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At least 19 records

Experimental and simulation study of target biasing effects on plasma transport in linear plasma device MPS-LD

Linear plasma devices (LPDs) are important experimental platforms for investigating plasma–material interactions (PMI). In PMI experiments, it has been found that applying a target bias not only effectively modifies the incident ion energy, but also induces significant changes in the electron density and electron temperature, whereby the evolution of these plasma parameters is primarily governed by plasma transport processes. However, at present, the physical process and mechanism underlying such bias-induced variations remain unclear. In this work, biasing experiments under argon plasma discharge conditions were first carried out on the MPS-LD device. For the corresponding experiments, an electric potential model was newly developed based on the BOUT++ LPD module, enabling self-consistent simulations of plasma transport under biased conditions. Numerical simulations were then performed to reproduce the experimental results and to validate the accuracy of the proposed model. Finally, by combining experimental measurements with numerical simulations, a bias-voltage scan was performed to investigate how the electron density and electron temperature vary with the bias voltage (U bias ). The results show that applying negative bias decreases the target electron density (n e,T ) while increasing the target electron temperature (T e,T ). In contrast, positive bias increases both n e,T and T e,T ; however, at high positive bias, n e,T first reaches a maximum and subsequently decreases with further increases in U bias . The underlying physical mechanisms are analyzed using particle flux, momentum, and energy conservation. It indicates that the applied bias regulates the parallel electric field, thereby changing ion and electron velocities, and consequently affecting the electron density. At high positive bias, the ion velocity is further influenced by ion viscosity, leading to the reversal in n e,T . Meanwhile, the enhanced parallel electric field drives stronger currents, significantly increasing ion–electron frictional work and converting the input bias power into electron energy, which raises the electron temperature. In conclusion, these results contribute to a deeper understanding of the effects and mechanisms of biasing on plasma transport in the MPS-LD device.

BOUT++ simulation

Effect of stress and temperature on zero group velocity Lamb modes

Zero group velocity (ZGV) Lamb wave resonances are highly localized and sensitive to changes in material properties, making them a viable option for probing residual stresses and elastic nonlinearity through acoustoelastic effects. Temperature changes also influence ZGV modes and need to be accounted for, particularly when measuring the small frequency shifts associated with acoustoelastic effects. We use a laser-based ultrasonic system to measure the third-order elastic constants of several materials. A temperature compensation scheme is devised to remove the effects of temperature fluctuations from the measurements. Furthermore, the measured third-order elastic constants are used to predict the temperature dependence of the ZGV resonances using thermo-acoustoelasticity theory, and these predictions are compared to experimental measurements. We find that thermo-acoustoelasticity theory was unable to reliably predict the shift in ZGV resonances with temperature. These results could have important implications in understanding the limitations of thermo-acoustoelasticity theory and in developing precision ZGV resonance-based systems to detect and quantify residual stress in parts, a particularly relevant problem in additive manufacturing techniques including powder bed fusion and directed energy deposition.

Engineering

Symmetrization of Strong Hydrogen Bond under High Pressure in Bihydroxide-Ion-Containing NaCu 2 (SO 4 ) 2 ·H 3 O 2 Revealed by Experimental Charge Density, Single-Crystal Electron Diffraction, and Neutron Diffraction Studies

In minerals and inorganic compounds, strong hydrogen bonding can lead to the formation of complex ionic species such as the H 3 O 2 – bihydroxide anion and Zundel cation H 5 O 2 + . We studied [NaCu 2 (SO 4 ) 2 ·H 3 O 2 ] natrochalcite, which contains bihydroxide anions and undergoes hydrogen bond symmetrization at the lowest pressure reported so far among inorganic compounds. Hydrogen bond symmetrization leads to changes in the bulk modulus, seismic wave velocities, and proton mobility and plays a primary role in high-temperature superconductivity, but its characteristics are not well understood due to a lack of systematic studies and limitations of experimental methods sensitive to this subtle change. In this work, we applied experimental charge density analysis based on in situ single-crystal X-ray diffraction data, along with the single-crystal neutron and electron diffraction experiments, to probe the behavior of hydrogen atoms during the hydrogen bond symmetrization process under high-pressure conditions. On the way to the symmetrical H-bonding, natrochalcite undergoes a series of complex redistributions of electron density, which we trace with multipole refinement and detailed analysis of changes in the Laplacian of electron density values. Additionally, we deconvoluted the equation of state (volume of the unit cell vs pressure relation) into the atomic equation of states describing dependencies of atomic charges or volumes vs pressure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Phase Selection During Solidification and Solid-State Phase Transformations in an Al-10Ce-8Mn (wt pct) Alloy

In multicomponent Al-Ce alloys, and especially after additive manufacturing (AM), complex and metastable solidification microstructures are frequently observed. Here, in this research, the relationship between solidification conditions and phase selection are explored for an Al-10Ce-8Mn (wt pct) alloy using a systematic study of laser melting conditions. Three solidification modes were observed: primary Al 10 Mn 2 Ce; primary Al 20 Mn 2 Ce; and eutectic FCC Al + Al 20 Mn 2 Ce. These solidification modes were correlated to specific liquid-solid interface velocities using a simple thermal model, showing the change in primary solidification phase for low (< 6.8 × 10 −4 m/s), moderate (between 8.2 × 10 −4 and 5.9 × 10 −2 m/s) and high solidification velocities (> 6.2 x 10 −2 m/s) for the above three solidification microstructures, respectively. These results were rationalized by using interface response function (IRF) theory to describe the solidification undercooling for the possible primary intermetallic phases. The implication of the local phase selection from differing solidification conditions is summarized by a comparison of hardness which demonstrates the potential variance of Vickers hardness from 101 to 242 (VHV) by changing the laser velocity from 1 to 83 mm/s. Interestingly, on heat treatment at 400°C, the decomposition pathways of the solidification microstructure and hardness were also found to be different, thereby opening multiple pathways for spatial microstructure and property control within AM components.

Sisco, Kevin

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is a physics-rich collection of two-dimensional, cylindrically symmetric, simulations generated using an Eulerian, multi-material, shock-propagation code developed at Los Alamos National Laboratory. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE

Surface and sub-surface porosity effects on the initial free surface expansion in shocked single crystal aluminum

Defects and roughness at a material’s surface can allow for the formation of a material jet when a shockwave reaches a surface. The formation of a jet can lead to significant material damage of the shocked material, as well as the downstream material that the jet impacts. Here, we utilize planar shocks in single crystal aluminum to assess initial jetting formation for surface notches and sub-surface porosity. In the case of surface notches, we find that changing the width of the notch can cause the shock breakout response to transition from a standard jetting mechanism to an atomic atomization at high velocities. This transition occurs due to the mechanisms associated with lateral relaxations within the notch and how this interacts with the shock focusing event that induces jetting. For sub-surface pores, the pore collapse induces a re-shock, localized near the pore, that is stronger than the initial shock, but unsupported. Changing the pore dimensions and location relative to the surface influences the strength of the shock that emanates from its collapse when it reaches the surface, leading to a variety of different breakout conditions including jetting and localized material failure.

36 MATERIALS SCIENCE

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

A declining spring snowpack is expected to have widespread effects on montane and subalpine forests in western North America and across the globe. The way that tree water demands respond to this change will have important impacts on forest health and downstream water subsidies. Here, we present data from a network of sap velocity sensors and xylem water isotope measurements from three common tree species (Picea engelmannii, Abies lasiocarpa and Populus tremuloides) across a hillslope transect in a subalpine watershed in the Upper Colorado River basin. We use these data to compare tree- and stand-level responses to the historically high spring snowpack but low summer rainfall of 2019 against the low spring snowpack but high summer rainfall amounts of 2021 and 2022. From the sap velocity data, we found that only 40 % of the trees showed an increase in cumulative transpiration in response to the large snowpack year (2019), illustrating the absence of a common response to interannual spring snowpack variability. The trees that increased water use during the year with the large spring snowpack were all found in dense canopy stands – irrespective of species – while trees in open-canopy stands were more reliant on summer rains and, thus, more active during the years with modest snow and higher summer rain amounts. Using the sap velocity data along with supporting measurements of soil moisture and snow depth, we propose three mechanisms that lead to stand density modulating the tree-level response to changing seasonality of precipitation: Topographically mediated convergence zones have consistent access to recharge from snowmelt which supports denser stands with high water demands that are more reliant and sensitive to changing snow. Interception of summer rain in dense stands reduces the throughfall of summer rain to surface soils, limiting the sensitivity of the dense stands to changes in summer rain. Shading in dense stands allows the snowpack to persist deeper into the growing season, providing high local reliance on snow during the fore-summer (early-summer) drought period. Combining data generated from natural gradients in stand density, like this experiment, with results from controlled forest-thinning experiments can be used to develop a better understanding of the responses of forested ecosystems to futures with reduced spring snowpack.

54 ENVIRONMENTAL SCIENCES

Flame Characterization and Flashback Studies of Hydrogen-Enriched Low-Swirl Flames Using High-Speed OH-PLIF

Here, this paper reports the flashback mechanism observed in hydrogen-enriched flames stabilized in a low-swirl burner (LSB) at atmospheric temperature and pressure. The fundamentals of hydrogen-rich stable flames and spatiotemporal information of flashback phenomena were observed experimentally using a high-repetition-rate nanosecond (ns)-duration hydroxyl planar laser-induced fluorescence (OH-PLIF) diagnostic. Testing was conducted for methane and hydrogen (50–90%H 2 , by mole) blends in an optically accessible LSB premixer with measured swirl numbers varying from 0.43 to 0.49. The flashback propensity showed dependence on liftoff length, which was dependent on premixer velocity (𝑉), hydrogen content (𝑋 H 2 ), and equivalence ratio (𝜙) at constant temperature and pressure. High-speed OH-PLIF images revealed that lifted flames were first observed at low 𝜙/𝑋 H 2 conditions, which were changed to an M-shaped flame attached to the burner rim with an increase in 𝜙/𝑋 H 2 . A further increase in 𝜙/𝑋 H 2 triggered the flame flashback into the premixer. Flame 𝜙 at flashback (𝜙 FB ) showed an expected linearly increasing trend with increasing 𝑉 and decreasing 𝑋 H 2 , and the conclusions drawn aligned well with detailed liftoff length investigations. The 𝜙 FB increased with increasing perforated plate hole diameter and increasing swirler vane angle. The vane angle had little effect on flashback tendency at high premixer velocity.

combustion

Dominant Controls on Preferential Flow and Their Implications for Future Soil Water Fluxes

Abstract Soil water flow, particularly preferential flow (PF), is a critical control on hydrological and biogeochemical processes, including groundwater recharge, contaminant transport, and carbon cycling. However, it remains challenging to predict PF occurrence across large environmental gradients. Here, we developed a deep learning (DL) model to estimate event‐scale soil water flow velocity and the probability of PF occurrence using high‐frequency soil moisture and precipitation data from 33 sites across the National Ecological Observatory Network. The model demonstrated high skill in predicting the binary occurrence of PF (91% F1‐score; 85% accuracy) but the performance was limited in predicting soil water velocity ( R 2 = 0.31). We found that precipitation characteristics (duration, volume, and intensity) were the most important predictors for soil water velocity. Among the non‐precipitation event variables, sand content showed relatively high predictive skill, though differences among non‐event climate variables were generally modest. Lower sand content was associated with increased predicted soil water velocity, a finding that highlights the role of soil structure in producing more non‐uniform flow, which contrasts with traditional uniform flow models. Projecting a reduced DL model under both moderate and high‐emissions future climate scenarios (2060–2099 Representative Concentration Pathways 4.5 and 8.5), we found ∼7.3% increase under RCP4.5 and ∼15% under RCP8.5 of soil water velocities compared to the historical simulation, while modeled likelihood of PF changed little. These findings suggest climate change is not making PF more frequent, but it is making existing PF pathways more efficient with important consequences for associated nutrient and contaminant transport under climate change. Plain Language Summary Water movement in soil is critical for water quality. While often modeled as a uniform flow process, in reality water moves rapidly through cracks and burrows in what is called “preferential flow” (PF), which limits natural filtration and can transport pollutants. We developed a deep learning model, trained on data from 33 U.S. sites, to predict when and how fast this PF occurs based on precipitation, soil, and climate data. The model showed that precipitation characteristics (duration, intensity, volume) were the most important predictors of PF. Lower soil sand content/higher clay content was associated with faster water flow, likely due to clay soils forming aggregates and cracks that water moves through rather than infiltrating uniformly. Further analyses based on climate projections suggest that the speed at which PF occurs will become more rapid under future climate scenarios compared to historical simulation. This highlights the need to represent PF in soil water models when assessing future water quality. Key Points The effect of precipitation peak intensity on soil water velocities declined with increasing precipitation intensity Antecedent soil moisture failed to predict preferential flow (PF), contrasting the high predictive power of sand content Climate predictions suggest that soil water velocities through PF paths will increase ∼15% by 2099

Li, Bonan

Competition response of cloud supersaturation explains diminished Twomey effect for smoky aerosol in the tropical Atlantic

The Twomey effect brightens clouds by increasing aerosol concentrations, which activates more droplets and decreases cloud supersaturation in response to more competition for water vapor. To quantify this competition response, we used marine low cloud observations in clean and smoky conditions at Ascension Island in the tropical South Atlantic during the Layered Aerosol Smoke Interactions with Cloud (LASIC) campaign. These observations show similar increases in droplet number for increased accumulation-mode particles from surface-based and satellite cloud retrievals, demonstrating the importance of below-cloud aerosol measurements for retrieving aerosol–cloud interactions (ACI) in clean and smoky aerosol conditions. Four methods for estimating cloud supersaturation from aerosol–cloud measurements were compared, with cloud scene-based and parcel-based methods showing sufficient variability for a strong dependence on both aerosol accumulation number concentration and cloud-base updraft velocities. Decomposing aerosol-related changes in cloud albedo and optical depth shows the calculated competition response accounts for dampening the activation response by 12 to 35%, explaining the diminished Twomey effect at high aerosol concentrations observed for smoky conditions at LASIC and previously around the world. This result was consistent for independent supersaturation retrievals by cloud scene-based droplet number and cloud condensation nuclei and parcel-based multimode size-resolving Lagrangian methods. Translating aerosol effects to local radiative forcing with clean conditions as a proxy for preindustrial and smoky conditions for present-day showed that the competition response reduces cooling from the Twomey radiative forcing by 12 to 35%, providing an essential process-specific constraint for improving the representation of aerosol competition in climate model simulation of indirect aerosol forcing.

54 ENVIRONMENTAL SCIENCES

Delving into the depths of NGC 3783 with XRISM V. Broad-band modelling of ionized outflows

The Seyfert 1 galaxy NGC 3783 hosts a multi-phase warm absorber (WA) that has been extensively studied in the X-ray band. High-resolution spectra from 2000−2001 revealed a complex outflow with multiple ionization and velocity components. Two decades later, new XMM-Newton and XRISM observations allow us to investigate the long-term evolution of these outflows. We performed joint spectral modelling of the XMM-Newton /RGS and XRISM/Resolve time-averaged spectra using the pion photoionization code within SPEX. We derived the ionization parameter, column density, turbulent velocity, and outflow velocity for each absorption component, and investigated their thermal stability and absorption measure distribution (AMD) to characterize the physical and dynamical properties of the WA in NGC 3783 in 2024. We compared these results with the 2000−2001 epoch to assess long-term variability, stability, and possible changes in the absorber population. We identify eight WA components spanning log ξ = 1.08 − 3.38 and outflow velocities of 480−1230 km s −1 . The ranges of column densities and turbulent velocities remain broadly consistent with the WAs from 2000−2001, but the earlier data contained more low-ionization, high-velocity components. The total column density of all the outflows in 2024 is 1.5 times larger than in 2000−2001, which means that it has been replenished by fresh material. The dominant unresolved transition array (UTA) absorber (component B3) has increased its column density by a factor of three while maintaining a similar ionization parameter. The WAs in NGC 3783 have undergone significant structural and dynamical evolution over the past 24 years.

79 ASTRONOMY AND ASTROPHYSICS

Energy-Optimal Vehicle Longitudinal Motion Control via Pontryagin’s Minimum Principle and Ultra-Local Model

Longitudinal vehicle motion control is essential for enhancing performance and optimizing a vehicle’s energy usage. However, it remains a challenging task due to the nonlinear and uncertain nature of vehicle dynamics, along with varying driving conditions. This paper presents a novel ultra-local optimal control approach based on Pontryagin’s Minimum Principle (PMP) that circumvents the need for detailed system identification by employing an ultra-local model. The control objective is to minimize the total energy consumption under boundary conditions while ensuring smooth traction force generation. The proposed approach is evaluated using a high-fidelity vehicle model in three representative scenarios: (i) nominal driving, (ii) a change in tire road friction coefficient (TRFC) from 0.5 to 0.65 and road slope from 0% to 5% during the maneuver, with target velocity unchanged, and (iii) a change in target velocity from 20 m/s to 0 m/s during the maneuver, while maintaining nominal TRFC and slope conditions. The simulation results demonstrate that the proposed method delivers robust performance, effectively balancing consumption and tracking accuracy in all tested scenarios.

Waleed khan, Muhammad [The University of Texas at

A map of the rubisco biochemical landscape

Rubisco is the primary CO 2 -fixing enzyme of the biosphere, yet it has slow kinetics. The roles of evolution and chemical mechanism in constraining its biochemical function remain debated. Engineering efforts aimed at adjusting the biochemical parameters of rubisco have largely failed, although recent results indicate that the functional potential of rubisco has a wider scope than previously known. Here we developed a massively parallel assay, using an engineered Escherichia coli in which enzyme activity is coupled to growth, to systematically map the sequence–function landscape of rubisco. Composite assay of more than 99% of single-amino acid mutants versus CO 2 concentration enabled inference of enzyme velocity and apparent CO 2 affinity parameters for thousands of substitutions. This approach identified many highly conserved positions that tolerate mutation and rare mutations that improve CO 2 affinity. These data indicate that non-trivial biochemical changes are readily accessible and that the functional distance between rubiscos from diverse organisms can be traversed, laying the groundwork for further enzyme engineering efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Unique optical excitations in topological insulators (Final Technical Report)

The overall objective of this research is to understand how light interacts with topological insulator (TI) films and layered structures. Unlike normal materials, the electrons in TI films are trapped at the top and bottom surfaces of the film. These electrons have unusual properties, including low mass and high velocity. Light shining on these trapped electrons will excite electron density waves, called plasmons, which inherit the unusual properties of the electrons. This project aims to understand how these plasmons interact with each other and how the plasmon properties change as the film dimensions change. By controlling the physical properties of the films, the optical response of the film can also be controlled. In addition to single TI films, the project will also investigate the properties of stacks of TI films layered with normal insulating films. Stacking these materials results in multiple layers of trapped electrons whose plasmons can interact in ever more complex ways. After these interactions are understood, we can begin to engineer complex TI structures to obtain designer optical phenomena in the far-infrared and THz, wavelength ranges of interest for environmental monitoring and chemical sensing. This research directly addresses DOE Grand Challenges, including understanding how properties of matter emerge from complex electronic correlations and learning how to control these properties as well as the mission of the Basic Energy Sciences program to understand and control matter at the electronic/atomic level.

36 MATERIALS SCIENCE

Two-dimensional burn velocity and analysis of burn products of nitromethane at high pressure

We have studied the laser-initiated deflagration of nitromethane (CH 3 NO 2 ) under high static pressure in the diamond anvil cell. Time-resolved images of the deflagrations have been obtained using intensified CCDs (ICCD). In contrast with previous work, we rely on spontaneous emission from the reaction, rather than changes in the speckle pattern produced by artificial illumination of the sample. Furthermore, as opposed to the 1D records obtained previously with streak cameras, ICCDs permit imaging of the burn in two dimensions providing the ability to directly observe anisotropic deflagration behavior. Here, we report several examples of this behavior and discuss its possible origins. We have also investigated the products of the reaction using Raman spectroscopy. At pressures below 25 GPa, the burn product is observed to be opaque and has a Raman spectrum consistent with a carbonaceous soot. At pressures above 25 GPa, the burn product is observed to be transparent (consistent with earlier reports) and its Raman spectrum reveals the presence of molecular N 2 and a nitrogen-carbonate species. The latter species can be recovered to ambient pressure and has a Raman spectrum consistent with ammonium carbonate or ammonium bicarbonate. To aid interpretation of the Raman spectra, measurements have also been made on the isotopologues CH 3 15 NO 2 and 13 CH 3 NO 2 . This work establishes the importance of advanced time-resolved imaging to reveal the details of deflagration under high pressure and further advances our understanding of the corresponding chemistry.

Deflagration

Remote Influence of Andean Convection on Amazonian Rainfall and Its Mechanisms

Models from Coupled Model Intercomparison Project Phase 6 produce too much precipitation over the Andes but too little over the Amazon or the Wet Andes-Dry Amazon (WADA) bias pattern. Unlike the conventional view that convection parameterization and land model deficiencies can contribute to Amazonian rainfall biases, we approach this long-standing biased model behavior through the lens of Andean convection. Using Community Earth System Model v1.1 and focusing on the wet season, our mechanism-denial experiments demonstrate that Andean convection notably reduces precipitation over the Amazon during austral summer. The Andean forced Amazonian response operates on weather timescale. Furthermore, the reduction of Amazonian rainfall is detectable within a few hours after initial Andean forcing. The precipitation response is primarily driven by variations in the moisture budget and is moderated by changes in convective available potential energy over the Amazon. Changes in the total advection of moisture over the Amazon are dominated by the vertical advection term and can be attributed to discrepancies in the dynamic omega field. In the experiments, the Andean east flank region is scrutinized where the vertical velocity and moisture fields play an intermediary role for the Andean driven WADA connection. The Andean forcing induces descending anomalies on the Andean east flank. The disturbances of wind and geopotential fields over the Andean east flank propagate eastward via Kelvin waves. Over the Amazon, descending anomalies and advective drying lead to reduction of mid-to-high level cloud, increase of shortwave cloud forcing and surface net radiation, and enhancement of themodynamic stability and rainfall reduction.

58 GEOSCIENCES

Urban wash-off of tire wear particles

Tire wear particles (TWPs) are an important class of microplastics due to their toxicity and abundance. Because most TWPs are generated on impervious road surfaces, urban wash-off is the critical first phase of waterborne transport from their zone of production to stormwater drainage. However, little is known about the driving factors behind their mobilization. In this study, we use a rainfall simulator to investigate how surface roughness, rainfall intensity, and surface slope affect wash-off behaviors of TWPs. We also analyze how the size and shape of mobilized TWPs change over the course of simulated storm events. We found that low surface roughness, high rainfall intensity (most significant factor), and low slope result in the most rapid conveyance of TWP load. On average, large particles (>1000 µm) travelled faster than small particles (<125 µm). Particle shape explained a very small amount of variance in TWP wash-off velocity but was found to be more important under higher surface roughness conditions. In addition to wash-off velocity, we found similar conditions controlled the percent mobilization of TWPs. Low surface roughness and high rainfall intensity resulting in higher TWP wash-off rates is consistent with mineral sediment wash-off behavior. Conversely, low surface slope and large particle size leading to faster conveyance is directly opposed to mineral sediment wash-off. Our findings suggest drag-dominated flow and that sufficient runoff depth is the most important parameter governing TWP wash-off. These findings are important first steps to understanding wash-off behaviors of TWPs and informing future modeling efforts and mitigation strategies.

13 HYDRO ENERGY

Ambient field seismology in critical zone hydrological sciences

Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.

58 GEOSCIENCES