loading page

The East River Community Observatory Data Collection: Diverse, multiscale data from a mountainous watershed in the East River, Colorado
  • +11
  • Zarine Kakalia,
  • Charuleka Varadharajan,
  • Erek Alper,
  • Eoin Brodie,
  • Madison Burrus,
  • Rosemary Carroll,
  • Danielle Christianson,
  • Valerie Hendrix,
  • Matthew Henderson,
  • Susan Hubbard,
  • Douglas Johnson,
  • Roelof Versteeg,
  • Kenneth Williams,
  • Deborah Agarwal
Zarine Kakalia
Lawrence Berkeley National Laboratory

Corresponding Author:zarinekakalia@lbl.gov

Author Profile
Charuleka Varadharajan
Lawrence Berkeley National Laboratory
Author Profile
Erek Alper
Subsurface Insights LLC
Author Profile
Eoin Brodie
Lawrence Berkeley National Laboratory
Author Profile
Madison Burrus
Lawrence Berkeley National Laboratory
Author Profile
Rosemary Carroll
Desert Research Institute
Author Profile
Danielle Christianson
Lawrence Berkeley National Laboratory
Author Profile
Valerie Hendrix
Lawrence Berkeley National Laboratory
Author Profile
Matthew Henderson
Lawrence Berkeley National Laboratory
Author Profile
Susan Hubbard
Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory
Author Profile
Douglas Johnson
Subsurface Insights LLC
Author Profile
Roelof Versteeg
Subsurface Insights LLC
Author Profile
Kenneth Williams
E O Lawrence Berkeley National Laboratory
Author Profile
Deborah Agarwal
Lawrence Berkeley National Laboratory
Author Profile

Abstract

The U.S. Department of Energy’s (DOE) East River community observatory (ER) in the Upper Colorado River Basin was established in 2015 as a representative mountainous, snow-dominated watershed to study hydrobiogeochemical responses to hydrological perturbations in headwater systems. Led by the Watershed Function Science Focus Area (SFA), the ER has both long-term and spatially-extensive observations paired with experimental campaigns. The Watershed Function SFA, led by Berkeley Laboratory, includes researchers from over 30 organizations who conduct cross-disciplinary process-based investigations and mechanistic modeling of watershed behavior in the ER. The data generated at the ER are extremely heterogeneous, and include hydrological, biogeochemical, climate, vegetation, geological, remote sensing, and model data that together comprise an unprecedented collection of data and value-added products within a mountainous watershed, across multiple spatiotemporal scales, compartments, and life zones. Within 5 years of data collection, these datasets have already revealed insights into numerous aspects of watershed function such as factors influencing snow accumulation and melt timing, water balance partitioning, and impacts of floodplain biogeochemistry and hillslope ecohydrology on riverine geochemical exports. Data generated by the SFA are managed and curated through its Data Management Framework. The SFA has an open data policy, and over sixty ER datasets are publicly available through relevant data repositories. A public interactive map of data collection sites run by the SFA is available to inform the broader community about SFA field activities. Here, we describe the ER and the SFA measurement network, present the public data collection generated by the SFA and partner institutions, and highlight the value of collecting multidisciplinary multiscale measurements in representative catchment observatories.
29 Sep 2020Submitted to Hydrological Processes
30 Sep 2020Submission Checks Completed
30 Sep 2020Assigned to Editor
30 Sep 2020Reviewer(s) Assigned
07 Dec 2020Review(s) Completed, Editorial Evaluation Pending
27 Dec 2020Editorial Decision: Revise Minor
16 Jan 20211st Revision Received
18 Jan 2021Submission Checks Completed
18 Jan 2021Assigned to Editor
18 Jan 2021Reviewer(s) Assigned
13 Mar 2021Review(s) Completed, Editorial Evaluation Pending
22 Mar 2021Editorial Decision: Revise Minor
10 Apr 20212nd Revision Received
12 Apr 2021Reviewer(s) Assigned
12 Apr 2021Submission Checks Completed
12 Apr 2021Assigned to Editor
25 Apr 2021Review(s) Completed, Editorial Evaluation Pending
27 Apr 2021Editorial Decision: Accept