Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/34682
Title: Discovering flood rising pattern in hydrological time series data mining during the pre monsoon period
Authors: Mishra, Satanand
Saravanan, C
Dwivedi, V K
Pathak, K K
Keywords: Clustering;Agglomerative hierarchical clustering;Data mining;Runoff;Hydrological time series;Pattern discovery;Pre monsoon;Rising patern;Similarity search;Ward criterion;Regression analysis
Issue Date: Mar-2015
Publisher: NISCAIR-CSIR, India
Abstract: Present study examines the flood rising pattern for the river discharge data in the river Brahmaputra basin. The months from January to May comes under the pre monsoon season. In this paper, with the help of time series data mining techniques, analysis has made for hydrological daily discharge time series data, measured at the Panchratna station during the pre monsoon in the river Brahmaputra under Brahmaputra and Barak Basin Organization before coming the high flood. Statistical analysis has made for standardization of data. K-means clustering, Dynamic Time Warping (DTW), Agglomerative Hierarchical Clustering (AHC), Ward’s criterion and regression analysis are used to cluster and discover the discharge patterns in terms of the autoregressive model. A forecast model has been developed for the discharge process. For validation of the flood rising pattern, Gauge–Discharge Curve, Water Level Hydrographs, Rainfall Bar Graphs, Mean maximum -minimum temperature and evaporation  graphs have been developed and also discharge rising coefficient has been calculated. This study gives the behavioral characteristics of rivers discharge during rising of high floods with the time series data mining.
Page(s): 303-317
ISSN: 0975-1033 (Online); 0379-5136 (Print)
Appears in Collections: IJMS Vol.44(03) [March 2015]

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