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DOI10.1029/2020WR028511
Temporal scale-dependent sensitivity analysis for hydrological model parameters using the discrete wavelet transform and active subspaces
Daniel Bittner; Michael Engel; Barbara Wohlmuth; David Labat; Gabriele Chiogna
2021-10-11
发表期刊Water Resources Research
出版年2021
英文摘要

Global sensitivity analysis is an important step in the process of developing and analyzing hydrological models. Measured data of different variables are used to identify the number of sensitive model parameters and to better constrain the model output. However, data scarcity is a common issue in hydrology. Since in hydrology we are dealing with multi-scale time dependent problems, we want to overcome that issue by exploiting the potential of using the decomposed wavelet temporal scales of the discharge signal for the identification of sensitive model parameters. In the proposed methodology, we coupled the discrete wavelet transform with a technique for model parameter dimension reduction, i.e. the active subspace method. We apply the proposed methodology to the LuKARS model, a lumped karst aquifer model for the Kerschbaum spring in Waidhofen/Ybbs (Austria). Our results demonstrate that the temporal scale dependency of hydrological processes affects the structure and dimension of the active subspaces. The results reveal that the dimensionality of an active subspace increases with the increasing number of hydrologic processes affecting a temporal scale. As a consequence, different parameters are sensitive on different temporal scales. Finally, we show that the total number of sensitive parameters identified at different temporal scales is larger than the number of sensitive parameters obtained using the complete spring discharge signal. Hence, instead of using multiple time series to determine the number of sensitive parameters, we can also obtain more information about parameter sensitivities from one single, decomposed time series.

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文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/339925
专题资源环境科学
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Daniel Bittner,Michael Engel,Barbara Wohlmuth,et al. Temporal scale-dependent sensitivity analysis for hydrological model parameters using the discrete wavelet transform and active subspaces[J]. Water Resources Research,2021.
APA Daniel Bittner,Michael Engel,Barbara Wohlmuth,David Labat,&Gabriele Chiogna.(2021).Temporal scale-dependent sensitivity analysis for hydrological model parameters using the discrete wavelet transform and active subspaces.Water Resources Research.
MLA Daniel Bittner,et al."Temporal scale-dependent sensitivity analysis for hydrological model parameters using the discrete wavelet transform and active subspaces".Water Resources Research (2021).
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