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Potential Impact of Climate Change on Rainfall Intensity-Duration-Frequency Curves in Roorkee, India

Author

Listed:
  • Ronit Singh

    (Indian Institute of Technology Roorkee)

  • D. S. Arya

    (Indian Institute of Technology Roorkee)

  • A. K. Taxak

    (Indian Institute of Technology Roorkee)

  • Z. Vojinovic

    (UNESCO-IHE Institute for Water Education)

Abstract

Intensification and frequency of hydrologic events are attributed to climate change and are expected to increase in coming future. Intensity-Duration-Frequency (IDF) curves quantify the extreme precipitation and are used extensively to assess the return periods of rainfall events. It is expected that climate change will modify the occurrence of extreme rainfall events. Thus a need of updating IDF curves arises under the climate change scenario. This paper aims at updating the IDF curves for a typical Indian town using an ensemble of five General Circulation Models (GCMs) for all the Representative Concentration Pathways (RCP) scenarios. Sub-daily maximum intensities (15-, 30-, 45-, 60-, 120-, and 180 min) were obtained from the observed records. Equidistance quantile method was used to study the relationships between the historical and projected GCM data, and the historical GCM and observed sub-daily data. This relationship was used to obtain projected sub-daily intensities. The IDF curves were developed using observed and projected data. Analysis of the curves indicated increase in precipitation intensities for all the RCP scenarios. It was also found that intensities of all return periods increases with intensifying RCP scenarios. The variation in the intensities across the GCMs was attributed to the driving forces considered in a particular GCM.

Suggested Citation

  • Ronit Singh & D. S. Arya & A. K. Taxak & Z. Vojinovic, 2016. "Potential Impact of Climate Change on Rainfall Intensity-Duration-Frequency Curves in Roorkee, India," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4603-4616, October.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:13:d:10.1007_s11269-016-1441-4
    DOI: 10.1007/s11269-016-1441-4
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    References listed on IDEAS

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    1. Roshan Srivastav & Andre Schardong & Slobodan Simonovic, 2014. "Equidistance Quantile Matching Method for Updating IDFCurves under Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(9), pages 2539-2562, July.
    2. Subash, N. & Singh, S.S. & Priya, Neha, 2011. "Extreme rainfall indices and its impact on rice productivity--A case study over sub-humid climatic environment," Agricultural Water Management, Elsevier, vol. 98(9), pages 1373-1387, July.
    3. Unknown, 2000. "Name Index," 2000 Conference, August 13-18, 2000, Berlin, Germany 197276, International Association of Agricultural Economists.
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    Cited by:

    1. Fahad Alzahrani & Ousmane Seidou & Abdullah Alodah, 2022. "Assessment and Improvement of IDF Generation Algorithms Used in the IDF_CC Tool," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(12), pages 4591-4606, September.
    2. Martín Montenegro & Daniel Mendoza & Diego Mora & Fernando García & Alex Avilés, 2022. "Extreme Rainfall Variations Under Climate Change Scenarios. Case of Study in an Andean Tropical River Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(15), pages 5931-5944, December.
    3. Subhra Sekhar Maity & Rajib Maity, 2022. "Changing Pattern of Intensity–Duration–Frequency Relationship of Precipitation due to Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5371-5399, November.
    4. M. Bermúdez & L. Cea & E. Van Uytven & P. Willems & J.F. Farfán & J. Puertas, 2020. "A Robust Method to Update Local River Inundation Maps Using Global Climate Model Output and Weather Typing Based Statistical Downscaling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(14), pages 4345-4362, November.
    5. Marzieh Mokarram & Tam Minh Pham, 2023. "Prediction of drought-driven land use/land cover changes in the Bakhtegan Lake watershed of Iran using Markov chain cellular automata model and remote sensing data," 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. 116(1), pages 1291-1314, March.

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