Identification and Review of Sensitivity Analysis Methods

Abstract

Identification and qualitative comparison of sensitivity analysis methods that have been used across various disciplines, and that merit consideration for application to food-safety risk assessment models, are presented in this article. Sensitivity analysis can help in identifying critical control points, prioritizing additional data collection or research, and verifying and validating a model. Ten sensitivity analysis methods, including four mathematical methods, five statistical methods, and one graphical method, are identified. The selected methods are compared on the basis of their applicability to different types of models, computational issues such as initial data requirement and complexity of their application, representation of the sensitivity, and the specific uses of these methods. Applications of these methods are illustrated with examples from various fields. No one method is clearly best for food-safety risk models. In general, use of two or more methods, preferably with dissimilar theoretical foundations, may be needed to increase confidence in the ranking of key inputs.

Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework

“…Numerous approaches that explore uncertainty in numerical models have been developed in the literature of statistics (Christopher Frey and Patil, 2002), environmental modeling (Matott et al, 2009), and optimization/calibration of hydrology and earth systems models (Beven and Binley, 1992;Duan et al, 1992;Kavetski et al, 2002Kavetski et al, , 2006aKuczera et al, 2010;Razavi and Gupta, 2015;Song et al, 2015;Vrugt et al, 2009Vrugt et al, , 2008. Among these, global sensitivity analysis is an elegant platform for testing the impact of input uncertainty on model outputs and for ranking the relative importance of inputs while considering coexisting sources of uncertainty.…”

Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications

“…Therefore, when we estimate the model parameters, unimportant or insensitive parameters should be locked at a fixed value to facilitate more efficient calibration (SA). At present, various SA methods (e.g., local or global methods, qualitative or quantitative methods, and screening or refined methods) are used widely in different fields, such as complex engineering systems, economics, physics, and the social sciences (Frey and Patil, 2002;Iman and Helton, 1988). However, there are large differences among these methods in terms of their sampling schemes, applicability, algorithm structures, and the importance measures used for the parameters.…”

“…Many reviews of SA methods have been conducted in different fields. In particular, Hamby (1994) reviewed the literature on parameter SA for environmental models; Frey and Patil (2002) and Mokhtari and Frey (2005) reviewed the SA methods used for food safety; Coyle et al (2003) discussed the SA measures employed in the field of economics; Saltelli et al (2005Saltelli et al ( , 2012 focused on SA in chemical models; Borgonovo (2007) investigated sensitivity and uncertainty measures; Mishra et al (2009) reviewed the global SA methods used in groundwater models; Peter and Dwight (2010) discussed numerical SA approaches for aerodynamic optimization; Perz et al (2013) reviewed the global SA and UA methods applied to ecological resilience; Tian (2013) summarized the application of SA methods to building energy analysis; and Wu et al (2013) review recent advances in SA for infectious disease models. Some of these reviews explicitly highlighted the advantages and disadvantages of various methods and they provided very good summaries of these topics.…”

“…The systematic investigation of the model responses to either perturbations of the model quantitative factors or variations in the model qualitative factors U.S. EPA (2001) Environmental models Sensitivity refers to the variation in output of a model with respect to changes in the values of the model's inputs, and SA attempts to provide a ranking of the model inputs based on their relative contributions to model output variability and uncertainty Frey and Patil (2002) Food-safety risk assessment models…”

Regional analysis of parameter sensitivity for simulation of streamflow and hydrological fingerprints

“…In recent decades, the method has been used and evaluated in a variety of fields such as hydrogeology (Fontaine et al, 1992), atmospheric sciences (Rodríguez-Camino and Avissar, 1998), geologic nuclear waste disposal modelling (Lu and Mohanty, 2001), food safety risk assessment (Frey and Patil, 2002), or ecologic forestry (Song et al, 2013). A number of studies treat the application of FAST in hydrological modelling Sanadhya et al, 2013;Guse et al, 2014;Pfannerstill et al, 2015;Guse et al, 2016a, b).…”