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Influence of threshold selection in modeling peaks over threshold based nonstationary extreme rainfall series

Agilan, V and Umamahesh, NV and Mujumdar, PP (2021) Influence of threshold selection in modeling peaks over threshold based nonstationary extreme rainfall series. In: Journal of Hydrology, 593 .

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Official URL: https://dx.doi.org/10.1016/j.jhydrol.2020.125625

Abstract

Recent studies report that the extreme rainfall characteristics in most parts of the globe exhibit temporal non-stationarity. Therefore, modeling the nonstationary behavior of extreme rainfall for different water resources applications is vital. When modeling non-stationarity in extreme rainfall series, previous studies consider a single threshold value in the peaks over threshold (POT) approach to extract extreme rainfall series. However, extreme rainfall series extracted with different threshold values may have a different degree of non-stationarity. Consequently, it is essential to understand the effect of threshold selection in modeling peaks over threshold based nonstationary extreme rainfall series. This study aims at quantifying the threshold uncertainty (i.e., uncertainty in extreme rainfall return levels due to the choice of the threshold) in modeling peaks over threshold based nonstationary extreme rainfall series using the Generalized Pareto Distribution (GPD). To study the threshold uncertainty, extreme rainfall series over India from the India Meteorological Department's high-resolution gridded (0.25° Longitude � 0.25° Latitude) daily rainfall dataset is used. For modeling non-stationarity in extreme rainfall series, different indices representing four physical processes, namely, global warming, El Niño�Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and local temperature anomaly are linked with the scale parameter of the GPD. Uncertainties in extreme rainfall return levels calculated over India indicate that the uncertainty created due to the choice of threshold is 54 higher under the nonstationary condition when compared to the stationary condition. © 2020 Elsevier B.V.

Item Type: Journal Article
Publication: Journal of Hydrology
Publisher: Elsevier B.V.
Additional Information: The copyright of this article belongs to Elsevier B.V.
Keywords: Atmospheric pressure; Global warming; Pareto principle; Uncertainty analysis; Water resources, Generalized Pareto distribution; Indian ocean dipoles; Non-stationary behaviors; Non-stationary condition; Peaks over threshold; Southern oscillation; Stationary conditions; Threshold selection, Rain
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Date Deposited: 15 Mar 2021 06:45
Last Modified: 15 Mar 2021 06:45
URI: http://eprints.iisc.ac.in/id/eprint/67488

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