Increasing parameter identifiability through clustered time-varying sensitivity analysis-Reference-Cited by-同舟云学术

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Increasing parameter identifiability through clustered time-varying sensitivity analysis

Published:2024-10 Issue: Volume:181 Page:106189
ISSN:1364-8152
Container-title:Environmental Modelling & Software
language:en
Short-container-title:Environmental Modelling & Software

Author:

Wang Lu,Xu Yue-Ping,Xu Jiliang,Gu Haiting,Bai Zhixu,Zhou Peng,Yu Hongjie,Guo Yuxue

Funder

Shanxi Provincial Key Research and Development Project

National Natural Science Foundation of China

Key Research and Development Program of Zhejiang Province

National Key Research and Development Program of China

Publisher

Elsevier BV

Reference88 articles.

1. Sensitivity and uncertainty analysis of the conceptual HBV rainfall-runoff model: implications for parameter estimation;Abebe;J. Hydrol.,2010

2. Sensitivity analysis of data-driven groundwater forecasts to hydroclimatic controls in irrigated croplands;Amaranto;J. Hydrol.,2020

3. Sampling methods and sensitivity analysis for large parameter sets;Andres;J. Stat. Compute. Sim.,1997

4. Hydrological processes and model representation: impact of soft data on calibration;Arnold;Transactions of the ASABE,2015

5. Improved covariance estimation for Gustafson-Kessel clustering;Babuška;Fuzzy Syst. Conf.,2002

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