Leveraging Next‐Generation Satellite Remote Sensing‐Based Snow Data to Improve Seasonal Water Supply Predictions in a Practical Machine Learning‐Driven River Forecast System

Abstract Seasonal predictions of spring‐summer river flow volume (water supply forecasts, WSFs) are foundational to western US water management. We test a new space‐based remote sensing product, spatially and temporally complete (STC) MODSCAG fractional snow‐covered area (fSCA), as input for the Nat...

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Autori principali:	Sean W. Fleming, Karl Rittger, Catalina M. Oaida Taglialatela, Indrani Graczyk
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Wiley 2024-04-01
Serie:	Water Resources Research
Soggetti:	remote sensing streamflow modeling snow monitoring water supply western US operational forecasting
Accesso online:	https://doi.org/10.1029/2023WR035785
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