Understanding the partitioning of snow and rain contributing to either catchment streamflow or evapotranspiration (ET) is of critical relevance for water management in response to climate change. To investigate this partitioning, we use endmember splitting and mixing analyses based on stable isotope (18O) data from nine headwater catchments in the East River, Colorado. Our results show that one third of the snow partitions to ET and 13% of the snowmelt sustains summer streamflow. Only 8% of the rainfall contributes to the summer streamflow, because most of the rain (67%) partitions to ET. The spatial variability of precipitation partitioning is mainly driven by aspect and tree density across the sub-catchments. Catchments with higher tree density have a higher share of snow becoming ET, resulting in less snow in summer streamflow. Summer streamflow did not contain more rain with higher rainfall sums, but more rain was taken up in ET.

A multi-scale understanding of processes controlling the nitrogen budget is essential for predicting how nitrogen loads will be affected by climate-induced disturbances. Recent studies in snowmelt-dominated catchments have documented changes in nitrogen retention over time, such as declines in watershed exports of nitrogen, though there is a limited understanding of the controlling processes driving these trends. Working in the mountainous headwater East River Colorado watershed, our study aims to refine this process-based understanding by exploring the effects of riparian hollows as nitrogen cycling hotspots. The objectives of this study are to (1) quantify the influence of riparian hollows on nitrogen retention in snowmelt-dominated catchments, (2) understand how disturbances (i.e. early snowmelt, long summer droughts) and heterogeneities affect the nitrogen-retention capacity of riparian hollows, and (3) quantify the relative contribution of riparian hollows to the watershed nitrogen budget using high-resolution LIDAR watershed data. We used a multi-component flow and reactive transport model, MIN3P, to simulate the biogeochemical kinetics of riparian hollows, using data from the East River watershed to parameterize, constrain, and validate the model. Several hydrological, biogeochemical, and geological perturbations were then imposed across simulations to assess the effects of abrupt and gradual perturbations on riparian hollow hydrobiogeochemical dynamics. Topographic position and wetness indices were used to scale the net yearly storage and flux terms from riparian hollows, and reveal the significant impacts hollows can have on aggregated watershed biogeochemistry. Initial model results suggest that riparian hollows serve as significant nitrogen sinks, and that earlier snowmelt and extended dry season considerably limit denitrifying processes. Our work linking remote sensing and empirical scaling techniques to numerical biogeochemical simulations is an important first-step in assessing nitrogen-retaining features relative to the watershed nitrogen budget.

Stable isotopes of water are important tracers in hydrologic research for understanding water partitioning between vegetation, groundwater, and runoff, but are rarely applied to large watersheds with persistent snowpack and complex topography. We combined an extensive isotope dataset with a coupled hydrologic and snow isotope fractionation model to assess mechanisms of isotopic inputs into the soil zone and implications on recharge dynamics within a large, snow-dominated watershed of the Upper Colorado River Basin. Results indicate seasonal isotopic variability and isotope lapse rates of net precipitation are the dominant control on isotopic inputs to the basin. Snowpack fractionation processes account for <5% annual isotope influx variability. Isotopic fractionation processes are most important in the shrub-dominated upper montane. Effects of isotopic fractionation are less important in the low-density conifer forests of the upper subalpine due to vegetative shading, low aridity, and a deep, persistent snowpack that buffers small sublimation losses. Melt fractionation can have sub-seasonal effects on snowmelt isotope ratios with initial snowmelt depleted but later snowmelt relatively enriched in heavy isotopes through the isotopic mass balance of the remaining snowpack, with the efficiency of isotopic exchange between ice and liquid water declining as snow ablation progresses. Hydrologic analysis indicates maximum recharge in the upper subalpine with wet years producing more isotopically depleted snowmelt (1-2‰ reduction in d18O) through reduced aridity when energy-limited. The five-year volume-weighted d18O in this zone (18.2±0.4‰) matches groundwater observations from multiple deep wells, providing evidence that the upper subalpine is a preferential recharge zone in mountain systems.

Patterns of watershed nitrogen (N) retention and loss are shaped by how watershed biogeochemical processes retain, biogeochemically transform, and lose incoming atmospheric deposition of N. Loss patterns represented by concentration, discharge, and their associated stream exports are important indicators of watershed N retention patterns because they reveal hysteresis patterns (i.e. return to initial state) or one-way transition patterns (i.e. new steady state) that provide insight into watershed conditions driving long term stream trends. We examined the degree to which Continental U.S. (CONUS) scale deposition patterns (wet and dry atmospheric deposition), vegetation trends, and stream trends can be potential indicators of watershed N-saturation and retention conditions, and how watershed N retention and losses vary over space and time. By synthesizing changes and modalities in watershed nitrogen loss patterns based on stream data from 2200 U.S. watersheds over a 50 year record, our work characterized a new hysteresis conceptual model based on factors driving watershed N-retention and loss, including hydrology, atmospheric inputs, land-use, stream temperature, elevation, and vegetation. Our results show that atmospheric deposition and vegetation productivity groups that have strong positive or negative trends over time are associated with patterns of stream loss that uniquely indicate the stage of watershed N-saturation and reveal unique characteristics of watershed N-retention hysteresis patterns. In particular, regions with increasing atmospheric deposition and increasing vegetation health/biomass patterns have the highest N-retention capacity, become increasingly N-saturated over time, and are associated with the strongest declines in stream N exports—a pattern that is consistent across all land cover categories. In particular, the second largest factor explaining watershed N-retention was in-stream temperature and dissolved organic carbon concentration trends, while land-use explained the least amount of variability in watershed N-retention. Our CONUS scale investigation supports an updated hysteresis conceptual model of watershed N-retention and loss, providing great value to using long-term stream monitoring data as indicators of watershed N hysteresis patterns.

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.