Articles | Volume 23, issue 5
https://doi.org/10.5194/hess-23-2439-2019
https://doi.org/10.5194/hess-23-2439-2019
Research article
 | 
21 May 2019
Research article |  | 21 May 2019

Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska

Katrina E. Bennett, Jessica E. Cherry, Ben Balk, and Scott Lindsey

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Cited articles

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Anderson, E. A.: Snow Accumulation and Ablation Model – SNOW-17, Nat. Weather Serv. NOAA, 44 pp., available at: http://www.nws.noaa.gov/oh/hrl/nwsrfs/users_manual/part2/_pdf/22snow17.pdf (last access: 17 August 2018), 2006. 
Andreadis, K. M. and Lettenmaier, D. P.: Assimilating remotely sensed snow observations into a macroscale hydrology model, Adv. Water Res., 29, 872–886, https://doi.org/10.1016/j.advwatres.2005.08.004, 2006. 
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Short summary
Remotely sensed snow observations may improve operational streamflow forecasting in remote regions, such as Alaska. In this study, we insert remotely sensed observations of snow extent into the operational framework employed by the US National Weather Service’s Alaska Pacific River Forecast Center. Our work indicates that the snow observations can improve snow estimates and streamflow forecasting. This work provides direction for forecasters to implement remote sensing in their operations.