Non-stationary approach to at-site flood frequency modelling. III. Flood analysis of Polish rivers

Abstract

This paper, the last of a three-part paper, investigates into trends in annual maximum flows of Polish rivers using 39 flow series for a period of 70 years from 1921 to 1990. The gradients of trends in the mean and the standard deviation (SD) are estimated by the weighted least squares method and the best fitting linear model of trend is with the aid of the Akaike Information Criterion (AIC). It is shown that for every time series, a trend in the variance has a considerable effect on the trend estimators of the mean value. The analysis also includes seasonal peak flow series in order to obtain further insight into the detected non-stationarity of the peak flow series. Using the maximum likelihood method for parameter estimation and AIC for identification of an optimum model, the best fitting probability distribution and trend model are identified, following the methods discussed in part 1. Then, the 1% quantiles for the first and the last years of observation, denoted, respectively, as Q 1%(1921) and Q 1%(1990), are estimated and analysed. The influence of the distribution assumption on the values of estimators of time-dependent moments is demonstrated. In general, a decreasing tendency in both the mean and the SD of annual peak flow series is detected. This tendency is more pronounced on rivers with a high contribution of winter floods to the annual peak flow discharge series. Summer season peak flow series is found to be stationary.