Harnessing the Seasonal Predictability of Streamflow (Extended Abstract)

TitleHarnessing the Seasonal Predictability of Streamflow (Extended Abstract)
Publication TypeConference Proceedings
Year of Conference2016
AuthorsMendoza, Pablo, Vano Julie, Wood Andy, Clark Elizabeth, Nijssen Bart, Rothwell Eric, Clark Martyn, Brekke Levi, and Arnold Jeffrey
Conference Name84th Annual Western Snow Conference
Date Published2016
Conference LocationSeattle, Washington

In the western United States, most operational forecasts of seasonal streamflow either use: (i) regression equations based on in situ observations (e.g., snow water equivalent, rainfall) or (ii) hydrologic model simulations that employ current hydrologic conditions and historically observed weather sequences to generate an ensemble of possible futures (e.g., Ensemble Streamflow Prediction, ESP) (Day, 1985; Wood and Lettenmaier, 2006; Pagano et al, 2014;). In this project, we are developing a framework that includes benchmark forecasts and new techniques which include additional predictive information.  More specifically, the framework currently generates forecasts for a range of techniques (statistical, dynamical, and hybrid methods) that leverage predictability from both the land surface and climate