A comparison of sensitivity analysis and error analysis based on a stream ecosystem model

Gardner, Robert H.; O’Neill, Robert V.; Mankin, J.B.; Carney, J.H.

doi:10.1016/0304-3800(81)90056-9

Cited by 153 publications

(66 citation statements)

References 4 publications

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“…Methods in the literature range from solving simple partial derivatives to spatial and temporal sensitivity analyses (Morisawa and Inoue, 1974;Atherton et al, 1975;Dickinson and Gelinas, 1976;Koda et al, 1979;Dunker, 1981;Gardner et al, 1981;Summers and McKellar, 1981;Koda, 1982;Helton et al, 1985;Iman and Helton, 1985;Helton et al, 1986;Iman and Helton, 1988;Helton et al, 1991;Zimmerman et al, 1991). A sensitivity coefficient is basically the ratio of the change in output to the change in input while all other parameters remain constant (Kfieger et al, 1977).…”

Section: Differential Sensitivity Analysismentioning

confidence: 99%

“…Inherent to this calculation are the assumptions that the higher ordered partials are negligible and there is no correlation between input parameters (Atherton et al, 1975;Gardner et al, 1981). For large sets of equations, the partial derivative can be approximated as a finite difference and output values calculated for small changes in the input parameter (Downing et al, 1985).…”

Section: ¢~-Oximentioning

confidence: 99%

“…For large sets of equations, the partial derivative can be approximated as a finite difference and output values calculated for small changes in the input parameter (Downing et al, 1985). Thus, if nonlinearities are neglected, the partial derivative can be approximated as, %AY ¢i-%AXi Gardner et al (1981) report that the partial derivative approach to sensitivity analysis may become so complex that implementation is impractical. Also, since this approach is only valid for small changes in parameter values, when parameter variability is allowed to take on 'realistic' values, the direct approach is seriously violated (Gardner et al, 1981).…”

Section: ¢~-Oximentioning

confidence: 99%

“…Thus, if nonlinearities are neglected, the partial derivative can be approximated as, %AY ¢i-%AXi Gardner et al (1981) report that the partial derivative approach to sensitivity analysis may become so complex that implementation is impractical. Also, since this approach is only valid for small changes in parameter values, when parameter variability is allowed to take on 'realistic' values, the direct approach is seriously violated (Gardner et al, 1981). The differential analysis is typically much more demanding to implement than other sensitivity methods and yet provides only comparable results.…”

Section: ¢~-Oximentioning

confidence: 99%

“…More than a dozen methods have been reviewed (Bellman and Asrrom, 1970;Cukier et al, 1973;Morisawa and Inoue, 1974;Kfieger et al, 1977;Box et al, 1978;Oblow, 1978;Conover, 1980;Demiralp and Rabitz, 1981;Gardner et al, 1981;Iman et al, 1981b;Hoffman and Gardner, 1983;Downing et al, 1985;Helton et al, 1985;Crick et aL, 1987;IAEA, 1989;Iman and Helton, 1991;Hamby, 1993). This paper is a comprehensive assessment of several of the more practical methods for conducting parameter sensitivity studies, ranging from one-at-a-time sensitivity measures to standardized regression coefficients to statistical tests based on partitioning of empirical input distributions.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A review of techniques for parameter sensitivity analysis of environmental models

Hamby

1994

Environ Monit Assess

1,563

852

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Abstract. Mathematical models are utilized to approximate various highly complex engineering, physical, environmental, social, and economic phenomena. Model parameters exerting the most influence on model results are identified through a 'sensitivity analysis'. A comprehensive review is presented of more than a dozen sensitivity analysis methods. This review is intended for those not intimately familiar with statistics or the techniques utilized for sensitivity analysis of computer models. The most fundamental of sensitivity techniques utilizes partial differentiation whereas the simplest approach requires varying parameter values one-at-a-time. Correlation analysis is used to determine relationships between independent and dependent variables. Regression analysis provides the most comprehensive sensitivity measure and is commonly utilized to build response surfaces that approximate complex models.

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Section: Differential Sensitivity Analysismentioning

confidence: 99%

Section: ¢~-Oximentioning

confidence: 99%

Section: ¢~-Oximentioning

confidence: 99%

Section: ¢~-Oximentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A review of techniques for parameter sensitivity analysis of environmental models

Hamby

1994

Environ Monit Assess

1,563

852

View full text Add to dashboard Cite

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Modellierung der Wirkung von Chemikalien auf aquatische Ökosysteme (Fließ‐ und Stillgewässer)

Poethke

Hommen

2004

Handbuch Der Umweltwissenschaften

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Modeling dynamics of native and invasive species to guide prioritization of management actions

et al. 2017

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Abstract. Action to achieve biodiversity conservation is usually expensive, and resources are limited relative to conservation goals. Prioritizing management investment therefore is essential if important goals are to be achieved. New software, the "Islands DSS," has been developed to prioritize the mix of management actions that will optimally mitigate biodiversity loss. Here, we present novel temporally dynamic models of species population growth, interaction, and management efficacy that have been incorporated into the software. We have analyzed the sensitivity of these models to uncertainty in four parameters: maximum rate of population growth (r max ), coefficient of species interaction (a ij ), quantity of food resources required to maintain species equilibrium (J i ), and the coefficient of management efficacy (h i ). We focused on the projected abundance of species by simulating interactions among one to four species, both invasive and native, on a hypothetical arid-tropical island that is 1000 ha in size and consists of five evenly distributed habitat types. Sensitivity analysis revealed significant variation in species abundance due to uncertainty in r max (coefficient = 51.34; P < 0.001) and a ij (N i = À16.48; P = 0.43; N j = À2.33 2 ; P = 2.00 À16 ), a significant but potentially stabilizing effect of modeling multiple species simultaneously (coefficient = À65.80; P = 2.00 À16 ), and mirroring by species response trajectories of threat mitigation trajectories. There are several benefits of using temporally dynamic models of species responses to threat mitigation in systematic conservation planning including increased accuracy in estimates of the cost of management; locally relevant understanding of lag-times between threat establishment and unacceptable impacts on valued species; understanding of threat abundance and required intensity of control for biodiversity features to persist; site-and species-specific understanding of time to eradication and threat recovery when management is interrupted; and an improved understanding of the opportunity cost, in terms of threat levels and responses of native species, for islands not selected for management. Our models and associated software are based on decades of ecological research, potentially useful in a wide range of situations, including islands, the mainland, and marine regions, and we suggest that they provide managers with novel and powerful tools to efficiently prioritize conservation actions via the new systematic conservation planning software, "Islands DSS."

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A comparison of sensitivity analysis and error analysis based on a stream ecosystem model

Cited by 153 publications

References 4 publications

A review of techniques for parameter sensitivity analysis of environmental models

A review of techniques for parameter sensitivity analysis of environmental models

Modellierung der Wirkung von Chemikalien auf aquatische Ökosysteme (Fließ‐ und Stillgewässer)

Modeling dynamics of native and invasive species to guide prioritization of management actions

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