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At least 73 records · Page 4

Data for Approximately 15% of Miscanthus Yield is Lost at Current Commercial Cutting Heights in Iowa

Various works have quantitatively characterized the effects of environmental and management factors on Miscanthus x giganteus Greef et Deu ( mxg ) yield and, therefore, anticipated land requirement per unit production. However, little work has addressed the effects of cutting height, which may significantly contribute to the difference between the standing aboveground biomass at harvest (i.e., biological yield) and harvested yield. This study quantitatively characterized the effect of cutting height using a replicated nitrogen trial of a 5-year-old mxg stand in southeast Iowa and related this information to observations of cutting height in nearby commercial fields. Nitrogen fertilizer did not significantly change the relationship of the stem segment mass to length, and overall, a 1-cm stem segment contributes 0.5% of the total stem biomass within the bottom 44 cm of the stem. This results in an average harvest loss of 15% of the aboveground standing biomass when cutting at 30 cm, typically seen in commercial mxg fields in eastern Iowa. Cutting height should be considered when accurately predicting commercial mxg harvest yields and changes in soil organic carbon in a commercial mxg agroecosystem.

Biomass Analytics↗

Population genomic response to geographic gradients by widespread and endemic fishes of the Arabian Peninsula

Genetic structure within marine species may be driven by local adaptation to their environment, or alternatively by historical processes, such as geographic isolation. The gulfs and seas bordering the Arabian Peninsula offer an ideal setting to examine connectivity patterns in coral reef fishes with respect to environmental gradients and vicariance. The Red Sea is characterized by a unique marine fauna, historical periods of desiccation and isolation, as well as environmental gradients in salinity, temperature, and primary productivity that vary both by latitude and by season. The adjacent Arabian Sea is characterized by a sharper environmental gradient, ranging from extensive coral cover and warm temperatures in the southwest, to sparse coral cover, cooler temperatures, and seasonal upwelling in the northeast. Reef fish, however, are not confined to these seas, with some Red Sea fishes extending varying distances into the northern Arabian Sea, while their pelagic larvae are presumably capable of much greater dispersal. These species must therefore cope with a diversity of conditions that invoke the possibility of steep clines in natural selection. Here, we test for genetic structure in two widespread reef fish species (a butterflyfish and surgeonfish) and eight range-restricted butterflyfishes across the Red Sea and Arabian Sea using genome-wide single nucleotide polymorphisms. We performed multiple matrix regression with randomization analyses on genetic distances for all species, as well as reconstructed scenarios for population subdivision in the species with signatures of isolation. We found that (a) widespread species displayed more genetic subdivision than regional endemics and (b) this genetic structure was not correlated with contemporary environmental parameters but instead may reflect historical events. We propose that the endemic species may be adapted to a diversity of local conditions, but the widespread species are instead subject to ecological filtering where different combinations of genotypes persist under divergent ecological regimes.

59 BASIC BIOLOGICAL SCIENCES↗

Unlocking Solutions: Innovative Approaches to Identifying and Mitigating the Environmental Impacts of Undocumented Orphan Wells in the United States

In the United States, hundreds of thousands of undocumented orphan wells have been abandoned, leaving the burden of managing environmental hazards to governmental agencies or the public. These wells, a result of over a century of fossil fuel extraction without adequate regulation, lack basic information like location and depth, emit greenhouse gases, and leak toxic substances into groundwater. For most of these wells, basic information such as well location and depth is unknown or unverified. Addressing this issue necessitates innovative and interdisciplinary approaches for locating, characterizing, and mitigating their environmental impacts. Our survey of the United States revealed the need for tools to identify well locations and assess conditions, prompting the development of technologies including machine learning to automatically extract information from old records (95%+ accuracy), remote sensing technologies like aero-magnetometers to find buried wells, and cost-effective methods for estimating methane emissions. Notably, fixed-wing drones equipped with magnetometers have emerged as cost-effective and efficient for discovering unknown wells, offering advantages over helicopters and quadcopters. Efforts also involved leveraging local knowledge through outreach to state and tribal governments as well as citizen science initiatives. These initiatives aim to significantly contribute to environmental sustainability by reducing greenhouse gases and improving air and water quality.

54 ENVIRONMENTAL SCIENCES↗

EPC-ES WIPP WAC Appendix A Equivalence Support Measurements 2019-2020

Characterization of low-level waste (LLW) at Los Alamos National Laboratory (LANL) is primarily performed by the Environmental Protection and Compliance - Environmental Stewardship (EPC-ES) Characterization Services team and/or the Nuclear Process Infrastructure (NPI--9) Nuclear Material Support Services team (hereafter referred to as the gamma spectroscopy teams). The gamma spectroscopy teams use portable high-purity germanium (HPGe) detector systems for the nondestructive assay (NDA) characterization of LLW. Controlled-approved procedures and processes for the use of such systems to assay LLW items are currently in place. Additionally, a number of performance studies have been conducted by the gamma spectroscopy teams to support the efficacy and quality of assay results generated by the established NDA process.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

VA-Environmental Determinants of Health’s Software Pipeline Framework

In order to characterize US communities in terms of social and environmental determinants of health (EDH) that affect veterans, the Social and Environmental Determinants of Health (SEDH) project, a collaboration between the Veterans Affairs (VA) Social Department and the Oak Ridge National Laboratory (ORNL), aims to identify, extract, and prepare datasets that include community variables known to be associated with health outcomes in veterans. The EDH project's responsibilities include investigating SEDH data, providing technical documentation for SEDH datasets, and automating the download, extraction, and preparation of the data through the creation of a software pipeline framework.

54 ENVIRONMENTAL SCIENCES↗

Multiple experimental studies of pore structure and mineral grain sizes of the Woodford shale in southern Oklahoma, USA

Pore structure study is an important part of unconventional shale reservoir characterization, since the pore system provides the primary petroleum storage space and fluid flow pathways. Previous studies have suggested that the pore structure is related to the total organic carbon (TOC) content, mineral compositions, and the maturity of the organic matter (OM). However, few studies have focused on the mineral grains, the primary grains being deposited but before cementation, which are the building blocks of shale. Eight Woodford Shale outcrop samples from southern Oklahoma were chosen to study the effects of mineral grain size on the pore structure characterization, using multiple and complementary experimental approaches, including laser diffraction, mineralogy, TOC, pyrolysis, liquid immersion porosimetry, mercury intrusion porosimetry, gas physisorption, (ultra) small angle X-ray scattering, scanning electron microscopy, and spontaneous imbibition. The results from different experiments of eight samples show that the Woodford Shale has the mean mineral grain diameters at 3–6 μm, a wide range of porosity at 3–40% and pore diameters at 50–1,000 nm, and various pore connectivity. Grain size variation was probably caused by the sea-level fluctuation during its deposition, which affect the porosity, pore size distribution, and pore connectivity. With decreasing mineral grain sizes, the porosity tends to increase while the pore connectivity worsens. The results also indicate that OM and carbonates in this low-maturity Woodford Shale could block the pores and decrease the porosity. Coupling with the grain size analyses, the control of depositional environment on grain sizes and subsequent effects on pore structure is identified. The pore structure characteristics over a wide pore-diameter range provided by multiple experiments could improve the understanding of storage space and fluid flow in the Woodford Shale to further increase its petroleum production.

54 ENVIRONMENTAL SCIENCES↗

MAPPRAISER: A massively parallel map-making framework for multi-kilo pixel CMB experiments

Forthcoming cosmic microwave background (CMB) polarized anisotropy experiments have the potential to revolutionize our understanding of the Universe and fundamental physics. The sought-after, tale-telling signatures will be however distributed over voluminous data sets which these experiments will collect. These data sets will need to be efficiently processed and unwanted contributions due to astrophysical, environmental, and instrumental effects characterized and efficiently mitigated in order to uncover the signatures. This poses a significant challenge to data analysis methods, techniques, and software tools which will not only have to be able to cope with huge volumes of data but to do so with unprecedented precision driven by the demanding science goals posed for the new experiments. A keystone of efficient CMB data analysis is solvers of very large linear systems of equations. Such systems appear in very diverse contexts throughout CMB data analysis pipelines, however they typically display similar algebraic structures and can therefore be solved using similar numerical techniques. Linear systems arising in the so-called map-making problem are one of the most prominent and common ones. In this work we present a massively parallel, flexible and extensible framework, comprised of a numerical library, MIDAPACK, and a high level code, MAPPRAISER, which provide tools for solving efficiently such systems. Here, the framework implements iterative solvers based on conjugate gradient techniques: enlarged and preconditioned using different preconditioners. We demonstrate the framework on simulated examples reflecting basic characteristics of the forthcoming data sets issued by ground-based and satellite-borne instruments, executing it on as many as 16,384 compute cores. The software is developed as an open source project freely available to the community at: https://github.com/B3Dcmb/midapack.

79 ASTRONOMY AND ASTROPHYSICS↗

Controls on Stable Methane Isotope Values in Northern Peatlands and Potential Shifts in Values Under Permafrost Thaw Scenarios

Abstract Northern peatlands are a globally significant source of methane (CH 4 ), and emissions are projected to increase due to warming and permafrost loss. Understanding the microbial mechanisms behind patterns in CH 4 production in peatlands will be key to predicting annual emissions changes, with stable carbon isotopes (δ 13 C‐CH 4 ) being a powerful tool for characterizing these drivers. Given that δ 13 C‐CH 4 is used in top‐down atmospheric inversion models to partition sources, our ability to model CH 4 production pathways and associated δ 13 C‐CH 4 values is critical. We sought to characterize the role of environmental conditions, including hydrologic and vegetation patterns associated with permafrost thaw, on δ 13 C‐CH 4 values from high‐latitude peatlands. We measured porewater and emitted CH 4 stable isotopes, pH, and vegetation composition from five boreal‐Arctic peatlands. Porewater δ 13 C‐CH 4 was strongly associated with peatland type, with δ 13 C enriched values obtained from more minerotrophic fens (−61.2 ± 9.1‰) compared to permafrost‐free bogs (−74.1 ± 9.4‰) and raised permafrost bogs (−81.6 ± 11.5‰). Variation in porewater δ 13 C‐CH 4 was best explained by sedge cover, CH 4 concentration, and the interactive effect of peatland type and pH (r 2 = 0.50,p < 0.001). Emitted δ 13 C‐CH 4 varied greatly but was positively correlated with porewater δ 13 C‐CH 4 . We calculated a mixed atmospheric δ 13 C‐CH 4 value for northern peatlands of −65.3 ± 7‰ and show that this value is more sensitive to landscape drying than wetting under permafrost thaw scenarios. Our results suggest northern peatland δ 13 C‐CH 4 values are likely to shift in the future which has important implications for source partitioning in atmospheric inversion models.

Environmental Sciences & Ecology↗

scyjth/biosteam_lca

An agile life cycle assessment (LCA) platform that simultaneously characterize the economic and environmental impacts of biofuels and bioproducts under uncertainty.

Shi, Lynn↗

Transposition of HOPPLA in siRNA-deficient plants suggests a limited effect of the environment on retrotransposon mobility in Brachypodium distachyon

Long terminal repeat retrotransposons (LTR-RTs) are powerful mutagens regarded as a major source of genetic novelty and important drivers of evolution. Yet, the uncontrolled and potentially selfish proliferation of LTR-RTs can lead to deleterious mutations and genome instability, with large fitness costs for their host. While population genomics data suggest that an ongoing LTR-RT mobility is common in many species, the understanding of their dual role in evolution is limited. Here, we harness the genetic diversity of 320 sequenced natural accessions of the Mediterranean grass Brachypodium distachyon to characterize how genetic and environmental factors influence plant LTR-RT dynamics in the wild. When combining a coverage-based approach to estimate global LTR-RT copy number variations with mobilome-sequencing of nine accessions exposed to eight different stresses, we find little evidence for a major role of environmental factors in LTR-RT accumulations in B. distachyon natural accessions. Instead, we show that loss of RNA polymerase IV (Pol IV), which mediates RNA-directed DNA methylation in plants, results in high transcriptional and transpositional activities of RLC_BdisC024 (HOPPLA) LTR-RT family elements, and that these effects are not stress-specific. This work supports findings indicating an ongoing mobility in B. distachyon and reveals that host RNA-directed DNA methylation rather than environmental factors controls their mobility in this wild grass model.

59 BASIC BIOLOGICAL SCIENCES↗

Benthic Kinetic Energy in an Earth System Model and Observations

The benthic layer of the ocean is closely correlated with every upper layer above it. Close analysis of benthic layer stress can yield an accurate depiction of the state of the ocean, as well as the atmosphere above it. Through the use of the Department of Energy’s Energy Exascale Earth System Model (E3SM), we took a look at how these features changed over time in a simulation spanning the historical period from 1958 to 2018 in the Arctic Ocean north of 60° N. Making use of E3SM’s regional refinement capability to place higher resolution in regions of interest, the E3SM-Arctic configuration has ~10 km resolution in the ocean and sea ice components in this region, coarsening up to ~60 km outside of the Arctic (Veneziani et al. 2022). In particular, we narrowly focused on the benthic kinetic energy levels, and how trends changed over time. To validate the fidelity of the E3SM model, we compared model current speed outputs over a 369-day period in the Bering Strait to actual recorded observations during this time period. Our analysis of the benthic kinetic energy mean, standard deviation, and trend throughout this time period can be used to characterize the effects of environmental impacts in the Arctic Ocean.

54 ENVIRONMENTAL SCIENCES↗

Impact of Harvest on Switchgrass Leaf Microbial Communities

Switchgrass is a promising feedstock for biofuel production, with potential for leveraging its native microbial community to increase productivity and resilience to environmental stress. Here, we characterized the bacterial, archaeal and fungal diversity of the leaf microbial community associated with four switchgrass (Panicum virgatum) genotypes, subjected to two harvest treatments (annual harvest and unharvested control), and two fertilization levels (fertilized and unfertilized control), based on 16S rRNA gene and internal transcribed spacer (ITS) region amplicon sequencing. Leaf surface and leaf endosphere bacterial communities were significantly different with Alphaproteobacteria enriched in the leaf surface and Gammaproteobacteria and Bacilli enriched in the leaf endosphere. Harvest treatment significantly shifted presence/absence and abundances of bacterial and fungal leaf surface community members: Gammaproteobacteria were significantly enriched in harvested and Alphaproteobacteria were significantly enriched in unharvested leaf surface communities. These shifts were most prominent in the upland genotype DAC where the leaf surface showed the highest enrichment of Gammaproteobacteria, including taxa with 100% identity to those previously shown to have phytopathogenic function. Fertilization did not have any significant impact on bacterial or fungal communities. We also identified bacterial and fungal taxa present in both the leaf surface and leaf endosphere across all genotypes and treatments. These core taxa were dominated by Methylobacterium, Enterobacteriaceae, and Curtobacterium, in addition to Aureobasidium, Cladosporium, Alternaria and Dothideales. Local core leaf bacterial and fungal taxa represent promising targets for plant microbe engineering and manipulation across various genotypes and harvest treatments. Our study showcases, for the first time, the significant impact that harvest treatment can have on bacterial and fungal taxa inhabiting switchgrass leaves and the need to include this factor in future plant microbial community studies.

59 BASIC BIOLOGICAL SCIENCES↗

Challenges and Practical Solutions for Conducting Structural MARSSIM Surveys in Elevated Radon Environments - 20413

The Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) [1] provides comprehensive guidance for the development and implementation of radiological surveys conducted to demonstrate compliance with a dose- or risk-based cleanup goal during final status survey. The MARSSIM methodology follows an integrated strategy combining direct measurements and sampling to assess uniform residual contamination, and scanning surveys to identify localized areas of elevated activity. Building surveys assessing residual surface contamination present unique challenges from reliance on field measurements that may be subject to less than ideal environmental conditions. Additionally, limited characterization and excessive conservatism incorporated into the conceptual site model may result in derived concentration guideline levels (DCGL) and, as a consequence of relatively inefficient field instrumentation, corresponding attributable count rates generally comparable to background. The presence of elevated ambient radon concentrations and associated progeny deposition both exacerbate these intrinsic survey challenges and introduce a series of technical, logistic, and administrative obstacles that can wreak havoc on the statistical legitimacy of each component of the MARSSIM process. Short-lived radon progeny including polonium-218, lead-214, bismuth-214, and polonium-214 produce excessive alpha and beta radiation that may decrease instrument sensitivity through an increase in background count rates, and, at worst, may result in incorrect survey unit failure through the simulation of residual surface activity. Aside from the obvious solution of exhaustive radon mitigation, the primary objectives are to distinguish between radon progeny deposition and actual surface activity, and collect sufficient defensible data. The following is a technical discussion of the consequences of performing building MARSSIM surveys in the presence of elevated ambient radon atmospheres, conceptual examples, and an overview of practical strategies to minimize the effects of radon interference while collecting sufficient defensible data to complete the survey. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Transportation and Systems Analysis Collaborations in Support of a Federal Consolidated Interim Storage Facility

The U.S. Department of Energy’s Integrated Waste Management (IWM) program under the Office of Nuclear Energy is planning for the future transportation, storage, and eventual disposal of spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from nuclear power plant sites across the United States. To better enable informed decision-making regarding the back end of the nuclear fuel cycle, the IWM program has been sponsoring the development and application of system analysis tools capable of analyzing various options for managing SNF and HLW. With these tools, integrated waste management system (IWMS) architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analyses and assessments typically use these modeling and simulation tools to investigate implications of changes in various assumptions and parameters such as acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, start and stop dates of facilities, etc. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation toolkit that is used for a system-level simulation and analysis focused on SNF management in the United States. An analyst using NGSAM has the ability to define several factors like the number of storage facilities, capacity at each facility, transportation schedules, shipment rates, and other conditions. NGSAM’s primary purpose is to provide a system analyst with capabilities to model the IWMS and gain insights into SNF and HLW management alternatives including the impact of system choices, associated cost estimates, and development of integrated yet flexible approaches. IWM is also developing the Stakeholder Tool for Assessing Radioactive Transportation (START). START is a web-based geospatial tool developed to provide visualization and initial evaluation of transportation options associated with future SNF and HLW shipment planning and operations. This includes characterizing safety, economic, and environmental conditions on and in proximity to shipment origins as well as along prospective transportation routes. Information from the START tool can be presented/shared as maps, graphics, geospatial files, and tabular form to enable easy data representation and export functionality. The system analysis, NGSAM, and START teams had been working closely for several years before formalizing this collaboration. START provides the SNF routing information for use in NGSAM. System analysts use the NGSAM tool to generate results (schedule, costs, infrastructure acquisitions, shipment rates, etc.). Subject-matter experts and system analysts work together to inform how NGSAM should model the waste management system. Specifically, this paper discusses the collaborations between the system analysis, NGSAM, and START teams and their accomplishments over the past year. Some examples of these efforts include calibrating and adding data to the START output files to meet NGSAM needs, gaining a better understanding of START data used in NGSAM, as well as how updates in START data could result in an improved NGSAM analysis. Detailed examples of various tasks that have been performed by the team will be discussed in the full paper. Continued efforts in this direction are expected in the coming years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Transportation and System Analysis Collaborations in Support of a Federal Consolidated Interim Storage Facility

The U.S. Department of Energy’s Integrated Waste Management (IWM) program under the Office of Nuclear Energy is planning for the future transportation, storage, and eventual disposal of spent nuclear fuel (SNF) and high-level radioactive waste (HLW) from nuclear power plant and waste custodian sites across the United States. To better enable informed decision-making regarding the back end of the nuclear fuel cycle, the IWM program has been sponsoring the development and application of system analysis tools capable of analyzing various options for managing SNF and HLW. With these tools, integrated waste management system (IWMS) architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). System analyses and assessments typically use these modeling and simulation tools to investigate implications of changes in various assumptions and parameters such as acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, start and stop dates of facilities, etc. The Next Generation System Analysis Model (NGSAM) is an agent-based simulation toolkit that is used for a system-level simulation and analysis focused on SNF management in the United States. NGSAM’s primary purpose is to provide a system analyst with capabilities to model the IWMS and gain insights into SNF and HLW management alternatives including the impact of system choices, associated cost estimates, and development of integrated yet flexible approaches. An analyst using NGSAM can define several factors like the number of storage facilities, capacity at each facility, transportation schedules, shipment rates, and other conditions. IWM is also developing the Stakeholder Tool for Assessing Radioactive Transportation (START). START is a web-based geospatial tool developed to provide the visualization and initial evaluation of transportation options associated with future SNF and HLW shipment planning and operations. This includes characterizing safety, economic, and environmental conditions at and in proximity to shipment origins as well as along prospective transportation routes. Information from the START tool can be presented/shared as maps, graphics, geospatial files, and tabular form to enable easy data representation and export functionality. The system analysis, NGSAM, and START teams have been working closely for several years before formalizing this collaboration. START provides the SNF transportation routing information for use in NGSAM. System analysts use the NGSAM tool to generate results (schedule, costs, infrastructure acquisitions, shipment rates, etc.). Subject-matter experts and system analysts work together to inform how NGSAM should model the waste management system. Specifically, this paper discusses the collaborations between the system analysis, NGSAM, and START teams and their accomplishments over the past year. Some examples of these efforts include calibrating and adding data to the START output files to meet NGSAM needs, gaining a better understanding of START data used in NGSAM as well as how updates in START data could result in an improved NGSAM analysis. Detailed examples of various tasks that have been performed by the team will be discussed in the full paper. Continued efforts in this direction are expected in the coming years.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Biomolecular and Characterization Imaging Science Program: 2023 Principal Investigator Meeting Proceedings

The 2023 U.S. Department of Energy (DOE) Biological and Environmental Research (BER) program’s Biomolecular Characterization and Imaging Science (BCIS) Principal Investigator Meeting expanded in scope from previous Bioimaging Science Program (BSP) meetings to include BER Structural Biology and Imaging Resources, which are located largely at DOE Office of Science national laboratories. The BCIS meeting was part of BER’s Biological Systems Science Division (BSSD) annual PI meeting, which was held April 17–19, 2023, and featured parallel meetings of the BCIS and Genomic Science programs (GSP). The meetings were held together to encourage networking and idea exchange across technologies and biological application areas, forging new multidisciplinary collaborations among researchers from adjacent BSSD programmatic areas. Two joint BCIS-GSP sessions were held: “BCIS Technologies for Investigating the Rhizosphere” and “Joint Emerging Topics and Technologies.” The rhizosphere session focused on scientific findings from BCIS and GSP PIs, including national laboratory collaborations. The intent was to identify new opportunities to measure and understand the complex community of microbes, roots, and soils that support plant growth under challenging environmental conditions. The emerging technologies session highlighted forward-looking approaches and tools to tackle challenges within the scope of BSSD research on investigating and modifying genomic and molecular function. A final interactive discussion of the BCIS program was led by plenary session chairs.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Intelligence-Centered System for Automated Characterization of Functional Materials and Interfaces

Classic design of experiment relies on a time-intensive workflow that requires planning, data interpretation, and hypothesis building by experienced researchers. Here, in this paper, we describe an integrated, machine-intelligent experimental system which enables simultaneous dynamic tests of electrical, optical, gravimetric, and viscoelastic properties of materials under a programmable dynamic environment. Specially designed software controls the experiment and performs on-the-fly extensive data analysis and dynamic modeling, real-time iterative feedback for dynamic control of experimental conditions, and rapid visualization of experimental results. The system operates with minimal human intervention and enables time-efficient characterization of complex dynamic multifunctional environmental responses of materials with simultaneous data processing and analytics. The system provides a viable platform for artificial intelligence (AI)-centered material characterization, which, when coupled with an AI-controlled synthesis system, could lead to accelerated discovery of multifunctional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian Poroelastic Aquifer Characterization From InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate

Characterizing the properties of groundwater aquifers is essential for predicting aquifer response and managing groundwater resources. In this work, we develop a high-dimensional scalable Bayesian inversion framework governed by a three-dimensional quasi-static linear poroelastic model to characterize lateral permeability variations in groundwater aquifers. In this work, we determine the maximum a posteriori (MAP) point of the posterior permeability distribution from centimeter-level surface deformation measurements obtained from Interferometric Synthetic Aperture Radar (InSAR). The scalability of our method to high parameter dimension is achieved through the use of adjoint-based derivatives, inexact Newton methods to determine the MAP point, and a Mat´ern class sparse prior precision operator. Together, these guarantee that the MAP point is found at a cost, measured in number of forward/adjoint poroelasticity solves, that is independent of the parameter dimension. We apply our methodology to a test case for a municipal well in Mesquite, Nevada, in which InSAR and GPS surface deformation data are available. We solve problems with up to 320,824 state variable degrees of freedom (DOFs) and 16,896 parameter DOFs. A consistent treatment of noise level is employed so that the aquifer characterization result does not depend on the pixel spacing of surface deformation data. Our results show that the use of InSAR data significantly improves characterization of lateral aquifer heterogeneity, and the InSAR-based aquifer characterization recovers complex lateral displacement trends observed by independent daily GPS measurements.

54 ENVIRONMENTAL SCIENCES↗