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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

2020 Postclosure Groundwater Monitoring and Inspection Report, Central Nevada Test Area, Subsurface Corrective Action Unit 443

This report presents the groundwater monitoring data collected by the U.S. Department of Energy (DOE) Office of Legacy Management (LM) from the Central Nevada Test Area (CNTA), Nevada, Site, Subsurface Corrective Action Unit (CAU) 443 in Nye County, Nevada (Figure 1). The CNTA is the site of an underground nuclear test in 1968 that resulted in residual contamination near the detonation depth of 3200 feet (ft); the contamination requires long-term monitoring. Responsibility for the environmental restoration and long-term monitoring was transferred from DOE’s National Nuclear Security Administration, Nevada Field Office, to LM on October 1, 2006. The environmental restoration and site closure process were completed in 2015 in accordance with the amended 1996 Nevada Federal Facility Agreement and Consent Order (FFACO) (State of Nevada et al. 1996, as amended) and all applicable Nevada Division of Environmental Protection (NDEP) policies and regulations. The Closure Report, Central Nevada Test Area, Subsurface Corrective Action, Unit 443 (DOE 2018), also called the Closure Report, originally was completed in January 2016 and revised in October 2018; it describes LM’s plan for long-term postclosure monitoring. This includes monitoring of the radioisotopes of interest and water elevations, inspecting the site and maintaining the institutional controls (ICs), evaluating and reporting data, and documenting the site’s records and data management processes (DOE 2018).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)

We present a new 3D unstructured-grid global ocean model to study both tidal and nontidal processes, with a focus on the total water elevation. Unlike existing global ocean models, the new model resolves estuaries and rivers down to ~8 m without the need for grid nesting. The model is validated with both satellite and in situ observations for elevation, temperature, and salinity. Tidal elevation solutions have a mean complex root-mean-square error (RMSE) of 4.2 cm for M2 and 5.4 cm for all five major constituents in the deep ocean. The RMSEs for the other four constituents, S2, N2, K1, and O1, are, respectively, 2.05, 0.93, 2.08, and 1.34 cm). The nontidal residual assessed by a tide gauge dataset (GESLA) has a mean RMSE of 7 cm. For the first time ever, we demonstrate the potential for seamless simulation on a single mesh from the global ocean into several estuaries along the US West Coast. The model is able to accurately capture the total elevation, even at some upstream stations. The model can therefore potentially serve as the backbone of a global tide surge and compound flooding forecasting framework.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Instability of U 3 Si 2 in pressurized water media at elevated temperatures

Following the Fukushima Daiichi accident, significant efforts from industry and the scientific community have been directed towards the development of alternative nuclear reactor fuels with enhanced accident tolerance. Among the proposed materials for such fuels is a uranium silicide compound (U 3 Si 2 ), which has been selected for its enhanced thermal conductivity and high density of uranium compared to the reference commercial light water reactor (LWR) nuclear fuel, uranium oxide (UO 2 ). To be a viable candidate LWR fuel, however, U 3 Si 2 must also demonstrate that, in the event of this fuel coming in contact with aqueous media, it will not degrade rapidly. In this contribution, we report the results of experiments investigating the stability of U 3 Si 2 in pressurized water at elevated temperatures and identify the mechanisms that control the interaction of U 3 Si 2 under these conditions. Our data indicate that the stability of this material is primarily controlled by the formation of a layer of USiO 4 (the mineral, coffinite) at the surface of U 3 Si 2 . The results also show that these layers are destabilized at T > 300 °C, leading to the complete decomposition of U 3 Si 2 and its pulverization due to its full oxidation to UO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

The behavior of methane–water mixtures under elevated pressures from simulations using many-body potentials

Non-polarizable empirical potentials have been proven to be incapable of capturing the mixing of methane–water mixtures at elevated pressures. Although density functional theory-based ab initio simulations may circumvent this discrepancy, they are limited in terms of the relevant time and length scales associated with mixing phenomena. Here, we show that the many-body MB-nrg potential, designed to reproduce methane–water interactions with coupled cluster accuracy, successfully captures this phenomenon up to 3 GPa and 500 K with varying methane concentrations. Two-phase simulations and long time scales that are required to fully capture the mixing, affordable due to the speed and accuracy of the MBX software, are assessed. Constructing the methane–water equation of state across the phase diagram shows that the stable mixtures are denser than the sum of their parts at a given pressure and temperature. As a result, we find that many-body polarization plays a central role, enhancing the induced dipole moments of methane by 0.20 D during mixing under pressure. Overall, the mixed system adopts a denser state, which involves a significant enthalpic driving force as elucidated by a systematic many-body energy decomposition analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Stream water sourcing from high-elevation snowpack inferred from stable isotopes of water: a novel application of d-excess values

About 80 % of the precipitation at the Colorado River's headwaters is snow, and the resulting snowmelt-driven hydrograph is a crucial water source for about 40 million people. Snowmelt from alpine and subalpine snowpack contributes substantially to groundwater recharge and river flow. However, the dynamics of snowmelt progression are not well understood because observations of the high-elevation snowpack are difficult due to challenging access in complex mountainous terrain as well as the cost and labor intensity of currently available methods. We present a novel approach to infer the processes and dynamics of high-elevation snowmelt contributions predicated upon stable hydrogen and oxygen isotope ratios observed in streamflow. We show that deuterium-excess (d-excess) values of stream water could serve as a comparatively cost-effective proxy for a catchment-integrated signal of high-elevation snowmelt contributions to catchment runoff. We sampled stable hydrogen and oxygen isotope ratios of the precipitation, snowpack, and stream water in the East River, a headwater catchment of the Colorado River, and the stream water of larger catchments at sites on the Gunnison River and Colorado River. The d-excess of snowpack increased with elevation; the upper subalpine and alpine snowpack (> 3200 m) had substantially higher d-excess compared to lower elevations (< 3200 m) in the study area. The d-excess values of stream water reflected this because d-excess values increased as the higher-elevation snowpack contributed more to stream water generation later in the snowmelt/runoff season. End-member mixing analyses based on the d-excess data showed that the share of high-elevation snowmelt contributions within the snowmelt hydrograph was on average 44 % and generally increased during melt period progression, up to 70 %. The observed pattern was consistent during 6 years for the East River, and a similar relation was found for the larger catchments on the Gunnison and Colorado rivers. High-elevation snowpack contributions were found to be higher for years with lower snowpack and warmer spring temperatures. Thus, we conclude that the d-excess of stream water is a viable proxy to observe changes in high-elevation snowmelt contributions in catchments at various scales. Inter-catchment comparisons and temporal trends of the d-excess of stream water could therefore serve as a catchment-integrated measure to monitor if mountain systems rely on high-elevation water inputs more during snow drought compared to years of average snowpack depths.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Oxidation of Alloy X in Subcritical, Transition, and Supercritical Water

This work investigates the oxidation of a nickel-based superalloy, namely Alloy X, in water at elevated temperatures: subcritical water at 261°C and 27 MPa, the transition between subcritical and supercritical water at 374°C and 27 MPa, and supercritical water at 380°C and 27 MPa for 100 h. The morphology of the sample surfaces were studied using scanning electron microscopy coupled with focused ion beam milling, and the surface chemistry was investigated using x-ray diffraction, Raman spectroscopy, energy dispersive x-ray spectroscopy, and x-ray photoelectron spectroscopy before and after exposure studies. Surfaces of all samples were identified to comprise of a ferrite spinel containing aluminum.

Materials Science↗
DOE OSTI2020

Subsurface Flow Across Polygonal Tundra Measured by Bromide Tracer, Utqiagvik (Barrow), Alaska, 2015-2016

A bromide tracer study with the primary focus on hydrology in the active layer of polygonal tundra in the Barrow Environmental Observatory in Utqiagvik (Barrow), Alaska from July 2015 to September 2016. Sampling devices placed at various depths in the polygon centers, rims, and troughs were used to monitor tracer concentrations during thaw seasons. The tracer was continually monitored simultaneously on a low- and high-centered polygon throughout thaw seasons. Included is one data file of the bromide tracer concentrations. Also included are measurements taken throughout the experiment - one data file each of frost table depth and precipitation; and twelve water table elevation data files. Water level data, meteorological data, and thaw depth measurements were taken throughout the experiment. Our approach permits a comparison of hydrological behaviors in low- and high-centered polygons over the same time period and meteorological conditions.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Groundwater table elevation and temperature from 2015 to 2024 across Meander C at the Lower Montane site in the East River Watershed, Colorado.

This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells ER-CPA1 to ER-CPA6. Another dataset contains the data from wells at nearby Locations. Each file contains the water level elevation and the water temperature. Water level elevation has been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file Well_Location.csv). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements were initially added to the archive for the period 2015 to 2019, and later updated with time-series until 2024 (end of data collection). The dataset contains 7 *.csv data files, and 3 *.csv metadata files. Feel free to contact the author with any questions or collaboration interests. The publication year was updated from "2020" to "2025" to reflect the revised version of this dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Groundwater table elevation and temperature from 2015 to 2024 at the Lower Montane site in the East River Watershed, Colorado.

This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells with Location ID's ER-DOW (alias DO1West), ER-DOE (alias DO2East), ER-MBA1 (alias M1Bend1), ER-MBA2 (alias M1Bend2), ER-UPW (alias UP1West), ER-UPM (alias UP2), ER-UPE (alias UP3East). Another dataset contains the data from wells with Location ID's ER-CPA1 to ER-CPA6. Each file contains the water level elevation and the water temperature. Water level elevation has been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file Well_Location.csv). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements were initially added to the archive for the period 2015 to 2019, and later updated with time-series until 2024 (end of data collection). The dataset contains 8 *.csv data files, and 3 *.csv metadata files. Feel free to contact the author with any questions or collaboration interests. The publication year was updated from "2020" to "2025" to reflect the revised version of this dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Peatland hydrology across scale: a probabilistic framework for confronting variability, heterogeneity, and uncertainty (Final Report)

Our project aimed to guide the representations of peatland hydrology and water-carbon feedbacks within Earth System Models, by improving process understanding and developing parsimonious models that elucidate the effects of hydroclimatic variability and spatial heterogeneity. Our research questions centered on the three key drivers of peatland hydrology: (1) seasonal and interannual hydroclimatic fluctuations, (2) spatial heterogeneity of peatland microtopography, and (3) hydrological connectivity across landscape units within a peatland watershed. Our analyses and model testing used existing long-term datasets within the Marcell Experimental Forest (MEF), with new data collected whenever necessary. To date, we have demonstrated the strong influence of water table elevations on the temperature sensitivity of CH 4 emissions, using a newly developed eddy covariance dataset spanning eleven years at MEF. Specifically, higher water tables dampen the increase in CH 4 emissions in the spring as well as their decrease in the fall, resulting in hysteresis. These results imply that any hydroclimatological changes in peatlands that shift seasonal water availability from winter to summer will increase annual CH 4 emissions, even if soil temperature remains unchanged. To further investigate water table elevation change within the peatland microtopography, we installed automated water table gauges across four bog-forest transects (the “lagg”) in two peatland watersheds at MEF, which are hotspots of intense biogeochemical activity. These measurements will give us new information about the extent of lagg expansion and contraction during snowmelt and high intensity rainfall events, as well as the directionality of water and nutrient flow into the bog from the surrounding forests. Finally, we investigated the hydrological connectivity across the peatland watershed complex during early spring – a critical period where water table is elevated from snowmelt – using extended hydrological records from MEF (e.g., snow and frost depths, water table elevations, streamflow). The importance of thermal and wintertime processes within the Energy Exascale Earth System Model (E3SM) was determined through sensitivity analyses. Results from data analyses show that (i) streamflow has decreased over decades likely due to increased evapotranspiration rates (despite no detectable trends in precipitation), (ii) spring streamflow generation is controlled by a sequence of fill-and-spill pathways from the snowpack to the stream through peatland water stores, and (iii) frost depth is a key explanatory variable for the timing and magnitude of streamflow. These results suggest that frost plays an important role in connecting surface water storage in peatlands to stream outlets, and that the hydrological connectivity across the peatland watershed complex can mediate the sensitivity of hydrological responses to climate variations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Attaining freshwater and estuarine-water soil saturation in an ecosystem-scale coastal flooding experiment

Abstract Coastal upland forests are facing widespread mortality as sea-level rise accelerates and precipitation and storm regimes change. The loss of coastal forests has significant implications for the coastal carbon cycle; yet, predicting mortality likelihood is difficult due to our limited understanding of disturbance impacts on coastal forests. The manipulative, ecosystem-scale Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m 2 ), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. Transient saturation (5 h) of the entire soil rooting zone (0–30 cm) across a 2000 m 2 coastal forest was attained by delivering 300 m 3 of water through a spatially distributed irrigation network at a rate just above the soil infiltration rate. Our water delivery approach also elevated the water table (typically ~ 2 m belowground) and achieved extensive, low-level inundation (~ 8 cm standing water). A TEMPEST simulation approximated a 15-cm rainfall event and based on historic records, was of comparable intensity to a 10-year storm for the area. This characterization was supported by showing that Hurricane Ida’s (~ 5 cm rainfall) hydrologic impacts were shorter (40% lower duration) and less expansive (80% less coverage) than those generated through experimental manipulation. Future work will apply TEMPEST treatments to evaluate coastal forest resilience to changing hydrologic disturbance regimes and identify conditions that initiate ecosystem state transitions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Technology Impact and Resource Assessment of Existing and Planned U.S. Biofuel Production: Life Cycle Water Consumption, Water Stress, Land Use, and Criteria Air Pollutants

Biofuels have the potential to strengthen the U.S. energy supply, enhance energy security, and promote economic development. As the United States continues to expand biofuel production, quantifying resource requirements and location-specific constraints is crucial for planning, siting, and technology development to support long-term viability. Accordingly, this work assesses the life cycle resource consumption (water consumption, and land use), water stress and criteria air pollutants associated with expanded U.S. biofuel production over the 2020–2035 period, based on producers’ plans. We perform a bottom-up technology impact assessment and resource assessment by integrating facility-level production statistics with Argonne’s Research and Development (R&D) GREET model and county-level water-stress characterization factors from Available Water Remaining for the United States (AWARE-US) model. Results suggest that by 2035, biofuels could meaningfully contribute to U.S. energy demand, driven primarily by first-generation and waste-based feedstocks with plans for substantial capacity expansion, although cellulosic and e-fuel technologies remain limited. However, growth must be managed to minimize impacts on water resources and land use. These impacts vary by fuel type and facility location, specifically, projected expansion increases water consumption and can elevate water-stress impacts in certain regions like Nebraska, Kansas, Colorado, Idaho, California and North Texas. Direct land use also increases overall, particularly for first-generation feedstocks such as corn and soybeans. These findings underscore the need for continued technological improvements and innovative strategies to manage resource demands as the industry scales and to support complementary deployment within the evolving U.S. energy system.

09 BIOMASS FUELS↗
DOE OSTI2023

Efficient Probabilistic Prediction and Uncertainty Quantification of Tropical Cyclone–Driven Storm Tides and Inundation

Abstract This study proposes and assesses a methodology to obtain high-quality probabilistic predictions and uncertainty information of near-landfall tropical cyclone–driven (TC-driven) storm tide and inundation with limited time and resources. Forecasts of TC track, intensity, and size are perturbed according to quasi-random Korobov sequences of historical forecast errors with assumed Gaussian and uniform statistical distributions. These perturbations are run in an ensemble of hydrodynamic storm tide model simulations. The resulting set of maximum water surface elevations are dimensionality reduced using Karhunen–Loève expansions and then used as a training set to develop a polynomial chaos (PC) surrogate model from which global sensitivities and probabilistic predictions can be extracted. The maximum water surface elevation is extrapolated over dry points incorporating energy head loss with distance to properly train the surrogate for predicting inundation. We find that the surrogate constructed with third-order PCs using elastic net penalized regression with leave-one-out cross validation provides the most robust fit across training and test sets. Probabilistic predictions of maximum water surface elevation and inundation area by the surrogate model at 48-h lead time for three past U.S. landfalling hurricanes (Irma in 2017, Florence in 2018, and Laura in 2020) are found to be reliable when compared to best track hindcast simulation results, even when trained with as few as 19 samples. The maximum water surface elevation is most sensitive to perpendicular track-offset errors for all three storms. Laura is also highly sensitive to storm size and has the least reliable prediction. Significance Statement The purpose of this study is to develop and evaluate a methodology that can be used to provide high-quality probabilistic predictions of hurricane-induced storm tide and inundation with limited time and resources. This is important for emergency management purposes during or after the landfall of hurricanes. Our results show that sampling forecast errors using quasi-random sequences combined with machine learning techniques that fit polynomial functions to the data are well suited to this task. The polynomial functions also have the benefit of producing exact sensitivity indices of storm tide and inundation to the forecasted hurricane properties such as path, intensity, and size, which can be used for uncertainty estimation. The code implementing the presented methodology is publicly available on GitHub.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The FLOod Probability Interpolation Tool (FLOPIT): A Simple Tool to Improve Spatial Flood Probability Quantification and Communication

Understanding flood probabilities is essential to making sound decisions about flood-risk management. Many people rely on flood probability maps to inform decisions about purchasing flood insurance, buying or selling real-estate, flood-proofing a house, or managing floodplain development. Current flood probability maps typically use flood zones (for example the 1 in 100 or 1 in 500-year flood zones) to communicate flooding probabilities. However, this choice of communication format can miss important details and lead to biased risk assessments. Here we develop, test, and demonstrate the FLOod Probability Interpolation Tool (FLOPIT). FLOPIT interpolates flood probabilities between water surface elevation to produce continuous flood-probability maps. FLOPIT uses water surface elevation inundation maps for at least two return periods and creates Annual Exceedance Probability (AEP) as well as inundation maps for new return levels. Potential advantages of FLOPIT include being open-source, relatively easy to implement, capable of creating inundation maps from agencies other than FEMA, and applicable to locations where FEMA published flood inundation maps but not flood probability. Using publicly available data from the Federal Emergency Management Agency (FEMA) flood risk databases as well as state and national datasets, we produce continuous flood-probability maps at three example locations in the United States: Houston (TX), Muncy (PA), and Selinsgrove (PA). We find that the discrete flood zones generally communicate substantially lower flood probabilities than the continuous estimates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Quantifying Subsurface Flow and Solute Transport in a Snowmelt‐Recharged Hillslope With Multiyear Water Balance

Abstract Quantifying flow and transport from hillslopes is vital for understanding water quantity and quality in rivers, but remains obscure because of limited subsurface measurements. Using measured hydraulic conductivity K profiles and water balance over a single year to calibrate a transmissivity feedback model for a hillslope in the East River watershed (Colorado) proved unsatisfactory for predicting flow over the subsequent years. Well‐constrained field‐scale K were obtained by optimizing subsurface flux predictions over years having large differences in recharge, and by including estimates of interannual transfer of excess snowmelt recharge. Water and solute exports during high snowmelt recharge occur predominantly via shallow groundwater flow through weathered rock and soil because of their enlarged transmissivities under saturated conditions. Conversely, these shallow pathways are less active in snow drought years when the water table remains deeper within the weathering zone. Hillslope soil water monitoring showed that rainfall does not infiltrate deeply during summer and fall months, and revealed water losses consistent with model ET predictions. By combining water table‐dependent fluxes with pore water chemistry in different zones, time‐dependent rates of solute exports become predictable. As an example, calibrated K were combined with dissolved nitrogen concentrations in pore waters to show the snowmelt‐dependence of reactive nitrogen exported from the hillslope, further supporting the recent finding that the weathering zone is the dominant source of reactive nitrogen at this site. Subsurface export predictions can now be obtained for wide ranges of recharge based on measurements of water table elevation and profiles of pore water chemistry.

54 ENVIRONMENTAL SCIENCES↗