An evaluation of automated GPD threshold selection methods for hydrological extremes across different scales

A - Papers appearing in refereed journals

Curceac, S., Atkinson, P. M., Milne, A. E., Wu, L. and Harris, P. 2020. An evaluation of automated GPD threshold selection methods for hydrological extremes across different scales. Journal of Hydrology. 585, p. 124845.

AuthorsCurceac, S., Atkinson, P. M., Milne, A. E., Wu, L. and Harris, P.
Abstract

This study investigated core components of an extreme value methodology for the estimation of high-flow frequencies from agricultural surface water run-off. The Generalized Pareto distribution (GPD) was used to model excesses in time-series data that resulted from the ‘Peaks Over Threshold’ (POT) method. First, the performance of eight different GPD parameter estimators was evaluated through a Monte Carlo experiment. Second, building on the estimator comparison, two existing automated GPD threshold selection methods were evaluated against a proposed approach that automates the threshold stability plots. For this second experiment, methods were applied to discharge measured at a highly-instrumented agricultural research facility in the UK. By averaging fine-resolution 15-minute data to hourly, 6-hourly and daily scales, we were also able to determine the effect of scale on threshold selection, as well as the performance of each method. The results demonstrate the advantages of the proposed threshold selection method over two commonly applied methods, while at the same time providing useful insights into the effect of the choice of the scale of measurement on threshold selection. The results can be generalised to similar water monitoring schemes and are important for improved characterisations of flood events and the design of associated disaster management protocols.

KeywordsGeneralized pareto distribution; Peaks over threshold; Threshold selection; Flood frequency analysis; Scale effects; Grassland agriculture
Year of Publication2020
JournalJournal of Hydrology
Journal citation585, p. 124845
Digital Object Identifier (DOI)doi:10.1016/j.jhydrol.2020.124845
Web address (URL)https://www.sciencedirect.com/science/article/pii/S002216942030305X?via%3Dihub#!
Open accessPublished as non-open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeThe North Wyke Farm Platform- National Capability [2017-22]
S2N - Soil to Nutrition - Work package 2 (WP2) - Adaptive management systems for improved efficiency and nutritional quality
S2N - Soil to Nutrition - Work package 3 (WP3) - Sustainable intensification - optimisation at multiple scales
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Output statusPublished
Publication dates
Online13 Mar 2020
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Accepted12 Mar 2020
PublisherElsevier Science Bv
ISSN0022-1694

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