Detecting the impact of climate and reservoirs on extreme floods using nonstationary frequency models

Abstract

The annual maximum flood records of the Danjiangkou reservoir displayed significant decreasing trends. The upper stream of the reservoir was characterized by minor changes in urbanization in recent decades, while several large reservoirs were built since 1975. To better explain the changes in floods, this paper used the nonstationary generalized extreme value (GEV) distribution by considering the impacts of climate change and human activity. The GEV parameters were expressed as functions of time, climate indices, and climate-reservoir index (CRI). By using CRI as the covariate, the performance of the nonstationary GEV distribution was much better than others. This paper also analyzed the risk of floods using design life level and annual average reliability methods. The reliability obtained from these methods can describe the effects of external indices on floods. Finally, the uncertainty analysis indicated that a nonstationary model might not be practical, and the large confidence intervals of the design flood implied that the results were meaningless. It is essential to build a deterministic relationship between parameters and covariates, and we should be prudent when using general circulation models outputs in extreme statistics.