Near‐term forecasts of stream temperature using deep learning and data assimilation in support of management decisions
Open Access
- 27 December 2022
- journal article
- research article
- Published by Wiley in Jawra Journal of the American Water Resources Association
- Vol. 59 (2), 317-337
- https://doi.org/10.1111/1752-1688.13093
Abstract
No abstract availableKeywords
This publication has 49 references indexed in Scilit:
- On improving the communication between models and dataPlant, Cell & Environment, 2013
- Scaling the gas transfer velocity and hydraulic geometry in streams and small riversLimnology and Oceanography: Fluids and Environments, 2012
- Development of gridded surface meteorological data for ecological applications and modellingInternational Journal of Climatology, 2011
- Warming alters the metabolic balance of ecosystemsPhilosophical Transactions B, 2010
- A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models1Jawra Journal of the American Water Resources Association, 2009
- Data assimilation methods in the Earth sciencesAdvances in Water Resources, 2008
- Ecological Forecasts: An Emerging ImperativeScience, 2001
- Global Water Resources: Vulnerability from Climate Change and Population GrowthScience, 2000
- Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statisticsJournal of Geophysical Research: Oceans, 1994
- Learning representations by back-propagating errorsNature, 1986