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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

X-ray spectral and flux variability of the microquasar GRS 1758-258 on timescales from weeks to years

We present the spectral and timing evolution of the persistent black hole X-ray binary GRS 1758-258 based on almost 12 years of observations using the Rossi X-ray Timing Explorer Proportional Counter Array. While the source was predominantly found in the hard state during this time, it entered the thermally dominated soft state seven times. In the soft state GRS 1758-258 shows a strong decline in flux above 3 keV rather than the pivoting flux around 10 keV more commonly shown by black hole transients. In its 3–20 keV hardness intensity diagram, GRS 1758-258 shows a hysteresis of hard and soft state fluxes typical for transient sources in outburst. The RXTE-PCA and RXTE-ASM long-term light curves do not show any orbital modulations in the range of 2–30 d. However, in the dynamic power spectra significant peaks drift between 18.47 and 18.04 d for the PCA data, while less significant signatures between 19 d and 20 d are seen for the ASM data as well as for the Swift/BAT data. We discuss different models for the hysteresis behavior during state transitions as well as possibilities for the origin of the long term variation in the context of a warped accretion disk.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2020

X-Ray Spectral and Flux Variability of the Microquasar GRS 1758-258 on Timescales from Weeks to Years

We present the spectral and timing evolution of the persistent black hole X-ray binary GRS 1758-258 based on almost 12 years of observations using the Rossi X-ray Timing Explorer Proportional Counter Array. While the source was predominantly found in the hard state during this time, it entered the thermally dominated soft state seven times. In the soft state GRS 1758-258 shows a strong decline in flux above 3 keV rather than the pivoting flux around 10 keV more commonly shown by black hole transients. In its 3-20 keV hardness intensity diagram, GRS 1758-258 shows a hysteresis of hard and soft state fluxes typical for transient sources in outburst. The RXTE-PCA and RXTE-ASM long-term light curves do not show any orbital modulations in the range of 2 to 30 d. However, in the dynamic power spectra significant peaks drift between 18.47d and 18.04d for the PCA data, while less significant signatures between 19d and 20d are seen for the ASM data as well as for the Swift/BAT data. We discuss different models for the hysteresis behavior during state transitions as well as possibilities for the origin of the long term variation in the context of a warped accretion disk.

Maria Hirsch↗
DOE OSTI2019

Clustered BSRs: Evidence for gas hydrate-bearing turbidite complexes in folded regions, example from the Perdido Fold Belt, northern Gulf of Mexico

We detail previously undocumented but extensive gas hydrate accumulations in the mouth of Perdido Canyon in the northern Gulf of Mexico. The accumulations are located within central parts of structural domes (four-way closures) and are characterized by stacked, high-amplitude bottom simulating reflections (BSRs) that we call clustered BSRs. Seismic data from Perdido Canyon show two clustered BSRs associated with turbidite sequences within two dome folds formed from tectonic folding and salt diapir rise. The northwestern (NW) and southeastern (SE) clustered BSRs have aerial extents of ~25 km2 and 50 km2, respectively. Well log data confirm gas hydrate occurs above the NW clustered BSR, within a 225 m-thick consistently high-resistivity interval that we interpret as gas hydrate in near-vertical fractures and turbidite sands. The SE dome is only drilled at the edge of the BSR; nevertheless, the well log data indicate that a 30 m-thick gas hydrate accumulation is present. Gas chromatographic logs in both domes suggest a gradual transition from predominantly microbial gas below the BSR (500–1000 m below seafloor (mbsf)) to thermogenic gas at 1000–2000 mbsf. Based on the well log data and seismic stratigraphic analysis, we find gas hydrate is concentrated in fractures in marine mud, as well as in the pores of submarine fan turbidities, where saturations reach as high as 75%. An estimate of the total gas hydrate-bound gas volume at standard temperature and pressure is between 0.04 and 0.17 trillion cubic meters (TCM) assuming average hydrate saturation of 5-20% in a ~45 m thick turbidite sand unit above the Perdido Canyon BSR area. Measured BSR extent and gas volume estimates indicate that the NW and SE reservoirs are among the largest gas hydrate occurrences known in the Gulf of Mexico.

58 GEOSCIENCES↗
NASA NTRS2012

NASA GSFC Space Weather Center - Innovative Space Weather Dissemination: Web-Interfaces, Mobile Applications, and More

The NASA GSFC Space Weather Center (http://swc.gsfc.nasa.gov) is committed to providing forecasts, alerts, research, and educational support to address NASA's space weather needs - in addition to the needs of the general space weather community. We provide a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, custom space weather alerts and products, weekly summaries and reports, and most recently - video casts. There are many challenges in providing accurate descriptions of past, present, and expected space weather events - and the Space Weather Center at NASA GSFC employs several innovative solutions to provide access to a comprehensive collection of both observational data, as well as space weather model/simulation data. We'll describe the challenges we've faced with managing hundreds of data streams, running models in real-time, data storage, and data dissemination. We'll also highlight several systems and tools that are utilized by the Space Weather Center in our daily operations, all of which are available to the general community as well. These systems and services include a web-based application called the Integrated Space Weather Analysis System (iSWA http://iswa.gsfc.nasa.gov), two mobile space weather applications for both IOS and Android devices, an external API for web-service style access to data, google earth compatible data products, and a downloadable client-based visualization tool.

Maddox, Marlo↗
NASA NTRS2020

Central Valley Water Resources: Improving California Groundwater Assessments using GRACE and InSAR Datasets for Water Resource Management

California’s Central Valley is one of the most productive agricultural areas in the world, producing approximately $20 billion in crops annually. The recent California droughts of 2007-2010 and 2011-2017 resulted in increased groundwater pumping in the Central Valley to adequately irrigate farmland. Overdrafting of the Central Valley aquifer results in groundwater depletion, land subsidence, and permanent loss of groundwater storage. In 2014, depletion of groundwater led the state of California to enact the Sustainable Groundwater Management Act (SGMA), requiring critically overdrafted, high, and medium priority sub-basins to reach sustainable levels of groundwater pumping and recharge by 2042. SGMA allows local Groundwater Sustainability Agencies the authority to create Groundwater Sustainability Plans at the sub-basin level. To assist California’s Department of Water Resources, this project quantified groundwater change and land subsidence in Central Valley sub-basins with sparse or unreliable well and GPS data. This was done using NASA’s Gravity Recovery and Climate Experiment (GRACE), GRACE Follow-On (GRACE-FO), and interferograms derived from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-band Synthetic Aperture Radar 2 (PALSAR-2). Time series of the GRACE and InSAR data were compared with well and GPS data in data-dense sub-basins to determine the feasibility of these datasets for groundwater storage and subsidence monitoring. We found thatGRACE and InSAR data are effective tools for determining groundwater change and land subsidence and can be used on their own to monitor sub-basins in the absence of well and GPS data.

Water Resources↗
DOE OSTI2019

Optimizing wind farm siting to reduce power system impacts of wind variability

We introduce and solve two variants of a biobjective optimization model to reduce the negative impact of wind variability on the power system by strategically locating wind farms. The first model variant considers average changes in wind power over time; the second captures extreme fluctuations in wind power. A complementary set of wind sites is selected with the aim of minimizing both residual demand and the variability in residual demand. Because exact optimization is computationally intensive, we develop two heuristics—forward and backward greedy algorithms—to find approximate solutions. The results are compared with the exact optimization results for a well-selected subset of the data as well as to the results from selecting sites based on average wind alone. The two models are solved using demand data and potential wind sites for the Southwest Power Pool. Though both objectives can be improved by adding more sites, for a fixed number of sites, minimizing residual demand and variability in residual demand are competing objectives. Here, we find an approximate efficient frontier to compare trade-offs between the two objectives. We also vary the parameter in the heuristic that controls how the two objectives are prioritized. For the case study, the backward greedy algorithm is more effective at reducing the wind power variability than the forward greedy algorithm. Furthermore, using the backward algorithm for the full dataset is more effective than solving the exact optimization on a subset of the data when the results are evaluated using the full dataset.

17 WIND ENERGY↗
NASA NTRS2016

The NASA/AFRL Meter Class Autonomous Telescope

For the past decade, the NASA Orbital Debris Program Office (ODPO) has relied on using various ground-based telescopes in Chile to acquire statistical survey data as well as photometric and spectroscopic data of orbital debris in geosynchronous Earth orbit (GEO). The statistical survey data have been used to supply the Orbital Debris Engineering Model (ORDEM) v.3.0 with debris detections in GEO to better model the environment at altitudes where radar detections are limited. The data produced for the statistical survey ranged from 30 to 40 nights per year, which only accounted for ~10% of the possible observing time. Data collection was restricted by ODPO resources and weather conditions. In order to improve the statistical sampling in GEO, as well as observe and sample other orbits, NASA's ODPO with support from the Air Force Research Laboratory (AFRL), has constructed a new observatory dedicated to orbital debris - the Meter Class Autonomous Telescope (MCAT) on Ascension Island. This location provides MCAT with the unique ability to access targets orbiting at an altitude of less than 1,000 km and low inclinations (< 20 deg). This orbital regime currently has little to no coverage by the U.S. Space Surveillance Network. Unlike previous ODPO optical assets, the ability to operate autonomously will allow rapid response observations of break-up events, an observing mode that was only available via radar tasking prior to MCAT's deployment. The primary goal of MCAT is to statistically characterize GEO via daily tasking files uploaded from ODPO. These tasking files define which operating mode to follow, providing the field center, rates, and/or targets to observe over the entire observing period. The system is also capable of tracking fast-moving targets in low Earth orbit (LEO), middle Earth orbit (MEO), as well as highly eccentric orbits like geostationary transfer orbits. On 25 August 2015, MCAT successfully acquired scientific first light, imaging the Bug Nebula and tracked objects in LEO, MEO, and GEO. NASA is working towards characterizing the system and thoroughly testing the integrated hardware and software control to achieve fully autonomous operations by late 2016. This paper will review the history and current status of the MCAT project, the details of the telescope system, and its five currently manifested operating modes.

Cowardin, H.↗
DOE OSTI2024

Utah FORGE: Neubrex Well 16B(78)-32 DAS Data - April, 2024

This dataset comprises Distributed Acoustic Sensing (DAS) data collected from the Utah FORGE monitoring well 16B(78)-32 (the producer well) during hydraulic fracture stimulation operations conducted in April 2024. The data were acquired continuously over the stimulation period at a temporal sampling rate of 10,000 Hz (10 kS/s) and a spatial resolution of approximately 3.35 feet (1.02109 meters). The measurements were captured using a Neubrex NBX-S4100 Time Gated Digital DAS interrogator unit connected to a single-mode fiber optic cable, which was permanently installed within the casing string. All recorded channels correspond to downhole segments of the fiber optic cable, from a measured depth (MD) of 5,369.35 feet to 10,352.11 feet. The DAS data reflect raw acoustic energy generated by physical processes within and surrounding the well during stimulation activities at wells 16A(78)-32 and 16B(78)-32. These data have potential applications in analyzing cross-well strain, far-field strain rates (including microseismic activity), induced seismicity, and seismic imaging. Metadata embedded in the attributes of the HDF5 files include detailed information on the measured depths of the channels, interrogation parameters, and other acquisition details. The dataset also includes a recording of a seminar held on September 19, 2024, where Neubrex's Chief Operating Officer presented insights into the data collection, analysis, and preliminary findings. The raw data files, stored in HDF5 format, are organized chronologically according to the recording intervals from April 9 to April 24, 2024, with each file corresponding to a 12-second recording interval.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Harnessing Machine Learning and Data Fusion for Accurate Undocumented Well Identification in Satellite Images

This study utilizes satellite data to detect undocumented oil and gas wells, which pose significant environmental concerns, including greenhouse gas emissions. Three key findings emerge from the study. Firstly, the problem of imbalanced data is addressed by recommending oversampling techniques like Rotation–GaussianBlur–Solarization data augmentation (RGS), the Synthetic Minority Over-Sampling Technique (SMOTE), or ADASYN (an extension of SMOTE) over undersampling techniques. The performance of borderline SMOTE is less effective than that of the rest of the oversampling techniques, as its performance relies heavily on the quality and distribution of data near the decision boundary. Secondly, incorporating pre-trained models trained on large-scale datasets enhances the models’ generalization ability, with models trained on one county’s dataset demonstrating high overall accuracy, recall, and F1 scores that can be extended to other areas. This transferability of models allows for wider application. Lastly, including persistent homology (PH) as an additional input improves performance for in-distribution testing but may affect the model’s generalization for out-of-distribution testing. A careful consideration of PH’s impact on overall performance and generalizability is recommended. Overall, this study provides a robust approach to identifying undocumented oil and gas wells, contributing to the acceleration of a net-zero economy and supporting environmental sustainability efforts.

SMOTE↗
DOE OSTI2015

Newberry Well 55-29 Stimulation Data 2014

The Newberry Volcano EGS Demonstration in central Oregon, a 5 year project begun in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to run for weeks and deliver large volumes of water at moderate well-head pressure. Second, to stimulate multiple zones, AltaRock developed thermo-degradable zonal isolation materials (TZIMs) to seal off fractures in a geothermal well to stimulate secondary and tertiary fracture zones. The TZIMs degrade within weeks, resulting in an optimized injection/ production profile of the entire well. Third, the project followed a project-specific Induced Seismicity Mitigation Plan (ISMP) to evaluate, monitor for, and mitigate felt induced seismicity. An initial stimulation was conducted in 2012 and continued for 7 weeks, with over 41,000 m3 of water injected. Further analysis indicated a shallow casing leak and an unstable formation in the open hole. The well was repaired with a shallow casing tieback and perforated liner in the open hole and re-stimulated in 2014. The second stimulation started September 23rd, 2014 and continued for 3 weeks with over 9,500 m3 of water injected. The well was treated with several batches of newly tested TZIM diverter materials and a newly designed Diverter Injection Vessel Assembly (DIVA), which was the main modification to the original injection system design used in 2012. A second round of stimulation that included two perforation shots and additional batches of TZIM was conducted on November 11th, 2014 for 9 days with an additional 4,000 m3 of water injected. The stimulations resulted in a 3-4 fold increase in injectivity, and PTS data indicates partial blocking and creation of flow zones near the bottom of the well. This submission includes all of the files and reports associated with the stimulation, pressure testing, and monitoring included in the scope of the project.

15 GEOTHERMAL ENERGY↗
NASA NTRS1991

Effect of a simulated ice accretion on the aerodynamics of a swept wing

The effect of a simulated glaze ice accretion on the aerodynamic performance of a three-dimensional swept wing is studied experimentally. A semispan wing of effective aspect ratio four was mounted from the sidewall of the UIUC subsonic wind tunnel. The model uses a NACA 0012 airfoil section on a rectangular planform with interchangeable tip and root sections to allow for 0- and 30-degree sweep. A sidewall suction system is used to minmize the tunnel boundary-layer interaction with the model. Surface pressure data from five spanwise stations are compared to earlier data from a similar tunnel. A three-component sidewall balance has been designed, built and used to measure lift, drag and pitching moment on the clean and iced model. The data compare well to the integrated pressure data and to theory on the clean model. In addition, helium-bubble flow visualization has been performed on the iced model and reveals extensive spanwise flow in the separation bubble aft of the upper surface horn. This compares well to the computational results of other researchers. Sidewall suction was found to have no effect on the aerodynamics of the swept wing.

Bragg, M. B.↗
NASA NTRS1983

Regional geothermal exploration in Egypt

A study is presented of the evaluation of the potential geothermal resources of Egypt using a thermal gradient/heat flow technique and a groundwater temperature/chemistry technique. Existing oil well bottom-hole temperature data, as well as subsurface temperature measurements in existing boreholes, were employed for the thermal gradient/heat flow investigation before special thermal gradient holes were drilled. The geographic range of the direct subsurface thermal measurements was extended by employing groundwater temperature and chemistry data. Results show the presence of a regional thermal high along the eastern margin of Egypt with a local thermal anomaly in this zone. It is suggested that the sandstones of the Nubian Formation may be a suitable reservoir for geothermal fluids. These findings indicate that temperatures of 150 C or higher may be found in this reservoir in the Gulf of Suez and Red Sea coastal zones where it lies at a depth of 4 km and deeper.

Morgan, P.↗
DOE OSTI2016

Contaminant point source localization error estimates as functions of data quantity and model quality

We develop empirically-grounded error envelopes for localization of a point contamination release event in the saturated zone of a previously uncharacterized heterogeneous aquifer into which a number of plume-intercepting wells have been drilled. We assume that flow direction in the aquifer is known exactly and velocity is known to within a factor of two of our best guess from well observations prior to source identification. Other aquifer and source parameters must be estimated by interpretation of well breakthrough data via the advection-dispersion equation. We employ high performance computing to generate numerous random realizations of aquifer parameters and well locations, simulate well breakthrough data, and then employ unsupervised machine optimization techniques to estimate the most likely spatial (or space-time) location of the source. Tabulating the accuracy of these estimates from the multiple realizations, we relate the size of 90% and 95% confidence envelopes to the data quantity (number of wells) and model quality (fidelity of ADE interpretation model to actual concentrations in a heterogeneous aquifer with channelized flow). We find that for purely spatial localization of the contaminant source, increased data quantities can make up for reduced model quality. For space-time localization, we find similar qualitative behavior, but significantly degraded spatial localization reliability and less improvement from extra data collection. Since the space-time source localization problem is much more challenging, we also tried a multiple-initial-guess optimization strategy. Furthermore, this greatly enhanced performance, but gains from additional data collection remained limited.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Preserving NASA Historic and Current Mission Data and Adding Value to These for Future Researchers

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been actively involved in many aspects of ensuring the long-term preservation of NASA earth science data and knowledge. This involves both the recovery and preservation of early NASA meteorological and other earth observation data, as well as preserving the more recent Earth Observation System (EOS) mission data sets which continue or have reached their end of lifetime. The GES DISC adds value to these preserved data by adding metadata and making the data available online to future researchers. The early NASA meteorological and earth observation data sets from the 1960s and 70s were originally archived on magnetic tapes, and visualizations of these data were preserved on 70-mm film. As these media have aged, their contents have been at risk of permanent loss. NASA has given the task of preserving these early data sets to the GES DISC and making these data sets easily available to the public. The data from these early missions are potentially useful to climate researchers as these are some of the only global measurements made at their time. These old data on magnetic tapes and film strips do not contain easily readable metadata, and so to add value the GES DISC has added digital metadata to them so that the data are searchable and findable. The GES DISC is also involved in preserving the data and knowledge from the EOS era missions. The GES DISC follows the guidelines developed for the preservation of data as specified in the NASA EOS Data and Information System (EOSDIS) Earth Science Data Preservation Content Specification (423-SPEC-001) document. To date, the GES DISC has consulted with the data science teams from the following missions: UARS, Earth Probe TOMS, Aura HIRDLS, and SORCE, in order to properly preserve their data and accompanying documentation. The GES DISC is also currently working with the EOS science teams from TRMM, AIRS, MLS, OMI and additional missions to ensure that the relevant documents and data sets are properly archived for future researchers. A standardized procedure for mission data preservation following 423-SPEC-001 makes preservation among the many NASA EOSDIS data centers uniform, so that these could be transitioned easily to a common EOSDIS preservation repository. This presentation will give an overview of the preservation and recovery of the old NASA historical data sets archived at the GES DISC, as well as the data and documentation preservation efforts of the EOS era missions.

James Johnson↗
NASA NTRS2004

Comparison of TOMS, SBW & SBUV/2 Version 8 Total Column Ozone Data with Data from Groundstations

The Nimbus-7 and Earth Probe Total Ozone Mapping Spectrometer (TOMS) data as well as SBUV and SBUV/2 data have been reprocessed with a new retrieval algorithm (Version 8) and an updated calibration procedure. An overview will be presented systematically comparing ozone values to an ensemble of Brewer and Dobson spectrophotometers. The comparisons were made as a function of latitude, solar zenith angle, reflectivity and total ozone. Results show that the accuracy of the TOMS retrieval has been improved when aerosols are present in the atmosphere, when snow/ice and sea glint are present, and when ozone in the northern hemisphere is extremely low. TOMS overpass data are derived from the single TOMS best match measurement, almost always located within one degree of the ground station and usually made within an hour of local noon. The Version 8 Earth Probe TOMS ozone values have decreased by an average of about 1% due to a much better understanding of the calibration of the instrument. N-7 SBUV as well as the series of NOAA SBUV/2 column ozone values have also been processed with the Version 8 algorithm and have been compared to values from an ensemble of groundstations. Results show that the SBW column ozone values agree well with the groundstations and the datasets are useful for trend studies.

Labow, G. J.↗
DOE OSTI2024

3-D Geological Modeling for Numerical Flow Simulation Studies of Gas Hydrate Reservoirs at the Kuparuk State 7-11-12 Pad in the Prudhoe Bay Unit on the Alaska North Slope

Accurate reservoir evaluation requires reliable three-dimensional (3-D) geological models. Here, this study conducted 3-D geological modeling for numerical flow simulation of the B1 sand gas hydrate reservoir at the Kuparuk State 7-11-12 pad, Prudhoe Bay Unit, Alaska North Slope. The model integrates well logs, core, and seismic data to address spatial heterogeneity in geological structures and reservoir properties. Two modeling types were performed: structural framework modeling and petrophysical property modeling. For structural framework modeling, seismic data and well log markers were used to reproduce subsurface structures characterized by a normal fault system. A volume-based modeling algorithm and stair-stepping grid were applied. The resulting 3-D model comprised 2,640,000 grid cells across 264 layers, including seven fault grids. For petrophysical property modeling, total porosity was initially modeled using sequential Gaussian simulation with collocated cokriging. To reproduce the upward coarsening of the B1 sand, upscaled log-derived total porosity and a three-dimensional (3-D) trend depicting total porosity variation were used as primary and secondary data, respectively. Gas hydrate saturation distribution was modeled similarly, with secondary data from estimated porosity distribution and seismic-derived acoustic impedance map enhancing accuracy. Results indicate higher gas hydrate saturation in the upper part of the B1 sand and areas with higher acoustic impedance. Intrinsic permeability was modeled from the total porosity and clay-bound water volume, and effective permeability was derived from the gas hydrate saturation and intrinsic permeability distributions based on the “Tokyo model”. Effective permeability distributions were influenced by the total porosity, gas hydrate saturation, and intrinsic permeability. Within the same layer, higher gas hydrate saturation leads to decreased effective permeability. In total, 100 sets of multiple scenarios were prepared, providing input data for dynamic flow simulations to evaluate the effects of lateral heterogeneity in reservoir properties and the hydraulic characteristics of faults on production behavior for preassessment before the long-term production test.

58 GEOSCIENCES↗
DOE OSTI2019

Nonnegative tensor decomposition with custom clustering for microphase separation of block copolymers

High–dimensional datasets are becoming ubiquitous in many applications and therefore unsupervised tensor methods to interrogate them are needed. Here, we report a new unsupervised machine learning (ML) approach (NTFk) based on nonnegative tensor factorization integrated with a custom k–means clustering. We demonstrate the ability of NTFk to extracting temporal and spatial features of phase separation of copolymers as they are modeled by self–consistent field theory. Microphase separation of block copolymers has been extensively studied both experimentally and theoretically. However, the interpretation of computer simulations and/or experimental data, representing temporal and spatial changes of molecular species concentration is still a challenging task. Thus, extracting the phase diagram from simulations or experimental data as well as the interpretation of data requires discernment of the model/experimental parameters (such as, temperature, concentrations, the number of molecular species and the interaction between species) impact on the microphase separation process. An attractive and unique aspect of the introduced ML method is that it ensures the nonnegativity of the extracted latent features. Nonnegativity is an essential constraint needed to obtain interpretable and sparse latent features that are parts–based representation of the data. The custom clustering in NTFk serves to estimate the number of latent features in the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture

Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process–guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.

54 ENVIRONMENTAL SCIENCES↗