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NASA NTRS1977

Basalts from Mare Crisium

The stratified core sample returned from Mare Crisium by the Luna 24 unmanned space probe is composed primarily of a variety of subophitic to ophitic basalt with very low contents of TiO2 and MgO. This consists of clinopyroxene, calcic plagioclase, olivine, and minor amounts of silica, chromite, ulvoespinel, ilmenite, troilite, apatite, and Fe-metal. Granular metabasalts have the same bulk composition, but mineral phases exhibit less compositional variation. Fine-grained impact melts have similar compositions and are apparently derived from these basalts. It is concluded that the basalts, which are chemically distinct from the very-low-titanium basalts found elsewhere on the moon, represent the local surface flows of Mare Crisium. Sparse fragments of an olivine vitrophyre that is low in TiO2 but high in MgO and approaches the composition of the Apollo 15 green glasses may be derived from patches of dark mantling materials 20 km from the landing site.

Ryder, G.↗

DOE OSTI2020

UQ Toolkit v 2.0

The Uncertainty Quantification (UQ) Toolkit is a software library for the characterizaton and propagation of uncertainties in computational models. For the characterization of uncertainties, Bayesian inference tools are provided to infer uncertain model parameters, as well as Bayesian compressive sensing methods for discovering sparse representations of high-dimensional input-output response surfaces, and also Karhunen-Loève expansions for representing stochastic processes. Uncertain parameters are treated as random variables and represented with Polynomial Chaos expansions (PCEs). The library implements several spectral basis function types (e.g. Hermite basis functions in terms of Gaussian random variables or Legendre basis functions in terms of uniform random variables) that can be used to represent random variables with PCEs. For propagation of uncertainty, tools are provided to propagate PCEs that describe the input uncertainty through the computational model using either intrusive methods (Galerkin projection of equations onto basis functions) or non-intrusive methods (perform deterministic operation at sampled values of the random values and project the obtained results onto basis functions).

Safta, Cosmin↗

DOE OSTI2013

UQ Toolkit v 2.0

Source record↗

DOE OSTI2012

Distribution function approach to redshift space distortions. Part III: halos and galaxies

It was recently shown that the power spectrum in redshift space can be written as a sum of cross-power spectra between number weighted velocity moments, of which the lowest are density and momentum density. We investigate numerically the properties of these power spectra for simulated galaxies and dark matter halos and compare them to the dark matter power spectra, generalizing the concept of the bias in density-density power spectra. Because all of the quantities are number weighted this approach is well defined even for sparse systems such as massive halos. This contrasts to the previous approaches to RSD where velocity correlations have been explored, but velocity field is a poorly defined concept for sparse systems. We find that the number density weighting leads to a strong scale dependence of the bias terms for momentum density auto-correlation and cross-correlation with density. This trend becomes more significant for the more biased halos and leads to an enhancement of RSD power relative to the linear theory. Fingers-of-god effects, which in this formalism come from the correlations of the higher order moments beyond the momentum density, lead to smoothing of the power spectrum and can reduce this enhancement of power from the scale dependent bias, but are relatively small for halos with no small scale velocity dispersion. In comparison, for a more realistic galaxy sample with satellites the small scale velocity dispersion generated by satellite motions inside the halos leads to a larger power suppression on small scales, but this depends on the satellite fraction and on the details of how the satellites are distributed inside the halo. We investigate several statistics such as the two-dimensional power spectrum P(k,μ), where μ is the angle between the Fourier mode and line of sight, its multipole moments, its powers of μ{sup 2}, and configuration space statistics. Overall we find that the nonlinear effects in realistic galaxy samples such as luminous red galaxies affect the redshift space clustering on very large scales: for example, the quadrupole moment is affected by 10% for k < 0.1hMpc{sup −1}, which means that these effects need to be understood if we want to extract cosmological information from the redshift space distortions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Acoustic Event Location and Background Noise Characterization on a Free Flying Infrasound Sensor Network in the Stratosphere

We present that a variety of Earth surface and atmospheric sources generate low frequency sound waves that can travel great distances. Despite a rich history of ground-based sensor studies, very few experiments have investigated the prospects of free floating microphone arrays at high altitudes. However, recent initiatives have shown that such networks have very low background noise and may sample an acoustic wave field that is fundamentally different than that at Earth’s surface. The experiments have been limited to at most two stations at altitude, making acoustic event detection and localization difficult. We describe the deployment of four drifting microphone stations at altitudes between 21 and 24 km above sea level. The stations detected one of two regional ground-based chemical explosions as well as the ocean microbarom while traveling almost 500 km across the American Southwest. The explosion signal consisted of multiple arrivals; signal amplitudes did not correlate with sensor elevation or source range. The waveforms and propagation patterns suggest interactions with gravity waves in the 35-45 km altitude. A sparse network method that employed curved wave front corrections was able to determine the backazimuth from the free flying network to the acoustic source. Episodic signals similar to those seen on previous flights in the same region were noted, but their source remains unclear. Lastly, background noise levels were commensurate with those on infrasound stations in the International Monitoring System below 2 seconds.

58 GEOSCIENCES↗

NASA NTRS2009

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.

Molthan, Andrew↗

DOE OSTI2026

Bayesian Physics Informed Spatio-Temporal Network for Streamflow Data Imputation

Reliable reconstruction of incomplete streamflow records is critical for improving hydrological forecasting, flood preparedness, and water resource management. However, large observational gaps and uncertainties in governing physical parameters limit the accuracy of traditional statistical and machinelearning imputation frameworks. To address these challenges, we develop a Bayesian Physics-Informed Spatio-Temporal Network (BPI-STNet) that jointly captures spatial and temporal dependencies while enforcing hydrologic consistency through embedded physical constraints. The framework integrates a GraphSAGE-LSTM architecture to model spatial connectivity across gauges and temporal flow dynamics, coupled with a Bayesian update mechanism to estimate uncertain parameters in a simplified water-balance framework. Unlike conventional physics-informed networks that rely on sampling-based posterior estimation, BPI-STNet derives an analytic solution to the inverse problem, allowing closed-form Bayesian updates of uncertain parameters Λ={α,β,k} using Gaussian priors and likelihoods. Applied to daily observations from the Susquehanna River Basin (1980-2022), BPI-STNet achieves substantial improvements over a purely data-driven RGNN baseline, which reduced RMSE by 23 % and MAE by 9 %, and achieving an average NSE values up to 0.96. The results demonstrate that coupling Bayesian inference with physics-informed learning yields physically consistent, uncertainty-aware reconstructions that preserve the temporal persistence and statistical distribution of observed flows. The proposed framework establishes a generalizable paradigm for data-sparse hydrologic systems where both data fidelity and physical interpretability are essential.

Krishnan Kutty Ambika, Anukesh [ORNL] (ORCID:00000↗

NASA NTRS2020

Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels

We introduce a multiscale superpixel approach that leverages repeat-pass interferometric coherence and sparse AGB estimates from a simulated spaceborne lidar in order to extend the NISAR mission’s applicable range of aboveground biomass (AGB) in tropical forests. Airborne and spaceborne L-band radar and full-waveform airborne lidar data are used to simulate the NISAR and GEDI mission, respectively. In addition to UAVSAR data, we use spaceborneALOS-2/PALSAR-2 imagery with 14-day temporal baseline, which is comparable to NISAR’s 12-daybaseline. Our reference AGB maps are derived from the airborne LVIS data during the AfriSAR campaign for three sites (Mondah, Ogooue, and Lope). Each tropical site has mean AGB of at least 125 Mg/ha in addition to areas with AGB exceeding 700 Mg/ha. Spatially sampling from these LVIS-derived AGB reference maps, we approximate GEDI AGB estimates. To evaluate our methodology, we perform several different analyses. First, we partition each study site into low(≤100 Mg/ha) and high (>100 Mg/ha) AGB areas, in conformity with the NISAR mission requirement to provide AGB estimates for forests between 0 and 100 Mg/ha with a RMSE below 20 Mg/ha. In the low AGB areas, this RMSE requirement is satisfied in Lope and Mondah and it fell short of the requirement in Ogooue by less 3 Mg/ha with UAVSAR and 6 Mg/ha with PALSAR-2. We note that our maps have finer spatial resolution (50 m) than NISAR requires (1 hectare). In the high AGB areas, the normalized RMSE increases to 51% (i.e.,<90 Mg/ha), but with negligible bias for all three sites. Second, we train a single model to estimate AGB across both high and low AGB regimes simultaneously and obtain a normalized RMSE that is<60% (or<100 Mg/ha). Lastly, we show the use of both (a) multiscale superpixels and (b) interferometric coherence significantly improves the accuracy of the AGB estimates. The InSAR coherence improved the RMSE by approximately 8% at Mondah with both sensors, lowering the RMSE from 59 Mg/ha to 47.4 Mg/h with UAVSAR and from 57.1 Mg/ha to 46 Mg/ha. This work illustrates one of the numerous synergistic relationships between the spaceborne lidars, such as GEDI, with L-band SAR, such as PALSAR-2 and NISAR, in order to produce robust regional AGB in high biomass tropical regions.

NISAR↗

NASA NTRS2022

Herbarium records provide reliable phenology estimates in the understudied tropics

1. Plant phenology has been shifting dramatically in response to climate change, a shift that may have significant and widespread ecological consequences. Of particular concern are tropical biomes, which represent the most biodiverse and imperilled regions of the world. However, compared to temperate floras, we know little about phenological responses of tropical plants because long-term observational datasets from the tropics are sparse. 2. Herbarium specimens have greatly increased our phenological knowledge in temperate regions, but similar data have been underutilized in the tropics and their suitability for this purpose has not been broadly validated. Here, we compare phenological estimates derived from field observational data (i.e. plot surveys) and herbarium specimens at various spatial and taxonomic scales to determine whether specimens can provide accurate estimations of reproductive timing and its spatial variation. 3. Here, we demonstrate that phenological estimates from field observations and herbarium specimens coincide well. Fewer than 5% of the species exhibited significant differences between flowering periods inferred from field observations versus specimens regardless of spatial aggregation. In contrast to studies based on field records, herbarium specimens sampled much larger geographic and climatic ranges, as has been documented previously for temperate plants, and effectively captured phenological responses across varied environments. 4. Synthesis. Herbarium specimens are verified to be a vital resource for closing the gap in our phenological knowledge of tropical systems. Tropical plant reproductive phenology inferred from herbarium records is widely congruent with field observations, suggesting that they can and should be used to investigate phenological variation and their associated environmental cues more broadly across tropical biomes.

Brazil↗

DOE OSTI2014

Photometric and structural properties of NGC 6544: A combined VVV-Hubble space telescope study

We combine archival Hubble Space Telescope imaging with wide-field near-infrared photometry to study the neglected metal-poor Galactic globular cluster NGC 6544. A high spatial resolution map of differential reddening over the inner portion of the cluster is constructed, revealing variations of up to half of the total reddening, and the resulting corrected color-magnitude diagrams reveal a sparse blue horizontal branch and centrally concentrated blue straggler population, verified via relative proper motions. Using the corrected photometry to investigate the cluster distance, reddening, and age via direct comparison to well-calibrated photometry of clusters with similar metallicities, we estimate (m – M){sub 0} = 11.96, E(B – V) = 0.79, and an age coeval with M13 to within the relevant uncertainties. Although our data are insufficient to place tight constraints on the reddening law toward NGC 6544, we find no strong evidence that it is non-standard at optical or near-infrared wavelengths. We also provide near-infrared fiducial sequences extending nearly 2 mag below the cluster main sequence turnoff, generated from a statistically decontaminated sample of cluster stars. Lastly, we redetermine the cluster center and construct a radial number density profile which is well fit by an atypically flat power law with a slope of about 1.7. We discuss this result, together with a flattened main sequence luminosity function and inverted mass function, in the context of mass segregation and tidal stripping via interactions with Milky Way potential.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Sawtooth lattice multiferroic BeCr 2 O 4 : Noncollinear magnetic structure and multiple magnetic transitions

Noncollinear magnetic structures and multiple magnetic phase transitions in a sawtooth lattice antiferromagnet consisting of Cr 3+ are experimentally identified in this work, thereby proposing the scenario of magnetism-driven ferroelectricity in a sawtooth lattice. The title compound, BeCr 2 O 4 , displays three magnetic phase transitions at low temperatures—at T N1 ≈ 7.5 K, at T N2 ≈ 25 K, and at T N3 ≈ 26 K—revealed through magnetic susceptibility, specific heat, and neutron diffraction in this work. These magnetic phase transitions are found to be influenced by externally applied magnetic fields. Isothermal magnetization curves at low temperatures below the magnetic transitions indicate the antiferromagnetic nature of BeCr 2 O 4 with two spin-flop-like transitions occurring at H c1 ≈ 29 kOe and H c2 ≈ 47 kOe. Our high-resolution x-ray and neutron diffraction studies, performed on single crystal and powder samples, unambiguously determined the crystal structure as orthorhombic Pbnm. By performing the magnetic superspace group analysis of the neutron diffraction data at low temperatures, the magnetic structure in the temperature range T N3,N2 < T < T N1 is determined to be the polar magnetic space group P21nm. 1' (00g) 0s0s with a cycloidal magnetic propagation vector k 1 = (0, 0, 0.090 (1)) . The magnetic structure in the newly identified phase below T N1 is determined as P21/b.1' [b] (00 g) 00s with the magnetic propagation vector k 2 = (0, 0, 0.908 (1)). Finally, the cycloidal spin structure determined in our work is usually associated with electric polarization, thereby making BeCr 2 O 4 a promising multiferroic belonging to the sparsely populated family of sawtooth lattice antiferromagnets.

36 MATERIALS SCIENCE↗

NASA NTRS1986

Comparison of various techniques for calibration of AIS data

The Airborne Imaging Spectrometer (AIS) samples a region which is strongly influenced by decreasing solar irradiance at longer wavelengths and strong atmospheric absorptions. Four techniques, the Log Residual, the Least Upper Bound Residual, the Flat Field Correction and calibration using field reflectance measurements were investigated as a means for removing these two features. Of the four techniques field reflectance calibration proved to be superior in terms of noise and normalization. Of the other three techniques, the Log Residual was superior when applied to areas which did not contain one dominant cover type. In heavily vegetated areas, the Log Residual proved to be ineffective. After removing anomalously bright data values, the Least Upper Bound Residual proved to be almost as effective as the Log Residual in sparsely vegetated areas and much more effective in heavily vegetated areas. Of all the techniques, the Flat Field Correction was the noisest.

Dar A. Roberts↗

DOE OSTI2022

Assessing entropy for catalytic processes at complex reactive interfaces

When chemical reactions are accelerated by a catalyst, entropy differences between reactants and their transient intermediates can be the driving force behind the promotion or inhibition of desired and parasitic chemical pathways. Understanding and controlling catalytic processes therefore requires both a fundamental and practicable understanding of entropy in addition to enthalpy. In unstructured media such as the vapor phase equilibrated with sparsely covered surfaces, entropy can be adequately accounted for by well-established approaches based on translational, rotational, and harmonic vibrational partition functions. However, these approximations become inadequate in more complex condensed phase environments, e.g., solid liquid interfaces of confined reaction spaces. In this chapter, we provide an overview of the state-of-art in the computational quantification of entropy and its known ramifications on catalysis. The fundamental roles of thermodynamics and kinetics in catalysis are covered in enough detail to appreciate and contextualize the computational methods employed to compute chemically accurate estimates of entropy. These methods are discussed in appropriate detail and range from the ubiquitous harmonic oscillator approximation where entropy unrelated to high frequency oscillations is typically underestimated, to enhanced free energy sampling with molecular dynamics where the desired accuracy must be weighed against the associated computational cost of obtaining it. The rising importance of machine learning and artificial intelligence in accelerating methodological progress in this field is touched upon, as well. Finally, applications, successes, and pitfalls of using these methods are provided to showcase past and present accomplishments while clarifying where improvements in both understanding and methodology are still needed.

Kollias, Loukas↗

NASA NTRSDate not supplied

Joint Retrieval of Surface BRDF from Geostationary and Polar-Orbiting Satellite Sensors

The latest geostationary sensors like GOES 16/17 ABI and Himawari 8/9 AHI provide high frequent observations of the Earth surface with continuously changing solar illumination geometries, which allow us to retrieve the surface Bidirectional Reflectance Distribution Function (BRDF) with dedicated atmospheric correction algorithms like MAIAC (Multi-Angle Implementation of Atmospheric Correction). However, because the viewing geometry of a specific location from the geostationary satellites are fixed, the angular sampling of surface BRDF by GEO (Geostationary Earth Orbit) sensors is far from comprehensive. This study tries to address this issue by exploring a GEO-LEO (Low-Earth-Orbit) synergy, in particular, jointly retrieving surface BRDF parameters with concurrent ABI/AHI and VIIRS top-of-atmosphere (TOA) reflectance for the near-infrared (NIR) band. The NIR band is chosen because the ABI, AHI, and VIIRS instruments have very similar spectral response functions in this band and therefore simplifies the requirements for cross-sensor radiometric calibration. We compile ABI/AHI and VIIRS TOA data with the best quality (cloud-free and low aerosol loading) at chosen AERONET sites. We then run the GeoNEX MAIAC algorithm to retrieve the Ross-Thick-Li-Sparse (RTLS) surface BRDF parameters with or without the AEORNET measured atmospheric aerosol optical depth (AOD) as inputs. The joint retrieval results are considered the best estimate of surface BRDF. We compare the joint BRDF retrievals with the corresponding MAIAC BRDF products, retrieved with ABI/AHI or VIIRS separately, to evaluate their differences. We expect that the jointly retrieved BRDF data are more robust than the standard products and may help us reduce uncertainties in higher-level earth observation satellite products.

Remote Sensing↗

DOE OSTI2014

Sparse signal reconstruction from polychromatic X-ray CT measurements via mass attenuation discretization

We propose a method for reconstructing sparse images from polychromatic x-ray computed tomography (ct) measurements via mass attenuation coefficient discretization. The material of the inspected object and the incident spectrum are assumed to be unknown. We rewrite the Lambert-Beer’s law in terms of integral expressions of mass attenuation and discretize the resulting integrals. We then present a penalized constrained least-squares optimization approach for reconstructing the underlying object from log-domain measurements, where an active set approach is employed to estimate incident energy density parameters and the nonnegativity and sparsity of the image density map are imposed using negative-energy and smooth ℓ{sub 1}-norm penalty terms. We propose a two-step scheme for refining the mass attenuation discretization grid by using higher sampling rate over the range with higher photon energy, and eliminating the discretization points that have little effect on accuracy of the forward projection model. This refinement allows us to successfully handle the characteristic lines (Dirac impulses) in the incident energy density spectrum. We compare the proposed method with the standard filtered backprojection, which ignores the polychromatic nature of the measurements and sparsity of the image density map. Numerical simulations using both realistic simulated and real x-ray ct data are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

High temperature oxidation behavior of Ni-based superalloy GH202

The isothermal oxidation kinetic and oxidation behavior of Ni-based superalloy GH202 were investigated at temperatures from 800 °C to 1100 °C. The microstructure of GH202 was characterized by scanning electron microscope (SEM) and electron back-scattered diffraction (EBSD). The composition and morphologies of oxide scales of the surface and cross-section samples were examined by X-ray diffraction (XRD), electron probe microanalysis (EPMA), and SEM combined with energy-dispersive spectroscopy (EDS). The results show that the growth of the oxide scales on GH202 obeyed a parabolic law with an activation energy of 247.8 KJ·mol{sup −1} from 800 °C to 1100 °C. The continuous and dense oxide scales that formed at 800 °C and 900 °C were composed of Cr{sub 2}O{sub 3}, NiCr{sub 2}O{sub 4} and a small amount of TiO{sub 2}. Beneath the oxide scales, aluminum-rich oxides formed along the grain boundaries due to internal oxidation. After treatment at 1000 °C for 150 h, the oxide scale was separated into two layers, the outer layer with sparse holes that was mainly composed of Cr{sub 2}O{sub 3} and TiO{sub 2} and an inner layer of dense Cr{sub 2}O{sub 3}. At 1100 °C for 100 h the outer layer was spalled, due to the looser oxide scale with large blocks of TiO{sub 2} and NiCr{sub 2}O{sub 4} which provided channels for oxygen diffusion. - Highlights: •Isothermal oxidation kinetic of GH202 obeys a parabolic law from 800 °C to 1100 °C. •The activation energy of GH202 is closed to the diffusion activation of Cr{sup 3+}. •The evolution process of oxide scales from 800 °C to 1100 °C is displayed by EPMA. •The oxidation behavior of GH202 is mainly controlled by Cr{sup 3+} and Ti{sup 4+}.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Statistics of Wide Pre-main-sequence Binaries in the Orion OB1 Association

Statistics of low-mass pre-main-sequence binaries in the Orion OB1 association with separations ranging from 0."6 to 20" (220 to 7400 au at 370 pc) are studied using images from the VISTA Orion mini survey and astrometry from Gaia. The input sample based on the CVSO catalog contains 1137 stars of K and M spectral types (masses between 0.3 and 0.9 M ⊙ ), 1021 of which are considered to be association members. There are 135 physical binary companions to these stars with mass ratios above ~0.13. The average companion fraction is 0.09 ± 0.01 over 1.2 decades in separation, slightly less than, but still consistent with, the field. We found a difference between the Ori OB1a and OB1b groups, the latter being richer in binaries by a factor of 1.6 ± 0.3. No overall dependence of the wide-binary frequency on the observed underlying stellar density is found, although in the Ori OB1a off-cloud population, these binaries seem to avoid dense clusters. The multiplicity rates in Ori OB1 and in sparse regions like Taurus differ significantly, hinting that binaries in the field may originate from a mixture of diverse populations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Characterizing the Influence of Fracture Density on Network Scale Transport

The topology of natural fracture networks is inherently linked to the structure of the fluid velocity field and transport therein. Here we study the impact of network density on flow and transport behaviors. We stochastically generate fracture networks of varying density and simulate flow and transport with a discrete fracture network model, which fully resolves network topology at the fracture scale. We study conservative solute trajectories with Lagrangian particle tracking and find that as fracture density decreases, solute channelization to large local fractures increases, thereby reducing plume spreading. Furthermore, in sparse networks mean particle travel distance increases and local network features, such as velocity zones where flow is counter to the primary pressure gradient, become increasingly important for transport. As the network density increases, network statistics homogenize and such local features have a reduced impact. We quantify local topological influence on transport behavior with an effective tortuosity parameter, which measures the ratio of total advective distance to linear distance at the fracture scale; large tortuosity values are correlated to slow-velocity regions. Additionally, these large tortuosity, slow-velocity regions delay downstream transport and enhance tailing on particle breakthrough curves. Finally, we predict transport with an upscaled, Bernoulli spatial Markov random walk model and parameterize local topological influences with a novel tortuosity parameter. Furthermore, Bernoulli model predictions improve when sampling from a tortuosity distribution, as opposed to a fixed value as has previously been done, suggesting that local network topological features must be carefully considered in upscaled modeling efforts of fracture network systems.

58 GEOSCIENCES↗