Mountainous watersheds are characterized by variability in functional traits, including vegetation, topography, geology, and geomorphology, which together determine nitrogen (N) retention, and release. Coal Creek and East River are two contrasting catchments within the Upper Colorado River Basin that differ markedly in total nitrate (NO3-) export. The East River has a diverse vegetation cover, sinuous floodplains, and is underlain by N-rich marine shale, resulting in a three to twelve times greater total NO3- export relative to the conifer-dominated Coal Creek. While this can partly be explained by the larger size of the East River, the distinct watershed traits of these two catchments imply different mechanisms controlling the aggregate N-export signal. A causality analysis shows biogenic and geogenic processes were critical in determining NO3- export from the East River catchment. Stable isotope ratios of NO3- (δ15NNO3 and δ18ONO3) show the East River catchment is a strong hotspot for biogeochemical processing of NO3- at the soil-saprolite interface and within the floodplain prior to export. By contrast, the conifer-dominated Coal Creek retained nearly all (~97 %) atmospherically-deposited NO3-, and its export was controlled by catchment hydrological traits (i.e., snowmelt periods and water table depth). The conservative N-cycle within Coal Creek is likely due to the abundance of conifer trees, and a smaller riparian region, retaining more NO3- overall and reduced processing prior to export. This study highlights the value of integrating isotope systematics to link watershed functional traits to mechanisms of watershed element retention and release.

Carbon distribution in soil is intricately linked to soil health. However, repeatable measurements of carbon distribution typically require destructive sampling and laboratory analyses. Soil carbon distributions in both natural and managed landscapes significantly vary due to numerous factors related to topography, mineralogy, hydrology, land use history, and vegetation. In order to accurately inventory soil C distributions and dynamics over time, we are developing a new technique that relies on neutron inelastic scattering to measure elemental distribution. This approach can be used to image a volume of approximately 50 cm × 50 cm × 30 cm (depth) with a few centimeters resolution, for example the root zone of a plant. To achieve this, we use neutrons created in a deuterium-tritium fusion reaction. The products of this reaction are an alpha particle and a neutron. Due to momentum conservation, both particles are emitted in opposite directions in the center-of-mass frame. This allows us to measure the neutron direction by detecting the alpha particle with a position sensitive detector. The neutron can then induce an inelastic scattering reaction on a carbon nucleus present in the soil, and this event produces a gamma ray with a characteristic energy for the carbon isotope. Using a gamma detector, we measure these gamma rays, which allows us to perform time-of-flight analysis between arrival times of the alpha and gamma particles. Using the information from both measurements (alpha and gamma), we can reconstruct the spatial distribution of the carbon atoms and other elements in soil. We will report on the design, potential applications, and limitations of the instrument. We will also report on initial results from laboratory experiments and progress towards future field experiments. The information, data, or work presented herein was funded by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Contract No. DE-AC02-05CH11231.

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.

Carbon sequestration in soils represents an important opportunity to reduce the amount of greenhouse gases in the atmosphere and thereby offsetting the effects of climate change. To monitor carbon sequestration accurate measurements of soil carbon are needed that can be repeated over several growing cycles. Furthermore, soil carbon is an important indicator of soil health; accurately measuring carbon distribution is therefore important for informing land use management practices. We are developing a new instrument that images a volume of approximately 50 cm × 50 cm × 30 cm (depth) with a few centimeters resolution by applying neutron scattering techniques. Contrary to current coring methods, this approach is non-destructive, samples a large area, and allows real-time analysis of the soil carbon density. In this technique a neutron and an alpha particle are created in a deuterium-tritium fusion reaction. Due to momentum conservation the two particles move in opposite directions. Creating the particles in a small point source allows us to calculate the direction in which the neutron is moving by tracking the associated alpha particle using a position sensitive detector. The neutron can then enter the soil and inelastically scatter off atoms in the soil, creating an isotope-specific gamma ray in the process. Measuring the energy of the gamma ray allows identification of the isotope. Measuring the time-of-flight between the alpha detection and the gamma detection together with the direction of travel of the neutron allows the calculation of the 3D position of the scattering center. Using this Associate Particle Imaging (API) technique 3D density plots of carbon, oxygen, silicon, and aluminum can be obtained. In this poster we present first results from applying API to pre-mixed and standard soil samples in a laboratory setting (field tests are planned in the future). We will compare measured data to neutron-transport simulations and discuss our data analysis algorithm to reconstruct the carbon density in the soil from API data. We will further discuss achievable resolution and time requirement for measurements in the field. The information, data, or work presented herein was funded by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Contract No. DE-AC02-05CH11231.

In studying problems like plant-soil-microbe interactions in environmental biogeochemistry and ecology, one usually has to quantify and model how substrates control the growth of, and interaction among, biological organisms. To address these substrate-consumer relationships, many substrate kinetics and growth rules have been developed, including the famous Monod kinetics for single substrate-based growth, Liebig’s law of the minimum for multiple-nutrient co-limited growth, etc. However, the mechanistic basis that leads to these various concepts and mathematical formulations and the implications of their parameters are often quite uncertain. Here we show that an analogy based on Ohm’s law in electric circuit theory is able to unify many of these different concepts and mathematical formulations. In this Ohm’s law analogy, a resistor is defined by a combination of consumers’ and substrates’kinetic traits. In particular, the resistance is equal to the mean first passage time that has been used by renewal theory to derive the Michaelis-Menten kinetics under substrate replete conditions for a single substrate as well as the predation rate of individual organisms. We further show that this analogy leads to important insights on various biogeochemical problems, such as (1) multiple-nutrient co-limited biological growth, (2) denitrification, (3) fermentation under aerobic conditions, (4) metabolic temperature sensitivity, and (5) the accuracy of Monod kinetics for describing bacterial growth. We expect our approach will help both modelers and non-modelers to better understand and formulate hypotheses when studying certain aspects of environmental biogeochemistry and ecology.

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.