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. 10.1080/02626667.2022.2084342
Full text not available from this repository. (Request a copy)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): | 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 |
Actions (login required)
View Item |
Document Downloads
Downloads for past 30 days
Downloads per month over past year