Stochastic Hydrology and Hydraulics

, Volume 2, Issue 3, pp 189–200 | Cite as

A continous point process model for daily rainfall

  • W. Najem
Originals
Accepted:

Abstract

A probabilistic model for the temporal description of daily rainfall at a fixed point is presented. The model is a member of the family of point process models. Model development is based on statistics estimated from rainfall data in Lebanon. Scale considerations for Markovian models and a theory of projection are used to determine the continuous process of alternation between dry and wet periods. The wet spells are defined by a number of storms each of which is associated with a storm depthYi and an interstorm time intervalTi. Computational results are presented for data from Lebanon. The model is successful in preserving the structure of the occurrence process, as well as the distributional properties of the rainfall amount.

Key words

Point process rainfall model renewal Cox process 
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Caskey, J.E. 1963. A Markov chain model for the probability of precipitation occurrence in intervals of various length. Monthly Weather Review. 298–301Google Scholar
  2. Catafago, S.; Najem, W. 1976: Contribution a L'etude de la pluviometrie Libanaise. These de Doctorat presentee a l' Universite des Sciences et Techniques du Languedoc, Montpellier, FranceGoogle Scholar
  3. Chang, T.J.; Kavvas, M.L.; Delleur, J.W. 1984: Daily precipitation modeling by discrete autoregressive moving average processes. Water Resour. Res. 20, 565–580Google Scholar
  4. Foufoula-Georgiou, E.; Lettenmair, D. 1987: A Markov renewal model for rainfall occurrences. Water Resour. Res. 23, 875–884Google Scholar
  5. Gabriel, K.R.; Neumann, J. 1962: A Markov chain model for daily rainfall occurrences at Tel Aviv. Quart. J. Royal Meteorol. Soc. 88, 90–95Google Scholar
  6. Haan, C.T.; Allen, D.M.; Street, J.O. 1981: A Markov chain model for daily rainfall. Water Resour. Res. 12, 443–449Google Scholar
  7. Kavvas, M.L.; Delleur, J.W. 1981: A stochastic cluster model for daily rainfall sequences. Water Resour. Res. 17, 1151–1160Google Scholar
  8. Le Cam, L. 1961: A stochastic description of precipitation. In: Neyman, J. (ed.) Fourth Berkeley Symposium on Mathematics Statistics, and Probability Proceedings. Berkeley: University of California PressGoogle Scholar
  9. Neyman, J.E.; Scott, E.L. 1958: A statistical approach to problems of cosmology. J.R. Stat. Soc. B. 20, 1–43Google Scholar
  10. Smith, J.A. 1987: Statistical modeling of daily rainfall occurrence. Water Resour. Res. 23, 885–893Google Scholar
  11. Smith, J.A.; Karr, A. 1983: A point process model of summer season rainfall occurrences. Water Resour. Res. 19, 95–103Google Scholar
  12. Todorovic, P.; Woolhiser, D. 1971: Stochastic model of daily rainfall. Paper presented at the U.S.D.A.-I.A.S.P.S. Symposium on Statistical Hydrology. Tucson, Ariz.Google Scholar

Copyright information

© Springer-Verlag 1988

Authors and Affiliations

  • W. Najem
    • 1
  1. 1.Ecole Superieure d'Ingenieurs de BeyrouthUniversité Saint JosephLebanon

Personalised recommendations