Ordinal pattern dependence between hydrological time series
Loading...
Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Ordinal patterns provide a method to measure correlation between time series. In
contrast to classical correlation measures like the Pearson correlation coefficient they
are able to measure not only linear correlation but also non-linear correlation even
in the presence of non-stationarity. Hence, they are a noteworthy alternative to the
classical approaches when considering discharge series. Discharge series naturally
show a high variation as well as single extraordinary extreme events and, caused by
anthropogenic and climatic impacts, non-stationary behaviour. Here, the method
of ordinal patterns is used to compare pairwise discharge series derived from macroand
mesoscale catchments in Germany. Differences of coincident groups were detected
for winter and summer annual maxima. Hydrological series, which are mainly
driven by annual climatic conditions (yearly discharges and low water discharges)
showed other and in some cases surprising interdependencies between macroscale
catchments. Anthropogenic impacts as the construction of a reservoir or different
flood conditions caused by urbanization could be detected.
Description
Table of contents
Keywords
ordinal patterns, homogeneous groups, discharge correlation