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: 0635752
• 负责人: Murugesu Sivapalan
• 金额: --
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard 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=0635752&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.

景观结构和气候控制流域的水文反应到底有什么范围？了解这种关系对于建立一个流域分类系统是必要的，该系统可以帮助建立低维和可伪造的水文模型，并更可靠地预测Ungaiged盆地的反应。我们建议基于无量纲指数开发和测试流域水文学的统一相似性理论，这些指数既捕获景观的内部结构（地貌，教育和植被模式）和盛行的气候特征。研究的创新在于，我们将（i）将自下而上的以及自上而下的维度分析应用于各种气候地区的大量美国流域的观察，以及（ii）将这些相似性度量的区域化为不确定性框架中的这些相似性度量，以对未命名基础的水文行为产生约束。这种统一的相似性理论将增强我们对水文周期中景观功能的基本理解，并将促进技术的发展，这些技术允许在流域规模上对水预算进行综合分析，以及生态系统扰乱和土地使用变化的影响。主要的研究假设是，通过关注景观水文过程的地貌和生态控制，可以通过关注流域规模的水文反应的进步。最终的建议目标是提高我们对流域规模流动过程的基本理解。建立这种新颖的水文学相似性理论，包括相关的模型套件，将为各种时空和时间尺度上的水文驾驶机制提供新的见解。了解水文模型的复杂性水平直接将我们的建议与美国运营预测社区的当前问题联系起来。该提案包括在美国三个不同机构的三个不同部门的协作研究环境中进行高级水文建模和合成的研究生培训。