Fractal domain refinement of models simulating hydrological time series

Habib, Abrar; Butler, Adrian P.; Bloomfield, John P. ORCID: https://orcid.org/0000-0002-5730-1723; Sorensen, James P.R.. 2022 Fractal domain refinement of models simulating hydrological time series. Hydrological Sciences Journal, 67 (9). 1342-1355. https://doi.org/10.1080/02626667.2022.2084342

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Abstract/Summary

Fractal analysis of a time series provides information on how the series varies across all (possible) temporal scales with respect to a given statistical measure. Dynamic hydrological models are typically optimized/calibrated using performance criteria defined in the time domain; however, the performance of models in simulating the fluctuation structure of a time series is seldom investigated. We use a multi-objective pattern search algorithm to calibrate a combined 15-minute resolution recharge–groundwater flow model. The non-dominated simulations of the model are then analysed in the fractal domain using robust detrended fluctuation analysis. The results show that some non-dominated simulations can be eliminated based on poor performance in the fractal domain, hence ensuring that the fluctuation structure of the optimized simulations is captured; this was named fractal-domain-refinement. Furthermore, some recharge parameters are sensitive to fractal-domain-refinement. This gives insights into which parameters are sensitive to the fractal behaviour of the simulated variable.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1080/02626667.2022.2084342
ISSN:	0262-6667
Additional Keywords:	GroundwaterBGS, Groundwater
Date made live:	06 Jan 2023 09:49 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/533829

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