4.7 Article

Modeling the influence of hypsometry, vegetation, and storm energy on snowmelt contributions to basins during rain-on-snow floods

Journal

WATER RESOURCES RESEARCH
Volume 51, Issue 10, Pages 8551-8569

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2014WR016576

Keywords

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Funding

  1. National Science Foundation [EAR-1215771]
  2. NASA Headquarters under the NASA Earth and Space Science Fellowship [NNX12AN53H]
  3. Directorate For Geosciences
  4. Division Of Earth Sciences [1215771] Funding Source: National Science Foundation

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Point observations and previous basin modeling efforts have suggested that snowmelt may be a significant input of water for runoff during extreme rain-on-snow floods within western U. S. basins. Quantifying snowmelt input over entire basins is difficult given sparse observations of snowmelt. In order to provide a range of snowmelt contributions for water managers, a physically based snow model coupled with an idealized basin representation was evaluated in point simulations and used to quantify the maximum basin-wide input from snowmelt volume during flood events. Maximum snowmelt basin contributions and uncertainty ranges were estimated as 29% (11-47%), 29% (8-37%), and 7% (2-24%) of total rain plus snowmelt input, within the Snoqualmie, East North Fork Feather, and Upper San Joaquin basins, respectively, during historic flooding events between 1980 and 2008. The idealized basin representation revealed that both hypsometry and forest cover of a basin had similar magnitude of impacts on the basin-wide snowmelt totals. However, the characteristics of a given storm (antecedent SWE and available energy for melt) controlled how much hypsometry and forest cover impacted basin-wide snowmelt. These results indicate that for watershed managers, flood forecasting efforts should prioritize rainfall prediction first, but cannot neglect snowmelt contributions in some cases. Efforts to reduce the uncertainty in the above snowmelt simulations should focus on improving the meteorological forcing data (especially air temperature and wind speed) in complex terrain.

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