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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June to October 2020)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June to October 2020 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 30 cm depth below surface to just above the cobble layer (~190-250 cm depth) at discrete depths every 40 cm for microbial analyses. A total of 35 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 2848 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (September 2019)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken September 2019 at one locations (OBJ1) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 50 to 150 cm depth below surface at discrete depths every 20 cm for microbial analyses. A total of 6 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 2562 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June 2018)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June 2018 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 50 to 150 cm depth below surface at discrete depths every 20 cm for microbial analyses. A total of 12 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 1233 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from East River floodplain sediments near Crested Butte, CO, USA (June to September 2019)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken in 2019 in June (flooded conditions) and September (drained conditions) at two locations (MCB1 and MCB3) near the Meander C/Pumphouse floodplain sites of the East River. Sediment cores were collected from 2 depths, a near-surface, generally unsaturated depth (30-40 centimeter (cm) depth below surface) and a deeper depth influenced by flooding with redoximorphic features (70-80 cm depth below surface). Sediments were homogenized from the 10 cm core for microbial analyses. A total of 24 metagenomes were sequenced through the Joint genome institute (JGI) corresponding to 8 samples sequenced in triplicate. These metagenomes can be found under Genomes Online Database (GOLD) sequencing project: Gs0141020. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 436 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from East River floodplain sediments near Crested Butte, CO, USA (June to September 2017)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken in 2017 in June (flooded conditions) and September (drained conditions) at two locations (MCB1 and MCB3) in an active meander (Meander C) of the East River. Sediment cores were collected from 2 depths, a near-surface, generally unsaturated depth (15-40 centimeter (cm) depth below surface) and a deeper depth influenced by flooding with redoximorphic features (50-88 cm depth below surface). Sediments were homogenized from the ~10 cm cores for microbial analyses. A total of 24 metagenomes were sequenced through the Joint genome institute (JGI) corresponding to 8 samples sequenced in triplicate. These metagenomes can be found under Genomes Online Database (GOLD) sequencing project: Gs0151851. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 405 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Metagenome-assembled genomes from East River floodplain sediments near Crested Butte, CO, USA (May to September 2018)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken in 2018 in May (flooded conditions) and September (drained conditions) at two locations (MCB1 and MCB3) near the Meander C/Pumphouse floodplain sites of the East River. Sediment cores were collected from 2 depths, a near-surface, generally unsaturated depth (30-40 centimeter (cm) depth below surface) and a deeper depth influenced by flooding with redoximorphic features (70-80 cm depth below surface). Sediments were homogenized from the 10 cm core for microbial analyses. A total of 24 metagenomes were sequenced through the Joint genome institute (JGI) corresponding to 8 samples sequenced in triplicate. These metagenomes can be found under Genomes Online Database (GOLD) sequencing project: Gs0141020. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 478 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hyporheic zone, river, and groundwater metagenome resolved genomes and rpS3 genes in East River Watershed, Colorado USA Summer 2020, 2021

Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from water filter collected across 8 locations along the East River Watershed, CO, and 1 nearby groundwater well. The purpose was to look for connectivity and similarities across the network and to see the impact of the groundwater. As a part of Lawrence Berkeley National Laboratory (LBNL) Watershed Science Focus Area (SFA), we assessed community composition and strain similarities between the sites and we also compared it to previous metagenomic studies within the watershed looking at floodplain (Matheus Carnevali et al. 2021) and hillslope (Lavy et al. 2019) microbiomes. Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from filters across 8 locations during August 2020 and July 2021. This resulted in 32 samples. The groundwater sample was sequenced at UC Berkley's QB3. The other 31 samples were sequenced at University of Maryland. Metagenomes were assembled using four autobinners and the best bins were selected using dasTool. The genomes were dereplicated at 95% with dRep and the subset of winning genomes were manually curated based on visual inspection of taxonomic profile, GC content, coverage, and a set of 51 bacterial single copy genes (BSCG), and 38 archaeal signal copy genes (ASCG). The dataset includes a zip file of 311 genomes (HZ_River_SW_MAGS_Dereplicated_95.zip). The dataset additionally includes a zipped file of ribosomal protein small subunit 3 (rpS3) proteins from the hyporheic zone and river data (rpS3_Proteins_HZ_River.zip), a metadata file used to register associated samples with IGSNs (International Generic Sample Numbers) (samples.csv), a location metadata file (locations.csv). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

DNA↗
DOE OSTI2022

FATES crown damage simulation outputs 2022

This dataset contains outputs from the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) and accompanies the paper "Needham, J.F., Arellano, A., Davies, S.J., Fisher, R.A., Hammer, V., Knox, R., Mitre, D., Muller-Landau, H.C., Zuleta, D., Koven, C.D. Tree crown damage and its effects on forest carbon cycling in a tropical forest, 2022, Global Change Biology". Data are unprocessed netcdf file outputs from simulations that were run to test the effect of a new crown damage module in FATES. Specifically, this data package contains a sensitivity analysis to the carbon cushion parameter damage_Ccushion_ensemble_e1b5bd9_bf013ef_2021-09-02.h0.ensemble.sofar.nc, a sensitivity analysis to the root nitrogen stoichiometry parameter damage_Nstoich_ensemble_e1b5bd9_bf013ef_2021-09-02.h0.ensemble.sofar.nc, a sensitivity analysis to parameters controlling crown damage and recovery damage_recovery_ensemble_e1b5bd9_354f0b0_2021-09-02.h0.ensemble.sofar.nc, and a sensitivity analysis to the number of crown damage bins elm_fates_bci_*_damagebins.Eac53ccb80b-F8f994c29.2022-04-19.elm.h0.fullrun.nc. This data package also contains a high root nitrogen configuration of FATES, including both a control, and a crown damage simulation high_root_N_control_e1b5bd9_354f0b0_2021-09-02.clm2.h0.fullrun.nc and high_root_N_damage_e1b5bd9_354f0b0_2021-09-02.clm2.h0.fullrun.nc. There is an analogous low root nitrogen configuration of FATES, including a control, low_root_N_control_e1b5bd9_bf013ef_2021-09-02.clm2.h0.fullrun.nc a damage only simulation low_root_N_damageonly_e1b5bd9_bf013ef_2021-09-02.clm2.h0.fullrun.nc, a damage plus mortality simulation low_root_N_damage_mort_e1b5bd9_bf013ef_2021-09-02.clm2.h0.fullrun.nc, and a mortality only simulation low_root_N_mort_only_e1b5bd9_ef845c8_2021-09-02.clm2.h0.fullrun.nc. Finally, there is a two PFT simulation in which we test the effect of recovery on competitive dynamics, low_root_N_damage_two_pfts_stoichastic_e1b5bd9_bf013ef_2021-09-10.clm2.h0.fullrun.nc. These simulations test the effect of representing crown damage in FATES, compared with simulations that have an equivalent increase in mortality. Jupyter notebooks to analyse these files can be found at https://github.com/JessicaNeedham/Needham_etal_GCB_2022_FATES_crown_damage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Tree damage and mortality measurements across seven ForestGEO plots in the tropics between Oct 2016 and Mar 2023

Annual records (raw data) on tree survival and structural completeness of 36,524 trees (2,467 species) collected across 29 censuses in seven tropical forests distributed across the Neotropics (Amacayacu, Colombia; Barro Colorado Island (BCI), Panamá; Yasuní, Ecuador) and Asia (Fushan, Taiwan; Huai Kha Khaeng (HKK), Thailand; Khao Chong (KC), Thailand; Pasoh, Malaysia). This dataset was used to compare aboveground biomass loss via damage to living trees relative to total AGB loss (mortality + damage). Variable definitions: site: name of the ForestGEO plot stemID.ams: Unique ID for the stem in the annual mortality surveys (ams) treeID.ams: Unique ID for the tree in the ams date.full.census: date of the previous full census of the plot, format: YYYY-MM-DD dbh.full.census: diameter at the breast height (dbh in mm) measured during the previous full census of the plot home: height of measurement of dbh (in m) meanWD: species-level wood density (g cm-3) date.ams: date of the ams, format: YYYY-MM-DD status: survival status of the tree (A: alive; D: dead; NF: not found; "?": unknown) H_considering_damage: living length of the main axis in meters; provides an estimate of the amount of remaining living tissues along the main axis of the stem (e.g., the height of breakage or the height discounting wood decay) b: the remaining proportion of branch volume within the living length (b∈[0,1]). weights.ind: frequency of the [size class x species] bins within the forest plot relative to their frequency in the sample. Necessary to extrapolate estimates to the whole plot.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Persistent, “Mysterious” Seismoacoustic Signals Reported in Oklahoma State during 2019

Here, we report on the source of seismoacoustic pulses that were observed across the state of Oklahoma (OK) during summer of 2019, and the subject of national media coverage and speculation. Seismic network data collected across four U.S. states and interviews with witnesses to the pulse’s effect on residential structures demonstrate that they were triggered by routine ammunition disposal operations conducted by McAlester Army Ammunition Plant (McAAP). During these operations, conventional explosives destroy obsolete munitions stored in pits through a controlled sequence of electronically timed shots that occur over tens of minutes. Despite noise-abatement efforts that reduce coupling of acoustic energy with air, some lower frequency, subaudible (infrasonic) sound radiates from these shots as discrete pulses. We use nine months of blast log documents, seismic network records, analyst picks, and physical modeling to demonstrate that seismic stations as far as 640 km from McAAP sample these pulses, which record seasonal patterns in stratospheric and tropospheric winds, as well as the dynamic formation of waveguides and shadow zones. Digital short-term average to long-term average detectors that we augment with dynamic thresholds and time-binning operations identify these pulses with a fair probability, when compared with visual observations. Our analyses thereby provide estimates of observation rates for both partial and full sequences of these pulses, as well as single shots. We suggest that disposal operations can exploit existing, composite seismic networks to predict where residents are likely to witness blasting. Crucially, our data also show that dense seismic networks can record multiscale atmospheric processes in the absence of infrasound arrays.

58 GEOSCIENCES↗
DOE OSTI2023

Crowdsourcing Felt Reports Using the MyShake Smartphone App

MyShake is a free citizen science smartphone app that provides a range of features related to earthquakes. Features available globally include rapid postearthquake notifications, live maps of earthquake damage as reported by MyShake users, safety tips, and various educational features. The app also uses the accelerometer in the mobile device to detect earthquake shaking, and to record and submit waveforms to a central archive. In addition, MyShake delivers earthquake early warning alerts in California, Oregon, and Washington. Here, in this study, we compare the felt shaking reports provided by MyShake users in California with the U.S. Geological Survey’s (USGSs) “Did You Feel It?” intensity reports. The MyShake app simply asks, “What strength of shaking did you feel?” and users report on a five-level scale. When the MyShake reports are averaged in spatial or time bins, we find strong correlation with the Modified Mercalli Intensity scale values reported by the USGS based on the DYFI surveys. The MyShake felt reports can therefore contribute to the creation of shaking intensity maps.

58 GEOSCIENCES↗
DOE OSTI2026

Rapid Analyses of Sparse Seismoacoustic Data Reveals the Timing and Size of the Accurate Energetic Systems Explosion

On 10 October 2025 an explosion occurred at a facility operated by Accurate Energetic Systems in Humphreys County, Tennessee. The incident resulted in 16 fatalities and created a debris field over several square kilometers. To address remaining questions about explosion timing and size, we collected about 20 seismic and 19 acoustic records of the blast from sensors up to hundreds of kilometers away. We then deployed 10 distinct physics-based, reduced order models (ROMs) that used validated geological structure and atmospheric conditions from the time of the event, along with observations of body- and surface-wave energy, as well as acoustic overpressure and phase duration. Each ROM predicted either timing, yield estimates, or both. We binned these estimates and their uncertainties according to each ROMs’ assumptions about confinement (aboveground, buried fully coupled, and buried partially coupled) and combined these estimates with other forensic data to conclude that the event occurred as a single, aboveground explosion on 10 December 2025 12:47:50.8 ±0.1 s with a yield equivalent to 11.8 [2.3,16.5] tons of Trinitrotoluene. Our estimates align with the Bureau of Alcohol, Tobacco, Firearms and Explosives inventory reports of 11–13 tons. This multimethod approach demonstrates the use of remotely observed geophysical data to rapidly aid conventional forensic investigations of accidental explosions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Power Plant Water Risk and Adaptive Measures Database

Project objective was to understand water-related constraints affecting conventional powerplant operations, specifically coal-fired power plants. Of concern were threats related to drought and flood affecting both water supply and ability of plant to discharge wastewater. Also of interest were adaptive measures taken to mitigate identified threats. This spreadsheet contains the responses provided by the power plant operators and owners. Data have been "sanitized" (e.g., random plant ID, binned location and generation capacity information) to ensure anonymity of individual power plants.

Adaptive Measures↗
DOE OSTI2025

Describing hadronization via histories and observables for Monte-Carlo event reweighting

We introduce a novel method for extracting a fragmentation model directly from experimental data without requiring an explicit parametric form, called Histories and Observables for Monte-Carlo Event Reweighting (HOMER), consisting of three steps: the training of a classifier between simulation and data, the inference of single fragmentation weights, and the calculation of the weight for the full hadronization chain. We illustrate the use of HOMER on a simplified hadronization problem, a q\bar{q} q q ‾ string fragmenting into pions, and extract a modified Lund string fragmentation function f(z) f ( z ) . We then demonstrate the use of HOMER on three types of experimental data: (i) binned distributions of high-level observables, (ii) unbinned event-by-event distributions of these observables, and (iii) full particle cloud information. After demonstrating that f(z) f ( z ) can be extracted from data (the inverse of hadronization), we also show that, at least in this limited setup, the fidelity of the extracted f(z) f ( z ) suffers only limited loss when moving from (i) to (ii) to (iii). Public code is available at https://gitlab.com/uchep/mlhad.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Higgs production via vector-boson fusion at the LHC

In this article, we summarise the recent experimental measurements and theoretical work on Higgs boson production via vector-boson fusion at the LHC. Along with this, we provide state-of-the-art predictions at fixed order as well as with parton-shower corrections within the Standard Model at 13.6 TeV. The results are presented in the form of multi-differential distributions as well as in the Simplified Template Cross Section bins. All materials and outputs of this study are available on public repositories. Finally, following findings in the literature, recommendations are made to estimate theoretical uncertainties related to parton-shower corrections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Ultra-High-Sensitivity Aerosol Spectrometer (UHSAS) Instrument Handbook

The Ultra-High-Sensitivity Aerosol Spectrometer (UHSAS) (Figure 1) is an optical-scattering, laser-based aerosol particle spectrometer system for sizing particles in the 60 to 1000 nanometer (nm) range [1–3]. The instrument counts particles in up to 100 user-specified sizing bins. The instrument’s laser illuminates particles, which scatter light. The system captures the peak light signals that are generated. These signals are used for particle sizing, since the amount of light scattered correlates strongly with particle size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

UNM High Energy Physics: Task B

The High Altitude Water Cherenkov (HAWC) observatory provides a unique window into the "TeV" gamma-ray universe. HAWC provides an important 1 TeV to 1000 TeV high-mass window for indirect searches for dark matter (DM) annihilation or decay. Additional fundamental physics studies benefit from HAWC's sensitivity to variable and/or transient sources. Such transient sources include: gamma ray bursts (GRBs), temporal studies of super massive black holes (specifically Markarian (Mrk) 421 and 501), and most recently searches for gamma-ray counterparts to PeV neutrino sources (observed by IceCube) and gravitational wave sources (observed by LIGO/Virgo). The UNM (Task B) research program includes leadership of the HAWC detector and of HAWC science. During this final reporting period the UNM group includes Professor John Matthews and graduate student Zhixiang Ren with the research goal focused on the development of analysis tools to enhance the sensitivity of HAWC to <1 TeV, gamma rays. This program began in 2016 with an initial focus to work to resolve known problems with the low energy analysis bins in the HAWC data. In 2017 this evolved to the development of new analysis tools to optimize current HAWC <1 TeV sensitivity as well as how HAWC (or a future HAWC-like detector) could be modified to be significantly more sensitive to <1 TeV gamma rays. In these studies Ren lead the development and evaluation of new HAWC <1 TeV analysis tools and Matthews lead the study of possible experimental modifications to HAWC to improve the <1 TeV sensitivity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems

An environmental model consists of multiple process level sub-models, and each sub-model represents a process that is key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this project develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis to address uncertainty in process models and parameters. The new method yields three process sensitivity indices. The first one is called first-order process sensitivity index, and it is derived as a single summary measure of relative process importance. Evaluating the index is computationally expensive, because it relies in a Monte Carlo scheme that requires thousands and even millions of model executions. To reduce computational cost, this project develops a computationally efficient, quasi Monte Carlo method, and this method is presented in Chapter 2 of this report with and a numerical example for demonstration. The numerical example shows that the results of the quasi Monte Carlo method are substantially close to those of the full Monte Carlo method, but the computational cost of the quasi Monte Carlo method is only 0.7% of that of the full Monte Carlo method. The second index is called total-effect process sensitivity index, and it measures interactions between different processes. Therefore, this sensitivity index includes the first-order process sensitivity index, and can be used to identify influential processes. On the other hand, the total-effect process sensitivity index can also be used to screen non-influential processes. This is demonstrated by two numerical examples using the Sobol-G* functions and groundwater flow models that consider recharge process, geological process, and snowmelt process. The numerical examples shows that the total-effect process sensitivity index is more informative than the first-order process sensitivity. The derivation of the process sensitivity index and the numerical examples are discussed in Chapter 3. Chapter 4 presents two computationally efficient methods for screening non-influential processes to exclude them from further investigation. The two methods are the multi-model difference-based sensitivity (MMDS) analysis method, which can be implemented using the Latin Hypercube Sampling. The second one is the implementation of MMDS method using a binning method. The numerical example for the Sobol-G* function indicates the two methods are capable of identifying non-influential models, and the numerical examples for the groundwater flow and reactive transport show that the two methods are effective for groundwater problems. However, it should be noted that the two methods are numerical approximations, and they can only be used for screening non-influential processes, not for ranking importance of system processes. All the sensitivity analysis methods are implemented by developing python codes, and the codes are in a software called SAMMPY: a python package for process sensitivity analysis under multiple models. The SAMMPY design and structure are discussed in Chapter 5, and the package is released to the public for free download.

54 ENVIRONMENTAL SCIENCES↗