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United States Department of Agriculture

Agricultural Research Service

Title: Modelling snowmelt runoff

Authors
item Dewalle, David - PENNSYLVANIA STATE UNIV
item Rango, Albert

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: June 1, 2008
Publication Date: July 1, 2008
Citation: Dewalle, D., Rango, A. 2008. Modelling snowmelt runoff. In: Dewalle, D., Rango, A., editors. Principles of Snow Hydrology. Cambridge, NY: Cambridge University Press. p. 266-305.

Interpretive Summary: Interpretive summary not required.

Technical Abstract: Hydrologic models used to predict streamflow can be generally classified as either deterministic or stochastic and as either lumped-parameter or distributed (Beven 2000). Deterministic models predict a single value of streamflow from a given set of input variables, while stochastic models predict a range of possible outcomes based upon the statistical distributions of input variables. Nearly all of the snowmelt models used to continuously predict streamflow from snowmelt are deterministic, but a type of statistical model has been historically used to great advantage to predict seasonal totals of streamflow using measured snowpack and precipitation data each spring. These models are in widespread use in the western United States to forecast spring runoff.

Last Modified: 11/1/2014