On characterizing the temporal dominance patterns of model parameters and processes
On characterizing the temporal dominance patterns of model parameters and processes
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DOI：
10.1002/hyp.10764
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发表时间：
2016-06
影响因子：
3.2
通讯作者：
B. Guse;M. Pfannerstill;M. Strauch;D. Reusser;S. Lüdtke;M. Volk;H. Gupta;N. Fohrer
中科院分区：
文献类型：
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作者：
B. Guse;M. Pfannerstill;M. Strauch;D. Reusser;S. Lüdtke;M. Volk;H. Gupta;N. Fohrer
水文模型的诊断分析旨在提高对过程及其动态如何在模型中表示的理解。时间模式的参数优势，可以精确地与时间分辨的参数敏感性分析。以这种方式，放电条件的特点，导致在模型中的参数优势。为了实现这一点，通过在不同聚合水平的三层框架中包括额外的信息来增强参数敏感性的时间动态分析。首先，参数敏感性的时间动态提供其敏感性的每日时间序列，以检测模型参数的主导变化。其次，每日敏感性与流量历时曲线（FDC）有关，以强调模型参数对特定流量量级的高敏感性。第三，参数敏感性每月平均分别为FDC的五个部分，以检测不同的放电量级的参数优势的典型模式。这三个有条理的步骤应用于两个对比流域（高地和低地集水区），以演示参数动态的时间模式如何代表不同的水文制度。在低地流域的流量动态控制的地下水参数的所有排放量。相比之下，不同的过程是相关的高地流域，因为在高地流域的快速和缓慢的径流分量的参数的优势是在一年中的不同流量大小的变化。这三个诊断步骤的联合解释提供了更深入的了解模型参数如何代表水文动态模型中不同的流量大小。因此，这种诊断框架导致更好地表征模型参数及其时间动态，并有助于了解水文模型中的过程行为。版权所有© 2015约翰威利父子有限公司.
Diagnostic analyses of hydrological models intend to improve the understanding of how processes and their dynamics are represented in models. Temporal patterns of parameter dominance could be precisely characterized with a temporally resolved parameter sensitivity analysis. In this way, the discharge conditions are characterized, that lead to a parameter dominance in the model. To achieve this, the analysis of temporal dynamics in parameter sensitivity is enhanced by including additional information in a three‐tiered framework on different aggregation levels. Firstly, temporal dynamics of parameter sensitivity provide daily time series of their sensitivities to detect variations in the dominance of model parameters. Secondly, the daily sensitivities are related to the flow duration curve (FDC) to emphasize high sensitivities of model parameters in relation to specific discharge magnitudes. Thirdly, parameter sensitivities are monthly averaged separately for five segments of the FDC to detect typical patterns of parameter dominances for different discharge magnitudes. The three methodical steps are applied on two contrasting catchments (upland and lowland catchment) to demonstrate how the temporal patterns of parameter dynamics represent different hydrological regimes. The discharge dynamic in the lowland catchment is controlled by groundwater parameters for all discharge magnitudes. In contrast, different processes are relevant in the upland catchment, because the dominances of parameters from fast and slow runoff components in the upland catchment are changing over the year for the different discharge magnitudes. The joined interpretation of these three diagnostic steps provides deeper insights of how model parameters represent hydrological dynamics in models for different discharge magnitudes. Thus, this diagnostic framework leads to a better characterization of model parameters and their temporal dynamics and helps to understand the process behaviour in hydrological models. Copyright © 2015 John Wiley & Sons, Ltd.