The Colorado East River Community Observatory Data Collection

The U.S. Department of Energy's (DOE) Colorado 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. The ER is characterized by steep elevation, geologic, hydrologic and vegetation gradients along floodplain, montane, subalpine, and alpine life zones, which makes it an ideal location for researchers to understand how different mountain subsystems contribute to overall watershed behaviour. The ER has both long‐term and spatially‐extensive observations and experimental campaigns carried out by the Watershed Function Scientific Focus Area (SFA), led by Lawrence Berkeley National Laboratory, and researchers from over 30 organizations who conduct cross‐disciplinary process‐based investigations and modelling of watershed behaviour. The heterogeneous data generated at the ER include hydrological, genomic, biogeochemical, climate, vegetation, geological, and remote sensing data, which combined with model inputs and outputs comprise a collection of datasets and value‐added products within a mountainous watershed that span multiple spatiotemporal scales, compartments, and life zones. Within 5 years of collection, these datasets have 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 70 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.

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.

K E Y W O R D S
diverse watershed data, East River, hydrobiogeochemical processes, mountainous watershed observatory, watershed function science focus area, watershed function SFA data 1 | DATA SET NAME The Colorado East River Community Observatory Data Collection.

| 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 kilometre headwater catchment representative of watersheds in the Rocky Mountains of the western United States (Hubbard et al., 2018). The ER contains significant geological, hydrological, vegetation, and climatic gradients, and spans first-order mountain streams to higher-order meandering floodplains across four drainages the East River, Washington Gulch, Slate River, and Coal Creek ( Figure 1). The mean annual air temperature in the ER is~2.4 C, with average daily temperatures of À7.6 C and 13.4 C in December and July, respectively, as measured at the Butte SNOTEL station. The F I G U R E 1 Map of ER site and measurements of the SFA and some collaborators. The yellow line indicates the East River community observatory domain. The red lines indicate the major drainage boundaries of the East River, Washington gulch (Wash. Gul.), Slate River, and Coal Creek. The blue lines show stream flow lines determined from the National Hydrography Dataset (U.S. Geological Survey, 2001). Measurements by community partners in the Slate River and Redwell basin are not shown. The white box shows the intensively sampled Pumphouse subregion, which includes measurements along a hillslope transect and the meandering floodplain of the East River average precipitation, which is mostly snowfall, is 1200 mm.yr À1 . The watershed has an average elevation of 3266 m, with an average slope of 18.7 ± 10.9 degrees.
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, Bearup, et al., 2018;Carroll, Williams, et al., 2018;Gaskill, 1991). The watershed comprises montane, subalpine, and alpine life zones that collectively include aspen, meadow, mixed conifer, sagebrush, grasses, and sedges. Further details about the ER are provided in Hubbard et al. (2018) and Carroll, Bearup, et al. (2018).
Since 2015, the ER has been the primary field site for the  The ER instrumentation network maintained by the SFA and collaborators includes 15 stream-gaging 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 2(a)-(c)), 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, whole snowpit and rain chemistry, and stable isotopes of snow, rain and snowmelt water have been conducted over multiple years to inform stream water sources (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 (Figure 2(d)). 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 solutes to the river Matheus Carnevali, Hobson, et al., 2020;Sorensen et al., 2020), resulting in over 5000 metagenome-assembled genomes. In addition, several multi-institutional remote sensing campaigns have been con-  F I G U R E 2 Photographs of some field locations and infrastructure installations in the ER: (a) hillslope borehole to measure subsurface water and carbon (b) weather station in the alpine zone (c) Pumphouse ISCO sampler for discharge and solute flux measurements (d) a plot to study impacts of early snowmelt on vegetation at a subalpine location along an elevation gradient T A B L E 1 ER data types, variables, and methods of data generation. Methods and instruments used, and uncertainties (if available) are described in the published datasets on the repositories. Several time series measurements are ongoing; see Varadharajan et al. (2020) for location and instrumentation metadata associated with these measurements.  Carroll, Bearup, et al., 2018;Carroll, Williams, et al., 2018;Carroll, Deems, et al., 2019;Bryant et al., 2019;Malenda et al., 2019;Briggs, Wang, et al., 2019;Briggs et al., 2017;Özgen-Xian et al., 2020;Faybishenko, 2020;Tran et al., 2020;Carroll et al., 2020 Williams, Beutler, Bill, et al., 2020;Sutfin & Rowland, 2019a;Dong, Beutler, Bouskill, et al., 2020;Rowland & Stauffer, 2020a;Sutfin & Rowland, 2019b;Saup et al., 2019;Dong, Beutler, Brown, et al., 2020a, Dong, Beutler, Brown, et al., 2020bZhi et al., 2019;Nelson et al., 2019;Fox et al., 2019;Newcomer, Raberg, et al., 2020;Dong, Fox, Bhattacharyya, et al., 2020;Bouskill et al., 2020;Rowland & Stauffer, 2020b;Sorensen et al., 2019a;Berkelhammer, 2020;Winnick et al., 2020;Sorensen et al., 2019b;Dong, Beutler, Bouskill et al., 2020;Sitchler et al., 2019Hubbard et al., 2019;Berkelhammer et al., 2020;Carroll, Deems, et al., 2019;Carroll, Manning, et al., 2019;Matheus Carnevali, Hobson, et al., 2020;Arora et al., 2020;Dwivedi, 2019;Tokunaga et al., 2019;Rogers et al., 2020;Wan & Tokunaga, 2021 The interdisciplinary data from the ER can also be used in future investigations that address science questions identified by the broader community such as the impacts of climate change and extreme events on the critical zone, and the scale dependence of hydrology (Blöschl et al., 2019). These data along with future measurements from the SAIL campaign will provide integrated observational datasets for benchmarking atmospheric and hydrological models in mountainous watersheds, thus addressing an identified data gap in modelling mountain rain and snow (Lundquist et al., 2019). More broadly the data from the ER will help understand the impacts of hydrological perturbations on water availability and quality in mountainous watersheds of the Western United States.