Variance-based global sensitivity analysis for multiple scenarios and models with implementation using sparse grid collocation

Author:

Dai Heng,Ye Ming

Funder

DOE Early Career Award

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference105 articles.

1. An integrated hydrologic Bayesian multimodel combination framework: confronting input, parameter, and model structural uncertainty in hydrologic prediction;Ajami;Water Resour. Res.,2007

2. Aziz, C.E., Newell, C.J., Gonzales, J.R., Haas, P.E., Clement, T.P., Sun, Y., 2000. BIOCHLOR Natural Attenuation Decision Support System: User’s Manual, Version 1.0. U.S. EPA Office of Research and Development, Washington, DC.

3. A general probabilistic framework for uncertainty and global sensitivity analysis of deterministic models: a hydrological case study;Baroni;Environ. Modell. Softw.,2014

4. High dimensional polynomial interpolation on sparse grid;Barthelmann;Adv. Comput. Math.,1999

5. Towards a coherent philosophy for modeling the environment;Beven;Proc. Roy. Soc. Lond. Ser. A Math. Phys. Eng. Sci.,2002

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