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).