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At least 73 records · Page 4

2018 Meander Y and Meander Z floodplain groundwater chemistry from the East River watershed, Colorado

This dataset includes groundwater geochemistry data from floodplain piezometers collected as a part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected in order to investigate the role of hyporheic exchange and other river corridor processes on riverine export of solutes. Floodplain piezometers installed in Meander Z (MZA, MZB wells) and Meander Y (MYP wells) just upstream of the confluence with Brush Creek were sampled on daily to weekly time scales during summer-fall 2018. Some river water grab samples are also included. Data includes in-field measurements (pH, electrical conductivity [EC], oxidation reduction potential [ORP], and groundwater level) along with laboratory measurements (dissolved inorganic carbon [DIC], dissolved organic carbon [DOC], metals and major cations, anions [chloride, sulfate, nitrate], and dissolved ammonium). Five files are included in this dataset, including: sample locations and depths in both a kmz file which can be opened in Google Earth and a csv file, sampling protocol as a pdf document, aqueous geochemistry data in a csv file, and analytical detection limits in a csv file.

54 ENVIRONMENTAL SCIENCES↗

Geochemistry of East River, Colorado floodplain sediments from Meander Z and Meander Y collected in 2017.

This dataset includes sediment geochemical characterization data from floodplain sediments collected as a part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected in order to investigate the role of biogeochemical cycling and other river corridor processes on riverine export of solutes. Sediment cores were collected from Meander Z (MZA, MZB) and Meander Y (MYP) just upstream of the confluence with Brush Creek in September 2017 to depths of approximately 40-95 cm in 15-20 cm intervals. Analyses include moisture content, particle size analysis, total inorganic and total organic carbon, and extractions by 1 M KCl (for adsorbed NH4), anoxic HCl (for Fe(II) content), ammonium oxalate (for amorphous Fe-oxide content), and dithionite (for crystalline Fe-oxide content). Sample locations are included in both a kmz file, which can be opened in Google Earth, and a csv file, and methods are included as a text document. All characterization data is summarized in a Microsoft Excel file, and is also included as individual .csv files for each extraction (ammonium oxalate, anoxic HCl, dithionite, and KCl) and for bulk sediment data (moisture content, particle size analysis, TIC, and TOC).

54 ENVIRONMENTAL SCIENCES↗

Sulfur x-ray absorption spectroscopy data from bedrock shale, soil, and floodplain sediment from the East River, Colorado watershed

This dataset includes sulfur x-ray absorption near edge spectroscopy (XANES) data collected on solid samples as a part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected in order to investigate the speciation of sulfur and degree of shale weathering in solid samples across the watershed and their impact on riverine export of sulfate. Solid samples, including shale, hillslope soil, and floodplain sediment samples collected in 2016-2018, were analyzed by bulk XANES. Density fractions of hillslope soil, including a light fraction representing particulate organic matter and a heavy fraction representing minerals are also analyzed by bulk XANES. Micro-focused XANES on a weathered shale sample (PLM6, 2.7 m) was also performed. Sample locations are included in the 'sample meta data.csv' file, and XANES data for each sample type are included in csv files.

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2017 Meander C sediment characterization from the East River, Colorado

This dataset includes characterization data collected on sediment samples from Meander C as part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected to investigate the nature of mineral-organic associations across the meander transect and with depth. Samples were collected in 2017, and analyzed using sequential extractions (water, pyrophosphate, HCl, and dithionite) and density fractionation. Data collected include: texture, pH, root biomass, and metals (Fe, Al, Ca, Si) of bulk sediment samples; C and N of heavy fraction; and extractable OC, Fe, and Al, and organic matter characterization using high-resolution mass spectrometry (FT-ICR-MS) of sequential extractions. Sample locations are included in the ‘sample_metadata.xlsx” file. Sediment characterization data is included in the accompanying csv files: bulk and density fractions (MCB2017_density-and-bulk-fractions.csv), sequential extractions (MCB2017_sequential-extractions.csv), and FT-ICR-MS data from sequential extractions in three files to be read by the R package ftmsRanalysis (MCB2017_FTICRMS-sequential-edata.csv, MCB2017_FTICRMS-sequential-emeta.csv, and MCB2017_FTICRMS-sequential-fdata.csv). Sediment was collected in triplicate; ID’s refer to individual samples.

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Groundwater and Surface Water Flow (GSFLOW) model files for the East River, Colorado

The data package contains model input files and executables for the East River, Colorado (750 km2) located in the headwaters of the Upper Colorado River Basin. The code applied is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution to represent topographic complexity and a daily timestep accounts for energy and water partitioning between the snowpack, vegetation, soil zone and bedrock. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model accounts for nine stratigraphic units and extends 400 m below land surface. Using this modeling framework we explore historical water budgets (water year 1987-2022) and the influence of seasonal warming and associated mechanisms driving groundwater declines and streamflow loss. A Readme_062424.txt file provides instructions on how to download all files. Input and output files are provided for the historical simulation representative of water years 1987 to 2022 (i.e. baseline) and the all-year +4C warming scenario. Instructions are provided to run the seasonal warming scenarios with warming applied only to the autumn, winter, spring or summer months. Modeled output used in figures for Carroll et al., 2024 are also provided with metadata describing where these data were obtained. This dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Updated on 06-24-2024: The dataset was updated to include model outputs (updated base.zip and 4C.zip files), figure source files (Figure_Source_Files.zip), an updated Readme file (Readme_062424.txt), climate input files (climate_input_files.zip), and the adoption of ESS-DIVE File Level Metadata and CSV reporting formats (inclusion of flmd.csv and dd.csv files).

54 ENVIRONMENTAL SCIENCES↗

2016 Floodplain Geochemistry from the East River Watershed, Colorado

This dataset includes groundwater geochemistry data from floodplain piezometers collected as a part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected in order to investigate the role of hyporheic exchange and other river corridor processes on riverine export of solutes. Floodplain piezometers installed in several meanders (Meander C, Meander D, and Meander O) in the vicinity of the Pumphouse were sampled at several dates in 2016. Data includes in-field measurements (pH, electrical conductivity, oxidation reduction potential, dissolved oxygen, dissolved Fe(II), dissolved sulfide, and groundwater level) along with laboratory measurements (dissolved inorganic carbon, dissolved organic carbon, metals and major cations). Five files are included in this dataset, including: sample locations and depths in a csv file (metadata.csv), aqueous geochemistry data in a csv file, analytical detection limits in a csv file, a file-level metadata (flmd.csv) file, and a data dictionary (dd.csv) file. Data that was below the detection limit is reported as one half of the detection limit and missing data is listed as "-9999".

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Groundwater and Surface Water Flow (GSFLOW) model files to explore bedrock circulation depth and porosity in Copper Creek, Colorado

This data package contains integrated hydrological model input and output files for Copper Creek, Colorado (24 km2), a tributary of the East River located in the headwaters of the Upper Colorado River Basin. The model code is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution and a daily timestep. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model contains 12 model layers and extends 400 m below land surface. The original Copper Creek model was modified to contain geologic layers representing saprolite, shallow bedrock, and deep bedrock. Endmember depth versus hydraulic conductivity relationships and porosity values for fractured crystalline rock are simulated. For the shallow case, median flow depths occur in the shallow saprolite at depths <8 m, while the deep case promotes a median groundwater flow depth of 100 m. With this modeling framework we compare streamflow response to a plausible worst-case drought lasting up to five years. Streamflow metrics of analysis include average streamflow, fraction of stream network that is dry, no-flow duration, average groundwater flow to streams and time to recovery following the drought. Results and implications are presented in a paper submitted to Geophysical Research Letters titled, "The role of bedrock circulation depth and porosity in mountain streamflow response to prolonged drought" by Rosemary WH. Carroll, Andrew H. Manning and Kenneth H Williams. A Readme.txt file provides instructions on how to download all model files and execute each model scenario. In addition to the GSFLOW output/prms/copper_drought.csv file containing daily basin water stores and fluxes (refer to GSFLOW manual) and the output/prms/copper_drought_statvar.dat file with output defined in the gsflow3.control file (refer to GSFLOW Manual), output files also include spatially distributed daily values of total evapotranspiration, canopy evaporation, precipitation, snowfall, infiltration, snow water equivalent, potential evapotranspiration, recharge, sublimation, soil moisture, contributing interflow, water table elevations, changes in groundwater storage, groundwater evapotranspiration, interbasin groundwater flow (limited to the alluvium below the stream outlet), and surface-groundwater exchanges within the river system.

54 ENVIRONMENTAL SCIENCES↗

Mineralogy of floodplain sediments from Meanders C, O, and Z in the East River Watershed, CO, USA

This dataset includes bulk X-ray diffraction data from floodplain sediments collected as a part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected in order to investigate the role of biogeochemical cycling and other river corridor processes on riverine export of solutes. Sediment cores were collected from Meander C, Meander O, and Meander Z in July 2016 to September 2017 to depths of approximately 40-95 cm. Sample metadata including locations, depths, and sample dates are included in a csv file ("sample_list_and_locations.csv"). The file "diffraction_data.csv" contains raw diffraction data, and mineral quantification is in the file "mineral_abundance.csv". This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗

2019 Meander C and Meander Z floodplain groundwater chemistry from the East River Watershed, CO, USA

This dataset includes groundwater geochemistry data from floodplain piezometers collected as a part of the Watershed Function Scientific Focus Area (SFA) located in the Upper Colorado River Basin. The data were collected in order to investigate the role of hyporheic exchange and other river corridor processes on riverine export of solutes. Data includes samples from two intra-meander zones: Meander C, in the Pumphouse vicinity, and Meander Z, just upstream of the confluence with Brush Creek. Floodplain piezometers installed along two transects across Meander C (MCP and MCB wells) and Meander Z (MZA and MZB wells) were sampled on daily to weekly time scales during summer-fall 2019. Some river water grab samples are also included. Data includes in-field measurements (pH, electrical conductivity [EC], oxidation reduction potential [ORP], dissolved oxygen [DO], and groundwater level) along with laboratory measurements (dissolved inorganic carbon [DIC], dissolved organic carbon [DOC], metals and major cations, anions [chloride, sulfate, nitrate], and dissolved ammonium). Files are included in this dataset include: sample locations and depths in both a kmz file which can be opened in Google Earth and a csv file, aqueous geochemistry data in a csv files for Meander C and Meander Z, and analytical detection limits in a csv file. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes measured at 3 depths during snowmelt period in East River, CO (March, May, and June, September 2017)

Snowmelt is a critical biogeochemical period that accounts for large nitrogen (N) export events from high-elevation watersheds. Soil microbial populations bloom and immobilize N during snowmelt, yet the population size crashes in spring, which releases a pulse of soil N. We sought to discover the N sources fueling this microbial bloom and determine the fate of N following microbial die-off. Here, focusing on the snowmelt period within a headwater catchment of the Upper Colorado River Basin (East River, CO), we deployed strain-resolved metagenomics to identify the metabolic pathways and processes that mobilize soil N during and after snowmelt. Soil metagenome samples were taken from 6 snowpits from 3 depths (0-5cm, 5-15cm, >15cm) at 4 time points during snowmelt period (March 2017, May 2017, and June 2017, September 2017) generating 48 metagenomes. We reconstructed 474 metagenome-assembled genomes (MAGs) across all metagenomes.All 48 metagenomes were sequenced at JGI and raw data can be found under JGI (Joint Genome Institute) GOLD Study Gs0135149. Metagenome assemblies from IMG under the same study were used for genome binning. This dataset (1) a zip file of 474 MAGs (as fasta files, Gs0135149_bins_tar.gz), (2) sample metadata file with sample IGSNs (International Generic Sample Numbers) (samples.csv), (3) bounding box coordinates for the sampled locations (Gs0135149.kml), (4) metagenome metadata file listing IMG/M (Integrated Microbial Genomes/Metagenomes) metagenome accessions linking samples to metagenomes (metagenomes.csv), (5) location metadata file (locations.csv), (6) file-level metadata file (flmd.csv) and (7) data dictionary (dd.csv) file.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

Groundwater and river water elevations and temperature from 2017 to 2022 across Meander Z in the East River Watershed, Colorado

This dataset includes groundwater and river water elevations and temperature data collected in the East River watershed located in the Upper Colorado River Basin. The data were collected in order to investigate the coupling between hydrology and biogeochemical processes in the floodplain. Data was collected at ten groundwater locations in Meander Z (MZ), located just upstream of the confluence with Brush Creek and two river locations directly adjacent to Meander Z from 2017-2019. From 2019-2022, data was collected at five groundwater locations in Meander Z. Note that location names, not location identifiers (IDs), are used in the related publication Dewey et al. (2022). Both location IDs and names are included in data files. Files in this dataset include the main data files for each location zipped into a single folder (waterlevel_data.zip), an installation methods file describing sensor installation (InstallationMethods.csv), a file containing field metadata including GPS (Global Positioning System) coordinates and ground surface elevations (transducers_locations.csv). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. This dataset conforms to the ESS-DIVE hydrological reporting format. 2026-04-27 Update: The river water elevation data files (ER-MZR1.csv and ER-MZR2.csv) were corrected. The data for these two locations were inadvertently swapped in the original published data. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

Surface Water Quality Data from Beaver-Impacted Streams; Trail Creek and East River, Colorado 2025

This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

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2021 Annual Report: Atmospheric Radiation Measurement

In fiscal year 2021 (FY2021), the COVID-19 pandemic continued to have an impact on activities within the Atmospheric Radiation Measurement (ARM) user facility. Travel was limited, which affected field activities and forced the continuation of virtual meetings. However, the ability to travel expanded significantly through the year, bringing some return to normalcy, and throughout the year, there was a great deal of activity dedicated to advancing the facility. Because of COVID, ARM twice delayed the TRacking Aerosol Convection interactions ExpeRiment (TRACER) in the Houston, Texas, area. Originally planned to launch in the spring, TRACER started October 1, 2021, one month after the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign began near Crested Butte, Colorado. ARM teams worked onsite and remotely to make sure both campaigns could launch on this new schedule that was set early in the year. Data from SAIL and TRACER will be critical to improving earth system models, each contributing to different sets of issues. SAIL measurements will provide insights into how precipitation forms and water travels through the Upper Colorado River Basin. TRACER scientists want to know whether tiny atmospheric particles can influence the severity of thunderstorms. In October 2020, the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition ended after 13 months. MOSAiC data from ARM and other organizations are already helping scientists better understand how ice, atmosphere, and ocean systems are connected in the central Arctic. This report discusses some early investigations from MOSAiC, along with other ARM campaigns and activities generating prolific research. In this report, you will also learn how research activities moved forward during the pandemic at ARM’s fixed-location atmospheric observatories. There were important science applications from measurements across the facility. ARM spent a significant amount of FY2021 looking back—and ahead. In November 2020, ARM had its Triennial Review. This review is held every three years to evaluate ARM’s effectiveness in science, operations, and management. Overall, the reviewers had positive feedback regarding the breadth and impact of science activities using ARM data and the way ARM strives to meet changing user needs. The reviewers also provided some recommendations for strengthening ARM going forward. Incorporating feedback from the review, we finalized an updated Decadal Vision document that will help guide ARM priorities in the coming years. This report describes the four themes driving ARM’s Decadal Vision.

54 ENVIRONMENTAL SCIENCES↗

SAIL Aerosol Vertical Profiles (SAIL-AVP) Field Campaign Report

Aerosols are central to understanding the water cycle within mountainous regions, but a complete understanding of this role cannot be provided without vertically resolved observations, particularly for aerosol-cloud interactions, since we simultaneously need to know aerosol information and meteorology near cloud bases. The goal of SAIL Aerosol Vertical Profiles (SAIL-AVP) was to perform tethered balloon system (TBS) measurements during different seasons to elucidate process-level understanding of the aerosols and associated meteorological conditions within complex mountainous terrain. Measurements were conducted during the deployment of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s second Mobile Facility (AMF2) as part of the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in the East River Watershed of the Upper Colorado River Basin (UCRB) in southwestern Colorado. In mid-latitude continental interior mountain ranges, and especially at SAIL, aerosol vertical profiles and their relationships with meteorology are, almost without exception, inferred from a combination of ground-based and remote-sensing data. These flights provided many more dimensions to aerosol-cloud interactions that are unavailable to those inferential approaches: the TBS collected in situ information in the vertical, optical, chemical, and biological dimensions for aerosol-cloud interactions. Furthermore, the collocation of these flights with longstanding collaborative resources in the region, including the ongoing surface and subsurface hydrologic observations from the DOE’s Watershed Function Science Focus Area (SFA), produced a unique set of atmospheric observations that are complemented by existing land-surface and subsurface (e.g., groundwater) observations.

54 ENVIRONMENTAL SCIENCES↗

Investigating spatial variability of aerosol, cloud condensation nuclei, and ice nucleating particles in mountainous terrain

The ASR-supported Surface Atmosphere Integrated field Laboratory (SAIL) in the East River Watershed (ERW) of the Upper Colorado River Basin in southwestern Colorado ran from fall 2021 to spring 2023. Two monitoring sites were deployed in the East River Watershed as part of SAIL. The two sites were the Aerosol Observation System (AOS) located on Crested Butte Ski Mountain, and the ARM Mobile Facility (AMF-2), located at the Rocky Mountain Biological Laboratory in Gothic, Colorado. To gain a more comprehensive understanding of aerosols in complex, mountainous terrain, Handix Scientific deployed SAIL-Net, a distributed network of six measurement nodes spanning the domain of the SAIL research area from October 2021 to July 2023. Each node measured aerosol particles between 140 nm and 3.4 μm in diameter using a small particle counter (POPS, (Gao et al., 2016)), CNN using a miniature CCN counter (CloudPuck), and INP using the Time-Resolved Aerosol Filter Sampler (TRAPS, Creamean et al. (2018)). Our approach was similar to other studies that aimed to better characterize and understand aerosols and gas-phase pollutants using networks of lower-cost sensors (Caubel et al., 2019; Kelly et al., 2021; Asher et al., 2022). Such studies have identified neighborhood-level variations in pollutant concentrations (Schneider et al., 2017; Popoola et al., 2018; Caubel et al., 2019). Small-scale variations such as this are poorly represented in models and poorly measured by a single monitoring system (Caubel et al., 2019). Previous work has shown the representation error (the ability of measurements to represent a larger area) increases with complex orography, leading to decreases in model accuracy (Schutgens et al., 2017). The overall goal of SAIL-Net was to improve our understanding of the variability of aerosol in ERW, thus increasing our knowledge of aerosol-cloud interactions in this region and informing the usefulness of distributed networks of measurements for future studies.

54 ENVIRONMENTAL SCIENCES↗

Investigating Spatial Variability of Aerosol, Cloud Condensation Nuclei, and Ice Nucleating Particles in Mountainous Terrain Field Campaign Report

The U.S. Department of Energy Atmospheric System Research (ASR)-supported Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in the East River Watershed (ERW) of the Upper Colorado River Basin in southwestern Colorado ran from fall 2021 to spring 2023. Two monitoring sites were deployed in the ERW as part of SAIL. The two sites were the Aerosol Observation System (AOS) located on Crested Butte Ski Mountain, and the second ARM Mobile Facility (AMF2), located at the Rocky Mountain Biological Laboratory in Gothic, Colorado. To gain a more comprehensive understanding of aerosols in complex, mountainous terrain, Handix Scientific deployed SAIL-Net, a distributed network of six measurement nodes spanning the domain of the SAIL research area from October 2021 to July 2023. Each node measured aerosol particles between 140 nm and 3.4 μm in diameter using a small portable optical particle spectrometer (POPS; Gao et al. 2016), cloud condensation nuclei (CNN) using a miniature CCN counter (CloudPuck), and ice nucleating particles (INP) using the time-resolved aerosol filter sampler (TRAPS; Creamean et al. 2018). Our approach was similar to other studies that aimed to better characterize and understand aerosols and gas-phase pollutants using networks of lower-cost sensors (Caubel et al. 2019, Kelly et al. 2021, Asher et al. 2022). Such studies have identified neighborhood-level variations in pollutant concentrations (Schneider et al. 2017, Popoola et al. 2018, Caubel et al. 2019). Small-scale variations such as this are poorly represented in models and poorly measured by a single monitoring system (Caubel et al. 2019). Previous work has shown the representation error (the ability of measurements to represent a larger area) increases with complex orography, leading to decreases in model accuracy (Schutgens et al. 2017). The overall goal of SAIL-Net was to improve our understanding of the variability of aerosol in the ERW, thus increasing our knowledge of aerosol-cloud interactions in this region and informing the usefulness of distributed networks of measurements for future studies. We met this goal by answering the following science questions: 1. What is the aerosol temporal variability, and how does aerosol inhomogeneity vary seasonally? Is there significant seasonal variability in sources, or are short-term meteorological conditions the most important determining factor in sources for cloud nuclei? 2. What is the aerosol spatial variability? What are the aerosol characteristics at cloud base, presumably the particles most representative of those acting as cloud nuclei? 3. How should measurement networks be designed to capture aerosol-cloud interactions, and what do they need to measure? Can a single measurement site accurately represent aerosol properties in regions of complex terrain? SAIL-Net consisted of six measurement nodes spread across the ERW near Crested Butte, Colorado. The primary objective in site placement was to select locations that captured the vertical variation in aerosol properties while also spanning the domain of the SAIL campaign. The elevation of the sites ranged from roughly 2750 m along the valley floor of the ERW to approximately 3500 m near the top of Crested Butte Mountain, which is one of the taller peaks in the ERW. The farthest distance between sites was 14 km, while the closest two sites were approximately 1 km apart. Two of the sites were collocated with the ARM SAIL sites; our instruments sat on top of one of the trailers at AOS and another one of our sites was located in a meadow just above AMF2.

54 ENVIRONMENTAL SCIENCES↗

SAIL Field Campaign X-Band Precipitation Radar Seasonal Surface Hydrometeor Phase Classification Value-Added Product Report

The Surface Atmosphere Integrated Field Laboratory (SAIL) campaign generated an unprecedented, multisensory record of cold-season precipitation in the Upper Colorado River Basin (UCRB). To complement the Surface Quantitative Precipitation Estimation (SQUIRE) snow water equivalent (SWE) product derived from the Colorado State University (CSU) X-band radar, a hydrometeor phase classification data set was developed to systematically identify phase of the near-surface precipitation. The algorithm uses Corrected Moments in Antenna Coordinates (CMAC) fields with semi-supervised classification (SSC) and fuzzy-logic hydrometeor classification (FHC) methods and maps hydrometeor classes to a compact set of phase classes suitable for Quantitative Precipitation Estimation (QPE) and hydrologic applications. We used SQUIRE grid projections to mitigate beam-blockage issues by selecting the near-surface gates for each beam as well as to make it directly usable for the QPE products.

54 ENVIRONMENTAL SCIENCES↗

Advanced monitoring of soil-vegetation co-dynamics reveals the successive controls of snowmelt on soil moisture and on plant seasonal dynamics in a mountainous watershed

Evaluating the interactions between above- and below-ground processes is important to understand and quantify how ecosystems respond differently to atmospheric forcings and/or perturbations and how this depends on their intrinsic characteristics and heterogeneity. Improving such understanding is particularly needed in snow-impacted mountainous systems where the complexity in water and carbon storage and release arises from strong heterogeneity in meteorological forcing and terrain, vegetation and soil characteristics. This study investigates spatial and temporal interactions between terrain, soil moisture, and plant seasonal dynamics at the intra- and inter-annual scale along a 160 m long mountainous, non-forested hillslope-to-floodplain system in the upper East River Watershed in the upper Colorado River Basin. To this end, repeated UAV-based multi-spectral aerial imaging, ground-based soil electrical resistivity imaging, and soil moisture sensors were used to quantify the interactions between above and below-ground compartments. Results reveal significant soil-plant co-dynamics. The spatial variation and dynamics of soil water content and electrical conductivity, driven by topographic and soil intrinsic characteristics, correspond to distinct plant types, with highest plant productivity in convergent areas. Plant productivity in heavy snow years benefited from more water infiltration as well as a shallow groundwater table depth. In comparison, low snowpack years with an early first bare-ground date, which are linked to an early increase in plant greenness, imply a short period of saturated conditions that leads to lower average and maximum greenness values during the growing season. Overall, these results emphasize the strong impact of snowpack dynamics, and terrain and subsurface characteristics on the heterogeneity in plant type and seasonal dynamics.

54 ENVIRONMENTAL SCIENCES↗