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.
Site Description
The East River community observatory (ER) in the Upper Colorado Basin,
United States (39.033° N 107.12° W, 38.83° N 106.88° W) is a 300 square
kilometer headwater catchment representative of watersheds in the Rocky
mountains of the Western United States
(Hubbard et al., 2018).
Since 2015, the ER has been the primary field site for the U.S.
Department of Energy’s Watershed Function Scientific Focus Area (SFA;http://watershed.lbl.gov), and
now serves as a community testbed for over 30 collaborating institutions
that collectively aim to understand the impacts of perturbations, such
as drought and early snowmelt, on the hydrobiogeochemical dynamics of
mountainous, headwater catchments at seasonal to decadal timescales. The
ER spans first-order mountain streams and meandering floodplains across
four drainages - the East River, Washington Gulch, Slate River, and Coal
Creek (Figure 1a). The ER lithology consists of igneous formations
intruding into carbon-rich marine shale in the Mancos Formation, as well
as sedimentary strata grading older (Permian) to younger (Tertiary) as
one moves east to west across the ER domain with pockets of significant
mineralization (Carroll
et al., 2018; Gaskill, 1991). In addition to geologic variability, the
ER is characterized by steep elevation, hydrologic and vegetation
gradients along floodplain, montane, subalpine, and alpine life zones,
which makes it an ideal location to understand how different mountain
subsystems contribute to overall watershed behavior.
Measurements and field infrastructure
The SFA and collaborators have collected extensive sample- and
sensor-based measurements at several locations across the East River and
adjacent drainages (Figure 1a). Regions of particular emphasis include
“SFA-intensive” sites located within representative meanders and a
hillslope in a lower montane (Pumphouse) subregion of the pristine East
River drainage basin, where several cross-disciplinary, co-located
measurements are being conducted (Figure 1b). Additional “satellite”
sites, targeting specific research questions are located near the Brush
Creek confluence floodplain, an elevation gradient of research meadows
along Washington Gulch and on the flanks of Cinnamon Mountain and Mount
Baldy, Snodgrass Mountain, and mining-impacted sites in both Coal Creek
and the Redwell Basin.
The ER instrumentation network maintained by the SFA and collaborators
includes 15 stream-gauging and water quality stations used to obtain
paired concentration-discharge measurements, 6 weather stations with
soil moisture and temperature probes, 18 instrumented groundwater wells
(e.g Figure 2a-2c), and about ~40 piezometers,
~15 ecohydrological sensor stations, and
~40 digital phenocam locations (Varadharajan et al.
2020). An eddy flux tower is maintained in the East River floodplain by
the National Center for Atmospheric Research (NCAR). Extensive
measurements of depth-resolved snow density, snow water equivalent and
water isotopes as well as whole-pit chemistry, snowmelt water isotopes,
rain chemistry and water isotopes have been conducted over multiple
years to inform stream water source
(Fang et al., 2019).
Snowmelt manipulation experiments in vegetation plots in different
mountain life zones were used to study the impacts of snowmelt timing on
vegetation phenology. Metagenomic analyses of microbial communities have
been conducted for soils and sediments representing various locations
across the floodplain meanders and lower montane hillslopes that
contribute water and various elements to the river
(Lavy et al., 2020;
Matheus Carnevali et al., 2020; Sorensen et al., 2020). As a result,
and with watershed-scale surveys in progress, the East River watershed
in Colorado is fast becoming the most genomically characterized
high-elevation watershed in the world, with over 5,000
metagenome-assembled genomes to date enabled by DOE JGI-CSP and FICUS
awards. In addition, several multi-institutional remote sensing
campaigns have been conducted at the ER which include a 2015 Light
Detection and Ranging (LiDAR) survey led by the SFA
(Wainwright & Williams,
2017), Airborne Snow Observatory (ASO) flights by the National
Aeronautics and Space Administration’s Joint Propulsion Laboratory (NASA
JPL) in 2016, 2018 and 2019
(Painter et al., 2016), a
2017 USGS Airborne Electromagnetic survey, and a 2018 National
Ecological Observation Network (NEON) hyperspectral survey paired with
an extensive ground-based campaign conducted in coordination with
Stanford University (Chadwick
et al., 2020). In 2021, a two-year deployment of the DOE’s Atmospheric
Radiation Measurement (ARM) Program mobile Surface Atmosphere Integrated
Field Laboratory (SAIL) will use more than three dozen instruments to
collect a suite of meteorology, clouds, aerosol and other atmospheric
measurements in the ER
(http://sail.lbl.gov). The SFA’s ER
measurement locations are viewable through a public, user-friendly field
information portal
(https://wfsfa-data.lbl.gov/watershed/).
The ER watershed also has significant infrastructure maintained by
several federal, state, and local agencies that have different data
systems (some of these are indicated in Figure 1a). Notably, the Rocky
Mountain Biological Laboratory (RMBL, https://www.rmbl.org/) is situated
in the townsite of Gothic, and has over 90 years of data collection
activities in the watershed. Snow measurements and associated
meteorological data are available from the National Resources
Conservation Service (NRCS) snow Telemetry (SNOTEL) sites ‘Butte’ and
‘Schofield Pass’, Crested Butte Cooperative Observer Network (COOP), and
a number of Weather Underground stations. The USGS maintains gaging
stations and collects water quality measurements across the East-Taylor
watersheds, and makes the data available through NWIS (HUC: 14020001).
Additional water quality data are available from the National Water
Quality Portal, which includes measurements by the U.S. Environmental
Protection Agency (EPA), Colorado Department of Public Health and
Environment (CDPHE), and local groups including the Coal Creek Watershed
Coalition and the Rivers of Colorado Water Watch. The EPA also maintains
a National Atmospheric Deposition Program (NADP) Colorado Clean Air
Status and Trends Network (CASTNET) station at Gothic.
Overview of ER Datasets and Research Themes
The Watershed Function SFA and its collaborators generate vastly
diverse, multiscale datasets at the ER including hydrological,
(bio)geochemical, climate, vegetation, geophysical, microbiological,
remote sensing, and model data. Additionally, several model datasets are
generated from numerical simulations of different watershed subsystems
and their aggregated behavior. Detailed descriptions of the data types,
data variables collected, and methods used are listed in Table 1. The
most common publicly available data types from the ER during 2015-2020
are biogeochemistry and hydrology data (Figure 3).
The simultaneous collection of these data types across the watershed
allows researchers across institutions to share knowledge and draw
conclusions. Examples of research topics that these data were collected
to address include correlations of hydrologic data with variation in
climate and microclimate; effects of snow accumulation and melt timing
on vegetation, microbial and watershed function; stream gas exchange
rates, groundwater and surface water interactions, biogeochemical
hotspots and hydrodynamics; cycling and sourcing of metal nutrients by
plants, nitrogen release dynamics from shale bedrock; sources of
elemental contributions to the East River and weathering processes
impact on river water; solute concentration responses and water
partitioning to quantify seasonal stream water; and more broadly an
aggregated understanding of watershed hydrobiogeochemical processes
given their variation over space and different watershed functional
zones and compartments.
Data Policy, Curation Process, and Availability
The SFA has a Data Management Framework component that provides services
and infrastructure to support the project’s data lifecycle. The
framework comprises systems, workflows and scripts to acquire and store
data in a queryable database, conduct QA/QC, integrate project data with
external data for real-time queries, discover and download data, and to
publish data with digital object identifiers (DOIs) in the DOE’s
Environmental Systems Science Data Infrastructure for a Virtual
Ecosystem (ESS-DIVE) repository
(Varadharajan et al., 2019).
Additionally, the SFA has developed an integrated field-data workflow to
acquire critical metadata from these diverse data streams, and to manage
data at each stage of the scientific process. The field-data workflow
outlines guidelines for managing metadata and identifiers for field
locations, samples, sensors, and data package creation and publication.
While developed by the SFA, the workflow is available to other
collaborating organizations, and is built based on community feedback
and established data management best practices.
The SFA has an open data policy where project-generated data are made
publicly available following the U.S. Department of Energy’s guidelines
(https://watershed.lbl.gov/data/data-policy/).
Several datasets generated by the SFA and collaborators at the ER are
publicly available in online repositories, including ESS-DIVE, NCBI,
United States Geological Survey (USGS), NASA DAAC: National Snow and Ice
Data Center, Figshare, and HydroShare (Table 2). The SFA alone has 36
public datasets with associated metadata available on ESS-DIVE that
include many of the long-term monitoring and spatially-extensive remote
sensing and associated ground campaign datasets. A collection of data
packages generated across institutions at the ER can be accessed on
ESS-DIVE through the East River watershed portal
(https://data.ess-dive.lbl.gov/portals/east-river-watershed).
The data are typically licenced under Creative Commons by Attribution
(CC-By4.0) or Creative Commons Public Domain (CC0) usage policies. Large
datasets such as the remote sensing or model products are stored and
distributed through public data transfer nodes on the DOE’s National
Energy Scientific Computing Center (NERSC).
Scientific Impact of ER Datasets
The multidisciplinary data from the ER have already advanced significant
understanding of hydrological processes in mountainous catchments, and
they have been used in numerous publications of which a select few are
highlighted here. For example by combining measurements of river, rain,
groundwater and snow chemistry, stream discharge, remote sensing (LIDAR,
ASO), Carroll et al. (2018, 2019) found that groundwater recharge, an
important contributor to streamflow, is dependent on elevation and
vegetation and increases in higher elevations, such as the upper
subalpine zone where there is greater snow accumulation and lower canopy
cover. Through analyses of data on groundwater chemistry, water table
depth, and rock mineralogy,
Wan et al. (2019) found that
the seasonal water table depth determines the weathering zone and
weathering front in sedimentary bedrock, and that the Mancos shale can
be a significant contributor to river nitrogen exports. Combining snow
measurements with metagenome analysis,
(Sorensen et al., 2020)
found that snowmelt triggers a pulse of nitrogen in hillslope soils
concomitant with a collapse in microbial biomass, and changes in
microbial community composition. Using model simulations of floodplain
meanders and regions of hyporheic exchange,
Dwivedi et al. (2017,
2018) found these subsystems exert critical controls on nitrogen
cycling and other solute exports to the river. These findings, and
others from the ER community, highlight the value of designing
multidisciplinary watershed observatories using open science by design
principles, and publishing data generated in open, public repositories
(Stegen et al., 2019).