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|Resource type:||Collection Resource|
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|Created:||Apr 06, 2021 at 3:10 a.m.|
|Last updated:|| Oct 12, 2021 at 3:56 a.m.
|Citation:||See how to cite this resource|
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The overall goal of this collection is to use the basic strategy and architecture presented by Choi et al. (2021) to make components of a modern and complex hydrologic study (VBstudy; Van Beusekom et al., 2021) easier to reproduce.
In VBstudy, hydrological outputs from the SUMMA model for the 671 CAMELS catchments across the contiguous United States (CONUS) are investigated to understand their dependence on input forcing behavior across CONUS. VBstudy layes out a simple methodology that can be applied to understand the relative importance of seven model forcings (precipitation rate, air temperature, longwave radiation, specific humidity, shortwave radiation, wind speed, and air pressure).
Choi et al. (2021) integrated three components through seamless data transfers for a reproducible research: (1) online data and model repositories; (2) computational environments leveraging containerization and self-documented computational notebooks; and (3) Application Programming Interfaces (APIs) that provide programmatic control of complex computational models.
Therefore, in the current research, we integrated the following three components through seamless data transfers to make components of a modern and complex hydrologic study (VBstudy) easier to reproduce:
(1) HydroShare as online data and model repository;
(2) CyberGIS-Jupyter for Water for self-documented computational notebooks as computational environment (with and without HPC notebooks);
(3) pySUMMA as Application Programming Interfaces (APIs) that provide programmatic control of complex computational models.
This collection includes three resources:
1- First resource, provides the entire NLDAS forcing datasets used in the paper.
2- Second resource provides an end-to-end workflow of CAMELS basin modeling with SUMMA for the paper simulations configured for execution in connected JupyterHub compute platforms. This resource is well-suited for a smaller scale exploration: it explores one example CAMELS site and a period of 18-month simulation to only demonstrate the capabilities of the notebooks.
3- Third resource, however, uses HPC (High-Performance Computing) through CyberGIS Computing Service. The HPC enables a high-speed running of simulations which makes it suitable for running larger simulations (even as large as the entire 671 CAMELS sites and the whole 60-month simulation period used in the VBstudy) practical and much faster than the second resource.
Greater details can be found in each resource.
Resource Level Coverage
|Add||Title||Type||Owners||Sharing Status||My Permission||Remove|
|NLDAS Forcing NetCDF using CAMELS datasets from 1980 to 2018||CompositeResource||Young-Don Choi||Public & Shareable||Open Access|
|SUMMA Simulations using CAMELS Datasets on CyberGIS-Jupyter for Water||CompositeResource||Bart Nijssen||Public & Shareable||Open Access|
|SUMMA Simulations using CAMELS Datasets for HPC use with CyberGIS-Jupyter for Water||CompositeResource||Iman Maghami||Public & Shareable||Open Access|
|This resource is referenced by||Van Beusekom, A., Hay, L, (in no particular order -->) Nijssen, B., Bennett, A., Tarboton, D., Wood, A., Choi, Y., Li, Z., Maghami, I., Clark, M., Goodall, J.L. “Hydrologic model sensitivity to temporal disaggregation of meteorological forcing data across CONUS” (In preparation for …)|
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|National Science Foundation||Collaborative Research: SI2-SSI: Cyberinfrastructure for Advancing Hydrologic Knowledge through Collaborative Integration of Data Science, Modeling and Analysis||OAC-1664061, OAC-1664018, OAC-1664119|
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/