Abstract
The PAWN index is gaining traction among the modelling community as a sensitivity measure. However, the robustness to its design parameters has not yet been scrutinized: the size (N) and sampling (ε) of the model output, the number of conditioning intervals (n) or the summary statistic (θ). Here we fill this gap by running a sensitivity analysis of a PAWN-based sensitivity analysis. We compare the results with the design uncertainties of the Sobol’ total-order index (STi∗). Unlike in STi∗, the design uncertainties in PAWN create non-negligible chances of producing biased results when ranking or screening inputs. The dependence of PAWN upon (N,n,ε,θ) is difficult to tame, as these parameters interact with one another. Even in an ideal setting in which the optimum choice for (N,n,ε,θ) is known in advance, PAWN might not allow to distinguish an influential, non-additive model input from a truly non-influential model input.
Original language | English |
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Article number | 104679 |
Journal | Environmental Modelling and Software |
Volume | 127 |
DOIs | |
Publication status | Published - May 2020 |
Bibliographical note
Funding Information:We thank Francesca Pianosi, Razi Sheikholeslami, Thorsten Wagener and two anonymous reviewers for their constructive comments on previous versions of this manuscript. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 792178 (A.P.).
Publisher Copyright:
© 2020 The Authors
Keywords
- Environmental modelling
- Risk
- Statistics
- Uncertainty
ASJC Scopus subject areas
- Software
- Environmental Engineering
- Ecological Modelling