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At least 991 records · Page 55

Forward Drift Chamber for the GlueX experiment

The GlueX experiment will search for exotic mesons produced by 9 GeV linearly polarized photon beam from the 12 GeV CEBAF machine. A hermetic solenoid-based detector system that includes tracking and calorimetry is in the final construction phase. The Forward Drift Chamber consists of 24 circular planar drift chambers of 1 m diameter. Additional cathode strip information is required to achieve efficient pattern recognition in forward direction, resulting in 12,000 readout channels in total. Description and results from the tests of the completed detector will be presented. Challenges related to the specific features of the detector will be discussed. A small modification of the standard geometry allowed us to study the possibility for PID by cluster counting and investigate some gas properties based on single electron detection.

Pentchev, Lubomir↗

Statistical analysis of spatial distribution of pores in metal additive manufacturing

We report mechanical properties of additively manufactured parts are sensitive to the presence of pores form during the manufacturing process. The impact of pores on the mechanical performance has been investigated extensively with respect to different parameters, such as pore volume fraction, shape, and size. However, statistical investigations focusing on the relationships between the spatial distribution of pores and process parameters; and consequently, the performance of the manufactured parts are scattered and limited. Also, these sparse investigations usually suffer from an ambiguous definition of terminologies. For instance, the required criteria to consider a point pattern as complete spatial randomness (CSR) are generally not clarified. Moreover, no numerical formalism is yet developed to show how much the observed spatial results are statistically significant. To address these shortcomings, the statistical definition of CSR in a point pattern and the procedure to quantitatively determine the deviation of a pattern from CSR were discussed. The explained statistical approach was used to investigate the effect of scanning speed parameter on the spatial distribution of gas pores in laser powder bed fusion manufactured stainless steel parts. Furthermore, and to highlight the impact of the spatial distribution of pores on mechanical properties, fatigue performances of parts with clustered and randomly distributed pores were simulated by finite element analysis. It is shown that by reducing the scanning speed, the spatial distribution of gas pores deviated more from CSR, and correspondingly fatigue performance deteriorated.

36 MATERIALS SCIENCE↗

Ab initio structural and spectroscopic study of HPS{sup x} and HSP{sup x} (x = 0,+1,−1) in the gas phase

Accurate ab initio computations of structural and spectroscopic parameters for the HPS/HSP molecules and corresponding cations and anions have been performed. For the electronic structure computations, standard and explicitly correlated coupled cluster techniques in conjunction with large basis sets have been adopted. In particular, we present equilibrium geometries, rotational constants, harmonic vibrational frequencies, adiabatic ionization energies, electron affinities, and, for the neutral species, singlet-triplet relative energies. Besides, the full-dimensional potential energy surfaces (PESs) for HPS{sup x} and HSP{sup x} (x = −1,0,1) systems have been generated at the standard coupled cluster level with a basis set of augmented quintuple-zeta quality. By applying perturbation theory to the calculated PESs, an extended set of spectroscopic constants, including τ, first-order centrifugal distortion and anharmonic vibrational constants has been obtained. In addition, the potentials have been used in a variational approach to deduce the whole pattern of vibrational levels up to 4000 cm{sup −1} above the minima of the corresponding PESs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mapping the Sedna-Lavinia Region of Venus

Geologic mapping of Venus at 1:5 M scale has shown in great detail the flow complexes of volcanoes, coronae, and shield fields, and the varying structural patterns that differentiate tesserae from corona rims and isolated patches of densely lineated terrain. In most cases, however, the lower-elevation plains between the higher-standing landforms are discriminated only on the basis of potentially secondary features such as late-stage lava flooding or tectonic overprinting. This result, in which volcanoes and tesserae appear as "islands in the sea," places weak constraints on the relative age of large upland regions and the nature of the basement terrain. In this work, we focus on the spatial distribution and topography of densely lineated and tessera units over a large region of Venus, and their relationship to apparently later corona and shield flow complexes. The goal is to identify likely connections between patches of deformed terrain that suggest earlier features of regional extent, and to compare the topography of linked patches with other such clusters as a guide to whether they form larger tracts beneath the plains. Mapping Approach. We are mapping the region from 57S to 57N, 300E-60E. Since the 1:5 M quadrangles emphasize detail of tessera structure and corona/edifice flows, we simply adopt the outlines of these features as they relate to the outcrops of either "densely lineated terrain" or tessera (Fig. 1). The densely lineated material is mapped in many quadrangles based on pervasive structural deformation, typically with a single major axis (in contrast to the overlapping orthogonal patterns on tesserae). This unit definition is often extended to include material of corona rims. We do not at present differentiate between plains units, since earlier efforts show that their most defining attributes may be secondary to the original emplacement (e.g., lobate or sheet-like flooding by thin flow units, tectonic patterns related to regional and localized stress regimes) [1].

Campbell, Bruce A.↗

Lévy-like movement patterns of metastatic cancer cells revealed in microfabricated systems and implicated in vivo

Metastatic cancer cells differ from their non-metastatic counterparts not only in terms of molecular composition and genetics, but also by the very strategy they employ for locomotion. Here, we analyzed large-scale statistics for cells migrating on linear microtracks to show that metastatic cancer cells follow a qualitatively different movement strategy than their non-invasive counterparts. The trajectories of metastatic cells display clusters of small steps that are interspersed with long “flights”. Such movements are characterized by heavy-tailed, truncated power law distributions of persistence times and are consistent with the Lévy walks that are also often employed by animal predators searching for scarce prey or food sources. In contrast, non-metastatic cancerous cells perform simple diffusive movements. These findings are supported by preliminary experiments with cancer cells migrating away from primary tumors in vivo. The use of chemical inhibitors targeting actin-binding proteins allows for “reprogramming” the Lévy walks into either diffusive or ballistic movements.

60 APPLIED LIFE SCIENCES↗

An investigation of non-canonical mixing in red giant stars using APOGEE 12 C/ 13 C ratios observed in open cluster stars

Standard stellar evolution theory poorly predicts the surface abundances of chemical species in low-mass, red giant branch (RGB) stars. Observations show an enhancement of p–p chain and CNO cycle products in red giant envelopes, which suggests the existence of non-canonical mixing that brings interior burning products to the surface of these stars. The 12 C/ 13 C ratio is a highly sensitive abundance metric used to probe this mixing. We investigate extra RGB mixing by examining: (1) how 12 C/ 13 C is altered along the RGB, and (2) how 12 C/ 13 C changes for stars of varying age and mass. Our sample consists of 43 red giants, spread over 15 open clusters from the Sloan Digital Sky Survey’s APOGEE DR17, that have reliable 12 C/ 13 C ratios derived from their APOGEE spectra. We vetted these 12 C/ 13 C ratios and compared them as a function of evolution and age/mass to the standard mixing model of stellar evolution, and to a model that includes prescriptions for RGB thermohaline mixing and stellar rotation. We find that the observations deviate from standard mixing models, implying the need for extra mixing. Additionally, some of the abundance patterns depart from the thermohaline model, and it is unclear whether these differences are due to incomplete observations, issues inherent to the model, our assumption of the cause of extra mixing, or any combination of these factors. Nevertheless, the surface abundances across our age/mass range clearly deviate from the standard model, agreeing with the notion of a universal mechanism for RGB extra mixing in low-mass stars.

79 ASTRONOMY AND ASTROPHYSICS↗

FLUORINE VARIATIONS IN THE GLOBULAR CLUSTER NGC 6656 (M22): IMPLICATIONS FOR INTERNAL ENRICHMENT TIMESCALES

Observed chemical (anti)correlations in proton-capture elements among globular cluster stars are presently recognized as the signature of self-enrichment from now extinct, previous generations of stars. This defines the multiple population scenario. Since fluorine is also affected by proton captures, determining its abundance in globular clusters provides new and complementary clues regarding the nature of these previous generations and supplies strong observational constraints to the chemical enrichment timescales. In this paper, we present our results on near-infrared CRIRES spectroscopic observations of six cool giant stars in NGC 6656 (M22): the main objective is to derive the F content and its internal variation in this peculiar cluster, which exhibits significant changes in both light- and heavy-element abundances. Across our sample, we detected F variations beyond the measurement uncertainties and found that the F abundances are positively correlated with O and anticorrelated with Na, as expected according to the multiple population framework. Furthermore, our observations reveal an increase in the F content between the two different sub-groups, s-process rich and s-process poor, hosted within M22. The comparison with theoretical models suggests that asymptotic giant stars with masses between 4 and 5 M {sub Sun} are responsible for the observed chemical pattern, confirming evidence from previous works: the difference in age between the two sub-components in M22 must be not larger than a few hundred Myr.

79 ASTRONOMY AND ASTROPHYSICS↗

Household energy resilience in extreme weather events: An investigation of energy service importance, HVAC usage behaviors, and willingness to pay

Household energy resilience, particularly maintaining essential energy services within an acceptable and affordable level, is critical during extreme weather events (e.g., winter storms, heat waves) with power shortages or outages. However, the research on the importance and acceptable compromise levels of energy services, HVAC usage behavior changes, and willingness to pay (WTP) for energy services during disasters is limited. Therefore, this study investigates the importance and compromise of household energy services, HVAC usage behaviors, and WTP, as three key dimensions of household energy resilience, in both normal days and disaster scenarios through surveys (n=485). First, 12 common residential end-uses are grouped into high, mid, and low-priority services using hierarchical clustering, in which high-priority services (perceived as important and un-compromisable) include food cooking and storage (refrigerator and freezer) and thermal comfort (space heating and cooling), mid-priority services involve water heating and lighting, while low-priority services are mostly related to entertainment and housework (e.g., TV, laundry). Also, HVAC use patterns demonstrate that occupants become more energy conservative during disasters, e.g., reducing durations of running HVAC and adjusting temperature setpoints to save energy. In terms of energy cost, approximately 60% of respondents are willing to pay more to maintain energy services during disasters, although only 13% are prepared to pay over double the normal energy prices. The regression models further reveal that household energy resilience varies across different sociodemographic groups (e.g., age, income, family size) and is impacted by disaster experience and beliefs in clean energy and climate. In conclusion, these research findings provide important perspectives to understand household energy resilience and inform measures for disaster adaptation of households in extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Contribution of El Niño Southern Oscillation (ENSO) Diversity to Low‐Frequency Changes in ENSO Variance

Abstract El Niño Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific events are typically weaker than Eastern Pacific events. SSTA pattern and intensity undergo low‐frequency modulations, affecting ENSO prediction skill and remote impacts, and resulting in low‐frequency changes in ENSO variance. Yet, how different ENSO types contribute to these decadal variance changes remains unclear. Here, we decompose the low‐frequency changes of ENSO variance into contributions from ENSO diversity categories. We propose a fuzzy clustering of monthly SSTA to allow for non‐binary event category memberships, where each event can belong to different clusters. Our approach identifies two La Niña and three El Niño categories and shows that the major shift of ENSO variance in the mid‐1970s was associated with an increasing likelihood of strong La Niña and extreme El Niño events.

Geology↗

ROTATIONAL AND CYCLICAL VARIABILITY IN {gamma} CASSIOPEIAE. II. FIFTEEN SEASONS

The B0.5 IVe star {gamma} Cas is of great interest because it is the prototype of a small group of classical Be stars having hard X-ray emission of unknown origin. We discuss results from ongoing B and V observations of the {gamma} Cas star-disk system acquired with an Automated Photometric Telescope during the observing seasons 1997-2011. In an earlier study, Smith, Henry, and Vishniac showed that light variations in {gamma} Cas are dominated by a series of comparatively prominent cycles with amplitudes of 0.02-0.03 mag and lengths of 2-3 months, superimposed on a 1.21 day periodic signal some five times smaller, which they attributed to rotation. The cycle lengths clustered around 70 days, with a total range of 50-91 days. Changes in both cycle length and amplitude were observed from year to year. These authors also found the V-band cycles to be 30%-40% larger than the B-band cycles. In the present study, we find continued evidence for these variability patterns and for the bimodal distribution of the {Delta}B/{Delta}V amplitude ratios in the long cycles. During the 2010 observing season, {gamma} Cas underwent a mass-loss event ({sup o}utburst{sup )}, as evidenced by the brightening and reddening seen in our new photometry. This episode coincided with a waning of the amplitude in the ongoing cycle. The Be outburst ended the following year, and the light-curve amplitude returned to pre-outburst levels. This behavior reinforces the interpretation that cycles arise from a global disk instability. We have determined a more precise value of the rotation period, 1.215811 {+-} 0.000030 days, using the longer 15-season data set and combining solutions from the V and B light curves. Remarkably, we also find that both the amplitude and the asymmetry of the rotational waveform changed over the years. We review arguments for this modulation arising from transits of a surface magnetic disturbance. Finally, to a limit of 5 mmag, we find no evidence for any photometric variation corresponding to the {gamma} Cas binary period, 203.55 days, or to the first few harmonics.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling temporal and hormonal regulation of plant transcriptional response to wounding

Plants respond to wounding stress by changing gene expression patterns and inducing the production of hormones including jasmonic acid. This wounding transcriptional response activates specialized metabolism pathways such as the glucosinolate pathways in Arabidopsis thaliana. While the regulatory factors and sequences controlling a subset of wound-response genes are known, it remains unclear how wound response is regulated globally. Here, we how these responses are regulated by incorporating putative cis-regulatory elements, known transcription factor binding sites, in vitro DNA affinity purification sequencing, and DNase I hypersensitive sites to predict genes with different wound-response patterns using machine learning. We observed that regulatory sites and regions of open chromatin differed between genes upregulated at early and late wounding time-points as well as between genes induced by jasmonic acid and those not induced. Expanding on what we currently know, we identified cis-elements that improved model predictions of expression clusters over known binding sites. Using a combination of genome editing, in vitro DNA-binding assays, and transient expression assays using native and mutated cis-regulatory elements, we experimentally validated four of the predicted elements, three of which were not previously known to function in wound-response regulation. Our study provides a global model predictive of wound response and identifies new regulatory sequences important for wounding without requiring prior knowledge of the transcriptional regulators.

59 BASIC BIOLOGICAL SCIENCES↗

Adversarial Ensemble Modeling of Multi-modal Mechanical Properties for Iron-Based Alloys

Mechanical properties of alloys are controlled by their microstructure; and microstructure evolution is controlled by internal and external stressors. Chemical complexity during the alloy processing may result in heterogeneity and observation of multimodal performance patterns. Thus, to ensure the desired performance of stressed components it is important to understand the origin and mechanisms of such behavior. Adversarial ensemble modeling was introduced here to explain multimodal mechanical properties of the iron-based alloys. The modeling results showed that the areas of a single mechanism predominance were contiguous across the alloy compositions clustered by similarity, with sharp and persistent boundaries separating the single-mechanism domains. The marginal compositions resulted in increased competition between the adversarial models but only led to the multimodal behavior when the competing models diverged. Transparency of the clustering method allowed explicit interpretation of the chemistries leading to such competition. The adversarial ensemble was interpreted through transition from ductile to brittle microstructure.

36 MATERIALS SCIENCE↗

Design strategies for self-assembly of discrete targets

Both biological and artificial self-assembly processes can take place by a range of different schemes, from the successive addition of identical building blocks to hierarchical sequences of intermediates, all the way to the fully addressable limit in which each component is unique. In this paper, we introduce an idealized model of cubic particles with patterned faces that allows self-assembly strategies to be compared and tested. We consider a simple octameric target, starting with the minimal requirements for successful self-assembly and comparing the benefits and limitations of more sophisticated hierarchical and addressable schemes. Simulations are performed using a hybrid dynamical Monte Carlo protocol that allows self-assembling clusters to rearrange internally while still providing Stokes-Einstein-like diffusion of aggregates of different sizes. Our simulations explicitly capture the thermodynamic, dynamic, and steric challenges typically faced by self-assembly processes, including competition between multiple partially completed structures. Self-assembly pathways are extracted from the simulation trajectories by a fully extendable scheme for identifying structural fragments, which are then assembled into history diagrams for successfully completed target structures. For the simple target, a one-component assembly scheme is most efficient and robust overall, but hierarchical and addressable strategies can have an advantage under some conditions if high yield is a priority.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Local control of defects and switching properties in ferroelectric thin films

Electric-field switching of polarization is the building block of a wide variety of ferroelectric devices. In turn, understanding the factors affecting ferroelectric switching and developing routes to control it are of great technological significance. This research provides systematic experimental evidence of the role of defects in affecting ferroelectric-polarization switching and utilizes the ability to deterministically create and spatially locate point defects in $PbZr_{0.2}Ti_{0.8}O_3$ thin films via focused-helium-ion bombardment and the subsequent defect-polarization coupling as a knob for on-demand control of ferroelectric switching (e.g., coercivity and imprint). At intermediate ion doses ($0.22-2.2×10^{14}\,ions\,cm^{-2}$), the dominant defects (isolated point defects and small clusters) show a weak interaction with domain walls (pinning potentials from $200-500\,K\,MV\,cm^{-1}$), resulting in small and symmetric changes in the coercive field. At high doses ($0.22-1×10^{15}\,ions\,cm^{-2}$), on the other hand, the dominant defects (larger defect complexes and clusters) strongly pin domain-wall motion (pinning potentials from 500 to $1600\,K\,MV\,cm^{-1}$), resulting in a large increase in the coercivity and imprint, and a reduction in the polarization. This local control of ferroelectric switching provides a route to produce novel functions; namely, tunable multiple polarization states, rewritable pre-determined 180° domain patterns, and multiple zero-field piezoresponse and permittivity states. Such an approach opens up pathways to achieve multilevel data storage and logic, nonvolatile self-sensing shape-memory devices, and nonvolatile ferroelectric field-effect transistors.

36 MATERIALS SCIENCE↗

47 Tuc in Rubin Data Preview 1. Exploring Early LSST Data and Science Potential

We present analyses of the early data from Rubin Observatory’s Data Preview 1 (DP1) for the field of the globular cluster 47 Tuc. The DP1 data set for 47 Tuc includes four nights of observations from the Rubin Commissioning Camera (LSSTComCam), covering multiple bands (ugriy). We address challenges of crowding in the inner region of the cluster and toward the SMC in DP1, and demonstrate improved star–galaxy separation by fitting fifth-degree polynomials to the stellar loci in color–color diagrams and applying multidimensional sigma clipping. We compile a catalog of 3576 probable 47 Tuc member stars selected via a combination of isochrone, Gaia proper-motion, and color–color space matched filtering. We explore the sources of photometric scatter in the 47 Tuc color–color sequence, evaluating contributions from various potential sources, including differential extinction within the cluster. Finally, of the 72 well-characterized variables in the field, we recover three known variable stars, including two RR Lyrae and one eclipsing binary, in the coadd-based object catalog, and identify 62 in the difference image-based object catalog. Although the DP1 lightcurves have sparse temporal sampling, they appear to follow the patterns of densely sampled literature lightcurves well. Despite some data limitations for crowded-field stellar analysis, DP1 demonstrates the promising scientific potential for future LSST data releases.

Choi, Yumi [NSF National Optical-Infrared Astronom↗

Assessing the Application of a Genomic Network Analysis in Population Ecology: Inferring Patterns of Dispersal and Geographic Structure in the Emerging Pathogen, Coccidioides

A challenge in population ecology studies is identifying how to best group individuals into populations, especially when individual origin is unknown. Machine learning has improved upon traditional methods of identifying population structure and is more efficient at handling large, complex datasets. We demonstrate the applicability of a machine learning method to identify hierarchical population structure in an emerging pathogen, Coccidioides spp., the causative agent of Valley fever. We compared the network clusters to structure identified by traditional tools as a validation of the network performance. We used publicly available whole-genome data for 48 C. immitis and 102 C. posadasii, resulting in 168,211 genome-wide SNPs among the two species. The network analysis grouped samples into populations comparable to the literature for these species but also identified fine-scale geographic structure and travel-associated cases not reported thus far. Exploring different resolutions in the network made it easy to identify unique genotypes specific to California and possibly Nevada, as well as Phoenix- and Tucson-acquired infections in non-endemic areas, regardless of reported travel history. The present study provides a promising example of how a ML-based network analysis can improve our ability to understand pathogen ecology, group cases into populations and infer travel-associated infections.

59 BASIC BIOLOGICAL SCIENCES↗

On the consistency of Monte Carlo track structure DNA damage simulations

Purpose: Monte Carlo track structures (MCTS) simulations have been recognized as useful tools for radiobiological modeling. However, the authors noticed several issues regarding the consistency of reported data. Therefore, in this work, they analyze the impact of various user defined parameters on simulated direct DNA damage yields. In addition, they draw attention to discrepancies in published literature in DNA strand break (SB) yields and selected methodologies. Methods: The MCTS code Geant4-DNA was used to compare radial dose profiles in a nanometer-scale region of interest (ROI) for photon sources of varying sizes and energies. Then, electron tracks of 0.28 keV–220 keV were superimposed on a geometric DNA model composed of 2.7 × 10{sup 6} nucleosomes, and SBs were simulated according to four definitions based on energy deposits or energy transfers in DNA strand targets compared to a threshold energy E{sub TH}. The SB frequencies and complexities in nucleosomes as a function of incident electron energies were obtained. SBs were classified into higher order clusters such as single and double strand breaks (SSBs and DSBs) based on inter-SB distances and on the number of affected strands. Results: Comparisons of different nonuniform dose distributions lacking charged particle equilibrium may lead to erroneous conclusions regarding the effect of energy on relative biological effectiveness. The energy transfer-based SB definitions give similar SB yields as the one based on energy deposit when E{sub TH} ≈ 10.79 eV, but deviate significantly for higher E{sub TH} values. Between 30 and 40 nucleosomes/Gy show at least one SB in the ROI. The number of nucleosomes that present a complex damage pattern of more than 2 SBs and the degree of complexity of the damage in these nucleosomes diminish as the incident electron energy increases. DNA damage classification into SSB and DSB is highly dependent on the definitions of these higher order structures and their implementations. The authors’ show that, for the four studied models, different yields are expected by up to 54% for SSBs and by up to 32% for DSBs, as a function of the incident electrons energy and of the models being compared. Conclusions: MCTS simulations allow to compare direct DNA damage types and complexities induced by ionizing radiation. However, simulation results depend to a large degree on user-defined parameters, definitions, and algorithms such as: DNA model, dose distribution, SB definition, and the DNA damage clustering algorithm. These interdependencies should be well controlled during the simulations and explicitly reported when comparing results to experiments or calculations.

60 APPLIED LIFE SCIENCES↗

Interpreting the spatial distribution of soil properties with a physically-based distributed hydrological model

Digital soil maps are commonly data-driven as the development of physically-based models for soil mapping is difficult due to the complexity of soils. However, physically-based hydrologic models have been successful in simulating water dynamics. Since water movement is a major driver of pedogenesis, the physical rules that govern water movement might help explain and predict the spatial variation of soil properties. Here, we demonstrate the novel use of a physically-based, distributed hydrologic model to inform the spatial distribution of soil properties. The Distributed Hydrology Soil Vegetation Model (DHSVM) was utilized to simulate soil moisture content (SM) and water table depth (WTD) in two hillslope catchments under pasture and forest management wherein hydrologic model outputs were then compared with soil properties measured in situ. SM sensors and wells were installed in both catchments to validate simulations of soil water movement via Nash-Sutcliffe Efficiency (E). In-situ observations were made at 87 sites within both catchments to study the connection between simulated water movement (SM and WTD) and observed soil properties, namely the depth and thickness of the argillic (Bt), fragic (Btx), and C horizons, and the depth of redoximorphic features. The simulated time series of SM and WTD were also clustered per season using Dynamic Time Warping (DTW), which identified similarity among time series at varying timescales. Model validation suggested that simulations of surficial SM (0–20 cm) were reasonable (E = 0.45), however, simulated subsurface SM (45–60 cm) and WTD were not sufficiently accurate. The thickness of Btx horizons were spatially grouped into different populations by SM clusters from every season except spring. For the other properties, only SM dynamics of specific seasons grouped into significantly different populations, suggesting that the explanatory power of simulated water movement varies seasonally and was greater during winter. Here, we show clusters of simulated SM separated soil properties into statistically different populations, showing that hydrologic models could inform areas that followed different water dynamics related to pedogenic trajectories and related biogeochemical processes not necessarily simulated by the model. As such, physically-based modeling of water dynamics can, therefore, inform and advance digital soil mapping by linking water movement patterns stemming from hydrologic model outputs to spatial patterns of soil properties and pedogenesis.

54 ENVIRONMENTAL SCIENCES↗