Hydrological characteristic-based methodology for dividing flood seasons: an empirical analysis from China

Abstract

A hydrological characteristic -based methodology for dividing flood seasons into sub-seasons is proposed to make full use of a reservoir’s flood control storage during the flood season via multi-stage flood-limited water levels. The proposed framework is mainly composed of three parts: the selection of indices depicting flood seasonality, the establishment of segmentation methods that can address clustering problems with high-dimensional time series and unknown numbers of clusters, and multi-scheme comparison and rationality analysis. The reasonability and validity of the proposed framework is illustrated through an empirical case study of China’s Panjiakou Reservoir basin. The results indicated that the dynamic fuzzy c-means method with clustering validity function provided more objective and quantitative divisions than other methods, including the Fisher optimal partition. The flood season of the Panjiakou Reservoir basin (June 1–September 30) is divided into three sub-seasons according to the principle of optimal clustering: a pre-flood season (June 1–July 10), a main flood season (July 11–August 20), and a post-flood season(August 21–September 30).