Detecting Annual and Seasonal Hydrological Change Using Marginal Distributions of Daily Flows

Abstract

Changes in the hydrological regime are widely investigated using a variety of approaches. In this study, we assess changes in annual and seasonal flow characteristics based on a probabilistic representation of the seasonal runoff regime at the daily time scale. The probabilistic seasonal runoff pattern is constructed by determining quantiles from marginal distributions of daily flows for each day within the year. By applying Fourier transformation on the statistics of the daily flow partial series, we obtain smooth periodical functions of distribution parameters over the year and consequently of the quantiles. The main findings are based on the comparison of the dry, average, and wet hydrologic condition zones as defined by the daily flow quantiles of selected probabilities. This analysis was conducted for ten catchments in Serbia by considering changes between two 30-year nonoverlapping periods, 1961–1990 and 1991–2020. It was found that the relative change in runoff volume is the most pronounced in the extreme dry condition zone in the winter season (−33% to 34%). The annual time shift is the largest in the dry and average condition zones, ranging from −11 to 12 days. The applied methodology is not only applicable to the detection of hydrologic change, but could also be used in operational hydrology and extreme flow studies via drought indices such as the Standardized Streamflow Index.