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Title: Practical Use of Computationally Frugal Model Analysis Methods

Computationally frugal methods of model analysis can provide substantial benefits when developing models of groundwater and other environmental systems. Model analysis includes ways to evaluate model adequacy and to perform sensitivity and uncertainty analysis. Frugal methods typically require 10s of parallelizable model runs; their convenience allows for other uses of the computational effort. We suggest that model analysis be posed as a set of questions used to organize methods that range from frugal to expensive (requiring 10,000 model runs or more). This encourages focus on method utility, even when methods have starkly different theoretical backgrounds. We note that many frugal methods are more useful when unrealistic process-model nonlinearities are reduced. Inexpensive diagnostics are identified for determining when frugal methods are advantageous. Examples from the literature are used to demonstrate local methods and the diagnostics. We suggest that the greater use of computationally frugal model analysis methods would allow questions such as those posed in this work to be addressed more routinely, allowing the environmental sciences community to obtain greater scientific insight from the many ongoing and future modeling efforts
 [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6] ;  [7] ;  [8]
  1. U.S. Geological Survey, Boulder, CO (United States); Univ. of Kansas, Lawrence, KS (United States)
  2. Univ. of Adelaide, SA (Australia)
  3. National Center for Atmospheric Research, Boulder, CO (United States)
  4. Florida State Univ., Tallahassee, FL (United States)
  5. Colorado State Univ., Fort Collins, CO (United States)
  6. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  7. Univ. of Darmstadt (Germany)
  8. California State Univ. (CalState), Chico, CA (United States)
Publication Date:
Grant/Contract Number:
AC05-00OR22725; SC0008272; 0911074; 21-66885
Accepted Manuscript
Journal Name:
Ground Water
Additional Journal Information:
Journal Volume: 54; Journal Issue: 2; Journal ID: ISSN 0017-467X
Wiley - NGWA
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Laboratory Directed Research and Development (LDRD) Program
Country of Publication:
United States
97 MATHEMATICS AND COMPUTING; 54 ENVIRONMENTAL SCIENCES; Model calibration; Sensitivity analysis; Uncertainty; Bayesian; regression; transparency; falsifiability
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1400448