Abstract
With the changing environment, a number of researches have revealed that the assumption of stationarity of flood sequences is questionable. In this paper, we established univariate and bivariate models to investigate nonstationary flood frequency with distribution parameters changing over time. Flood peak Q and one-day flood volume W1 of the Wangkuai Reservoir catchment were used as basic data. In the univariate model, the log-normal distribution performed best and tended to describe the nonstationarity in both flood peak and volume sequences reasonably well. In the bivariate model, the optimal log-normal distributions were taken as marginal distributions, and copula functions were addressed to construct the dependence structure of Q and W1. The results showed that the Gumbel-Hougaard copula offered the best joint distribution. The most likely events had an undulating behavior similar to the univariate models, and the combination values of flood peak and volume under the same OR-joint and AND-joint exceedance probability both displayed a decreasing trend. Before 1970, the most likely combination values considering the variation of distribution parameters over time were larger than fixed parameters (stationary), while it became the opposite after 1980. The results highlight the necessity of nonstationary flood frequency analysis.
Highlights
Flood frequency analysis is the premise and foundation of water conservancy project planning and construction
In this study, following the identification of the nonstationarity for the Wangkuai Reservoir inflow flood sequences, two nonstationary models based on GAMLSS theory were established, in which the flood peak Q and flood volume W1 were considered as the independent response variables, and time t was adopted as the explanatory variable
Most of the observed data points are distributed in the grayscale range between 5% to 95% quantiles, indicating that the model results are able to capture the nonstationarity of the flood data
Summary
Flood frequency analysis is the premise and foundation of water conservancy project planning and construction. With climate change and intensification of human activities, especially the construction of large-scale water conservancy and water conservation engineering and the urbanization process, the runoff yield and concentration mechanism, and the temporal and spatial distribution of flooding have been changed [2]. This results in the inconsistency of flood series and the unreliability of the frequency obtained from current frequency analysis methods [3]. Existing nonstationary flood frequency analysis methods in literature include mixture distribution methods, conditional probability distribution methods, and time-varying moment methods.
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