Identification of Homogeneous Rainfall Regimes in Northeast Region of India using Fuzzy Cluster Analysis

Regionalization methods are often used in hydrology for frequency analysis of floods. The hydrologically homogeneous regions should be determined using cluster analysis instead of the geographically close stations. In view of the ongoing environmental and climate changes in the Northeastern of India...

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Vydáno v:Water resources management Ročník 28; číslo 13; s. 4491 - 4511
Hlavní autoři: Goyal, Manish Kumar, Gupta, Vivek
Médium: Journal Article
Jazyk:angličtina
Vydáno: Dordrecht Springer-Verlag 01.10.2014
Springer Netherlands
Springer
Springer Nature B.V
Témata:
Algorithms
Atmospheric Sciences
basins
Civil Engineering
Climate change
Cluster analysis
Clustering
Correlation analysis
Earth and Environmental Science
Earth Sciences
Earth, ocean, space
Engineering and environment geology. Geothermics
Environment
Exact sciences and technology
Flood frequency
Floods
Forecasting
Frequency analysis
Freshwater
Fuzzy
Geotechnical Engineering & Applied Earth Sciences
Homogeneity
Hydrogeology
Hydrologic data
Hydrology
Hydrology. Hydrogeology
Hydrology/Water Resources
India
Natural hazards: prediction, damages, etc
Partitions
Precipitation
rain
Regional
Regions
Studies
Validity
Water resources
Water resources management
India
Asia
Clustering
Regionalization
Flood frequency analysis
algorithms
floods
partition coefficients
rainfall
atmospheric precipitation
frequency
homogeneity
entropy
water resource management
cluster analysis
methodology
climate change
ISSN:0920-4741, 1573-1650
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Shrnutí:Regionalization methods are often used in hydrology for frequency analysis of floods. The hydrologically homogeneous regions should be determined using cluster analysis instead of the geographically close stations. In view of the ongoing environmental and climate changes in the Northeastern of India, regionalization of homogeneous rainfall region is essential to lay out an effective flood frequency analysis of this region. The choice of appropriate cluster approach used according to the data of the basin is also significant. In the context of this study, total precipitation data of stations operated by Indian Meteorological Department (IMD) in Northeastern of India basins for cluster analysis are used. Further, five cluster validity indices, namely Partition Coefficient, Partition Entropy, Extended Xie-Beni index, Fukuyama-Sugeno index and Kwon index have been tested to determine the effectiveness in identifying optimal partition provided by the fuzzy c mean clustering algorithm (FCM). A comparison is also performed using K- Mean clustering algorithm. Additionally, regional homogeneity tests based on L-moments approach are used to check homogeneity of regions identified by both cluster analysis approaches. It was concluded that regional homogeneity test results show that regions defined by FCM method are sufficiently homogeneous for regional frequency analysis.
Bibliografie:http://dx.doi.org/10.1007/s11269-014-0699-7
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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-014-0699-7