In the context of global warming and average rise in sea level, obvious changes are witnessed with regard to the frequency and intensity of major extreme weather and climate events. Climate change has become an important cause of non-stationarity in hydrology. Several approaches have been proposed to tackle non-stationarity of hydro-meteorological extremes in the literatures. The structures and extreme inference methods of non-stationary sequences model applied usually in climate and hydrology change are summarized in this paper. Some typical examples in statistical modeling of extremes of non-stationary hydrologic sequences are analyzed. The applications demonstrate that changes of hydrology variables according to time or covariates can be reflected by statistical modeling of extremes of non-stationary sequences,and the return period and risk assessment for non-stationary situations can be quite different from those corresponding to stationary conditions. Finally, perspectives on statistical modeling of extremes of non-stationary sequences are proposed.