Dataset Listing

Marshall Gulch - Precipitation (2007-2018)

Precipitation Data from the Marshall Gulch Site

Variables:  Precipitation

Date Range:  (2007-05-01 to 2018-04-19)

Dataset Creators/Authors:  Peter Troch; Ingo Heidbüchel; Nate Abramson

Contact:  Peter Troch, Department of Hydrology and Water Resources, University of Arizona, 1133 E James E. Rogers Way Tucson, AZ 85721,

Field Area:   Marshall Gulch (High-Elevation)

Keywords & XML
  • Description

    Marshall Gulch (high elevation site in the Santa Catalina Mountains, Arizona) precipitation is measured at nine locations. Six locations are equipped with a cluster of three RAINEW 111 Tipping Bucket Wired Rain Gauges. Data are recorded every 15 minutes and after quality control, precipitation values are averaged for each cluster. Three additional locations are instrumented with a single rain gage. RAINEW 111 Tipping Bucket is installed at Marshall Gulch weir, Campbell Scientific Heated Rain Gage 385 is installed at Mt. Lemmon site. Winter precipitation was recorded using Onset S-RGB-M002 rain gage equipped with an antifreeze tipping bucket CS 705 snowfall adapter at the Schist catchment.

    Data are provisional and may be subject to revision. Data for 2007-2012 were collected and computed by Ingo Heidbuechel, Graduate assistant, University of Arizona, From 2012, instrumentation is maintained and data are collected and computed by Nate Abramson, University of Arizona, Three additional rain gages added at the following sites: MG weir, Mt. Lemmon and MG Schist catchment in 2012. MG Schist catchment rain gage (MG_Schist_Winter_Rain) collects only winter precipitation typically from December to April.
  • Keywords

    Precipitation, Rain, Santa Catalina Mountains, Marshall Gulch, Arizona

    XML Metadata

    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; Ingo Heidbüchel; Nate Abramson (2018). "CZO Dataset: Marshall Gulch - Precipitation (2007-2018)." Retrieved 18 Jun 2019, from

  • Publications

    Primary Publications


    The master transit time distribution of variable flow systems. Heidbüchel I., Troch P.A., Lyon S.W., and Weiler M. (2012): Water Resources Research 48(6): W06520

    Other Publications


    Determining Controls on Variable Response Times from Nested Sub-catchments. I. Heidbuechel, Troch, P.A. (2011): AGU Fall Meeting Presentations Abstract H43N-05.


    Tracking Varying Mean Transit Time in a Semi-Arid Catchment . Heidbuechel, I., Troch, P.A., Lyon, S.W. (2010): AGU Fall Meeting (Poster) Abstract H11C-0813.

  • Acknowledgements


    National Science Foundation EAR-0724958
    National Science Foundation EAR-1331408


Sites - Methods

(nas/)   Data Level 0

Marshall Gulch - Precipitation 2007

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2008

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2009

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2010

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2011

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2012

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2013

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2014

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2015

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2016

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2017

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Precipitation 2018

(.csv)   Data Level 2,  Metadata

Marshall Gulch - Schist Winter Precipitation 2012-13

(.csv)   Data Level 1,  Metadata

Marshall Gulch - Schist Winter Precipitation 2013-14

(.csv)   Data Level 1,  Metadata

Marshall Gulch - Schist Winter Precipitation 2014-15

(.csv)   Data Level 1,  Metadata

Marshall Gulch - Schist Winter Precipitation 2015-16

(.csv)   Data Level 1,  Metadata

Marshall Gulch - Schist Winter Precipitation 2016-17

(.csv)   Data Level 1,  Metadata

Marshall Gulch - Schist Winter Precipitation 2017-18

(.csv)   Data Level 1,  Metadata

Data Use Policy
Data Sharing Policy
Research Groups/Foci
  • Data Use Policy

    DRAFT v.0.4.0

    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 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

    DRAFT v.0.2.5

    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.

    3. Request, in writing, data privacy up to 4 years. CZO PIs will review short written applications to extend data privacy beyond 2 years and up to 4 years from time of collection. Extensions beyond 3 years should not be the norm, and will be granted only for compelling cases.

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    * 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

  • Research Groups/Foci

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