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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Pahute Mesa-Oasis Valley Hydrostratigraphic Framework Model for Corrective Action Units 101 and 102: Central and Western Pahute Mesa, Nye County, Nevada (Rev. 0)

A new, revised three-dimensional (3-D) hydrostratigraphic framework model (HFM) for the Central and Western Pahute Mesa Corrective Action Units 101 and 102 was completed in 2019. The initial (Phase I) model was completed in 2002 and was documented in A Hydrostratigraphic Model and Alternatives for the Groundwater Flow and Contaminant Transport Model of Corrective Action Units 101 and 102: Central and Western Pahute Mesa, Nye County, Nevada (BN, 2002). Subsequent flow and transport modeling revealed the need to collect additional data to reduce uncertainties. The Phase II data collection and characterization effort included extensive well drilling and testing activities, and rebuilding of the Phase I 3-D HFM, resulting in the Phase II HFM (NSTec, 2014). Further drilling (Well ER-20-12), data collection, and interpretive work (e.g., Thirsty Canyon Lineament [Wurtz and Day, 2018]) were incorporated into the Pahute Mesa-Oasis Valley (PM-OV) HFM. The PM-OV HFM incorporates the area of interest from the Phase II HFM and adds additional areas, primarily to the north and west with minor additions to the south and east. The new, expanded area matches the PM-OV groundwater basin as defined in Fenelon et al. (2016) and includes Pahute Mesa, a former nuclear testing area at the Nevada National Security Site; and Oasis Valley, a groundwater discharge area downgradient from contaminant source areas on Pahute Mesa. The data and information necessary to build the PM-OV HFM are provided in Navarro (2019). The PM-OV HFM will be used by hydrologic modelers who are tasked with developing a model to determine how contaminants are transported by groundwater flow in an area of complex geology. The model area is large (more than 6,250 square kilometers) and geologically complex, including Paleozoic- to Mesozoic-age structures (e.g., thrust faults, Thirsty Canyon Lineament), at least seven Tertiary-age calderas, several intrusive bodies, and many relatively recent basin-and-range normal faults. Investigators from the U.S. Geological Survey; National Security Technologies, LLC; National Laboratories; and U.S. Department of Energy contractors have organized the more than 300 volcanic units and other rocks in the model area into 77 hydrostratigraphic units (HSUs). The volcanic rocks are subdivided into 42 aquifers, 11 confining units, and 9 composite units (containing both aquifer and confining unit rocks). The underlying pre-Tertiary rocks were divided into 5 HSUs, comprising 2 aquifers and 3 confining units. The model also includes 1 alluvial aquifer unit, 8 intrusive confining units, and 1 granite confining unit. The model depicts the thickness, extent, and geometric relationships of these HSUs (“layers” in the model) along with all the major structural features that control them, including calderas and faults. The most substantive differences between the Phase II HFM and the PM-OVHFM include (1) addition of the new data and resulting revised interpretations from the additional area encompassed by the PM-OV groundwater basin; (2) incorporation of 16 new faults; (3) 12 boreholes from the northern extension; (4) 2 additional caldera-collapse collars; and (5) correlation of the simulated faulting and hydrostratigraphy in the eastern part of the model domain with the delineations represented in the neighboring Rainier Mesa-Shoshone Mountain HFM-Prime and Yucca Flat-Climax Mine HFM. All PM-OV HFM delineations were based on published and unpublished data from geophysical investigations, surface geologic maps, and drill-hole records. Phase II approached model uncertainty using the model-building software to test model configurations and hydrologic consequences using a range of values for parameters such as fault offset amounts and HSU elevations. The PM-OV HFM expands on this approach to encompass the entire PM-OV groundwater basin.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

TRIDENT Drill Validation at Mars and Lunar Analog Field Sites

Drilling on Earth is typically a human-intensive activity. Drilling on other planets is further complicated by the lack of prior local field surveys of their target area, hence blindly drilling into uncertain target rocks. Field conditions on the Moon or Mars are also different than for shallow drilling on Earth: lower temperatures and pressures, less power available, low masses (hence less weight-on-bit). Given the cost of transport from Earth, no drilling muds or working fluids are likely to be available to carry away cuttings. And impact-gardened regolith and dust vary mechanically and texturally from most terrestrial soils. The Regolith and Ice Drill for Exploration of New Terrains (TRIDENT) is a rotary-percussive 1m-class drill from Honeybee Robotics. It is low-power (rotary and percussive actuators are 200 W each) and lightweight (<20 kg) with the maximum weight on bit limited to 200 N. TRIDENT has been manifested for the Volatiles Investigating Polar Exploration Rover (VIPER) and PRIME-1 lunar south pole missions in 2024, has previously been field tested at a hot, dry analog site in the Atacama Desert, and in lunar conditions in thermal vacuum chamber tests. TRIDENT was also part of the 2019 Icebreaker Mars Discovery proposal, as well as in the Mars Life Explorer concept. During ARADS tests, drill control and fault recovery automation software enabled hands-off operations of a rover-mounted TRIDENT drill. TRIDENT Drill Analog Site Validation: Past TRIDENT tests in thermal vacuum (TVAC) chambers targeted containers of manufactured lunar simulants with added volatiles. 2022 TRIDENT ambient testing at NASA Ames drilled into cemented lunar simulant materials. Low cuttings-permeability led to cuttings buildup, and drill choking and binding was observed. The Atacama analog site in ARADS had desiccated unconsolidated sediments that did not challenge the TRIDENT design. However, lunar polar regolith is expected to be diverse and heterogeneous with varying clast sizes, with abundant impactites and perhaps subsurface ice deposits. Neither the simulants nor Atacama testing had completely covered the TRIDENT-targeted field characteristics, motivating further analog tests prior to the planned lunar missions. To gain more insight into the behavior of the TRIDENT hardware in diverse impactites and subsurface ice, and to verify the software automation in that environment, in August 2023 TRIDENT was brought to Haughton Crater, a field analog site in the Canadian Arctic. In September 2023 the same drill was brought to the Bishop Tuff in southern California to verify whether drilling binding behaviors previously seen in lunar simulant testing would be observed in naturally occurring fine-grained massive layers. The ~22 Ma Haughton Crater impact structure is located at 75 ̊22’ N, 89 ̊41’ W, on northwestern Devon Island, Nunavut, Canada. Numerous deposits of pale-grey crater-fill polymictic impact-melt breccia are found within the crater with a typical thickness reaching ~125 m or greater and covering ~60 km -2 . An approximately 600m-thick permafrost layer is also present with ice typically found within 0.5-0.6m of the surface. The volcanic tableland north of Bishop, CA exposes densely welded tuff laid down during the eruption that created the Long Valley Caldera at approximately 0.76 Ma. Extensional faults and the Owens River gorge expose cross-sections across the plateau. The area is viewed as an analog site for Mars features believed to be of pyroclastic origin. Results: Haughton Crater.Drilling tests were conducted 8-13 August 2023 at a previously undisturbed area separated 5-10 m from past years’ Drill Hill test sites (75.4208, -089.7613). In six days, TRIDENT drilled 8 holes to nearly 1 m depth each, totaling 7.80 m. The active layer/ice boundary was at ~67 cm depth, with a total of approximately 2.4 m drilled into ice or ice-cemented impact breccia. During drilling, five drill fault states were observed and successfully recovered. Holes 23-1, 4 and 7 were drilled under manual control, using Honeybee’s Thorax user interface. Holes 23-5, 6, and 8 were drilled with the Ames IBexec automated drilling control software. TRIDENT was observed to have little difficulty in the thawed uncemented impact breccia above the active layer boundary, but required percussion to make slower headway in the ice-cemented breccia. In Hole 23-7 (Fig.1), drilling slowed down in a massive unit just above the active-layer boundary (perhaps a large rock extending into the ice-cementation?), with only 7cm progress made in 27 minutes of high auger torque and constant percussion, leading to a choking fault and then a binding fault. A similar pattern had been observed in TRIDENT Rio Tinto test data from 2017 [6] as well as in the 2022laboratory tests.Bishop Tuff.A team from NASA Ames and the US Geological Survey deployed the same TRIDENT drill to Bishop Sites 1B and 1C (37.4203, -118.4289; 37.4265, -118.4215) on 13-16 September 2023, on the Bishop Tuff plateau. A third drill site was used 17-18 September 2023(37.4598, -118.3667) in an abandoned pumice mine. Four holes (totaling 2.5m depth) were drilled into the fine-grained, meters-thick tuff units at Sites 1B and 1C, and a further two boreholes (totaling 1.98m depth) were made at the pumice site. Drill behavior in the tuff below 10 cm depth was similar to that seen at 65-74 cm depth in Haughton Hole 23-7 (Fig. 1) and that seen in the 2022 lab simulant drilling. Drill safety torque limits were exceeded multiple times resulting in drill stops downhole. These freezes then required external added torques (with a pipe wrench) to resume rotation, to unstick the drill for withdrawal. To prevent this choking and binding behavior we found that more-frequent cuttings removal was necessary, e.g., reducing the “drill bite” size from the nominal 10 cm to 2 cm per bite --bringing the auger up to the surface more frequently, as seen in Bishop Site 1C Hole 2 (Fig.2). This permitted slow progress without drill binding and without external interventions. Conversely, TRIDENT drilling in the more porous pumice target material showed no cuttings buildup issue, and single bites as large as 40 cm were demonstrated. Discussion: We observed that TRIDENT easily penetrated unconsolidated heterogeneous soils (both above the active layer boundary at Haughton and previously in the Atacama). Cemented or consolidated targets that were cuttings-permeable (icy impact breccia, pumice) required more energy applied and percussion. However, in non-cuttings-permeable targets (welded microporous tuff, cemented simulants, boulder) TRIDENT was observed to be prone to excessive cuttings accumulation leading to choking/binding faults and stalling. The wedge cutting bit, used by TRIDENT in field tests and in its flight versions, pulverizes the target rock and creates fine cuttings that ideally are transported up the auger spirals for removal. In porous, fractured or vesicular target materials (such as at the Bishop pumice site) a significant portion of the cuttings are pushed aside, but for non-fractured, microporous targets the cuttings remain in the borehole and accumulate. Rock powder is relatively incompressible as a working fluid at only 100-200N downward force (TRIDENT limits) and hence eventual drilling progress slows or stops. Our recommended strategy for improving TRIDENT cuttings removal in massive target units with low cuttings-permeability is to reduce TRIDENT bite sizes when encountering these units, from 10cm to as little as 1-2cm, to effectively bail the accumulating cuttings. This approach was demonstrated to reduce choking and allowed slow progress to continue in cuttings-impermeable microporous target units (viz. the Bishop tuff in our September 2023 tests or cemented simulants in 2022 ambient tests).

robotic drilling↗
DOE OSTI2023

Distribution of rare earth and other critical elements in lignites from the Eocene Jackson Group, Texas

Coal is increasingly evaluated as a source of rare earth elements (REEs) in the United States to address the overreliance on imported REEs. The objective of this study was to assess the distribution of REEs in lignites from selected mining areas in the Texas Gulf Coastal Plain region. Thirty-one archived lignite and rock samples previously collected by the U.S. Geological Survey were analyzed for their rare earth element and critical mineral content. These include samples from one core (5400 and 5500 lignite horizons) and two opencast lignite mines (Gibbons Creek 3500 and 4500 horizons, and San Miguel horizons A to D) in the Eocene Jackson Group of the Texas Gulf of Mexico Coastal Plain. Some lithologies in the Gibbons Creek 3500 and 4500 lignite-bearing sections have high total rare earth, yttrium (Y), and scandium (Sc) (REYSc) values, up to 7800 ppm (ash basis) REYSc. The lignite lithologies show an enrichment in rare earths, [samarium (Sm) through gadolinium (Gd)]. The basal Gibbons Creek 3500 lignite bench shows a heavy rare earth element enrichment pattern resembling that often seen in peats through high volatile A bituminous coals. The 5500 lignite sequence, overlying the latter lignite sections, shows a light rare earth enrichment. The San Miguel lignite benches have heavy rare earth enrichments with a negative europium (Eu) anomaly.

58 GEOSCIENCES↗
DOE OSTI2023

When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates. Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the western United States using data from the U.S. Geological Survey's 2008 geothermal resource assessment. Two favorability maps are created using the expert decision-dependent methods from the 2008 assessment (i.e., weight-of-evidence and logistic regression). With the same data, we then create six different favorability maps using logistic regression (without underlying expert decisions), XGBoost, and support-vector machines paired with two training strategies. The training strategies are customized to address the inherent challenges of applying machine learning to the geothermal training data, which have no negative examples and severe class imbalance. We also create another favorability map using an artificial neural network. We demonstrate that modern machine learning approaches can improve upon systems built with expert decisions. We also find that XGBoost, a non-linear algorithm, produces greater agreement with the 2008 results than linear logistic regression without expert decisions, because the expert decisions in the 2008 assessment rendered the otherwise linear approaches non-linear despite the fact that the 2008 assessment used only linear methods. The F1 scores for all approaches appear low (F1 score < 0.10), do not improve with increasing model complexity, and, therefore, indicate the fundamental limitations of the input features (i.e., training data). Until improved feature data are incorporated into the assessment process, simple non-linear algorithms (e.g., XGBoost) perform equally well or better than more complex methods (e.g., artificial neural networks) and remain easier to interpret.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

RAPID UNSEPARATED RARE EARTH ELEMENT ANALYSES BY ISOTOPE DILUTION MULTICOLLECTOR INDUCTIVELY COUPLED MASS SPECTROMETRY (ID-MC-ICP-MS)

We present a method for analyzing rare earth elements (REEs) by isotope dilution without separation of individual elements. Utilizing a Nu Plasma 2 multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS) equipped with an Aridus II desolvation nebulizer, sample introduction tuning parameters (torch position, gas flows) were investigated and used to minimize oxide formation (e.g., NdO/Nd <0.05%) and remove the need to analyze the REEs as separated “cuts.” Ratios for spike/sample isotopes in mixed synthetic standards containing varying amounts of Ce, Nd, Sm, Eu, Gd, Dy, Er, and Yb were measured accurately within 1% of IUPAC values. La and Lu in the standards were more than 2% off from expected values due to more demanding interference corrections. A USGS BCR-2 rock standard was also processed with flux fusion, iron coprecipitation and a single column pass bulk separation followed by analysis. The concentrations for Ce, Nd, Sm, Eu, Dy, Er, and Yb fell within 2% of consensus values. A United States Geological Survey (USGS) BIR-1A rock standard was also processed in triplicate by hydrofluoric and nitric acid digestion, yielding rare earth concentrations within 3% of consensus values with 0.3% relative standard deviation (n=3). This demonstrates the ability to produce high quality REE patterns of comparable quality to traditional methods involving labor and time intensive REE separation, with sample preparation and analytical times that are comparable to analyses against isotope dilution by single-collector ICP-MS.

Shen, Steve D.↗
DOE OSTI2022

3D Simulations of gas injection on callovo-oxfordian claystone assuming spatial heterogeneity and anisotropy

A series of gas injection tests on Callovo-Oxfordian (COx) claystone from the Bure underground research laboratory (URL) in France were carried out at the British Geological Survey (BGS). The tests were performed using a triaxial apparatus specifically designed to capture small volumetric strains induced by the injected gas flow and consequent material dilatancy. The long-duration experiments were monitored throughout. Measurements also included pressure, stresses (axial and radial stresses prescribed for each test stage), rate of gas inflow, gas outflow volume as well as pore-pressures observed at various points of the sample. A coupled hydro-gas-mechanical 3D numerical model has been developed to simulate the tests. Initial permeability is assumed heterogeneous throughout the specimen and embedded fractures are incorporated in the formulation. Gas pressure-induced deformations during the test lead to variations of permeability due to changes in matrix porosity and, especially, fracture aperture as well as fracture orientation due to material anisotropy. A programme of sensitivity analyses involving the variation of different aspects and parameters of the model contributes to a better understanding of the phenomena and highlights its complexity. The model is able to reproduce the observed behaviour of the tests.

58 GEOSCIENCES↗
DOE OSTI2025

Enhancing 2D hydrodynamic flood models through machine learning and urban drainage integration

Two-dimensional hydrodynamic flood models are commonly employed for simulating flood extent and inundation depth. However, the influence of urban drainage network (UDN) is frequently overlooked in these models, potentially compromising their accuracy. Furthermore, the expensive computational costs and longer processing times make them challenging for large-scale hydrodynamic simulation. To address these challenges, this paper develops a machine learning (ML)-driven emulator for an open-source flood model, the Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON). A TRITON-ML Emulator (TR-Emulator) that utilizes Convolutional Long Short-Term Memory is developed to capture the spatiotemporal features of flood events based on the outputs from TRITON. We further enhance the emulator by integrating UDN parameters (TR-UDN), such as the flow capacity of drainage pipes, pipe size, and pipe length, via an ML stacking technique to improve the water surface elevation (WSE) simulation. Hurricane Harvey 2017 in Houston, TX is used as the case study. We compare WSE results from TRITON, TR-Emulator, TR-UDN, and the United States Geological Survey (USGS) observations to evaluate the performance of these models. The results indicate that the TR-Emulator effectively replicates the WSE simulated by TRITON. Additionally, TR-UDN performs well in capturing WSE patterns and peak flows, aligning more closely with USGS observations, except in areas with milder slopes where conveyance discrepancies are observed. We further test the generalizability of our ML-based models using another smaller event. This paper shows that the TR-Emulator is effective for users and engineers to emulate a 2D hydrodynamic model, and the enhanced version of the TR-Emulator, TR-UDN, can be an efficient tool for predicting WSEs during urban flooding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

An ICP-OES method for the precise and accurate quantification of rare earth elements in natural water: A comparative study from mine waste sites in New Mexico, USA

Inductively coupled plasma techniques such as ICP-OES and ICP-MS are routinely used to determine the concentrations of rare earth elements (REE) in water samples. However, their performance for the determination of REE concentration in mine drainage waters from epithermal vein and porphyry copper mining districts has not been evaluated extensively. In this work, we develop an REE analysis method on an Agilent 5900 ICP-OES instrument and assess the accuracy and precision for the quantification of REE in the natural waters collected from mine adits and an acid seep of mine sites in the Steeple Rock and Hillsboro mining districts, New Mexico, USA. The total REE concentrations in the water samples were measured using the methods we developed for both ICP-OES and ICP-MS. The power of the new ICP-OES method lies in routine analysis of μg/L level concentrations normally analyzed using ICP-MS, including a U.S. Geological Survey standard reference sample, laboratory blank samples spiked with a National Institute of Standards and Technology traceable standard, and surface water samples from mine waste sites. This ICP-OES method achieves low quantification limits ranging from 0.2 to 5 μg/L and excellent analytical accuracy and precision for REE analysis. The precision of light (La-Gd) and heavy (Tb-Lu) REE analysis using this method are better than 5% at average concentrations above 5 ± 4 μg/L and 3 ± 2 μg/L, respectively, and 3% at average concentrations above 10 ± 9 μg/L and 5 ± 4 μg/L, respectively. This method also shows excellent sensitivity and reproducibility for our laboratory and field samples.

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

Critical mineral source potential from oil & gas produced waters in the United States

The volume of produced water, a by-product of oil & gas operations and other energy processes, has been growing across the United States (U.S.) along with the need to manage or recycle this wastewater. Produced water contains many naturally occurring elements of varying concentrations, including critical minerals which are essential to the clean energy transition. However, the current understanding of critical mineral concentrations in produced water and the associated volumes across the U.S. is limited. This study has assessed available databases and literature to gain insight into the presence and concentration of five high priority critical minerals, namely cobalt, lithium, magnesium, manganese, and nickel. The U.S. Geological Survey's National Produced Waters Geochemical Database was the main data source used for determining average critical mineral concentrations in produced water from the major oil and gas reservoirs in the U.S. The volumes of produced water for these major reservoirs were coupled with these concentrations to provide insights into where critical minerals are likely to have high abundance and therefore more recovery options. The analysis indicated the highest recovery potential for lithium and magnesium from produced water in the Permian basin and the Marcellus shale region. However, these assessments should be considered conservative due to the limited availability of reliable concentration data. Finally, it is expected more critical mineral recovery options could emerge with comprehensive characterization data from more recent and representative sources of produced water.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Locating Undocumented Wells Using Historical Oil and Gas Exploration Maps: A Case Study in Osage County, Oklahoma

Undocumented oil and gas wells lack reliable information about their locations and characteristics, making them difficult to identify. These wells can result in unanticipated delays and costs in the development of nearby surface and subsurface resources, and, if improperly plugged, can cause contamination. This study leverages historical petroleum exploration maps to locate such wells, focusing on Osage County, Oklahoma. Two sets of early 20th century oil and gas exploration maps by the United States Geological Survey were georeferenced and analyzed using a computer vision model to detect well symbols. The locations of detected wells were compared to the location of known wells in the database from the Bureau of Indian Affairs Osage Agency to identify potential undocumented wells. The analysis yielded over 500 potential undocumented wells, with dry holes constituting the largest fraction. Field verification confirmed the presence of some undocumented wells. Comparison with prior work revealed limited overlap, underscoring the complementary value of historical oil and gas maps for locating undocumented wells. This approach demonstrates the utility of integrating historical cartographic resources with modern geospatial and machine learning techniques to improve the identification and management of undocumented wells.

Energy - Petroleum↗
DOE OSTI2021

Reanalysis of Water Withdrawal for Irrigation, Electric Power, and Public Supply Sectors in the Conterminous United States, 1950–2016

Accurately measuring water use by the economy is essential for developing reliable models of water resource availability. Indeed, these models rely on retrospective analyses that provide insights into shifting human population demands and adaptions to water shortages. However, accurate, methodologically consistent, empirically authentic, and spatiotemporally comprehensive historical datasets for water withdrawals are scarce. Herein, we present a reanalysis of annual resolution (1950–2016) historical data set on irrigation, electric power, and public supply water withdrawal within the conterminous United States (US) at the county-level, and, for power plants, at the site-level. To estimate electric power water use, we synthesized a historically comprehensive list of generators and historic patterns in generation across fuels, prime movers, and cooling technologies. Irrigation water use estimation required building a crop-demand model that utilized historical information on irrigated acreage for crops and golf courses, stage-specific crop water demand, and climate information. To estimate public water supply use, we developed a random forest model constructed from information on population, infrastructure, climate, and land cover. These estimates generally agree with total county and state water use information provided by the US Geological Survey (USGS) water use circular and estimates generated from independent studies for specific years. However, we also observed discrepancies between our estimates and USGS data that appear to be caused by inconsistencies in the methods used by the USGS's primary data sources at the state level over decades of data collection, highlighting the importance of reanalysis to yield spatiotemporally consistent and intercomparable estimates of water use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Magnetotelluric Investigations of the Kilauea Volcano, Hawaii

In 2002 and 2003 a collaborative effort was undertaken between Lawrence Berkeley National Laboratory, Sandia National Laboratories, the U.S. Geological Survey (USGS) Menlo Park, the USGS Hawaiian Volcano Observatory, and Electromagnetic Instruments Inc. to study the Kilauea volcano in Hawaii using the magnetotelluric (MT) technique. The work was motivated by a desire to improve understanding of the magma reservoirs and conduits within Kilauea and the East and Southwest Rift zones, which has implications for understanding Kilauea's plumbing system. An improved understanding of the rift zones has implications in understanding large-scale landslides that are generated in the Hilina Slump, which produce significant impacts on coastal communities. Up to eight stations operated simultaneously, with multiple remote reference sites, and data were processed using multi-station robust processing techniques. Data was acquired at 70 sites over the Southwest and East rift zones. Good to excellent quality data were obtained even in the harshest conditions, such as those encountered on the fresh lava flows of the East Rift Zone, where electrical contact resistances are on the order of 100 kΩ. A three-dimensional (3D) MT model study was done to guide interpretation of the observed MT measurements. Synthetic modeling demonstrates that conductive bodies in the upper 3 km can be spatially resolved where MT station sampling is good. Resistivity anomalies in the 3D inversions have a high degree of spatial correlation with previously published seismic velocity anomalies beneath Kilauea. Melt fractions between 0.096 and 0.117 are calculated for the Kilauea and Pu'u'ō'ō low resistivity anomalies, respectively.

58 GEOSCIENCES↗
DOE OSTI2023

National‐Scale Assessment of Total Gaseous Mercury Isotopes Across the United States

Abstract With the 2011 promulgation of the Mercury and Air Toxics Standards by the U.S. Environmental Protection Agency, and the successful negotiation by the United Nations Environment Program of the Minamata Convention, emissions of mercury (Hg) have declined in the United States. While the declines in atmospheric Hg concentrations in North America are encouraging, linking the declines to changing domestic and global source portfolios remains challenging. To address these research gaps, the U.S. Geological Survey initiated the first national‐scale effort to establish a baseline of total gaseous mercury stable isotope values at 31 sites distributed across the United States. Results indicated that unique Hg sources, such as Hg evasion from an elemental Hg contaminated site or free tropospheric intrusions in high altitude sites, were distinguishable from background atmospheric values. Minor gradients were observed across the nation, with regions of heavy industrial activity demonstrating lower δ 202 Hg, but no consistent changes in other isotopes such as Δ 199 Hg and Δ 200 Hg were observed. Furthermore, δ 202 Hg was impacted by foliar uptake and senescence but trends varied between forested regions in the northeastern and midwestern United States. These data demonstrate regional emission sources and other environmental variables can impact total gaseous Hg (TGM) isotope values, highlighting the need to characterize atmospheric Hg isotopes over larger geographical areas to evaluate changes related to national and international Hg regulations.

Tate, Michael T.↗
DOE OSTI2023

Insights From Dayflow: A Historical Streamflow Reanalysis Dataset for the Conterminous United States

Abstract Reconstructed historical streamflow time series can supplement limited streamflow gauge observations. However, there are common challenges of typical modeling approaches: process‐based hydrologic models can be data/computation‐intensive, and statistics‐based models can be region/stream‐specific. Here we present a nationally scalable modeling framework integrating the simulated runoff from the Variable Infiltration Capacity (VIC) model with the Routing Application for Parallel computatIon of Discharge (RAPID) routing model leveraging high‐performance computing. We demonstrate an efficient method of assimilating streamflow at US Geological Survey (USGS) streamflow monitoring sites using a simple hierarchical approach in the VIC‐RAPID framework. The result is a reconstructed 36‐year (1980–2015) daily and monthly streamflow dataset (Dayflow) at ∼2.7 million NHDPlusV2 stream reaches in the conterminous US (CONUS). We perform a comprehensive evaluation at 7,526 USGS sites and characterize their error statistics. The results demonstrate that 49% of the USGS sites demonstrate Kling–Gupta Efficiency (KGE) > 0.5 and 58% of the sites show percentage bias within ±20% for the daily naturalized streamflow. Streamflow data assimilation across CONUS shows an overall improvement over naturalized streamflow, notably in the western semiarid‐to‐arid regions. Comparison to other national and global streamflow reanalysis datasets such as the National Water Model and Global Reach‐scale A priori Discharge Estimates for SWOT demonstrates improved KGE, reduced bias, and directions for Dayflow improvements. Investigations of error statistics with key hydrologic, hydroclimatic, and geomorphologic basin characteristics reveal region‐specific patterns which may help improve future framework applications. Overall, Dayflow may enable a better understanding of hydrologic conditions in a changing environment, especially in locations currently not represented by streamflow monitoring networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Aerial imagery dataset of lost oil wells

Orphaned wells are wells for which the operator is unknown or insolvent. The location of hundreds of thousands of these wells remain unknown in the United States alone. Cost-effective techniques are essential to locate orphaned wells to address environmental problems. In this paper, we present a dataset consisting of 120,948 aerial images of recently documented orphan wells. Each of these 512 × 512 images is paired with segmentation masks that indicate the presence or absence of such well. These images, sourced from the National Agriculture Imagery Program, cover the continental United States with spatial resolutions ranging from 30 centimeters to 1 meter. Additionally, we included negative examples by selecting locations uniformly across the United States. Accompanying metadata includes the IDs and spatial resolution of the original images, which are available for free through the United States Geological Survey, and the pixel coordinates of documented orphaned wells identified in these images. This dataset is intended to support the development of deep-learning models that can help locating undocumented orphan wells from such imagery, thereby blunting the environmental damage they do.

Climate-change mitigation↗
DOE OSTI2025

River Dissolved Oxygen Prediction Using Machine Learning Models and Wireless Sensor Measurements

Simultaneous flooding&heat and droughts&heat events can potentially destabilize hydro-meteorological conditions to deteriorate the water quality of Neches River. Machine learning (ML) models utilizing wireless sensor measurements have been applied to predict water quality and optimize various water management strategies. This study aims to develop ML models to predict dissolved oxygen (DO) prediction under various hydro-meteorological conditions and enhance water management decision-making. Wireless sensor measurements of DO, water temperature, sample depth, conductivity, turbidity, and pH, along with discharge from the United States Geological Survey stations, are collected for model inputs at the Pine Island Bayou C749 station (PIB-C749) and Neches River Saltwater Barrier (SWB). Multilayer perceptron neural networks, recurrent neural networks, long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) with and without attention mechanism (AT) are tested to determine the best model, which is applied the rolling forecast method to predict 14-day DO. Traditional and recurrent transfer learning (TL and RTL) methods are adopted to overcome insufficient data at the SWB. The input feature importance analysis using the integrated gradients (IG) algorithm is applied to determine dominant inputs. The results show LSTM-based models are capable handling long sequential data. AT-BiLSTM and RTL-LSTM demonstrate the best performance at the PIB-C749 (RMSE=0.054) and the SWB (RMSE=0.028), respectively. TL and RTL methods significantly improve model performance at the SWB. DO, temperature, and pH show higher importance, consistent with hydrodynamics and water chemistry. Both best models are applied to predict 14-day DO and demonstrate reasonable performance for decision-making. Hydro-meteorological conditions of 2017 flood and 2012 drought events are simulated and reveal that possible hypoxia occurs after flooding due to increasing temperature and turbidity, and DO concentration decreases significantly under heat and drought conditions. In conclusion, LSTM-based models utilizing wireless sensor data can be a timely and effective approach to make appropriate decisions on water resource management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Forecast of Wildfire Potential Across California USA Using a Transformer

Wildfires are a major issue facing the United States, a matter further exacerbated by an ever-changing climate. In California alone, wildfires are responsible for billions of dollars in damages and take lives each year. Accurately predicting fire danger conditions allows preparation awareness before wildfires start. Transformers are a class of deep learning models designed to identify patterns in sequential datasets. In recent years, transformers have gained popularity through their impressive performance in natural language processing and other applications of signal recognition. This analysis demonstrates the ability of a transformer with a residual connection to forecast fire danger potential over the state of California. Wildland fire potential index (WFPI) maps collected from the US Geological Survey database from January 1st 2020 to December 31st 2023 were used to tune, train and evaluate the transformer. Meteorological inputs (provided by Daymet daily weather and climatological summaries), the normalized difference vegetation index (NDVI) (calculated from the Moderate Resolution Imaging Spectroradiometer (MODIS)), and outputs from the Scott and Burgman fire behavior fuel models (to characterize maps of fuel types), were used as inputs. Our results show that a transformer can effectively emulate the US Forest Service modeled WFPI maps of California USA for four week long forecasts over the month of July, 2023, with correlations ranging from 0.85 – 0.98.

Limber, Russell [ORNL]↗
DOE OSTI2020

The Water‐Year Water Balance of the Colorado River Basin

Abstract Model‐estimated monthly water balance components (i.e., potential evapotranspiration, actual evapotranspiration, and runoff ( R )) for 146 United States (U.S.) Geological Survey 8‐digit hydrologic units located in the Colorado River Basin (CRB) are used to examine the temporal and spatial variability of the CRB water balance for water years 1901 through 2014 (a water year is the period from October 1 of one year through September 30 of the following year). Results indicate that the CRB can be divided into six subregions with similar temporal variability in monthly R . The water balance analyses indicated that approximately 75% of total water‐year R is generated by just one CRB subregion and that most of the R in the basin is derived from surplus ( S ) water generated during the months of October through April. Furthermore, the analyses show that temporal variability in S is largely controlled by the occurrence of negative atmospheric pressure anomalies over the northwestern conterminous U.S. (CONUS) and positive atmospheric pressure anomalies over the southeastern CONUS. This combination of atmospheric pressure anomalies results in an anomalous flow of moist air from the North Pacific Ocean into the CRB, particularly the Upper CRB. Additionally, the occurrence of extreme dry and wet periods in the CRB appears to be related to variability of the Atlantic Multidecadal Oscillation and the Pacific Decadal Oscillation.

McCabe, Gregory J.↗