Skip to main content

Part of the book series: Nato Science Series ((NAIV,volume 23))

Abstract

A multitude of environmental processes embody both the elements of chance and the descriptive laws of physics. Excessive process description at one scale is lost through the processes of integration in time and space and through averaging. This justifies simplification in representation of the processes. It is hypothesized that if an environmental process is described by a linear or linearized governing equation, then the solution of this equation for a unit impulse (or Dirac delta) function can be interpreted as a probability density function for describing the probabilistic properties of the process. This hypothesis is tantamount to mapping from the unit impulse response function (UIR)h(t)to the probability density function (PDF)f(x)wherehis UIR as a function of time or space variable denoted bytandfis the PDF as a function of the random variable of the process. For example, the impulse response of a diffusion equation for pollutant transport described by space-time variation of concentration can be used as a probability distribution for pollutant concentration in a medium, such as a river, lake, tube, storm water, soil, or saturated geologic formation. Likewise, the impulse response of a linearized diffusion model of channel flow can be interpreted as a probability distribution for frequency analysis of extreme values (such as floods, droughts, hurricanes, earthquakes, and so on). Similarly, the impulse response of a linear reservoir can be used as an exponential probability distribution model. The impulse response of a cascade of linear reservoirs is the gamma distribution which has a number of applications in environmental data analysis. In this vein, a number of impulse responses of physically-based equations which apply to environmental processes and data are discussed and illustrated using field or laboratory data.

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

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Deymie, P. (1939) Propagation d’une intumescence allongee (Problem aval) [Propagation of an elongated intumescence]Proc. 5“’ International Cong. Appl. Mech., New York, pp.537–544.

    Google Scholar 

  2. Masse, P. (1939) Recherches sur la theorie des eaux courantes [Researches on the theory of water currents], Proc. 5’h Internat!. Cong. Appl. Mech., New York, pp. 545–549.

    Google Scholar 

  3. Dooge, J.C.I. and Harley, B.M. (1967) Linear routing in uniform open channelsProc. hut. Hydro!. Symp. Fort Collins. Co., Sept.1967, Paper No.8, 1, 57–63.

    Google Scholar 

  4. Dooge,.LC1., Napiorkowski J.J., and Strupezewski, W.G. (1987a) The linear downstream response of a generalized uniform channelActa Geoph. Pol.35, 277–291.

    Google Scholar 

  5. Dooge,.I.C.I., Napiorkowski, J.J.,and Strupczewski, W.G. (1987b) Properties of the general downstream channel response, ActaGeoph.Pol.35, 405–418.

    Google Scholar 

  6. Singh, V.P. (1996)Kinematic Wave Modeling in Water Resources: Surface Water HydrologyJohn Wiley & Sons, New York.

    Google Scholar 

  7. .Hayami, S. (1951) On the propagation of flood wavesKyoto Univ. Japan Disaster Prevention Res. Inst. Bull. 1 1-16.

    Google Scholar 

  8. Dooge, J.C.I. (1973)Linear Theory of Hydrologic Systems Tech. Bull.1468, Agricultural Research Service, Washington.

    Google Scholar 

  9. Strupczewski, W.G. and Napiorkowski, J.J. (1989)Properties of the distributed Muskingum model, Acta Geoph. Pol.V.XXXVII, 3–4, 3–4.

    Google Scholar 

  10. Moore, R.i. and Clarke, R.T. (1983) A distributed function approach to modeling basin sediment yieldJ. Hydrol.65, 239–257.

    Article  Google Scholar 

  11. Moore, R.J. (1984) A dynamic model of basin sediment yieldWater Resour. Res.20 (1), 89–103.

    Article  Google Scholar 

  12. Cox, D.R. and Miller, H.D. (1965)The Theory of Stochastic ProcessesChapman and Hall, London.

    Google Scholar 

  13. Tweedie, M.C.K. (1957) Statistical properties of the inverse Gaussian distributionsI. Ann. Math. Stat.28, 362–377.

    Article  Google Scholar 

  14. Johnston, N.L. and Kotz, S. (1970)Distribution in Statistics: Continuous Univariate Distributions1., Houghton-Mifflin, Boston, Mass.

    Google Scholar 

  15. Folks, J.L. and Chhikara, R.S. (1978) The inverse Gaussian distribution and its statistical application - a reviewJ.R.Stat. Soc. Ser. B.40(3), 263–289.

    Google Scholar 

  16. Strupczewski, W.G., Singh, V.P., and Weglarczyk, S. (2001) Impulse response of linear diffusion analogy as a flood probability density functionHydrol. Sc. J.46(5), 761–780.

    Article  Google Scholar 

  17. Strupczewski, W.G. and Napiorkowski, J.J. (1990a) Linear flood routing model for rapid flowHydrol. Sc. J.35, 1, 2, 49–64.

    Article  Google Scholar 

  18. Lighthill, M. H. and Witham, G.B. (1955) On kinematic waves. I. Flood movements in long riversProc. R. Soc. London Ser. A229, 281–316.

    Article  Google Scholar 

  19. Strupczewski, W.G., Napiorkowski, J.J., and Dooge, J.C.I. (1989) The distributed Muskingum modelJ. of Hydrol.111, 235–257.

    Article  Google Scholar 

  20. Strupczewski, W.G. and Napiorkowski, J.J. (1990b) What is the distributed Muskingum model?Hydrol. Sc. J.35, 1, 2, 65–78.

    Article  Google Scholar 

  21. Einstein HA. (1942)Formulas for the Transportation of Bed LoadTransactions ASCE, Paper No.2140, pp.561–597.

    Google Scholar 

  22. Eagleson, P.S. (1978) Climate, soil and vegetation. 2. The distribution of annual precipitation derived from observed storm sequencesWater Resour. Res.14(5), 713–721.

    Article  Google Scholar 

  23. Scott, E.J. (1955)Transform Calculus with an Introduction to Complex VariablesHarper&Brothers, New York, NY, pp. 71–73.

    Google Scholar 

  24. Özisik, M.N. (1968)Boundary Value Problems of Heat ConductionInternational Textbook Co., Scranton, PA, pp. 48–79.

    Google Scholar 

  25. Cleary, R.W. and Adrian, D.D. (1973) New Analytical Solutions for Dye Diffusion EquationsJournal of the Environmental Engineering Division ASCE99 (EE3), 213–227.

    Google Scholar 

  26. Jennings, M.E. and Benson M.A. (1969) Frequency curve for annual flood series with some zero events or incomplete dataWater Resour. Res.5(1), 276–280.

    Article  Google Scholar 

  27. Woo, M.K. and Wu, K. (1989) Fitting annual floods with zero flowsCan. Water Resour. J.14(2), 10–16.

    Article  Google Scholar 

  28. Wang, S.X. and Singh, V.P. (1995) Frequency estimation for hydrological samples with zero valueJ. of Water Resour. Planning and Management ASCE121(1), 98–108.

    Google Scholar 

  29. Rao, A.R. and Flamed, K.H. (2000)Flood Frequency AnalysisCRC Press, Boca Raton, Florida.

    Google Scholar 

  30. Freeze, R.A. (1975) A stochastic-conceptual analysis of one-dimensional groundwater flow in nonuniform homogenous mediaWater Resour. Res.11(5), 725–741.

    Article  Google Scholar 

  31. Chow, V.T. (1954) The log-probability law and its engineering applicationsProc. Am. Soc. Civ. Eng80, 1–25.

    Google Scholar 

  32. Kuczera, G. (1982) Robust flood frequency modelsWater Resour. Res.18(2), 315–324.

    Article  Google Scholar 

  33. Strupczewski, W.G., Singh, V.P., and Weglarczyk, S. (2002a) Asymptotic bias of estimation methods caused by the assumption of false probability distributionJ. of Hydrol.258, 122–148.

    Article  Google Scholar 

  34. Kendall, M.G. and Stuart, A. (1969)The Advanced Theory of Statistics V I. Distribution TheoryCharles Griffin&Comp. Limited,London.

    Google Scholar 

  35. Strupczewski, W.G., Singh, V.P., and Weglarczyk, S.(2002b) Physically based model of discontinuous distribution for hydrological samples with zero values, in Singh, Al-Rashed & Sherif (eds.)Proc. of the Int. Conf on Water Resources Management in Arid RegionsA.A. Balkema Publishers,Swets & Zeitlinger, Lisse, 523–537.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Strupczewski, W.G., Singh, V.P., Weglarczyk, S. (2003). Physics of Environmental Frequency Analysis. In: Harmancioglu, N.B., Ozkul, S.D., Fistikoglu, O., Geerders, P. (eds) Integrated Technologies for Environmental Monitoring and Information Production. Nato Science Series, vol 23. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0231-8_12

Download citation

  • DOI: https://doi.org/10.1007/978-94-010-0231-8_12

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-1399-7

  • Online ISBN: 978-94-010-0231-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics