Zobrazeno 1 - 10
of 25
pro vyhledávání: '"James McCreight"'
Publikováno v:
Frontiers in Water, Vol 4 (2023)
Externí odkaz:
https://doaj.org/article/33fd7e8f9142442c9a6faec28a01629f
Autor:
Seong Jin Noh, Timothy J. Hoar, Benjamin K. Johnson, Mohamad El Gharamti, James McCreight, A. Rafieeinasab
Publikováno v:
Hydrology and Earth System Sciences, Vol 25, Pp 5315-5336 (2021)
Predicting major floods during extreme rainfall events remains an important challenge. Rapid changes in flows over short timescales, combined with multiple sources of model error, makes it difficult to accurately simulate intense floods. This study p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b12c55ccbd0d3afdede09a97e2886318
https://doi.org/10.5194/hess-25-5315-2021
https://doi.org/10.5194/hess-25-5315-2021
Accurate representation of channel properties is important for forecasting in hydrologic models, as it affects the height, celerity, and attenuation of flood waves. Yet, considerable uncertainty in the parameterization of channel geometry and hydraul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::210ce712f49e465beb8eb3120b0afd51
https://hess.copernicus.org/preprints/hess-2021-552/
https://hess.copernicus.org/preprints/hess-2021-552/
Hydrologic Model Parameter Estimation in Ungauged Basins Using Simulated SWOT Discharge Observations
Publikováno v:
Water Resources Research. 57
In situ gauge networks are often used in hydrological model calibration, but these networks are limited or nonexistent in many regions. The upcoming Surface Water Ocean Topography (SWOT) mission pr...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7bcab63e0972e62c7aa1c5439fa5ac9e
https://doi.org/10.1029/2021wr029655
https://doi.org/10.1029/2021wr029655
Autor:
Erin Towler, James McCreight
Publikováno v:
Hydrology and Earth System Sciences, Vol 25, Pp 2599-2615 (2021)
Streamflow timing errors (in the units of time) are rarely explicitly evaluated but are useful for model evaluation and development. Wavelet-based approaches have been shown to reliably quantify timing errors in streamflow simulations but have not be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b84c34f954479958d1a53992aa372de
https://hess.copernicus.org/articles/25/2599/2021/
https://hess.copernicus.org/articles/25/2599/2021/
Autor:
Timothy J. Hoar, James McCreight, A. Rafieeinasab, Benjamin K. Johnson, Seong Jin Noh, Mohamad El Gharamti
Predicting major floods during extreme rainfall events remains an important challenge. Rapid changes in flows over short time-scales combined with multiple sources of model error makes it difficult to accurately simulate intense floods. This study pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2acceb86d87bffe7c83b1766960955d9
https://doi.org/10.5194/hess-2020-642
https://doi.org/10.5194/hess-2020-642
Publikováno v:
IGARSS
The Surface Water Ocean Topography (SWOT) mission, launching next year, will provide high-spatial resolution measurements of terrestrial surface water, including global rivers with widths greater than 50–100 m. SWOT measurements are naturally suite
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58c4cd2743190f4dda08f094d76b7a72
https://doi.org/10.1109/igarss39084.2020.9323136
https://doi.org/10.1109/igarss39084.2020.9323136
Accurately estimating the snow water equivalent (SWE) that is stored in the worlds mountains remains a challenging and important unsolved problem. The SWE reconstruction approach, where the remotely sensed seasonal depletion of fractional snow-covere
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a81be9357cf1d212c99ab99a78d0b8dc
https://doi.org/10.5194/egusphere-egu2020-14969
https://doi.org/10.5194/egusphere-egu2020-14969
Autor:
Timothy J. Hoar, Jeffrey L. Anderson, Seong Jin Noh, Arezoo Arezoo Rfieeinasab, Moha El Gharamti, James McCreight, Brett Raczka, John C. Lin, Kevin Raeder, Jingjing LIang, Nancy Collins, Frédéric Castruccio
The Data Assimilation Research Testbed (DART) is a community facility for ensemble data assimilation developed and maintained by the National Center for Atmospheric Research (NCAR). DART provides ensemble data assimilation capabilities for NCAR commu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::77ea6ee891100d232e998b4940fef49c
https://doi.org/10.5194/egusphere-egu2020-3128
https://doi.org/10.5194/egusphere-egu2020-3128