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Snow hydrology: The parameterization of subgrid processes within a physically based snow energy and mass balance model.

机译:积雪水文:基于物理的积雪能量和质量平衡模型中子网格过程的参数化。

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The objective of this research was to develop techniques for the representation and parameterization of subgrid and distributed snow processes within snowmelt models. Snowmelt is driven by energy exchanges at the snow surface that have horizontal variability down to scales of 1 to 10 m. When areas with large extent are modeled, it is impractical to apply models distributed on a 1 to 10 m grid. Large model elements, either grid squares or topographically delineated, need to be used. Therefore, it is necessary to develop modeling approaches that can parameterize the variability within these elements, referred to as subgrid variability. The role of subgrid variability increases as the model element size is increased, so as scale increases the representation of subgrid variability becomes more important. Computational tools are needed to explore the scale dependence of the subelement representation. Since subgrid variability is closely related to the topography, the parameterization of subgrid variability from the topography or topographical features was investigated.; This dissertation is a collection of four papers that address some of these challenges. The goal is to combine physically based modeling emphasizing physical understanding of the reasons for and processes involved in spatial variability of snow and snowmelt with the analysis of extensive existing remotely sensed and field-based data from a Colorado Front Range watershed - Green Lakes Valley (GLV) watershed. A small-scale distributed model was used to quantify and refine the representation of the spatial snow accumulation and melt processes. This then formed the basis for parameterization of subgrid variability through the use of depletion curves and the derivation of these depletion curves from digital elevation data. As a final step the scale dependence of depletion curves was explored and to some extent quantified.
机译:这项研究的目的是开发在融雪模型中表示和参数化次网格和分布雪过程的技术。融雪是由雪表面的能量交换驱动的,该能量交换的水平变化范围小至1到10 m。当对较大范围的区域进行建模时,应用分布在1至10 m网格上的模型是不切实际的。需要使用大型模型元素(网格正方形或地形图描绘)。因此,有必要开发一种可以对这些元素内的可变性进行参数化的建模方法,称为子网格可变性。子网格可变性的作用随着模型元素大小的增加而增加,因此,随着比例的增加,子网格可变性的表示就变得更加重要。需要计算工具来探索子元素表示的比例依赖性。由于亚网格变异性与地形密切相关,因此研究了根据地形或地形特征对亚网格变异性进行参数化的方法。本文是针对这些挑战的四篇论文的集合。目标是将强调对雪和融雪的空间变异性的原因和过程的物理理解的基于物理的建模与对科罗拉多州前岭流域-绿湖谷(GLV)的大量现有的遥感数据及基于实地的数据进行分析相结合)分水岭。使用小型分布式模型来量化和完善空间积雪和融化过程的表示。然后,这通过使用耗竭曲线以及从数字高程数据推导这些耗竭曲线,为亚电网可变性的参数化奠定了基础。作为最后一步,探索了损耗曲线的比例依赖性,并在一定程度上进行了量化。

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