Diagnosis of Model Errors With a Sliding Time‐Window Bayesian Analysis-Reference-Cited by-同舟云学术

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Diagnosis of Model Errors With a Sliding Time‐Window Bayesian Analysis

Published:2022-02 Issue:2 Volume:58 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Resources Research

Author:

Hsueh Han‐Fang¹²^ORCID,Guthke Anneli¹³^ORCID,Wöhling Thomas⁴⁵^ORCID,Nowak Wolfgang¹^ORCID

Affiliation:

1. Department of Stochastic Simulation and Safety Research for Hydrosystems (IWS/LS3) University of Stuttgart Stuttgart Germany

2. Center for Applied Geoscience University of Tübingen Tübingen Germany

3. Stuttgart Center for Simulation Science University of Stuttgart Stuttgart Germany

4. Department of Hydrology Technical University of Dresden Dresden Germany

5. Lincoln Environmental Research Lincoln Agritech Hamilton New Zealand

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021WR030590

Reference79 articles.

1. An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction

2. A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation

3. HESS Opinions "Crash tests for a standardized evaluation of hydrological models"

4. Automated Equilibrium Tension Lysimeters for Measuring Water Fluxes through a Layered, Volcanic Vadose Profile in New Zealand

5. Regionalisation of hydrological model parameters under parameter uncertainty: A case study involving TOPMODEL and basins across the globe

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