Dataset Listing

Icacos and Quebrada Sonadora - Streamflow / Discharge, Stream Suspended Sediment, Electrical Conductivity - Hysteresis Analysis (2016-2017)

Hysteretic response of solutes and turbidity at the event scale across forested tropical montane watersheds

Variables:  Discharge, specific conductance, turbidity

Standard Variables:  Discharge|Specific conductance|Turbidity

Date Range:  (2016-2017)

Dataset Creators/Authors:  Adam Wymore; Miguel C Leon; James B Shanley; William H McDowell

Contact:  Miguel Leon, Miguel.Leon@unh.edu

Field Area:   Rio Icacos | Quebrada Sonadora

Description
Keywords & XML
Citation
Publications
  • Description

    Concentration-discharge relationships are a key tool for understanding the sourcing and transport of material from watersheds to fluvial networks. Storm events in particular provide insight into variability in the sources of solutes and sediment within watersheds, and the hydrologic pathways that connect hillslope to stream channel. Here we examine high-frequency sensor-based specific conductance and turbidity data from multiple storm events across two watersheds (Quebrada Sonadora and Rio Icacos) with different lithology in the Luquillo Mountains of Puerto Rico, a forested tropical ecosystem. Our analyses include Hurricane Maria, a category 5 hurricane. To analyze hysteresis, we used a recently developed set of metrics to describe and quantify storm events including the hysteresis index (HI), which describes the directionality of hysteresis loops, and the flushing index (FI), which describes whether the mobilization of material is source or transport limited. We also examine the role of antecedent discharge to predict hysteretic behavior during storms. Overall, specific conductance and turbidity showed contrasting responses to storms. The hysteretic behavior of specific conductance was very similar across sites, displaying clockwise hysteresis and a negative flushing index indicating proximal sources of solutes and consistent source limitation. In contrast, the directionality of turbidity hysteresis was significantly different between watersheds, although both had strong flushing behavior indicative of transport limitation. Overall, models that included antecedent discharge did not perform any better than models with peak discharge alone, suggesting that the magnitude and trajectory of an individual event was the strongest driver of material flux and hysteretic behavior. Hurricane Maria produced unique hysteresis metrics within both watersheds, indicating a distinctive response to this major hydrological event. The similarity in response of specific conductance to storms suggests that solute sources and pathways are similar in the two watersheds. The divergence in behavior for turbidity suggests that sources and pathways of particulate matter vary between the two watersheds. The use of high-frequency sensor data allows the quantification of storm events while index-based metrics of hysteresis allow for the direct comparison of complex storm events across a heterogeneous landscape and variable flow conditions.

    Additional scripts for hysteresis analysis are available here in the 'python scripts for analysis' folder and at https://github.com/miguelcleon/HysteresisAnalysis/
  • Keywords

    hurricanes and tropical storms, hysteresis, specific conductance, sensors, turbidity

    XML Metadata

    criticalzone.org/luquillo/data/xml-metadata-test/7158/

    XML is in ISO-19115 geographic metadata format, compatible with ESRI Geoportal Server.

  • Citation for This Dataset

    Wymore, A., M. C. Leon, J. B. Shanley, W. H. McDowell (2019). LCZO-Stream Water Chemistry, Streamflow / Discharge, Hysteretic response of solutes and turbidity at the event scale across forested tropical montane watersheds - Luquillo Experimental Forest (2016-2017), HydroShare, https://doi.org/10.4211/hs.f8420c1447fe440eb93e656b2db0b64d, DOI for this published resource is pending activation.

    Citation for This Webpage

    Adam Wymore; Miguel C Leon; James B Shanley; William H McDowell (2017). "CZO Dataset: Icacos and Quebrada Sonadora - Streamflow / Discharge, Stream Suspended Sediment, Electrical Conductivity (2016-2017) - Hysteresis Analysis." Retrieved 22 Oct 2019, from http://criticalzone.org/luquillo/data/dataset/7158/

  • Publications

    Primary Publications

    2019

    Hysteretic response of solutes and turbidity at the event scale across forested tropical montane watersheds. Wymore, A., Leon M.C., Shanley J.B. McDowell W.H. (2019): Frontiers in Earth Science Biogeoscience

Data

Icacos and Quebrada Sonadora - Discharge, specific conductance, turbidity

(64d/)   Data Level 1

Icacos and Quebrada Sonadora - hysteresis analysis code

(sis/)   Data Level 4

Data Use Policy
Data Sharing Policy
  • 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 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

    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.

    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.

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