Similarity search in hydrological time series

Data mining in the time series similarity search was applied to hydrological time series data for mining similar hydrological processes. The characteristics of two kinds of similarity distance measuring methods,Euclidean distance and dynamic time warping distance,were analyzed. Owing to its satisfactory adaptability in terms of stretching and warping to the time axis,the dynamic time warping distance method was employed to perform a similarity search of 220 floods at Shaliguilanke Station in the Tarim River Basin in China from 1961 to 2000. Based on the similarity matrices,the similar flood discharge processes were mined. The results show that although the flood discharge processes at Shaliguilanke Station are diverse,they exhibit a certain similarity. The similarity search based on the dynamic time warping can be employed for effective mining of similar hydrological processes.