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A univariate model for long-term streamflow forecasting

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Abstract

This paper, the first in a series of two, employs the principle of maximum entropy (POME) via maximum entropy spectral analysis (MESA) to develop a univariate model for long-term streamflow forecasting. Three cases of streamflow forecasting are investigated: forward forecasting, backward forecasting (or reconstruction) and intermittent forecasting (or filling in missing records). Application of the model is discussed in the second paper.

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Authors and Affiliations

  1. H. T. Harvey and Associates, 906 Elizabeth Street, P. O. Box 1180, 95002, Alviso, CA, USA

    P. F. Krstanovic

  2. Dept. of Civil Engineering, Louisiana State University, 70803-6405, Baton Rouge, LA, USA

    V. P. Singh

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  1. P. F. Krstanovic
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  2. V. P. Singh
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Krstanovic, P.F., Singh, V.P. A univariate model for long-term streamflow forecasting. Stochastic Hydrol Hydraul 5, 173–188 (1991). https://doi.org/10.1007/BF01544056

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