Flow-Conditioned Parameter Grids: A CONUS Hydrologic Parameter Dataset For Mechanistic, Statistical, and Machine Learning Models

Barnhart, Theodore B; Shultz, August R; Siefken, Seth; Sando, T. Roy; McCarthy, Peter

doi:10.6084/m9.figshare.12598568.v1

ESIP_CDI_FCPG_Poster.pdf (1.74 MB)

Flow-Conditioned Parameter Grids: A CONUS Hydrologic Parameter Dataset For Mechanistic, Statistical, and Machine Learning Models

poster

posted on 2020-07-06, 23:23 authored by Theodore B Barnhart, August R Shultz, Seth Siefken, T. Roy Sando, Peter McCarthy

Poster describing the creation and use of flow-conditioned parameter grids for mechanistic, statistical, and machine learning models. This presentation was given at the Earth Science Information Partners (ESIP) Summer Meeting held online in July 2020.

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modeling machine learning hydrology statistical modeling basin characteristics Numerical Modeling ESIP Summer 2020 Hydrology

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MIT

Flow-Conditioned Parameter Grids: A CONUS Hydrologic Parameter Dataset For Mechanistic, Statistical, and Machine Learning Models

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