Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model

Farkhondeh Khorashadi Zadeh, Jiri Nossent, Fanny Sarrazin, Francesca Pianosi, Ann Van Griensven, Thorsten Wagener, Willy Bauwens

Research output: Contribution to journalArticle (Academic Journal)peer-review

53 Citations (Scopus)
556 Downloads (Pure)

Abstract

Global Sensitivity Analysis (GSA) is an essential technique to support the calibration of environmental models by identifying the influential parameters (screening) and ranking them. In this paper, the widely-used variance-based method (Sobol') and the recently proposed moment-independent PAWN method for GSA are applied to the Soil and Water Assessment Tool (SWAT), and compared in terms of ranking and screening results of 26 SWAT parameters. In order to set a threshold for parameter screening, we propose the use of a “dummy parameter”, which has no influence on the model output. The sensitivity index of the dummy parameter is calculated from sampled data, without changing the model equations. We find that Sobol' and PAWN identify the same 12 influential parameters but rank them differently, and discuss how this result may be related to the limitations of the Sobol' method when the output distribution is asymmetric.
Original languageEnglish
Pages (from-to)210-222
Number of pages13
JournalEnvironmental Modelling and Software
Volume91
Early online date17 Feb 2017
DOIs
Publication statusPublished - May 2017

Keywords

  • Global sensitivity analysis
  • Moment-independent method
  • Variance-based method
  • PAWN
  • Sobol'
  • SWAT

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