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Global climate change can have impacts on characteristics of rainfall–runoffevents and subsequently on the hydrological regime. Meanwhile, the catchmentitself changes due to anthropogenic influences. However, it is not easy toprove the link between the hydrology and the forcings. In this context, itmight be meaningful to detect the temporal changes of catchments independentfrom climate change by investigating existing long-term discharge records.For this purpose, a new stochastic system based on copulas for time seriesanalysis is introduced in this study.  A statistical tool like copula has the advantage to scrutinize the dependencestructure of the data and, thus, can be used to attribute the catchmentbehavior by focusing on the following aspects of the statistics defined inthe copula domain: (1) copula asymmetry, which can capture the nonsymmetricproperty of discharge data, differs from one catchment to another due to theintrinsic nature of both runoff and catchment; and (2) copula distances canassist in identifying catchment change by revealing the variability andinterdependency of dependence structures.  These measures were calculated for 100 years of daily discharges for theRhine River and these analyses detected epochs of change in the flowsequences. In a follow-up study, we compared the results of copula asymmetryand copula distance applied to two flow models: (i) antecedent precipitationindex (API) and (ii) simulated discharge time series generated by ahydrological model. The results of copula-based analysis of hydrological timeseries seem to support the assumption that the Neckar catchment had startedto change around 1976 and stayed unusual until 1990

Investigation of hydrological time series using copulas for detecting catchment characteristics and anthropogenic impacts