions in the United States.

景观结构和气候在多大程度上控制流域水文响应？了解这种关系是必要的，以开发一个流域分类系统，可以帮助建立低维和可证伪的水文模型，更可靠地预测无资料流域的响应。我们建议开发和测试一个统一的流域水文相似性理论的基础上，捕捉景观（地貌，土壤和植被模式）和流行的气候特征的内部结构的无量纲指数。创新的研究在于，我们将（i）应用自下而上以及自上而下的维度分析，从大量的美国观测流域在不同的气候区域，（ii）区域化这些相似性措施的不确定性框架中，以获得约束条件的水文行为在无资料流域。这种统一的流域水文相似性理论将提高我们对景观在水文循环中的作用的基本理解，并将促进技术的发展，允许在流域尺度上综合分析水收支，以及生态系统扰动和土地利用变化的影响。主要的研究假设是，在理解流域尺度水文响应的进步是可能的，通过专注于地貌和生态景观水文过程的控制。最终的建议目标是提高我们在流域尺度的流动过程的基本理解。构建这样一个新的流域水文相似性理论，包括一套相关的模型，将提供新的见解水文驱动机制在广泛的空间和时间尺度。了解水文模型所需的复杂程度直接将我们的建议与美国业务预报界当前的问题联系起来。该提案包括在美国三个不同机构的三个不同部门的合作研究环境中进行高级水文建模和综合方面的研究生培训。