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Activity Number:
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218
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #303432 |
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Title:
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Inter-Annual Modeling and Seasonal Forecasting of Intermountain Snowpack Dynamics
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Author(s):
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James B. Odei*+ and Mevin B. Hooten and Jiming Jin
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Companies:
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Utah State University and Utah State University and Utah State University
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Address:
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3900 Old Main Hill, Logan, UT, 84322,
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Keywords:
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Bayesian Model ; Empirical Orthogonal Functions ; SNOTEL ; Snow Water Equivalent ; Spatio-Temporal Model
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Abstract:
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Due to a continual increase in the demand for water as well as an ongoing regional drought, there is an imminent need to monitor and forecast water resources in the Western United States. In particular, water resources in the Intermountain West rely heavily on snow water storage, thus seasonal forecasts of snowpack would allow water resources to be more e?ectively managed throughout the entire water year. Many available models either require delicate calibrations, are inappropriate at certain scales, or only correspond to either the temporal or spatial domain. We present a data-based statistical model that characterizes seasonal snow water equivalent in terms of a nested time-series with the large scale focusing on the interannual periodicity of dominant signals and the small scale accommodating seasonal noise and autocorrelation. We use SNOTEL data to implement and validate this model
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