Abstract
Abstract. In this paper, a novel approach for non-stationary hydrological frequency analysis is proposed. The approach is due to the following consideration that, at present the data series used to detect mutation characteristic is very short, which may only reflect the partial characteristic of the population. That is to say, the mutation characteristic of short series may not fully represent the mutation characteristic of population, such as the difference of mutation degree between short sample and population. In this proposed method, an assumption is done that the variation hydrological series in a big time window owns an expected vibration center (EVC), which is a linear combination of the two mean values of the two subsample series obtained through separating the original hydrological series by a novel optimal segmentation technique (change rate of slope method). Then using the EVC to reconstruct non-stationary series to meet the requirement of stationary, and further ensure the conventional frequency analysis methods is valid.
Highlights
Hydrological frequency analysis (HFA) is widely used to obtain designed flood with a given horizon level, which is extremely important for hydraulic engineering construction and water resources management
An assumption is done that the mutation hydrological series in a big time window owns an expected vibration center (EVC), which is a linear combination of the two mean values of the two subsample series obtained through separating the original hydrological series by a optimal segmentation technique
An assumption is done that the trend-mutation hydrological series in a big time window owns an EVC, which is a linear combination of the two mean values of the two subsample obtained through separating the original hydrological series by an optimal segmentation technique named change rate of gradient method
Summary
Hydrological frequency analysis (HFA) is widely used to obtain designed flood with a given horizon level, which is extremely important for hydraulic engineering construction and water resources management. Hu et al.: Non-stationary hydrological frequency analysis based on extreme hydrological series tic of population, such as the difference of mutation degree between short sample and population. In this paper, we propose a novel statistical method for reconstructing the non-stationary series to ensure the conventional frequency analysis methods is valid. In this method, an assumption is done that the mutation hydrological series in a big time window owns an EVC, which is a linear combination of the two mean values of the two subsample series obtained through separating the original hydrological series by a optimal segmentation technique (change rate of gradient method).
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