Hurst; Potential evapotranspiration; Parametric model; R software; Trend analysis
We present an R function for testing the trend significance of time series. The function calculates the trend significance using a modified Mann- Kendall test, which takes into account the well-known physical behavior of the Hurst-Kolmogorov dynamics. The function is tested in 10 stations in Greece, with approximately 50 years of PET data with the use of a recent parametric approach. A significant downward trend was detected in two stations. The R software is now suitable for extensive use in the several fields of the scientific community, allowing a physical consistent of a trend analysis.
firstname.lastname@example.org, Hossein Tabari, Expert in Hydrological time series analysis email@example.com, María José Polo Gómez, Associate Professor of Hydraulic Engineering firstname.lastname@example.org, Cristina Aguilar Porro, Ph.D. Forestry Engineer
BYU ScholarsArchive Citation
Tegos, Aristoteles; Tyralis, Hristos; Koutsoyiannis, Demetris; and Hamed, Khaled
"An R function for the estimation of trend significance under the scaling hypothesis- application in PET parametric annual time series,"
Open Water Journal: Vol. 4
, Article 6.
Available at: https://scholarsarchive.byu.edu/openwater/vol4/iss1/6