Improving national water modeling: an intercomparison of two high-resolution, continental scale models, ParFlow-CONUS and WRF-Hydro configuration of the National Water Model - POSTERS
|Authors:||Danielle Tijerina Laura Condon Katelyn FitzGerald Wei Yu Aubrey Dugger David Gochis Reed Maxwell|
|Resource type:||Composite Resource|
|Storage:||The size of this resource is 8.6 MB|
|Created:||Jan 10, 2019 at 8:43 p.m.|
|Last updated:|| May 21, 2019 at 5:20 p.m.
|Citation:||See how to cite this resource|
These posters are work completed during my masters program at the Colorado School of Mines in Golden, CO and under the advising of Dr. Reed Maxwell. The posters were presented at the European Geophysical Union in Vienna, Austria (April 2018) and Computational Methods in Water Resources in St. Malo, France (May 2018) conferences.
Development of integrated hydrology modeling systems, where subsurface, land-surface, and energy budget processes are represented, is an increasing trend. In hydrologic science, there is a need for more intricate models for comprehensive hydrologic forecasting and water management over large spatial areas, specifically the Continental US (CONUS). We compare streamflow output from two models developed for the CONUS: ParFlow-CONUS, using the integrated model ParFlow and WRF-Hydro.NWM, a configuration of the National Water Model version 1.2 using the National Center for Atmospheric Research, Weather Research and Forecasting hydrological modeling extension package WRF-Hydro. Accurately representing large domains remains a challenge considering the difficult task of representing complex hydrologic processes, computational expense, and extensive data needs. Intercomparing models helps disentangle process, parameter, and formulation differences. Results show that WRF-Hydro.NWM and PF-CONUS generally capture flow magnitude, but WRF-Hydro.NWM better captures flow timing. Spatial differences exist as well—both models accurately simulate the humid east, but struggle with the Great Plains and intermountain west. Simulations such as these will help improve physical process representation in hydrologic models and give greater confidence in large-scale forecasts.
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This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|Department of Energy|
|American Association of University Women||Selected Professions Fellowship|
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