Identification of Dominant Hydrological Mechanisms Using Bayesian Inference, Multiple Statistical Hypothesis Testing, and Flexible Models-Reference-Cited by-同舟云学术

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Identification of Dominant Hydrological Mechanisms Using Bayesian Inference, Multiple Statistical Hypothesis Testing, and Flexible Models

Published:2021-08 Issue:8 Volume:57 Page:
ISSN:0043-1397
Container-title:Water Resources Research
language:en
Short-container-title:Water Res

Author:

Prieto Cristina¹²³^ORCID,Kavetski Dmitri⁴^ORCID,Le Vine Nataliya³⁵^ORCID,Álvarez César¹^ORCID,Medina Raúl¹^ORCID

Affiliation:

1. IHCantabria – Instituto de Hidráulica Ambiental de la Universidad de Cantabria Santander Spain

2. Eawag Swiss Federal Institute of Aquatic Science and Technology Dübendorf Switzerland

3. Department of Civil and Environmental Engineering Imperial College London London UK

4. School of Civil, Environmental and Mining Engineering University of Adelaide Adelaide SA Australia

5. Swiss Re Armonk NY USA

Publisher

American Geophysical Union (AGU)

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020WR028338

Reference117 articles.

1. Legacy, Rather Than Adequacy, Drives the Selection of Hydrological Models

2. A Ranking of Hydrological Signatures Based on Their Predictability in Space

3. A new look at the statistical model identification

4. The impacts of climate change on river ﬂood risk at the global scale;Arnell N. W.;Climatic Change,2014

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3. How do hydrologists perceive watersheds? A survey and analysis of perceptual model figures for experimental watersheds;Hydrological Processes;2023-03

4. A Review on the Development of Two-Way Coupled Atmospheric-Hydrological Models;Sustainability;2023-02-03

5. Improving structure identifiability of hydrological processes by temporal sensitivity with a flexible modeling framework;Journal of Hydrology;2023-01

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