Identification of hydrological trends in the presence of serial and cross correlations: A review of selected methods and their application to annual flow regimes of Canadian rivers

Identification of temporal changes in hydrological regimes of river basins is an important topic in contemporary hydrology because of the potential impacts of climate change on river flow regimes. For this purpose, generally parametric and nonparametric techniques have been employed; the latter have been widely used mainly because of a fewer number of assumptions involved in their implementation. The results of these techniques when applied at local/point scales are affected by the presence of serial correlation in time series of hydrological variables and interpretation of the collective results is sensitive to cross correlation present in a hydrological network. Though challenging, often these issues have received little attention in a majority of studies on trends. This study reviews the usefulness of some selected methods for the identification of hydrological trends in the presence/absence of short-term serial and cross correlations. To facilitate easy comprehension and clear demonstration of the ability of various reviewed methods for detecting trends in time series of hydrological variables and interpreting their collective results, a complete case study of annual mean daily flows of Canadian river basins, included in the reference hydrometric basin network, is presented and discussed. Such a comparative evaluation of various methods has never been attempted earlier. Both the reviewed literature and detailed results of the case study demonstrate that failure to incorporate the effects of serial and cross correlations in the trend investigation study could result in erroneous conclusions. Hence, the old practice of identifying hydrological trends without the consideration of serial and cross correlations should be avoided and these characteristics should be given adequate attention in all studies on temporal trends.