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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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tRIBS benchmark: SNOTEL point-scale simulation, Happy Jack, AZ, USA.

Authors: Raming, Logan; Vivoni, Enrique; Cederstrom, Charles; Hawkins, Gretchen;

tRIBS benchmark: SNOTEL point-scale simulation, Happy Jack, AZ, USA.

Abstract

This repository hosts the setup for executing a point-scale simulation (i.e. single computational element) of the Happy Jack SNOTEL Site in northern Arizona, USA, using the TIN-Based Real-Time Integrated Basin Simulator (tRIBS). This repository consists of : (1) A data subdirectory, which contains all the necessary data to run tRIBS at Happy Jack and includes bias corrected dataset of SWE for model comparison. 2) A doc subdirectory, which contains a jupyter notebook for analyzing and visualizing this specific benchmark case, alongside additional documentation. (3) A src subdirectory that is currently empty but intended to contain source code for the tRIBS executable, which can be obtained here. (4) A bin subdirectory, that is currently empty but intended to store the tRIBS executable, with instructions to build the model here. (5) A results subdirectory, which contains reference model output for results comparison. Instructions for running this benchmark are available in the README.html file within the repository, which can be opened with your web browser, and can also be found in the latest tRIBS documentation. Data from this model was originally collated by Gretchen Hawkins and Josh Cederstrom for their Master’s Thesis work at Arizona State University and associated publications: Hawkins, G.A., Vivoni, E.R., Robles-Morua, A., Mascaro, G., Rivera, E., and Dominguez, F. 2015. A Climate Change Projection for Summer Hydrologic Conditions in a Semiarid Watershed of Central Arizona. Journal of Arid Environments. 118: 9–20. https://doi.org/10.1016/j.jaridenv.2015.02.022 Cederstrom, C.J., Vivoni, E.R., Mascaro, G., and Svoma, B. 2024. Forest Thinning Effects on Watershed Responses under Warming. Water Resources Research. (In Review). Bias corrected SWE data is from: Sun N, Yan H, Wigmosta MS, Leung LR, Skaggs R, Hou Z. 2019. Regional Snow Parameters Estimation for Large-domain Hydrological Applications in the Western United States. Journal of Geophysical Research: Atmospheres. 124 : 5296–5313. Data for this model simulation were obtained from a number of public sources: Meteorological forcing was obtained from the Happy Jack SNOTEL Site (https://www.nrcs.usda.gov/wps/portal/wcc/) and NLDAS-2 (https://ldas.gsfc.nasa.gov/nldas/v2/forcing). Soil properties were obtained from the Soil Survey Geographic Database (https://nrcs.app.box.com/v/soils) with derived parameters informed from the literature and calibration process. Vegetation parameters were obtained from the LANDFIRE REMAP data set (https://landfire.gov). NOTE: If you encounter a situation where, after downloading and extracting the happy_jack.gz file, the extracted file has no extension, please follow these steps: Rename the File: Manually rename the extracted file to happy_jack.zip. Extract Again: After renaming, unzip the happy_jack.zip file to access the full folder with all the necessary files. This issue may occur if the file extraction process doesn't automatically add the .zip extension. By renaming the file and unzipping it again, you should be able to access the complete set of files without any issues.

Related Organizations
Keywords

forest hydrology, snow water equivalent, tRIBS model

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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