A hybrid time- and signature-domain Bayesian inference framework for calibration of hydrological models: a case study in the Ren River basin in China-Reference-Cited by-同舟云学术

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A hybrid time- and signature-domain Bayesian inference framework for calibration of hydrological models: a case study in the Ren River basin in China

Published:2022-08-04 Issue:1 Volume:37 Page:153-173
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

Liu Song,She Dunxian,Zhang Liping,Xia Jun

Funder

National Key Research and Development Program of China

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00477-022-02282-3.pdf

Reference67 articles.

1. Addor N, Nearing G, Prieto C, Newman AJ, Le Vine N, Clark MP (2018) A ranking of hydrological hignatures based on their predictability in space. Water Resour Res 54(11):8792–8812. https://doi.org/10.1029/2018wr022606

2. Albert C, Kunsch HR, Scheidegger A (2015) A simulated annealing approach to approximate Bayes computations. Stat Comput 25(6):1217–1232. https://doi.org/10.1007/s11222-014-9507-8

3. Baker DB, Richards RP, Loftus TT, Kramer JW (2004) A new flashiness index: characteristics and applications to midwestern rivers and streams. J Am Water Resour as 40(2):503–522. https://doi.org/10.1111/j.1752-1688.2004.tb01046.x

4. Barnes CP, Filippi S, Stumpf MPH, Thorne T (2012) Considerate approaches to constructing summary statistics for ABC model selection. Stat Comput 22(6):1181–1197. https://doi.org/10.1007/s11222-012-9335-7

5. Beaumont MA (2019) Approximate Bayesian computation. Annu Rev Stat Appl 6:379–403. https://doi.org/10.1146/annurev-statistics-030718-105212

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