Probabilistic Seasonal Water Supply Forecasting in an Operational Environment: The USDA-NRCS Perspective
Publication: World Environmental and Water Resources Congress 2008: Ahupua'A
Abstract
The NRCS creates seasonal forecasts for rivers of the Western US. Although these forecasts are probabilistic, NRCS products often frame the forecasts in deterministic terms. The probabilistic aspects of the forecasts are derived from the jackknife (i.e. leave-one-out cross validation) standard error of the statistical forecasting equations. Statistical techniques are believed to produce probabilistic forecasts with excellent reliability (i.e. the width of the forecast distribution is appropriately wide to reflect the uncertainty in the forecasts). In contrast, forecasts resulting from the use of simulation modeling techniques are not reliable unless all sources of uncertainty are accounted for. Current techniques mostly only consider future climate uncertainty. Accounting for remaining uncertainties requires the use of probabilistic parameters, multiple models and pre- and post- processing using retrospective forecasts. Finally, effective communication of uncertain information remains a critically important but under-researched topic.
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Copyright
© 2008 American Society of Civil Engineers.
History
Published online: Apr 26, 2012
ASCE Technical Topics:
- Climates
- Continuum mechanics
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Environmental engineering
- Errors (statistics)
- Forecasting
- Mathematics
- Models (by type)
- Motion (dynamics)
- Probability
- River engineering
- Rivers and streams
- Seasonal variations
- Simulation models
- Solid mechanics
- Statistics
- Uncertainty principles
- Water and water resources
- Water management
- Water supply
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