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Optimal Parameter Estimation of Conceptually-Based Streamflow Models by Time Series Aggregation

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Book cover Stochastic and Statistical Methods in Hydrology and Environmental Engineering

Part of the book series: Water Science and Technology Library ((WSTL,volume 10/3))

Abstract

In the framework of an integrated use, among different scales, of conceptually-based stochastic models of streamflows, some points related to efficient parameter estimation are discussed in this paper. Two classes of conceptual-stochastic models, ARMA and Shot Noise, are taken under consideration as equivalent to a conceptual system transforming the effective rainfall into runoff. Using these models, the possible benefits of data aggregation with regards to parameter estimation are investigated by means of a simulation study. The application made with reference to the ARMA(1,1) model shows advantageous effects of data aggregation, while the same benefits are not found for estimation of the conceptual parameters with the corresponding Shot Noise model.

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References

  • Bartolini, P. and J.D. Salas (1993) “Modeling of streamflow processes at different time scales”, Water Resour. Res., 29 (8), 2573–2587.

    Article  Google Scholar 

  • Benjamin, J.R. and C.A. Cornell (1970) Probability, Statistics and Decision for Civil Engineers, Mc. Graw Hill Book Co., New York.

    Google Scholar 

  • Box, G.E. and G. Jenkins (1970). Time Series Analysis, Forecasting and Control. Holden-Day, San Francisco (Revised Edition 1976 ).

    Google Scholar 

  • Bernier, J. (1970) “Inventaire des Modeles des Processus Stochastiques applicables a la Description des Debits Journaliers des Rivieres”, Rev. Int. Stat. Inst., 38, 49–61.

    Google Scholar 

  • Claps,P. e F. Rossi (1992) “A conceptually-based ARMA model for monthly streamflows”, in J.T. Kuo and G.F.Lin (Eds.) Stochastic Hydraulics ‘82, Proc. of the Sixth IAHR Intl. Symp. on Stochastic Hydraulics, Dept. of Civil Engrg., NTU, Taipei (Taiwan), 817–824.

    Google Scholar 

  • Claps, P. (1992) “Sulla validazione di un modello dei deflussi a base concettuale”, Proc. XXIII Conf. Hydraul. and Hydraul. Struct., Dept. Civil Eng., Univ. of Florence, D.91-D.102.

    Google Scholar 

  • Claps, P. and F. Murrone (1993) “Univariate conceptual-stochastic models for spring runoff simulation”, in M.H. Hamza (Ed.) Modelling and Simulation, Proc. of the XXIV TASTED Annual Pittsburgh Conference, May 10–12, 1993, Pittsburgh, USA, 491–494.

    Google Scholar 

  • Claps, P., F. Rossi and C. Vitale (1993) “Conceptual-stochastic modeling of seasonal runoff using Autoregressive Moving Average models and different scales of aggregation”, Water Resour. Res., 29 (8), 2545–2559.

    Article  Google Scholar 

  • Cowpertwait, P.S.P. and P.E. O’Connell (1992) “A Neyman Scott shot noise model for the generation of daily streamflow time series”, in J.P. O’Kane (Ed.) Advances in Theoretical Hydrology, Part A, chapter 6, Elsevier, The Netherlands.

    Google Scholar 

  • Jakeman, A.J. and G.M. Hornberger (1993) “How much complexity is warranted in a rainfall-runoff model?”, Water Resour. Res., 29 (8), 2637–2649.

    Article  Google Scholar 

  • Kavvas, M.L., L.J. Cote and J.W. Delleur (1977) “Time resolution of the hydrologic time-series models”, Journal of Hydrology, 32, 347–361.

    Article  Google Scholar 

  • Kron W, Plate E.J. and Ihringer J. (1990) “A Model for the generation of simultaneous daily discharges of two rivers at their point of confluence”, Stochastic Hydrol. and Hydraul., (4), 255–276.

    Google Scholar 

  • Obeysekera, J.T.B. and J.D. Salas (1986) “Modeling of aggregated hydrologic time series”, Journal of Hydrology, 86, 197–219.

    Article  Google Scholar 

  • O’Connell, P.E. (1971) “A simple stochastic modeling of Hurst’s law”, Int. Symp. on Math. Models in Hydrology, Int. Ass. Hydrol. Sci. Warsaw.

    Google Scholar 

  • Murrone, F., F. Rossi and P. Claps (1992). “A conceptually-based multiple shot noise model for daily streamflows”, in J.T. Kuo and G.F.Lin (Eds.) Stochastic Hydraulics ‘82, Proc. of the Sixth IAHR Intl. Symp. on Stochastic Hydraulics, Dept. of Civil Engrg., NTU, Taipei (Taiwan R.O.C.), 857–864.

    Google Scholar 

  • Rossi,F. and G. Silvagni (1980). “Analysis of annual runoff series”, Proc. Third IAHR Int. Symp. on Stochastic Hydraulics, Tokio, A-18(1–12).

    Google Scholar 

  • Salas, J.D. and R.A. Smith (1981) “Physical basis of stochastic models of annual flows”, Water Resour. Res., 17 (2), 428–430.

    Article  Google Scholar 

  • Salas J.D., Delleur J.W., Yevjevic V. and Lane W.L. (1980). Applied Modeling of Hydrologic Time Series. Water Resources Publications, Littleton, Colorado.

    Google Scholar 

  • Vecchia, A.V., J.T.B.Obeysekera, J.D. Salas and D.C. Boes (1983) “Aggregation and estimation of low-order periodic ARMA models”, Water Resour. Res., 19 (5), 1297–1306.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Dept. of Environm. Engineering and Physics, University of Basilicata Via della Tecnica, 3 Potenza, 85100, Italy

    P. Claps

  2. Dept Hydraul., Wat. Resour Manag. and Environm. Eng, Univ. of Naples “Federico II” Via Claudio, 21 Napoli, 80126, Italy

    F. Murrone

Authors
  1. P. Claps
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  2. F. Murrone
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Editor information

Editors and Affiliations

  1. Departments of Systems Design Engineering and Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada

    Keith W. Hipel

  2. Department of Statistical and Actuarial Sciences, The University of Western Ontario, London, Ontario, Canada

    A. Ian McLeod

  3. Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada

    A. Ian McLeod

  4. Department of Civil Engineering, Lakehead University, Thunder Bay, Ontario, Canada

    U. S. Panu

  5. Department of Civil Engineering, Louisiana State University, Baton Rouge, Louisiana, USA

    Vijay P. Singh

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© 1994 Springer Science+Business Media Dordrecht

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Claps, P., Murrone, F. (1994). Optimal Parameter Estimation of Conceptually-Based Streamflow Models by Time Series Aggregation. In: Hipel, K.W., McLeod, A.I., Panu, U.S., Singh, V.P. (eds) Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Water Science and Technology Library, vol 10/3. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-3083-9_30

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  • DOI: https://doi.org/10.1007/978-94-017-3083-9_30

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4379-5

  • Online ISBN: 978-94-017-3083-9

  • eBook Packages: Springer Book Archive

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