TECHNICAL PAPERS
Oct 1, 1997

Mixing Probabilistic Meteorology Outlooks in Operational Hydrology

Publication: Journal of Hydrologic Engineering
Volume 2, Issue 4

Abstract

There are now several kinds of probabilistic meteorology outlooks available to the water resource engineer or hydrologist. These outlooks are defined over different time periods at different lag times, and they forecast either event probabilities or only most-probable events. An existing operational hydrology approach (for making hydrology outlooks) builds a set of hydrological possibilities from past meteorology to match forecast event probabilities, but it does not consider most-probable event forecasts. This approach is extended to mix both types of probabilistic meteorology outlooks in determining weights to apply to the set of hydrological possibilities to make hydrological outlooks. Boundary condition equations for the weights are constructed corresponding to forecast event probabilities, and boundary condition inequalities are constructed corresponding to forecast most-probable events. The inequalities are converted to equivalent equations through the introduction of additional variables. The resulting set of all boundary condition equations is solved for physically relevant values. The solution is an optimization problem for the general case, similar to earlier consideration of only forecast event probabilities. An example illustrates the concepts and methods.

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References

1.
Croley II, T. E.(1996). “Using NOAA's new climate outlooks in operational hydrology.”J. Hydrologic Engrg., ASCE, 1(3), 93–102.
2.
Croley II, T. E. (1997). “Water resource predictions from meteorological probability forecasts.”Sustainability of water resources under increasing uncertainty (Proc., Rabat Symp.), D. Rosbjerg et al., ed., IAHS Publication No. 240, IAHS Press, Wallingford, U.K., 301–310.
3.
Day, G. N.(1985). “Extended streamflow forecasting using NWSRFS.”J. Water Resour. Plng. and Mgmt., ASCE, 111, 157–170.
4.
Hillier, F. S., and Lieberman, G. J. (1969). Introduction to operations research—appendix 2: classical optimization techniques. Holden-Day, San Francisco, Calif.
5.
Smith, J. A., Day, G. N., and Kane, M. D.(1992). “Nonparametric framework for long-range streamflow forecasting.”J. Water Resour. Plng. and Mgmt., ASCE, 118(1), 82–92.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 2Issue 4October 1997
Pages: 161 - 168

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Published online: Oct 1, 1997
Published in print: Oct 1997

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Thomas E. Croley II
Res. Hydro., Great Lakes Envir. Res. Lab., 2205 Commonwealth Blvd., Ann Arbor, MI 48105-1593.

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