Extreme streamflow time series analysis: trends, record length, and persistence

Abstract

Trends can be detected in time series of extreme hydrological events. However, persistence and record length are often ignored in those analyses resulting in contradicting conclusions. The aim of this study is to evaluate their influence on trend detection in extreme streamflow time series. In this study, 108 time series of maximum and minimum streamflow in Brazil were analysed, with a minimum length of 60 years and an average of 76 years. Mann-Kendall (MK), Spearman’s rho, and Pettitt statistical tests were applied to assess trends. Portmanteau and Hurst’s autocorrelation tests were adopted to assess the persistence. Modifications of the MK test were used to remove the persistence effects. We found a strong persistence in the studied time series. Even after removing it, several time series remained non-stationary. Record length significantly affected the results of the analyses, with an increase in the number of trends according to the period analysed.

KEYWORDS:

• time series
• trends
• stationarity
• persistence
• autocorrelation
• extreme streamflow

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Programa UNIEDU / FUMDES Pós-Graduação under number 1423/SED/2019; Fundação de Amparo à Pesquisa e Inovação do Estado de Santa Catarina (FAPESC) under Grant 2016TR2525; and CNPq under number 304475/2020-3. The fourth author acknowledges FAPESC for the scholarship (Registration 06.03121-801).

Notes on contributors

Leandro Jose Isensee

Leandro José Isensee, CPEng, civil and structural engineer. Student of a master's degree program in environmental engineering at the Fundação Universidade Regional de Blumenau. Researcher in hydrology and water resources.

Daniel Henrique Marco Detzel

Daniel Detzel, Dr. Eng. in Water Resources and Environmental Engineering. Professor at the Department of Hydraulics and Sanitation and researcher at the Graduate Program in Water Resources and Environmental Engineering, Federal University of Paraná, Brazil. Currently, he is interested in field topics related to stochastic and statistical hydrology, time series analysis, and water resources engineering.

Adilson Pinheiro

Adilson Pinheiro, Dr. in Agricultural and environmental engineering research. Professor at the Civil Engineering Department at the Fundação Universidade Regional de Blumenau. Researcher in hydrology and water resources.

Gustavo Antonio Piazza

Gustavo Antonio Piazza, Dr. in Environmental Engineering. Researcher at Secretariat for Sustainable Economic Development of Santa Catarina (SDE-SC), Executive Secretary of Environment (SEMA), Department of Water Resources and Sanitation. My expertise is on catchment monitoring, water quality and quantity, climate change, geoprocessing, and remote sensing.