Moment-independent regional sensitivity analysis: Application to an environmental model

Environmental Modelling and Software

Volumn 47, Issue , 2013, Pages 55-63

  Wei, Pengfei ^a   Lu, Zhenzhou ^a   Wu, Danqing ^a   Zhou, Changcong ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

Contribution to delta indices plot; Delta ratio function; Level E model; Moment independent; Uncertainty reduction

Indexed keywords

CONTRIBUTION TO DELTA INDICES PLOT; E-MODEL; ENVIRONMENTAL MODEL; ENVIRONMENTAL SCIENCE; GLOBAL SENSITIVITY ANALYSIS; MOMENT INDEPENDENTS; SENSITIVITY ANALYSIS TECHNIQUES; UNCERTAINTY REDUCTION;

PROBABILITY DENSITY FUNCTION; UNCERTAINTY ANALYSIS;

SENSITIVITY ANALYSIS;

ENVIRONMENTAL MODELING; MODEL TEST; NUMERICAL MODEL; PROBABILITY DENSITY FUNCTION; SENSITIVITY ANALYSIS; UNCERTAINTY ANALYSIS;

COCKSFOOT STREAK VIRUS;

EID: 84879290206     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2013.05.003     Document Type: Article

References (32)

1. Bolado-Lavin R., Castaings W., Tarantola S. Contribution to the sample mean plot for graphical and numerical sensitivity analysis. Reliab. Eng. Syst. Saf. 2009, 94:1041-1049.
2. Borgonovo E. Measuring uncertainty importance: investigation and comparison of alternative approach. Risk Anal. 2006, 26:1349-1361.
3. Borgonovo E. Anew uncertainty importance measure. Reliab. Eng. Syst. Saf. 2007, 92:771-784.
4. Borgonovo E., Castaings W., Tarantola S. Moment independent importance measures: new results and analytical test cases. Risk Anal. 2011, 31:404-428.
5. Borgonovo E., Castings W., Tarantola S. Model emulation and moment-independent sensitivity analysis: an application to environment modeling. Environ. Modell. Softw. 2012, 34:105-115.
6. Botev Z.I., JGrotowski L.F., Kroese D.P. Kernel density estimation via diffusion. Ann. Statist. 2010, 38:2916-2957.
7. Chun M.H., Han S.J., Tak N.-I.L. An uncertainty importance measure using a distance metric for the change in a cumulative distribution function. Reliab. Eng. Syst. Saf. 2000, 70:313-321.
8. Dimov I., Georgieva R., Ostromsky Tz Monte Carlo simulation sensitivity analysis of an Eulerian large-scale air pollution model. Reliab. Eng. Syst. Saf. 2012, 107:23-28.
9. Draper D., Pereira A., Prado P., Saltelli A., Cheal R., Eguilior S., Mendes B., Tarantola S. Scenario and parametric uncertainty in GESAMAC" A methodological study in nuclear waste disposal risk assessment. Comput. Phys. Commun. 1999, 117:142-155.
10. Estrada V., Diaz M.S. Global sensitivity analysis in the development of the first principle-based eutrophication models. Environ. Modell. Softw. 2010, 25:1539-1551.
11. Genest C., Favre A.C. Everything you always wanted to know about copula modeling but were afraid to ask. J.Hydrol. Eng. 2007, 12:347-368.
12. Homma T., Saltelli A. Importance measures in global sensitivity analysis of nonlinear models. Reliab. Eng. Syst. Saf. 1996, 52:1-17.
13. Ishigmi T., Homma T. An importance quantification technique in uncertainty analysts for computer modes. Proceedings of the ISUMA'90: First International Symposium on Uncertainty Modeling and Analysis 1990, 398-403.
14. Liu Q., Homma T. Anew computational method of a moment-independent uncertainty importance measure. Reliab. Eng. Syst. Saf. 2009, 94:1205-1211.
15. Liu Q., Homma T. Anew importance measure for sensitivity analysis. J.Nucl. Sci. Technol. 2010, 47:53-61.
16. Nelsen R.B. An Introduction to Copulas 2006, Springer, New York. second ed.
17. Pastres R., Chart K., Solidoro C., Dejak C. Global sensitivity analysis of a shallow-water 3D eutrophication model. Comput. Phys. Commun. 1999, 117:62-74.
18. Plischke E., Borgonovo E., Smith C.L. Global sensitivity measures from given data. Eur. J. Oper. Res. 2013, 226:536-550.
19. Qu L.M., Yin W. Copula density estimation by total variation penalized likelihood with linear equality constraints. Comput. Stat. Data Anal. 2012, 56:384-398.
20. Ratto M., Pagano A., Young P.C. State dependent parameter metamodelling and sensitivity analysis. Comput. Phys. Commun. 2007, 177:863-876.
21. Ratto M., Pagano A., Young P.C. Non-parametric estimation of conditional moments for sensitivity analysis. Reliab. Eng. Syst. Saf. 2009, 94:237-243.
22. Saltelli A., Tarantola S. On the relative importance of input factors in mathematical models. J.Amer. Statist. Assoc. 2002, 97:702-709.
23. Saltelli A. Sensitivity analysis for importance assessment. Risk Anal. 2002, 22:579-590.
24. Saltelli A., Tarantola S., Campolongo F., Ratto M. Sensitivity Analysis in Practice: a Guide to Assessing Scientific Models 2004, Wiley, New York.
25. Sobol I.M. Sensitivity analysis for non-linear mathematical models. Mat. Model. Comp. Exp. 1993, 1:407-414.
26. Sobol I.M., Kucherenko S. Derivative based global sensitivity measures and their link with global sensitivity indices. Math. Comput. Simul. 2009, 79:3009-3017.
27. Tarantola S., Gatelli D., Mara T.A. Random balance designs for the estimation of the first order global sensitivity indices. Reliab. Eng. Syst. Saf. 2006, 91:717-727.
28. Tarantola S., Kopustinskas V., Bolado-Lavin R., Kaliatka A., Uspuras E., Vaisnoras M. Sensitivity analysis using contribution to sample variance plot: application to a water hammer model. Reliab. Eng. Syst. Saf. 2012, 99:62-73.
29. Vezzaro L., Mikkelsen P.S. Application of global sensitivity analysis and uncertainty quantification in dynamic modelling of micropollutants in stormwater runoff. Environ. Modell. Softw. 2012, 27-28:40-51.
30. Wei P., Lu Z., Hao W., Feng J., Wang B. Efficient sampling methods for global reliability sensitivity analysis. Comput. Phys. Commun. 2012, 183:1728-1743.
31. Wei P., Lu Z., Yuan X. Monte Carlo simulation for moment-independent sensitivity analysis. Reliab. Eng. Syst. Saf. 2013, 110:60-67.
32. Zhan C., Song X., Xia J., Tong C. An efficient integrated approach for global sensitivity analysis of hydrological model parameters. Environ. Modell. Softw. 2013, 41:39-52.