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Under the impact of climate change and human activities, the stationarity of hydrometeorological extreme value series has been losing in many regions, which makes occurrence rules of hydrometeorological extreme events more complicated. In this study, the efficiencies of trend test methods such as Spearman rank correlation test and Mann-Kendall test, as well as the efficiencies of change-point test methods such as moving T test, moving rank sum test, Pettitt test, and sequential Mann-Kendall test were analyzed quantitatively through Monte Carlo simulation. Five representative level stations in the Yangtze River estuary were selected, and the methods listed above were used in the trend and change-point detection of the annual maximum tidal level records in the period of 1950–2008. It was found that obvious rising tendency existed in the annual maximum tidal level series for all these 5 stations, and year 1980 (for 3 stations) and year 1979 (for 2 stations) were statistically significant change-points. Two subseries were divided with the change-point as the dividing point for all these actual series in the stations. Frequency analyses were carried out, respectively, for all of the subseries, and the impact of nonstationary changes in annual maximum tidal levels on probability distribution was evaluated quantitatively.