Publication Date:
2015-12-16
Description:
Based on the theoretical framework for sensitivity analysis called “ Variogram Analysis of Response Surfaces ” (VARS), developed in Part I, we develop and implement a practical “ star-based ” sampling strategy (called STAR-VARS), for the application of VARS to real-world problems. We further develop a bootstrap approach to provide confidence level estimates for the VARS sensitivity measures and to evaluate the reliability of inferred factor rankings. The effectiveness, efficiency, and robustness of the new approach are demonstrated via two real-data hydrological case studies (a 5-parameter conceptual rainfall-runoff model and a 45-parameter land surface scheme hydrology model), and a comparison with the “derivative-based” Morris and “variance-based” Sobol approaches are provided. Our results show that STAR-VARS provides reliable and stable assessments of “global” sensitivity across the full range of scales in the factor space, while being 1-2 orders of magnitude more efficient than Morris or Sobol. This article is protected by copyright. All rights reserved.
Print ISSN:
0043-1397
Electronic ISSN:
1944-7973
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
