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Discovering flood rising pattern in hydrological time series data mining during the pre monsoon period

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Title Discovering flood rising pattern in hydrological time series data mining during the pre monsoon period
 
Creator Mishra, Satanand
Saravanan, C
Dwivedi, V K
Pathak, K K
 
Subject Clustering
Agglomerative hierarchical clustering
Data mining
Runoff
Hydrological time series
Pattern discovery
Pre monsoon
Rising patern
Similarity search
Ward criterion
Regression analysis
 
Description 303-317
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.
 
Date 2016-07-05T09:19:30Z
2016-07-05T09:19:30Z
2015-03
 
Type Article
 
Identifier 0975-1033 (Online); 0379-5136 (Print)
http://hdl.handle.net/123456789/34682
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJMS Vol.44(03) [March 2015]