Addressing ten questions about conceptual rainfall–runoff models with global sensitivity analyses in R

By Mun-Ju Shin, Joseph H. A. Guillaume, Barry F. W. Croke, Anthony J. Jakeman. 2013

183 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/54697bc6d909e22aa4b3b712fadb39a1318121c2

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In Civil and Structural Engineering

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Citations in the corpus

The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020, unknown): “The outcome of these methods is ‘sensitive ’ to these choices, among which the sensitivity to perturbation size is generally overlooked even though it can be profound (Shin et al., 2013; Haghnegahdar and Razavi, 2017).”
Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices (2017, methodology): “This observation is indeed supported in investigations focusing on one discipline, such as hydrology (Shin et al., 2013).”
Global Sensitivity Analysis of environmental models: Convergence and validation (2016, background): “Shin et al. (2013) for example demonstrate the in ﬂ uence of some of these choices on GSA results.”
Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications (2015, methodology): “Therefore, SA should be implemented based on multi-objective functions or by combining single functions for different objectives, which can provide valuable and comprehensive insights into the parameters of hydrological models (Hill and Tiedeman, 2007; Foglia et al., 2009; Shin et al., 2013).”
Sensitivity analysis of environmental models: A systematic review with practical workflow (2014, methodology): “A number of studies demonstrate how different de ﬁ nitions of X , each considered equally plausible by the analyst, can dramatically change the values of sensitivity measures and therefore the conclusions drawn from GSA (e.g. Shin et al., 2013).”
Improvement of hydrological model calibration by selecting multiple parameter ranges (2016, unknown): “Shin et al. (2013) reported that reducing or extending ranges might render insensitive parameters into sensitive ones or vice versa.”