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

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  • Manish Goyal
  • Vivek Gupta

Abstract

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. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Manish Goyal & Vivek Gupta, 2014. "Identification of Homogeneous Rainfall Regimes in Northeast Region of India using Fuzzy Cluster Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4491-4511, October.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:13:p:4491-4511
    DOI: 10.1007/s11269-014-0699-7
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    Citations

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    Cited by:

    1. Zaw Latt & Hartmut Wittenberg & Brigitte Urban, 2015. "Clustering Hydrological Homogeneous Regions and Neural Network Based Index Flood Estimation for Ungauged Catchments: an Example of the Chindwin River in Myanmar," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(3), pages 913-928, February.
    2. Arash Modaresi Rad & Davar Khalili, 2015. "Appropriateness of Clustered Raingauge Stations for Spatio-Temporal Meteorological Drought Applications," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(11), pages 4157-4171, September.
    3. Qianyu Gao & Guofang Li & Jin Bao & Jian Wang, 2021. "Regional Frequency Analysis Based on Precipitation Regionalization Accounting for Temporal Variability and a Nonstationary Index Flood Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4435-4456, October.
    4. Sultan Mahmud & Ferdausi Mahojabin Sumana & Md Mohsin & Md. Hasinur Rahaman Khan, 2022. "Redefining homogeneous climate regions in Bangladesh using multivariate clustering approaches," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1863-1884, March.
    5. Manish Kumar Goyal & Gupta Shivam & Arup K. Sarma, 2019. "Spatial homogeneity of extreme precipitation indices using fuzzy clustering over northeast India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(2), pages 559-574, September.
    6. Rakesh Kumar & Narendra Goel & Chandranath Chatterjee & Purna Nayak, 2015. "Regional Flood Frequency Analysis using Soft Computing Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(6), pages 1965-1978, April.
    7. Manish Kumar Goyal & Ashutosh Sharma, 2016. "A fuzzy c-means approach regionalization for analysis of meteorological drought homogeneous regions in western India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(3), pages 1831-1847, December.
    8. Sanat Nalini Sahoo & P. Sreeja, 2016. "Relationship between peak rainfall intensity (PRI) and maximum flood depth (MFD) in an urban catchment of Northeast India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1527-1544, September.
    9. A. Agarwal & R. Maheswaran & J Kurths & R. Khosa, 2016. "Wavelet Spectrum and Self-Organizing Maps-Based Approach for Hydrologic Regionalization -a Case Study in the Western United States," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4399-4413, September.
    10. Ting Wei & Songbai Song, 2019. "Utilization of the Copula-Based Composite Likelihood Approach to Improve Design Precipitation Estimates Accuracy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(15), pages 5089-5106, December.
    11. Schulze-González, Erik & Pastor-Ferrando, Juan-Pascual & Aragonés-Beltrán, Pablo, 2023. "Clustering and reference value for assessing influence in analytic network process without pairwise comparison matrices: Study of 17 real cases," Operations Research Perspectives, Elsevier, vol. 10(C).
    12. Muhammad Waseem & Ji-yae Shin & Tae-Woong Kim, 2015. "Comparing Spatial Interpolation Schemes for Constructing a Flow Duration Curve in an Ungauged Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(7), pages 2249-2265, May.

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