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- Title
Distribution‐Based Global Sensitivity Analysis in Hydrology.
- Authors
Ciriello, Valentina; Lauriola, Ilaria; Tartakovsky, Daniel M.
- Abstract
Global sensitivity analysis (GSA) is routinely used in academic setting to quantify the influence of input variability and uncertainty on predictions of a quantity of interest. Practical applications of GSA are hampered by its high computational cost, which arises from the need to run large (e.g., groundwater) models multiple times, and by its reliance on the analysis of variance, which formally requires input parameters to be uncorrelated. The former difficulty can be alleviated by replacing expensive models with inexpensive (e.g., polynomial) surrogates, while adoption of distribution‐based (rather than variance‐based) metrics can, in principle, overcome the latter but at significantly increased computational cost. To make use of distribution‐based GSA feasible for regional‐scale models with a large number of degrees of freedom, we supplement it with a surrogate model built with polynomial chaos expansions with analytically updated coefficients. We demonstrate the computational efficiency of our algorithm on a case study dealing with evaluation of the effects of temperature variability on annual evapotranspiration at the regional scale. Key Points: Surrogate models based on polynomial chaos accelerate moment‐independent GSAOur algorithm is used to identify impact of temperature variability on evapotranspirationOur spatial analysis of GSA metrics identifies possible climate change pathways
- Subjects
GLOBAL analysis (Mathematics); SENSITIVITY analysis; POLYNOMIAL chaos; DEGREES of freedom; ATMOSPHERIC models; HYDROLOGY; COEFFICIENTS (Statistics)
- Publication
Water Resources Research, 2019, Vol 55, Issue 11, p8708
- ISSN
0043-1397
- Publication type
Article
- DOI
10.1029/2019WR025844