30 minute and daily streamflow data measured and computed for flumes located around the Redondo Peak (Valles Caldera National Preserve). Streamflow are derived using pressure measurements in the bottom of stilling wells to infer water levels and hence discharge in the flumes. Three types of flumes are installed: Tracom inc. 6" and 12" Parshall Flumes, and 12" 45-degree Trapezoidal Flume.
Data are provisional and may be subject to revision.
Data for 2007-2008 were computed by Patrick Broxton, Graduate assistant, University of Arizona, firstname.lastname@example.org.
Data for 2009-2010 were computed by Adrian Harpold, postdoc University of Arizona, email@example.com.
Data from 2011 were computed by Xavier Zapata, Graduate student, University of Arizona, firstname.lastname@example.org.
Streamflow data have not been computed for the Lower Jaramillo (FLUME_01) since wy 2009.
Streamflow data have not been computed for the Lower Redondo (FLUME_02) and Redondo Meadow (FLUME_05) since wy 2011.
Streamflow data have not been computed for the Upper Redondo (FLUME_06) since wy 2012.
Added new flume Upper La Jara (FLUME_08) in wy 2012.
Both La Jara flumes and History Grove flume were damaged after the Thompson Ridge fire in July 2013.
Lower La Jara and History Grove flumes were reinstalled in November 2016.
Data from 11/10/2012 to 3/10/2017 are missing for MC ZOB Flume.
hydrology, streamflow, Jaramillo Creek, La Jara Creek, History Grove, Redondo Creek, Valles Caldera, Jemez Mountains, New Mexico
XML is in ISO-19115 geographic metadata format, compatible with ESRI Geoportal Server.
Citation for This Dataset
The following acknowledgment should accompany any publication or citation of these data - Logistical support and/or data were provided by the NSF-supported Jemez River Basin and Santa Catalina Mountains Critical Zone Observatory, EAR-0724958 and EAR-1331408.
Citation for This Webpage
Peter Troch; Patrick Broxton; Xavier Zapata-Rios; Mark Losleben; Matej Durcik (2018). "CZO Dataset: Jemez River Basin - Streamflow / Discharge (2007-2018)." Retrieved 21 May 2019, from http://criticalzone.org/national/data/dataset/2504/
On the role of aspect to quantify water transit times in small mountainous catchments. Broxton P. D., Troch P. A., and Lyon S. W. (2009): Water Resources Research 45: W08427
National Science Foundation EAR-0724958
National Science Foundation EAR-1331408
Data Use Policy
1. Use our data freely. All CZO Data Products* except those labelled Private** are released to the public and may be freely copied, distributed, edited, remixed, and built upon under the condition that you give acknowledgement as described below. Non-CZO data products — like those produced by USGS or NOAA — have their own use policies, which should be followed.
2. Give proper citation and acknowledgement. Publications, models and data products that make use of these datasets must include proper citation and acknowledgement. Most importantly, provide a citation in a similar way as a journal article (i.e. author, title, year of publication, name of CZO “publisher”, edition or version, and URL or DOI access information. See http://www.datacite.org/whycitedata). Also include at least a brief acknowledgement such as: “Data were provided by the NSF-supported Southern Sierra Critical Zone Observatory” (replace with the appropriate observatory name).
3. Let us know how you will use the data. The dataset creators would appreciate hearing of any plans to use the dataset. Consider consultation or collaboration with dataset creators.
*CZO Data Products. Defined as a data collected with any monetary or logistical support from a CZO.
**Private. Most private data will be released to the public within 1-2 years, with some exceptionally challenging datasets up to 4 years. To inquire about potential earlier use, please contact us.
Data Sharing Policy
All CZO investigators and collaborators who receive material or logistical support from a CZO agree to:
1. Share data privately within 1 year. CZO investigators and collaborators agree to provide CZO Data Products* — including data files and metadata for raw, quality controlled and/or derived data — to CZO data managers within one year of collection of samples, in situ or experimental data. By default, data values will be held in a Private CZO Repository**, but metadata will be made public and will provide full attribution to the Dataset Creators†.
2. Release data to public within 2 years. CZO Dataset Creators will be encouraged after one year to release data for public access. Dataset Creators may chose to publish or release data sooner.
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4. Consult with creators of private CZO datasets prior to use. In order to enable the collaborative vision of the CZO program, data in private CZO repositories will be available to other investigators and collaborators within that CZO. Releasing or publishing any derivative of such private data without explicit consent from the dataset creators will be considered a serious scientific ethics violation.
* CZO Data Products. Defined as data collected with any monetary or logistical support from a CZO. Logistical support includes the use of any CZO sensors, sampling infrastructure, equipment, vehicles, or labor from a supported investigator, student or staff person. CZO Data Products can acknowledge multiple additional sources of support.
** Private CZO Repository. Defined as a password-protected directory on each CZO’s data server. Files will be accessible by all investigators and collaborators within the given CZO and logins will be maintained by that local CZO’s data managers. Although data values will not be accessible by the public or ingested into any central data system (i.e. CUAHSI HIS), metadata will be fully discoverable by the public. This provides the dual benefit of giving attribution and credit to dataset creators and the CZO in general, while maintaining protection of intellectual property while publications are pending.
† Dataset Creators. Defined as the people who are responsible for designing, collecting, analyzing and providing quality assurance for a dataset. The creators of a dataset are analogous to the authors of a publication, and datasets should be cited in an analogous manner following the emerging international guidelines described at http://www.datacite.org/whycitedata.