Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2021WR030660 |
Inference of parameters for a global hydrological model: Identifiability and predictive uncertainties of climate-based parameters | |
T. Yoshida; N. Hanasaki; K. Nishina; J. Boulange; M. Okada; P. A. Troch | |
2022-01-31 | |
发表期刊 | Water Resources Research
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出版年 | 2022 |
英文摘要 | Calibration of global hydrological models (GHMs) has been attempted for over two decades; however, an effective and generic calibration method has not been explored. We present a novel framework for calibrating GHMs assuming that parameters can be regionalized by climate similarities. We calibrated four sensitive parameters of the H08 global hydrological model by aggregating the results of 5000 simulations with randomly generated parameters into 11 Köppen climate classes and using an objective function Nash–Sutcliffe Efficiency (NSE) with random sampling from the proposed parameter distribution. From a 100-fold split-sampling test, we found that both the representativeness and robustness of the transferred parameter sets were guaranteed when the upper 5% of the samples were accepted and assign the median of each accepted parameter distribution for the climate class. The simulation with the climate-based parameters yielded satisfactory (NSE > 0.0) and good (NSE > 0.5) performances at 480 and 234 stations (61.7% and 30.1% of 777 stations), respectively. The storage capacity (SD) and the conductive coefficient (CD) were sensitive to the climate classes and exhibited well-constrained distributions of the accepted samples, whereas the recession parameters for the subsurface storage (γ and τ) showed little or no explanatory power to climate. The identified parameters for climate classes exhibited consistency with the physical interpretation of soil formation and efficiencies in vapor transfer. The consistency of the identified parameter values with physical underpinnings indicates that the appropriate parameters were determined, which ensured the robustness of parameters, especially when they are transferred to ungauged watersheds. This article is protected by copyright. All rights reserved. |
领域 | 资源环境 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/346135 |
专题 | 资源环境科学 |
推荐引用方式 GB/T 7714 | T. Yoshida,N. Hanasaki,K. Nishina,et al. Inference of parameters for a global hydrological model: Identifiability and predictive uncertainties of climate-based parameters[J]. Water Resources Research,2022. |
APA | T. Yoshida,N. Hanasaki,K. Nishina,J. Boulange,M. Okada,&P. A. Troch.(2022).Inference of parameters for a global hydrological model: Identifiability and predictive uncertainties of climate-based parameters.Water Resources Research. |
MLA | T. Yoshida,et al."Inference of parameters for a global hydrological model: Identifiability and predictive uncertainties of climate-based parameters".Water Resources Research (2022). |
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