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Proceedings of the International Association of Hydrological Sciences An open-access publication for refereed proceedings in hydrology
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Volume 368
Proc. IAHS, 368, 204–208, 2015
https://doi.org/10.5194/piahs-368-204-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Proc. IAHS, 368, 204–208, 2015
https://doi.org/10.5194/piahs-368-204-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  06 May 2015

06 May 2015

Annual runoff prediction using a nearest-neighbour method based on cosine angle distance for similarity estimation

G. Qin1,2, H. Li1,2, X. Wang1,2, Q. He2, and S. Li2 G. Qin et al.
  • 1State Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University, Chengdu, 610065, China
  • 2College of Water Resource & Hydropower, Sichuan University, Chengdu, 610065, China

Keywords: Nearest neighbour, similarity estimation, Euclidean distance, cosine angle distance, annual runoff

Abstract. The Nearest Neighbour Method (NNM) is a data-driven and non-parametric scheme established on the similarity characteristics of hydrological phenomena. One of the important parts of NNM is to choose a proper distance measure. The Euclidean distance (EUD) is a commonly used distance measure, which represents the absolute distance of a spatial point and is directly related to the coordinate of the point, but is not sensitive to the direction of the feature vector. This paper used the cosine angle distance (CAD) for the similarity measure, which reflects more differences in the direction, and compared it to EUD. This technique is applied to annual runoff at YiChang station on the Yangtze River. The results show the NNM with CAD has a better performance than that of EUD.

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