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DOE OSTI2020

A meta-analysis of global cropland soil carbon changes due to cover cropping

Including cover crops within agricultural rotations may increase soil organic carbon (SOC). However, contradictory findings generated by on-site experiments make it necessary to perform a comprehensive assessment of interactions between cover crops, environmental and management factors, and changes in SOC. In this study, we collected data from studies that compared agricultural production with and without cover crops, and then analyzed those data using meta-analysis and regression. Our results showed that including cover crops into rotations significantly increased SOC, with an overall mean change of 15.5% (95% confidence interval of 13.8% to 17.3%). Whereas medium-textured soils had highest SOC stocks with (mean = 39 Mg ha-1) and without (mean = 37 Mg ha-1) cover crops, fine-textured soils showed the greatest increase in SOC after the inclusion of cover crops (mean change of 39.5%). Coarse-textured (11.4%) and medium-textured soils (10.3%) had comparatively smaller changes in SOC. Cover crop mixtures resulted in greater increases in SOC compared to mono-species cover crops, and using legumes resulted in greater SOC increases than grasses and broadleaf species. Cover cropping was associated with significant SOC increases in shallow soils (= 30 cm), but not in subsurface soils (> 30 cm). The regression analysis revealed that SOC changes from cover cropping were correlated with improvements in soil quality, specifically decreased runoff and erosion and increased mineralizable carbon, mineralizable nitrogen, and soil nitrogen. Soil carbon change was also affected by annual temperature, number of years after start of cover crop usage, latitude, and initial SOC concentrations. Finally, the mean rate of carbon sequestration from cover cropping across all studies was 0.56 Mg ha-1 yr-1. If 15% of current global cropland were to adopt cover crops, this value would translate to 0.17 Pg of carbon sequestered per year or ~1-2% of current fossil fuels emissions. Altogether, these results indicated that inclusion of cover crops into agricultural rotations can enhance soil carbon concentrations, improve many soil quality parameters, and serve as a potential sink for atmosphere CO2.

Cover crop, soil organic carbon, soil quality, soi↗

DOE OSTI2020

Global biogeography of fungal and bacterial biomass carbon in topsoil

Bacteria and fungi, representing two major soil microorganism groups, play an important role in global nutrient biogeochemistry. Biogeographic patterns of bacterial and fungal biomass are of fundamental importance for mechanistically understanding nutrient cycling. We synthesized 1323 data points of phospholipid fatty acid-derived fungal biomass C (FBC), bacterial biomass C (BBC), and fungi:bacteria (F:B) ratio in topsoil, spanning 11 major biomes. The FBC, BBC, and F:B ratio display clear biogeographic patterns along latitude and environmental gradients including mean annual temperature, mean annual precipitation, net primary productivity, root C density, soil temperature, soil moisture, and edaphic factors. At the biome level, tundra has the highest FBC and BBC densities at 3684 (95% confidence interval: 1678–8084) mg kg -1 and 428 (237–774) mg kg -1 , respectively; desert has the lowest FBC and BBC densities at 16.92 (14.4–19.89) mg kg -1 and 6.83 (6.1–7.65) mg kg -1 , respectively. The F:B ratio varies dramatically, ranging from 1.8 (1.6–2.1) in savanna to 8.6 (6.7–11.0) in tundra. An empirical model was developed for the F:B ratio and it is combined with a global dataset of soil microbial biomass C to produce global maps for FBC and BBC in 0–30 cm topsoil. Across the globe, the highest FBC is found in boreal forest and tundra while the highest BBC is in boreal forest and tropical/subtropical forest, the lowest FBC and BBC are in shrub and desert. Global stocks of living microbial biomass C were estimated to be 12.6 (6.6–16.4) Pg C for FBC and 4.3 (0.5–10.3) Pg C for BBC in topsoil. These findings advance our understanding of the global distribution of fungal and bacterial biomass, which facilitates the incorporation of fungi and bacteria into Earth system models. The global maps of bacterial and fungal biomass serve as a benchmark for validating microbial models in simulating the global C cycle under a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Electrochemical properties of poly(ethylene oxide) electrolytes above the entanglement threshold

The ion transport in electrolytes depends on three transport coefficients, conductivity (κ), salt diffusion coefficient (D), and the cation transference number with respect to the solvent velocity ($t_+^0$), and the thermodynamic factor ($T_f$). Current methods for determining these parameters involve four separate experiments, and the coupled nature of the equations used to determine them generally results in large experimental uncertainty. We present data obtained from 64 independent polymer electrolytes comprising poly(ethylene oxide) (PEO) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt. The molecular weights of PEO ranged from 5 to 275 kg mol -1 ; these samples are all above the entanglement threshold. We minimize the experimental uncertainty in transport and thermodynamic measurements by exploiting the fact that ion transport in entangled polymer electrolytes should be independent of molecular weight. The dependence of $κ, D, t_+^0$, and $T_f$ as a function of salt concentration in the range 0.035 ≤ r ≤ 0.30 are presented with a 95% confidence interval, where r is the molar ratio of lithium ions to ethylene oxide monomer units. While κ, D, and $T_f$ are all positive as required by thermodynamic constraints, there is no constraint on the sign of $t_+^0$. We find that $t_+^0$ is negative in the salt concentration range of 0.093 ≤ r ≤ 0.189.

25 ENERGY STORAGE↗

DOE OSTI2021

Genotoxicity evaluation using primary hepatocytes isolated from rhesus macaque ( Macaca mulatta )

Non-human primates (NHPs) have played a vital role in fundamental, pre-clinical, and translational studies because of their high physiological and genetic similarity to humans. We report a method to isolate primary hepatocytes from the livers of rhesus macaques (Macaca mulatta) after in situ whole liver perfusion. Isolated primary macaque hepatocytes (PMHs) were treated with various compounds known to have different pathways of genotoxicity/carcinogenicity and the resulting DNA damage was evaluated using the high-throughput CometChip assay. The comet data were quantified using benchmark dose (BMD) modeling and the BMD50 values for treatments of PMHs were compared with those generated from primary human hepatocytes (PHHs) in our previous study. The results showed that despite varying CYP450 enzyme activities, PMHs had the same sensitivity and specificity as PHHs in detecting four indirect-acting (i.e., requiring metabolic activation) and seven direct-acting genotoxicants/carcinogens, as well as five non-carcinogens that are negative or equivocal for genotoxicity in vivo. The BMD50 estimates and their confidence intervals revealed species differences for DNA damage potency, especially for direct-acting compounds. The present study provides a practical method for maximizing the use of animal tissues by isolating primary hepatocytes from NHPs. Our data support the use of PMHs as a reliable surrogate of PHHs for evaluating the genotoxic hazards of chemical substances for humans.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Structural response reconstruction using a system-equivalent singular vector basis

Here, this paper develops a novel method for reconstructing the full-field response of structural dynamic systems using sparse measurements. The singular value decomposition is applied to a frequency response matrix relating the structural response to physical loads, base motion, or modal loads. The left singular vectors form a non-physical reduced basis that can be used for response reconstruction with far fewer sensors than existing methods. The contributions of the singular vectors to measured response are termed singular-vector loads (SVLs) and are used in a regularized Bayesian framework to generate full-field response estimates and confidence intervals. The reconstruction framework is applicable to the estimation of single data records and power spectral densities from multiple records. Reconstruction is successfully performed in configurations where the number of SVLs to identify is less than, equal to, and greater than the number of sensors used for reconstruction. In a simulation featuring a seismically excited shear structure, SVL reconstruction significantly outperforms modal FRF-based reconstruction and successfully estimates full-field responses with as few as two uniaxial accelerometers. SVL reconstruction is further verified in a simulation featuring an acoustically excited cylinder. Finally, response reconstruction and uncertainty quantification are performed on an experimental structure with three shaker inputs and 27 triaxial accelerometer outputs.

42 ENGINEERING↗

DOE OSTI2024

The influence of the shock-to-reshock time on the Richtmyer–Meshkov instability in reshock

Experiments on the Richtmyer–Meshkov instability (RMI) in a dual driver vertical shock tube (DDVST) are described. An initially planar, stably stratified membraneless interface is formed by flowing air from above and sulfur hexafluoride from below the interface location using the method of Jones & Jacobs ( Phys. Fluids , vol. 9, issue 1997, 1997, pp. 3078–3085). A random three-dimensional, multi-modal initial perturbation is imposed by vertically oscillating the gas column to produce Faraday waves. The DDVST design generates two shock waves, one originating above and one below the interface, with these shocks having independently controllable strengths and interface arrival times. The shock waves have nominal strengths of $M_L=1.17$ and $M_H=1.18$ for the shock wave originating in the light and heavy gas, respectively, with these strengths chosen to result in arrested bulk interface motion following reshock. The influence of the length of the shock-to-reshock time, as well as the order of shock arrival, on the post-reshock RMI is examined. The mixing layer width grows according to $h\propto t^\theta$ , where $\theta _H=0.36\pm 0.018$ (95 %) and $\theta _L=0.38\pm 0.02$ (95 %) for heavy and light shock first experiments, respectively, indicating no strong dependence on the order of shock wave arrival. Volume integrated specific turbulent kinetic energy (TKE) in the mixing layer versus time is found to decay according to $E_{tot}/\bar {\rho }\propto t^p$ with $p_H=-0.823\pm 0.06$ (95 %) and $p_L=-1.061\pm 0.032$ (95 %) for heavy and light shock first experiments, respectively. Notably, the 95 % confidence intervals do not overlap. Analysis on the influence of the shock-to-reshock time on turbulent length scales, transition criteria, spectra and mixing layer anisotropy are also presented.

Ferguson, Kevin (ORCID:0000000166537482)↗

DOE OSTI2021

Lifetime risk of suicide among survivors of the atomic bombings of Japan

Abstract Aims The long-term physical health effects of the atomic bombings of Hiroshima and Nagasaki are well characterised, but the psychological effects remain unclear. Therefore, we sought to determine whether measures of exposure severity, as indirect measures of psychological trauma arising from exposure to the atomic bombings, are associated with suicide mortality among atomic bomb survivors. Methods The Life Span Study is a prospective cohort study of 93 741 Japanese atomic bomb survivors who were located within 10 km of the hypocentre in Hiroshima or Nagasaki at the time of the bombings in 1945, and 26 579 residents of Hiroshima and Nagasaki who were not in either city at the time of the bombings, matched to survivors on city, sex and age. Measures of exposure severity included: proximity to the hypocentre, type of shielding between the survivor and the blast and self-reported occurrence of acute radiation and thermal injuries. Date of death was obtained from the Japanese National Family Registry system. Cause of death was obtained from death certificates. Adjusted hazard ratios (HRs) were estimated from Cox regression models overall and stratified by sex and age. Results During the 60-year follow-up period (1950–2009), 1150 suicide deaths were recorded among 120 231 participants (23.6 per 100 000 person-years): 510 among 70 092 women (17.2 per 100 000 person-years) and 640 among 50 139 men (33.6 per 100 000 person-years). Overall, there was no association of proximity, type of shielding or the occurrence of acute injuries with suicide mortality. Among those <25 years of age at the time of the bombings, increased suicide risk was observed for survivors outside v . shielded inside any structure (HR: 1.24; 95% confidence interval (CI): 1.03, 1.48; interaction p = 0.054) and for those who reported flash burns (HR: 1.32; 95% CI: 1.00, 1.73; interaction p = 0.025). Sex-stratified analyses indicated that these associations were limited to men. Among women, closer proximity to the hypocentre was associated with a non-significant increase in suicide risk, with a positive association between proximity and suicide risk observed among women <15 years of age (HR: 1.09 per km; 95% CI: 1.00, 1.18; interaction p = 0.067). Conclusions Proximity to the hypocentre, shielding and acute injury presence do not generally appear to influence suicide mortality among atomic bomb survivors. However, heterogeneity may exist by age and sex, with younger survivors potentially more sensitive to psychological trauma. Coupled with other studies, our results suggest the importance of long-term monitoring of mental health among young populations exposed to catastrophic events or mass trauma.

Psychiatry↗

DOE OSTI2020

Methane Emissions from Gathering Compressor Stations in the U.S.

Using results from a nationally representative measurement campaign at 180 gathering compressor stations conducted with nine industry partners, this study estimated emissions for the U.S. gathering sector, where sector-specific emission factors have not been previously available. The study drew from a partner station population of 1705 stations—a significantly larger pool than was available for prior studies. Data indicated that whole gas emission rates from components on gathering stations were comparable to or higher than emission factors utilized by the EPA’s greenhouse gas reporting program (GHGRP) but less than emission factors used for similar components on transmission compressor stations. Field data also indicated that the national population of stations likely has a higher fraction of smaller stations, operating at lower throughput per station, than the data used to develop the per-station emission factor used in EPA’s greenhouse gas inventory (GHGI). This was the first national study to incorporate extensive activity data reported to the GHGRP, including 319 basin-level reports, covering 15,895 reported compressors. Further, combining study emission data with 2017 GHGRP activity data, the study indicated statistically lower national emissions of 1290 [1246–1342] Gg methane per year or 66% [64–69%] of current GHGI estimates, despite estimating 17% [12–22%] more stations than the 2017 GHGI (95% confidence interval). Finally, we propose a replicable method that uses GHGRP activity data to annually update GHGI gathering and boost sector emissions.

03 NATURAL GAS↗

DOE OSTI2023

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM 2.5 ) is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM 2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM 2.5 , and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM 2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM 2.5 -attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM 2.5 (>95 µg/m 3 ). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM 2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sources in South Asia.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2024

Land Resources for Wind Energy Development Requires Regionalized Characterizations

Estimates of the land area occupied by wind energy differ by orders of magnitude due to data scarcity and inconsistent methodology. Here, we developed a method that combines machine learning-based imagery analysis and geographic information systems and examined the land area of 318 wind farms (15,871 turbines) in the U.S. portion of the Western Interconnection. We found that prior land use and human modification in the project area are critical for land-use efficiency and land transformation of wind projects. Projects developed in areas with little human modification have a land-use efficiency of 63.8 ± 8.9 W/m 2 (mean ±95% confidence interval) and a land transformation of 0.24 ± 0.07 m 2 /MWh, while values for projects in areas with high human modification are 447 ± 49.4 W/m 2 and 0.05 ± 0.01 m 2 /MWh, respectively. We show that land resources for wind can be quantified consistently with our replicable method, a method that obviates >99% of the workload using machine learning. To quantify the peripheral impact of a turbine, buffered geometry can be used as a proxy for measuring land resources and metrics when a large enough impact radius is assumed (e.g., >4 times the rotor diameter). Our analysis provides a necessary first step toward regionalized impact assessment and improved comparisons of energy alternatives.

17 WIND ENERGY↗

DOE OSTI2025

Pervaporative Dehydration of 2,3-Butanediol by Dense Poly(vinylidene fluoride) Hollow Fiber Membranes: Parameter Estimation, Process Design, and Technoeconomic Evaluation under Uncertainty

Pervaporation, combined with other separation processes, can effectively remove water from fermentation product streams, making it highly suitable for purifying alcohols like 2,3-butanediol (BDO). In this study, a dense poly(vinylidene fluoride) (PVDF) hollow fiber membrane module prototype was fabricated for BDO dehydration, achieving >0.2 LMH total flux and >95% BDO rejection. With a Markov chain Monte Carlo (MCMC) approach, Bayesian inference was used to quantify the uncertainty of the permeance parameters. A membrane cascade model was developed to scale up a process that purifies a preconcentrated BDO feed (70 wt %) to high purity (90 wt %). Through propagation of the uncertainty of the parameters and sensitivity analyses of the process variables, a cascade design was recommended. Despite data and model limitations, the framework enabled a reliable system analysis and economic evaluation, validated through tight confidence intervals in key process metrics, establishing the foundation for future applications of Bayesian methods in membrane-based processes.

Animal feed↗

DOE OSTI2026

The Reaction of Atomic Hydrogen with an Imine: Direct Kinetic Measurements and Computational Studies

Imines are of interest in the combustion modeling of nitrogen-based fuels such as ammonia, as intermediates in atmospheric oxidation of amines, and may offer a new class of environmentally benign substitutes for perhalogenated reagents. Elementary gas-phase rate constants for the consumption of H atoms by 1,1,1,3,3,3-hexafluoro-2-propanimine were measured over 294–736 K using the laser flash photolysis/atomic resonance fluorescence technique. The results are summarized as 3.0 × 10 –11 exp(−14.5 kJ mol –1 /RT) cm 3 molecule –1 s –1 with a confidence interval of ±13%. These are the first temperature-dependent kinetic experiments on an imine of the form R 2 C═NH and thereby provide the only validation of transition-state modeling for such systems. Several pathways are feasible; comparison of theory and experiment suggests the dominant channel is addition of H atoms to the nitrogen atom. On this basis, the observations are rationalized quantitatively. Computations also yield the thermochemistry of (CF 3 ) 2 CNH, with Δ f H 298 = −1232 kJ mol –1 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Quantifying Errors in Effective Cluster Interactions of Lattice Gas Cluster Expansions

The promise of lattice gas (LG) cluster expansions (CEs) is that they can describe a given system property to any level of accuracy since the orthogonal “cluster basis functions” span the complete space of available configurations. Such an approach can be constructed to an arbitrarily large surface of a finite number of distinct adsorption sites. Unfortunately, this is only true for the case of an ideal, fixed lattice decorated with components at precise lattice points (the lattice “sites”) with no distortions or relaxations subsequently allowed. Since most systems, and surfaces specifically, do not conform to such an ideal set of constraints, errors in LG CEs must be expected or CE convergence severely hampered. Beyond this, numerical errors in the provided data can complicate the proper construction of a truly predictive and/or physically significant CE. In this work, we show here how reliance on typical statistical tools like confidence intervals cannot be expected to provide an accurate representation of the uncertainty of effective cluster interactions (ECIs) in the CE due to the nature of the target ab initio data and the nature of CEs themselves. We develop a method for estimating these errors that does not rely on statistical assumptions about the model or data. We then use these ECI errors to quantify fundamental consequences on the uncertainty of ECIs in CEs built from O/Fe(100) data whose surface and adsorbates have been allowed to relax in a typical manner and from O/Fe(100) data whose surface and adsorbates are fixed in ideal lattice positions. We also quantify the effect of using a different density functional theory exchange–correlation functional, using these ECI errors to assess the significance in any deviations. In both cases, our method is shown to have remarkable utility in the quantification of errors in the ECIs of CEs. While we stick to the lattice gas convention in this work, the method is equally applicable to the Ising convention or, in principle, any linear model of sufficient complexity.

08 HYDROGEN↗

DOE OSTI2020

Bounding Global Aerosol Radiative Forcing of Climate Change

Abstract Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth's radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable, and arguable lines of evidence, including modeling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes constrain the forcing from aerosol‐radiation interactions. A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol‐driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction is less clear, and the influence on mixed‐phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to a 68% confidence interval for the total aerosol effective radiative forcing of ‐1.6 to ‐0.6 W m −2 , or ‐2.0 to ‐0.4 W m −2 with a 90% likelihood. Those intervals are of similar width to the last Intergovernmental Panel on Climate Change assessment but shifted toward more negative values. The uncertainty will narrow in the future by continuing to critically combine multiple lines of evidence, especially those addressing industrial‐era changes in aerosol sources and aerosol effects on liquid cloud amount and on ice clouds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Leaf Trait Plasticity Alters Competitive Ability and Functioning of Simulated Tropical Trees in Response to Elevated Carbon Dioxide

The response of tropical ecosystems to elevated carbon dioxide (CO 2 ) remains a critical uncertainty in projections of future climate. Here, we investigate how leaf trait plasticity in response to elevated CO 2 alters projections of tropical forest competitive dynamics and functioning. We use vegetation demographic model simulations to quantify how plasticity in leaf mass per area and leaf carbon to nitrogen ratio alter the responses of carbon uptake, evapotranspiration, and competitive ability to a doubling of CO 2 in a tropical forest. Observationally constrained leaf trait plasticity in response to CO 2 fertilization reduces the degree to which tropical tree carbon uptake is affected by a doubling of CO 2 (up to -14.7% as compared to a case with no plasticity; 95% confidence interval [CI95%] -14.4 to -15.0). It also diminishes evapotranspiration (up to -7.0%, CI95% -6.4 to -7.7), and lowers competitive ability in comparison to a tree with no plasticity. Consideration of leaf trait plasticity to elevated CO 2 lowers tropical ecosystem carbon uptake and evapotranspirative cooling in the absence of changes in plant-type abundance. However, “plastic” responses to high CO 2 which maintain higher levels of plant productivity, many of which fall outside of the observed range of response, are potentially more competitively advantageous, thus, including changes in plant type abundance may mitigate these decreases in ecosystem functioning. Models that explicitly represent competition between plants with alternative leaf trait plasticity in response to elevated CO 2 are needed to capture these influences on tropical forest functioning and large-scale climate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A data-driven global soil heterotrophic respiration dataset and the drivers of its inter-annual variability

Soil heterotrophic respiration (SHR), one of the primary carbon fluxes from terrestrial ecosystems to the atmosphere, is important for carbon-climate feedbacks because of its sensitivity to available litter and soil carbon, climatic conditions, and nutrient availability. However, until recently limited SHR data were available, and most published global SHR estimates have either a short time span, coarse spatial resolution, or reply on overly-simple model formulations. To better understand and quantify the global distribution of SHR and its sensitivity to climate variability, we produced a new global SHR dataset using Random Forest algorithms, up-scaling 455 point data from the Global Soil Respiration Database (SRDB 4.0) with gridded fields of climatic, edaphic and productivity as explanatory variables. We estimated a global total SHR of 46.8 Pg C yr-1 over 1985-2013 (95% confidence interval: 38.6-56.3 Pg C yr-1), with a significant increasing trend of 0.03 Pg C yr-2 during this period. We found that the choice of soil moisture datasets contributes more to the difference among these data-driven SHR members rather than that of productivity, temperature and precipitation data sources. We also analyzed the influence of climatic variables on the inter-annual variability (IAV) of our SHR product. Water availability was the dominant driver of IAV at global scales, although the inferred sensitivity depends on the choice of the soil moisture gridded dataset. At the ecosystem scale, temperature strongly controls the IAV of SHR in tropical forests, while water availability dominates in extra-tropical forest and semi-arid regions. Our machine-learning gridded SHR dataset and outputs from process-based land surface models (TRENDYv6) show agreement for a strong association between water variability and SHR IAV at the global scale, but the two approaches lead to different temporal trend globally and different controlling variables for IAV at the ecosystem scale. Our study provides evidence for the pervasive and important role of water availability in driving SHR, indicating both a direct effect limiting decomposition rates and an indirect effect through the amount of fresh organic matter made available to SHR from productivity. In consideration of potential limitations and uncertainties remaining in our data-driven SHR datasets, we call for a more scientifically designed observation network for SHR, more observation data compilation, and increased use of deep learning methods making maximum use of observation data in hand. This will benefit process-based models, and improve our understanding of SHR response to future anomalous environmental conditions.

Yao, Yitong↗

DOE OSTI2021

Measuring Fault Zone and Host Rock Hydraulic Properties Using Tidal Responses

Pore pressure diffusion along faults influences induced seismicity and rupture mechanics. In situ hydraulic diffusivity measurements along faults are rare and generally lower than inferred from seismicity migration. Here we use the tidal response of deep geothermal boreholes to measure fault diffusivity and permeability. Initial interpretations of the observation with a homogeneous confined aquifer model result in diffusivities of 10 -3 –10 -1 m 2 /s. However, this model mixes signals from both the conduit and the host rock. We develop a model for tidal response with a fault passing through the aquifer based on the fault-guided fracture network and solve for hydraulic properties in both the fault and the host rock. The resulting fault permeability is 2 × 10 -14 –7 × 10 -14 m 2 (90% confidence interval[CI]) and fault diffusivity is 0.08–0.33 m 2 /s (90% CI), which is 2 orders of magnitude higher than the host rock diffusivity in some wells, thus highlighting the role of faults as fluid conduits.

58 GEOSCIENCES↗

DOE OSTI2021

Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask?

Abstract Estimates of Amazon rainforest gross primary productivity (GPP) differ by a factor of 2 across a suite of three statistical and 18 process models. This wide spread contributes uncertainty to predictions of future climate. We compare the mean and variance of GPP from these models to that of GPP at six eddy covariance (EC) towers. Only one model's mean GPP across all sites falls within a 99% confidence interval for EC GPP, and only one model matches EC variance. The strength of model response to climate drivers is related to model ability to match the seasonal pattern of the EC GPP. Models with stronger seasonal swings in GPP have stronger responses to rain, light, and temperature than does EC GPP. The model to data comparison illustrates a trade‐off inherent to deterministic models between accurate simulation of a mean (average) and accurate responsiveness to drivers. The trade‐off exists because all deterministic models simplify processes and lack at least some consequential driver or interaction. If a model's sensitivities to included drivers and their interactions are accurate, then deterministically predicted outcomes have less variability than is realistic. If a GPP model has stronger responses to climate drivers than found in data, model predictions may match the observed variance and seasonal pattern but are likely to overpredict GPP response to climate change. High or realistic variability of model estimates relative to reference data indicate that the model is hypersensitive to one or more drivers.

54 ENVIRONMENTAL SCIENCES↗