On the dynamic nature of hydrological similarity
On the dynamic nature of hydrological similarity
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DOI：
10.5194/hess-22-3663-2018
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发表时间：
2018-04
影响因子：
6.3
通讯作者：
R. Loritz;H. Gupta;C. Jackisch;M. Westhoff;A. Kleidon;U. Ehret;E. Zehe
中科院分区：
文献类型：
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作者：
R. Loritz;H. Gupta;C. Jackisch;M. Westhoff;A. Kleidon;U. Ehret;E. Zehe
抽象的。陆地系统空间分布数据的多样性和分辨率不断提高，极大地增强了水文建模的潜力。然而，要优化和节约地使用这些数据源，我们需要更好地了解 (a) 哪些系统特征对水文动力学发挥主要控制作用，以及 (b) 这些特征需要在模型中表示到什么程度的详细程度。在本研究中，我们开发并测试了一种利用信息论和热力学推理来探索这些问题的方法，并使用空间分布的地形信息作为简单的例子。具体来说，我们将中尺度流域细分为 105 个山坡，并用二维数值山坡模型表示每个山坡。这些山坡模型的不同之处在于源自数字高程模型 (DEM) 的地形相关参数；每个的其余设置和气象强迫都是相同的。我们通过检查香农信息熵来分析山坡之间模拟排放和储存的相似程度作为时间的函数。此外，我们还通过使用归一化互信息（NMI）作为距离度量将山坡模型聚类为类似径流生成的功能组来导出“压缩”流域模型。我们的结果表明，在给定的模型环境中，数字高程模型中存储的全部地形信息中只有一部分与分布式径流和蓄水动态的模拟相关。这通过将模型集合从整组 105 个山坡压缩到仅 6 个山坡来体现，每个山坡代表不同的功能组，这不会导致模型性能出现实质性损失。重要的是，我们发现水文相似性的概念不一定是时不变的。相反，香农熵作为模拟系综多样性的衡量标准显示出明显的年度模式，其中有高度冗余的模拟周期，反映了连贯和有组织的动态，以及山坡以明显不同的方式运行的周期。我们的结论是，所提出的方法提供了一个强大的框架，用于理解和诊断水文系统的过程组织和功能相似性如何以及何时出现。我们的方法既不限于模型，也不限于模型目标或我们在本研究中选择的数据源。总的来说，我们认为水文系统的概念相似（从而产生冗余）或显示独特的功能（因此不可替代）并不相互排斥。它们实际上是互补的，系统的运行是随着时间的推移逐渐转变为不同层次的组织。
Abstract. The increasing diversity and resolution of spatially distributed data on terrestrial systems greatly enhance the potential of hydrological modeling. Optimal and parsimonious use of these data sources requires, however, that we better understand (a) which system characteristics exert primary controls on hydrological dynamics and (b) to what level of detail do those characteristics need to be represented in a model. In this study we develop and test an approach to explore these questions that draws upon information theoretic and thermodynamic reasoning, using spatially distributed topographic information as a straightforward example. Specifically, we subdivide a mesoscale catchment into 105 hillslopes and represent each by a two-dimensional numerical hillslope model. These hillslope models differ exclusively with respect to topography-related parameters derived from a digital elevation model (DEM); the remaining setup and meteorological forcing for each are identical. We analyze the degree of similarity of simulated discharge and storage among the hillslopes as a function of time by examining the Shannon information entropy. We furthermore derive a “compressed” catchment model by clustering the hillslope models into functional groups of similar runoff generation using normalized mutual information (NMI) as a distance measure. Our results reveal that, within our given model environment, only a portion of the entire amount of topographic information stored within a digital elevation model is relevant for the simulation of distributed runoff and storage dynamics. This manifests through a possible compression of the model ensemble from the entire set of 105 hillslopes to only 6 hillslopes, each representing a different functional group, which leads to no substantial loss in model performance. Importantly, we find that the concept of hydrological similarity is not necessarily time invariant. On the contrary, the Shannon entropy as measure for diversity in the simulation ensemble shows a distinct annual pattern, with periods of highly redundant simulations, reflecting coherent and organized dynamics, and periods where hillslopes operate in distinctly different ways. We conclude that the proposed approach provides a powerful framework for understanding and diagnosing how and when process organization and functional similarity of hydrological systems emerge in time. Our approach is neither restricted to the model nor to model targets or the data source we selected in this study. Overall, we propose that the concepts of hydrological systems acting similarly (and thus giving rise to redundancy) or displaying unique functionality (and thus being irreplaceable) are not mutually exclusive. They are in fact of complementary nature, and systems operate by gradually changing to different levels of organization in time.