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Regional Flood Frequency Analysis using Soft Computing Techniques

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  • Rakesh Kumar
  • Narendra Goel
  • Chandranath Chatterjee
  • Purna Nayak

Abstract

For design of various types of hydraulic structures as well as for taking different flood management measures flood frequency estimates are required. Regional flood frequency analysis is carried out employing L-moments and soft computing techniques viz. artificial neural network (ANN) and fuzzy inference system (FIS) for the lower Godavari subzone 3(f) of India. The study area covers an areal extent of 174,201 km 2 and annual maximum peak flood data of 17 catchments ranging in size from 35 to 824 km 2 are used. The data screening is carried out employing L-moments based Discordancy measure (D i ) and regional homogeneity is examined based on the heterogeneity measure (H). On the basis of the L-moment ratio diagram and Z i dist –statistic criteria, Pearson Type III (PE3) distribution is chosen as the suitable frequency distribution for the region. For the region under study, a relationship is developed between mean annual maximum peak flood and area of the catchment using the Levenberg-Marquardt (LM) iteration and the same is coupled with the PE3 based regional flood frequency relationship developed for estimation of floods of various frequencies for the ungauged catchments of the region. The regional flood frequency relationships developed based on L-moments and soft computing techniques are compared. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:6:p:1965-1978
    DOI: 10.1007/s11269-015-0922-1
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    References listed on IDEAS

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    1. Abhijit Bhuyan & Munindra Borah & Rakesh Kumar, 2010. "Regional Flood Frequency Analysis of North-Bank of the River Brahmaputra by Using LH-Moments," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(9), pages 1779-1790, July.
    2. Purna Nayak & Y. Rao & K. Sudheer, 2006. "Groundwater Level Forecasting in a Shallow Aquifer Using Artificial Neural Network Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 20(1), pages 77-90, February.
    3. Rim Chérif & Zoubeida Bargaoui, 2013. "Regionalisation of Maximum Annual Runoff Using Hierarchical and Trellis Methods with Topographic Information," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 2947-2963, June.
    4. 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.
    5. Nejc Bezak & Matjaž Mikoš & Mojca Šraj, 2014. "Trivariate Frequency Analyses of Peak Discharge, Hydrograph Volume and Suspended Sediment Concentration Data Using Copulas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(8), pages 2195-2212, June.
    6. Leonardo Noto & Goffredo La Loggia, 2009. "Use of L-Moments Approach for Regional Flood Frequency Analysis in Sicily, Italy," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 23(11), pages 2207-2229, September.
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    2. Samiran Das, 2020. "Assessing the Regional Concept with Sub-Sampling Approach to Identify Probability Distribution for at-Site Hydrological Frequency Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 803-817, January.
    3. 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.

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