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Regionalized Design Rainfall Estimation: an Appraisal of Inundation Mapping for Flood Management Under Data-Scarce Situations

Author

Listed:
  • Mohit Prakash Mohanty

    (Indian Institute of Technology Bombay)

  • Mazhuvanchery Avarachen Sherly

    (IITB-Monash Research Academy)

  • Subhankar Karmakar

    (Indian Institute of Technology Bombay
    Indian Institute of Technology Bombay
    Indian Institute of Technology Bombay)

  • Subimal Ghosh

    (Indian Institute of Technology Bombay
    Indian Institute of Technology Bombay
    Indian Institute of Technology Bombay)

Abstract

Availability of regionalized design rainfall is crucial for flood modeling, particularly over the regions with sparse raingauge networks. This study proposes a new comprehensive framework for generating regionalized design rainfall time series for data-poor catchments involving non-linear and non-parametric optimization approaches. A large set of parametric and non-parametric families of distribution were considered for multivariate rainfall frequency analysis using at-site station data, while a unique design temporal pattern over the region was derived by quantifying the flood causing potential of design hyetographs. The regionalized design rainfall time series was used as one of the inputs to a two-dimensional (2D) flood model. The accuracy and performance of the derived regionalized design rainfall for flood inundation modeling were evaluated by comparing with those derived from different spatial interpolation methods. There was a high consensus of the former with those of widely used kriging and spline interpolation methods. A severely flood-prone and data-poor (no raingauge available within study area) large coastal catchment lying along the coast of the Bay of Bengal, India, was chosen for a demonstration of the proposed framework. The study showed that the framework can be used for extreme events arising due to floods, even under changing climatic scenarios. It further invokes the necessity for incorporating the proposed framework into various commercially and freely available flood models along with other existing interpolation techniques to support improved flood management.

Suggested Citation

  • Mohit Prakash Mohanty & Mazhuvanchery Avarachen Sherly & Subhankar Karmakar & Subimal Ghosh, 2018. "Regionalized Design Rainfall Estimation: an Appraisal of Inundation Mapping for Flood Management Under Data-Scarce Situations," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4725-4746, November.
    • Handle: RePEc:spr:waterr:v:32:y:2018:i:14:d:10.1007_s11269-018-2080-8
    DOI: 10.1007/s11269-018-2080-8
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    References listed on IDEAS

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    1. Marco Borga & Claudia Vezzani & Giancarlo Fontana, 2005. "Regional Rainfall Depth–Duration–Frequency Equations for an Alpine Region," 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. 36(1), pages 221-235, September.
    2. Lu-Hsien Chen & Gwo-Fong Lin & Chen-Wang Hsu, 2011. "Development of Design Hyetographs for Ungauged Sites Using an Approach Combining PCA, SOM and Kriging Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(8), pages 1995-2013, June.
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    Cited by:

    1. 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.
    2. Hongshi Xu & Kui Xu & Tianye Wang & Wanjie Xue, 2022. "Investigating Flood Risks of Rainfall and Storm Tides Affected by the Parameter Estimation Coupling Bivariate Statistics and Hydrodynamic Models in the Coastal City," IJERPH, MDPI, vol. 19(19), pages 1-18, October.
    3. Longxia Qian & Yong Zhao & Jianhong Yang & Hanlin Li & Hongrui Wang & ChengZu Bai, 2022. "A New Estimation Method for Copula Parameters for Multivariate Hydrological Frequency Analysis With Small Sample Sizes," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1141-1157, March.

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