Impact of climate change on regionalization using fuzzy clustering

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Abstract

Paucity of data restricts the hydrologist to analyze the meteorological characteristics of the basin reliably. Regionalization of precipitation in the basin helps in reliable flood and drought frequency analysis. Fuzzy c-means algorithm is an unsupervised classification algorithm and has been widely used in the literature for finding the homogeneous precipitation region. This paper analyzes the effect of climate change on the hydrological homogeneous region in the northeast India using fuzzy c-means algorithm. Two validity indexes named Extended Xie–Beni index and Kwon’s index have been used in this study.

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Gupta, V., & Goyal, M. K. (2015). Impact of climate change on regionalization using fuzzy clustering. In Advances in Intelligent Systems and Computing (Vol. 336, pp. 451–458). Springer Verlag. https://doi.org/10.1007/978-81-322-2220-0_37

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