Ordinal pattern dependence between hydrological time series

dc.contributor.authorFischer, Svenja
dc.contributor.authorSchumann, Andreas
dc.contributor.authorSchnurr, Alexander
dc.date.accessioned2016-12-22T12:29:13Z
dc.date.available2016-12-22T12:29:13Z
dc.date.issued2016
dc.description.abstractOrdinal 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.en
dc.identifier.urihttp://hdl.handle.net/2003/35732
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-17762
dc.language.isoende
dc.relation.ispartofseriesDiscussion Paper / SFB823;88, 2016en
dc.subjectordinal patternsde
dc.subjecthomogeneous groupsde
dc.subjectdischarge correlationde
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleOrdinal pattern dependence between hydrological time seriesen
dc.typeTextde
dc.type.publicationtypeworkingPaperde
dcterms.accessRightsopen access

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