Investigating the change of hydrological patterns of streamflow by using HDCE method

The change of streamflow patterns is one of the important information to water resources management. Especially, in the last few years, climate changes have not only caused increases in the intensity and frequency of extreme hydrological events, but also disrupted the monotony of climate which could lead to unexpected consequences and economic losses to our society. However, only a little research has paid attention to the change in patterns or schemes of the hydrological cycle. The issue is even more serious in Taiwan due to the uneven spatial-temporal distribution of rainfall. This research aims to discover the change in patterns in Taiwan. We proposed a HDCE framework which is composed of Hierarchical cluster, Dynamic time warping, Change point detection, and Empirical mode decomposition. With this framework, we apply the hierarchical cluster with different distance matrices, and obtain the optimal clustering number and linkage method according to clustering valid indexes. Dynamic time warping is used as the measure of distance to investigate the pattern of time series By this way, this framework determines the optimal cluster of patterns for the historical inflow data. After clustering, the AMOC (At Most One Change) is used to analyze the structure of the pattern. With AMOC, the change time point in each period is examined under the structure of each cluster. In the end, the empirical mode decomposition is adopted to determine the trend of the pattern change. With the proposed framework, this research applies these schemes to main inflow observation gage stations in Taiwan, and the results demonstrate that the groups and activities of positions of the stations indirectly affect the pattern of the inflow values, instead, the clusters formed are mainly affected by the region and geographical area of the locations. Furthermore, we will explain the results showing the different trends in changing time in each region and the correlation of breaks at each station. In this way, the results of HDCE not only examine the occurrence of droughts but provide information that is useful to develop the strategy to reduce the loss through better water management.