CHOSEN dataset
Description
CHOSEN: A synthesis of hydrometeorological data from intensively monitored catchments
1. Description
This project develops a pipeline to synthesize publicly available hydro-meteorological time series data from various resources. Using this pipeline, we have compiled data from 30 study areas from websites listed below into the CHOSEN (Comprehensive Hydrologic Observatory SEnsor Network) dataset. In the CHOSEN dataset, the data from different study areas have the same structures and formats, making them convenient to use for comparative hydrological studies.
Click on the study area will direct to its original website where the raw data were downloaded.
No.Study Area1East River2Dry Creek3Sagehen Creek4Andrews Forest5Baltimore6Bonanza Creek7California Current Ecosystem8Central Arizona9Coweeta10Florida Coastal Everglades11Georgia Coastal Ecosystems12Harvard Forest13Hubbard Brook14Jornada Basin15Kellogg16Konza Prairie17Northern Gulf of Alaska18Plum Island19Sevilleta20Boulder21Catalina22Jemez23Christina24Luquillo25Reynolds26Shale Hills27SanJoaquin28Providence29Wolverton30Calhoun
From each website, we downloaded (if available) field measured time-series data of streamflow, precipitation, air temperature, solar radiation, evapotranspiration, relative humidity, wind direction, wind speed, SWE, snow depth, snowmelt, vapor pressure, soil moisture, soil temperature, and water isotopes.
For more information and tutorials about the Jupyter Notebook data pipeline, please check our GitLab.
2.Data
On the zenodo platform, we provide the data in the NetCDF format. Check this link for an introduction to the NetCDF file format.
To extract data from NetCDF files, download the Jupyter Notebook (0_Extract_Data_From_NetCDF.ipynb) and data files (.nc). The Jupyter Notebook is a tutorial about extracting data and information from NetCDF files. Geographical Information about monitoring stations is also available to obtain using the Notebook.
3. Metadata
The metadata provided include time range of record, variable unit and name, and geographical information of hydro-meteorologcial stations. Those information can be extracted from the NetCDF files using the Jupyter Notebook (0_Extract_Data_From_NetCDF.ipynb).
4. Acknowledgements
This work is supported by the US Geological Survey Powell Center for Analysis and Synthesis, a Gordon and Betty Moore Foundation Data-Driven Discovery Investigator grant to LL, and the Jupyter Meets the Earth project, funded by NSF grant number (UC Berkeley: 1928406, NCAR: 1928374). Partial support for ASW is provided by the National Science Foundation and the Experimental Program to Stimulate Competitive Research (EPSCoR: EPS-1929148; Canary in the Watershed). Much of the data used in this study were available from the US. Long-Term Ecological Research Network, Critical Zone Observatory program, Lawrence Berkeley National Laboratory, Dry Creek Experimental Watershed (DCEW); we would like to acknowledge all the staff from these institutions for collecting and publicizing the data. We thank Dr. Adrian Harpold for providing the data from the Sagehen catchment. We would especially like to thank the Powell Center Working Group on Watershed Storage and Controls for their contributions to this project. We also thank Dr. Lindsey Heagy and Dr. Fernando Pérez for their suggestions on data publication and future development.
5. Collaboration
Please contact Berkeley ESDL lab or email angelikazhang@berkeley.edu if you have any questions about the CHOSEN dataset or would like to contribute data from another study area.
Notes
Files
0_Extract_Data_From_NetCDF.ipynb
Files
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