Skip to main content
SpringerLink
Log in

Analyzing Non-stationarity in the Hyderabad City Rainfall Intensity-Duration-Frequency Curves

  • Conference paper
  • First Online:
Climate Change Impacts

Part of the book series: Water Science and Technology Library ((WSTL,volume 82))

Abstract

The infrastructure design is primarily based on rainfall intensity-duration-frequency (IDF) curves and the current IDF curves are based on the concept of stationary extreme value theory (i.e. occurrence probability of extreme precipitation is not expected to change significantly over time). But, the extreme precipitation events are increasing due to global climate change and questioning the reliability of our current infrastructure design. In this study, the trend in Hyderabad city 1-, 2-, 3-, 6-, 12-, 24- and 48-h duration annual maximum rainfall series are analyzed using the Mann–Kendall (M–K) test, and a significant increasing trend is observed. Further, based on recent theoretical developments in the extreme value theory (EVT), non-stationary rainfall IDF curve for the Hyderabad city is developed by incorporating linear trend in the location parameter of the generalized extreme value (GEV) distribution. The study results indicate that the IDF curves developed under the stationary assumption are underestimating the precipitation extremes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Agilan V, Umamahesh NV (2015a) Effect of el Niño-southern oscillation (ENSO) cycle on extreme rainfall events of Indian urban area Vellore. In: proceedings of international conference on sustainable energy and built environment, pp. 569–573

    Google Scholar 

  • Agilan V, Umamahesh NV (2015b) Detection and attribution of non-stationarity in intensity and frequency of daily and 4-h extreme rainfall of Hyderabad, India. J Hydrol 530:677–697

    Article  Google Scholar 

  • Bayazit M, Önöz B (2007) To prewhiten or not to prewhiten in trend analysis? Hydrol Sci J 52(4):611–624

    Article  Google Scholar 

  • Bouza-Deaño R, Ternero-Rodríguez M, Fernández-Espinosa AJ (2008) Trend study and assessment of surface water quality in the Ebro river (Spain). J Hydrol 361(3–4):227–239

    Article  Google Scholar 

  • Burian SJ, Shepherd JM (2005) Effect of urbanization on the diurnal rainfall pattern in Houston. Hydrol Process 19:1089–1103

    Google Scholar 

  • Cheng L, AghaKouchak A (2014). Nonstationary precipitation intensity-duration-frequency curves for infrastructure design in a changing climate. Nat: Sci Rep (4):7093

    Google Scholar 

  • Cheng L, Kouchak AA, Gilleland E, Katz RW (2014) Non-stationary extreme value analysis in a changing climate. Clim Change 127:353–369

    Article  Google Scholar 

  • Coles S (2001) An introduction to statistical modelling of extreme values. Springer, London

    Book  Google Scholar 

  • Endreny TA, Imbeah N (2009) Generating robust rainfall intensity–duration–frequency estimates with short-record satellite data. J Hydrol 371:182–191

    Article  Google Scholar 

  • Jakob D (2013) Nonstationarity in extremes and engineering design. In: AghaKouchak A et al (eds) Extremes in a changing climate: detection, analysis and uncertainty. Springer, Dordrecht, pp 363–417

    Chapter  Google Scholar 

  • Katz RW (2013) Statistical methods for nonstationary extremes. In: Kouchak AA et al (eds) Extremes in a changing climate: detection, analysis and uncertainty. Springer, Dordrecht, pp 15–37

    Chapter  Google Scholar 

  • Kendall M (1962) Rank correlation methods, 3rd edn. Hafner Publishing Company, New York

    Google Scholar 

  • Kishtawal CM et al (2009) Urbanization signature in the observed heavy rainfall climatology over India. Int J Climatol 30(13)

    Google Scholar 

  • Kunkel KE et al (2013) Probable maximum precipitation and climate change. Geophys Res Lett 40:1402–1408

    Article  Google Scholar 

  • Lei M et al (2008) Effect of explicit urban land surface representation on the simulation of the 26 July 2005 heavy rain event over Mumbai. India Atmos Chem Phys 8:5975–5995

    Article  Google Scholar 

  • Mann HB (1945) Nonparametric tests against trend. J Econ Soci 13(3):245–259

    Google Scholar 

  • Miao S, Chen F, Fan QL (2011) Impacts of urban processes and urbanization on summer precipitation: a case study of heavy rainfall in Beijing on 1 August 2006. J Appl Meteor Climatol 50(4):806–825

    Article  Google Scholar 

  • Peel MC, Finlayson BL, McMahon TA (2007) Updated world map of the Koppen-Geiger climate classification. Hydrol Earth Syst Sci 11:1633–1644

    Article  Google Scholar 

  • Revadekar JV, Kulkarni A (2008) The El Nino-Southern oscillation and winter precipitation extremes over India. Int J Climatol 28:1445–1452

    Article  Google Scholar 

  • Rosner A, Vogel RM, Kirshen PH (2014) A risk-based approach to flood management decisions in a nonstationary world. Water Resour Res 50:1928–1942

    Article  Google Scholar 

  • Sugahara S, Rocha RP, Silveira R (2009) Non-stationary frequency analysis of extreme daily rainfall in Sao Paulo, Brazil. Int J Climatol 29:1339–1349

    Google Scholar 

  • Tramblay Y, Neppel L, Carreau J, Sanchez-Gomez E (2012) Extreme value modelling of daily areal rainfall over Mediterranean catchments in a changing climate. Hydrol Process 26(25):3934–3944

    Article  Google Scholar 

  • Villafuerte MQ, Matsumoto J (2015) Significant Influences of global mean temperature and ENSO on extreme rainfall in Southeast Asia. J Climate 28:1905–1919

    Article  Google Scholar 

  • Villarini G, Serinaldi F, Smith JA, Krajewski WF (2009) On the stationarity of annual flood peaks in the continental United States during the 20th century. Water Resour Res 45:W08417

    Google Scholar 

  • von Storch H (1995) Misuses of statistical analysis in climate research. In: von Storch H, Navarra A (eds) Analysis of climate variability: applications of statistical techniques. Springer, New York, pp 11–26

    Chapter  Google Scholar 

  • Westra S, Alexander LV, Zwiers FW (2013) Global increasing trends in annual maximum daily precipitation. J Clim 26(11):3904–3918

    Article  Google Scholar 

  • Xu L et al (2015) Precipitation trends and variability from 1950 to 2000 in arid lands of Central Asia. J Arid Land 7(4):514–526

    Article  Google Scholar 

  • Yilmaz AG, Perera JC (2014) Extreme rainfall nonstationary investigation and intensity–frequency–duration relationship. J Hydrol Eng 19(6):1160–1172

    Article  Google Scholar 

  • Yue S, Pilon P, Cavadias G (2002) Power of the Mann-Kendall and Spearman’s rho tests for detecting monotonic trends in hydrological series. J Hydrol 259(1–4):254–271

    Article  Google Scholar 

  • Zahmatkesh Z, Karamouz M, Goharian E, Burian SJ (2015) Analysis of the effects of climate change on urban storm water runoff using statistically downscaled precipitation data and a change factor approach. J Hydrol Eng 27(7):0501–4022

    Google Scholar 

Download references

Acknowledgements

This work is supported by Information Technology Research Academy (ITRA), Government of India under, ITRA-water grant ITRA/15(68)/water/IUFM/01. We also thank the India Meteorological Department for providing rainfall data.

Author information

Authors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology Warangal, Warangal, 506004, Telangana, India

    V. Agilan & N. V. Umamahesh

Authors
  1. V. Agilan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. N. V. Umamahesh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to N. V. Umamahesh .

Editor information

Editors and Affiliations

  1. Department of Biological and Agricultural Engineering, and Zachry Department of Civil Engineering, Texas A&M University, College Station, Texas, USA

    Vijay P Singh

  2. Department of Civil Engineering, AISECT University, Bhopal, Madhya Pradesh, India

    Shalini Yadav

  3. AISECT University, Hazaribagh, Jharkhand, India

    Ram Narayan Yadava

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Agilan, V., Umamahesh, N.V. (2018). Analyzing Non-stationarity in the Hyderabad City Rainfall Intensity-Duration-Frequency Curves. In: Singh, V., Yadav, S., Yadava, R. (eds) Climate Change Impacts. Water Science and Technology Library, vol 82. Springer, Singapore. https://doi.org/10.1007/978-981-10-5714-4_9

Download citation

Publish with us

Policies and ethics

Search

Navigation