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Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snowpack evolution now support a range of drought indicators that better reflect coupled water, energy, and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity, and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

Christa D Peters-lidard↗

NASA NTRS2022

Noninvasive Indicators of Intracranial Pressure Before, During, and After Long-Duration Spaceflight

Weightlessness induces a cephalad shift of blood and cerebrospinal fluid that may increase intracranial pressure (ICP) during spaceflight, while lower body negative pressure (LBNP) may provide an opportunity to caudally redistribute fluids and lower ICP. To investigate the effects of spaceflight and LBNP on noninvasive indicators of ICP (nICP), we studied thirteen crewmembers before and after spaceflight in seated, supine, and 15° head-down tilt postures, and at ~45 and ~150 days of spaceflight with and without 25 mmHg LBNP. We used 4 techniques to quantify nICP: cerebral and cochlear fluid pressure (CCFP), otoacoustic emissions (OAE), ultrasound measures of optic nerve sheath diameter (ONSD), and ultrasound-based internal jugular vein pressure (IJVp). On flight day 45, two nICP measures were lower than preflight supine posture (CCFP: mean difference -98.5 -nl [CI: -190.8 to -6.1 -nl], p = 0.037]; OAE: -19.7 degrees [CI: -10.4 to -29.1 degrees], p < 0.001), but not significantly different from preflight seated measures. Conversely, ONSD was not different than any preflight posture, whereas IJVp was significantly greater than preflight seated measures (14.3 mmHg [CI: 10.1 to 18.5mmHg], p < 0.001), but not significantly different than preflight supine measures. During spaceflight, acute LBNP application did not cause a significant change in nICP indicators. These data suggest that during spaceflight nICP is not elevated above values observed in the seated posture on Earth. Invasive measures would be needed to provide absolute ICP values and more precise indications of ICP change during various phases of spaceflight.

Jessica V. Jasien↗

NASA NTRS2022

Lightning Over Central Canada: Skill Assessment for Various Land-Atmosphere Model Configurations and Lightning Indices Over a Boreal Study Area

Current lightning predictions are uncertain because they rely on empirical diagnostic relationships and often use coarse-scale climate scenario simulations in which deep convection is parameterized. Previous studies demonstrated that simulations with convection permitting resolutions improve lightning predictions compared to coarser-grid simulations using convection parameterizations for different geographical locations but not over the boreal zone. In this study, lightning simulations with the NASA Unified-Weather Research and Forecasting (NU-WRF) model are evaluated over a domain including the Great Slave Lake in Canada, for six lightning seasons. The simulations are performed at convection parameterized (9 km) and convection-permitting (3 km) resolution using the Goddard 4ICE and the Thompson microphysics schemes. Four lightning indices are evaluated against observations from the Canadian Lightning Detection Network, in terms of spatiotemporal frequency distribution, spatial pattern, daily climatology, and an event-based overall skill assessment. The Thompson scheme is, regardless of the spatial resolution, superior to the Goddard 4ICE scheme in predicting daily climatology but worse in predicting the spatial patterns of lightning occurrence. Results indicate that lightning estimation benefits from modeling at convection-permitting resolution, in particular for the ice based lightning indices. In contrast, the product of convective available potential energy and precipitation rate proved to be the most robust index that was largely invariant to varying spatial resolution. Finally, this study reveals issues of the models to reproduce the observed spatial pattern of lightning well, which might be related to an insufficient representation of land surface heterogeneity, including peatlands, in the study area.

Jonas Mortelmans↗

NASA NTRS2023

Modeling Global Indices for Estimating Non-Photosynthetic Vegetation Cover

Non-photosynthetic vegetation (NPV) includes plant litter, senesced leaves, and crop residues. NPV plays an essential role in terrestrial ecosystem processes, and is an important indicator of drought severity, ecosystem disturbance, agricultural resilience, and wildfire danger. Current moderate spatial resolution multispectral satellite systems (e.g., Landsat and Sentinel-2) have only a single band in the 2000–2500 nm shortwave infrared “SWIR2” range where non-pigment biochemical constituents of NPV, including cellulose and lignin, have important spectral absorption features. Thus, these current systems have suboptimal capabilities for characterizing NPV cover. This research used simulated spectral mixtures accounting for variability among NPV and soils to evaluate globally-appropriate hyperspectral and multispectral indices for estimation of fractional NPV cover. The Continuum Interpolated NPV Depth Index (CINDI), a weighted ratio index measuring lignocellulose absorption near 2100 nm, was found to produce the lowest error in estimating NPV cover. CINDI was less sensitive to variability in soil spectra and green vegetation cover than competing indices. While CINDI was sensitive to the relative water content of soil and NPV, this sensitivity allowed for correcting error in estimated NPV cover as water content increased. CINDI bands were less capable than Dual Absorption NPV Index (DANI) bands for maintaining continuity with the heritage Landsat SWIR2 band, but combining multiple CINDI bands demonstrated adequate continuity. Three SWIR2 bands with band centers at 2038, 2108, and 2211 nm can provide superior capabilities for future moderate resolution multispectral/superspectral systems targeting NPV monitoring, including the next generation Landsat mission (Landsat Next). These bands and the associated CINDI index provide potential for global NPV monitoring using a constellation of future superspectral sensors and imaging spectrometers, with applications including improving soil management, preventing land degradation, evaluating impacts of drought, mapping ecosystem disturbance, and assessing wildfire danger.

Index optimization↗

DOE OSTI2021

Analysis of Lobe Power Calculator and Indication System with Physics and Cycle Based Models

The Advanced Test Reactor (ATR) at INL measures reactor power through two methods, thermal and Nitrogen-16 (N-16) activity. Water power calculator (WPC) is a thermal power system that measures flow and temperature to determine the thermal quadrant powers. The N-16 system utilizes a beta chamber detector that outputs reactivity levels to calculate lobe power through an algorithm called lobe power calculation and indication system (LPCIS). The LPCIS utilizes the N-16 system and the WPC system to determine reactor core power levels. The WPC provides accurate calculations of quadrant and total reactor thermal power. With the use of WPC measurements, thermal-to-N-16 (T2N) power ratios are produced to determine if the two indication systems agree on core power. Relative magnitude equations are used to utilize N-16 coefficients and multipliers to improve the indications of the LPCIS. This is crucial for maintaining safety limits. Currently, the LPCIS system uses linear equations and matrices to calculate lobe power through multipliers and coefficients. Advancements in technology and system upgrades have assisted system engineers at INL with the objective to reach a more dynamic system. In return the system demonstrates an increase in the accuracy of power reading while maintaining safety margins. The new proposed coefficient and multiple method implements a cycle specific, and a physics-based model intended for changing coefficients during operation. This calibration experiment focuses on power splitting, outer shim and neck shim, as well as fuel burning into the RDAS weighting factors. Results show that the Physics learning method yields a smaller error margin inside of the desired power range for the data set 166-A. This proved true for both constrained and unconstrained testing. This is most likely due to the physics data fitting approach that resulted in favorable coefficients and multipliers for 166-A. Continuing to improve the physics-based model will help improve the power accuracy of the LPCIS system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2025

Indicators of carbon alteration (ICAs) suggest patterns in reservoir methane emissions

Reservoir operations influence emissions via multiple causal pathways. In this paper, we quantify indicators of carbon alteration (ICAs) focused on methane. ICAs were chosen to reflect the potential for methane emission along four causal pathways: 1) water column mixing, 2) wet-dry cycles in sediment, 3) sediment redistribution, and 4) vegetation. We developed algorithms to calculate ICAs for three reservoirs along a longitudinal gradient in the Tennessee River basin of the southeast US. The ICAs revealed interesting longitudinal patterns. Indicators of both methane production and destruction increased downstream. The potential for ebullitive methane emissions driven by sub-daily water level fluctuations and emissions mediated by vegetation were higher in downstream mainstem reservoirs than in the upstream tributary reservoir. Along the remaining two pathways, longitudinal patterns were equivocal (sediment pathway) or suggested decreased emissions downstream (water-column mixing). We also observed seasonal patterns and, by combining ICAs, inferred times when ramping could be achieved with lower risk of emissions. The ICAs demonstrated here are the first step in quantifying mechanistic relationships between reservoir operation and methane emissions. In future, they may lead to improved operations in reservoir cascades and regional-scale estimates of emissions that account for differences among reservoirs.

Greenhouse gases↗

DOE OSTI2022

Diurnal and Seasonal Dynamics of Solar-Induced Chlorophyll Fluorescence, Vegetation Indices, and Gross Primary Productivity in the Boreal Forest

Remote sensing of solar-induced chlorophyll fluorescence (SIF) provides a powerful proxy for gross primary productivity (GPP). It is particularly promising in boreal ecosystems where seasonal downregulation of photosynthesis occurs without significant changes in canopy structure or chlorophyll content. The use of SIF as a proxy for GPP is complicated by inherent non-linearities due to both physical (illumination effects) and ecophysiological (light use efficiencies) controls at fine spatial (tower/leaf) and temporal (half-hourly) scales. Here, to study the SIF-GPP relationship, we investigated the diurnal and seasonal dynamics of continuous tower-based measurements of SIF, GPP, and common vegetation indices at the Southern Old Black Spruce Site (SOBS) in Saskatchewan, CA over the course of two years. We find that SIF outperforms other vegetation indices as a proxy for GPP at all temporal scales but shows a non-linear relationship with GPP at a half-hourly resolution. At small temporal scales, SIF and GPP are predominantly driven by light and non-linearity between SIF and GPP is due to the light saturation of GPP. Averaged over daily and monthly scales, the relationship between SIF and GPP is linear due to a reduction in the observed PAR range. Seasonal changes in the light responses of SIF and GPP are driven by changes in light use efficiency which co-vary with changes in temperature, while illumination and canopy structure partially linearize the SIF-GPP relationship. Additionally, we find that the SIF-GPP relationship has a seasonal dependency. Our results help clarify the utility of SIF for estimating carbon assimilation in boreal forests.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Tamper-Indicating Enclosures with Visually Obvious Tamper Response

Sandia National Laboratories is developing a way to visualize molecular changes that indicate penetration of a tamper-indicating enclosure (TIE). Such "bleeding" materials (analogous to visually obvious, colorful bruised skin that doesn't heal) allows inspectors to use simple visual observation to readily recognize that penetration into a material used as a TIE has been attempted, without providing adversaries the ability to repair damage. Such a material can significantly enhance the current capability for TIEs, used to support treaty verification regimes. Current approaches rely on time-consuming and subjective visual assessment by an inspector, external equipment, such as eddy current or camera devices, or active approaches that may be limited due to application environment. The complexity of securing whole volumes includes: (1) enclosures that are non-standard in size/shape; (2) enclosures that may be inspectorate- or facility-owned; (3) tamper attempts that are detectable but difficult or timely for an inspector to locate; (4) the requirement for solutions that are robust regarding reliability and environment (including facility handling); and (5) the need for solutions that prevent adversaries from repairing penetrations. The approach is based on a transition metal ion solution within a microsphere changing color irreversibly when the microsphere is ruptured. Investigators examine 3D printing of the microspheres as well as the spray coating formulation. The anticipated benefits of this work are passive, flexible, scalable, cost-effective TIEs with obvious and robust responses to tamper attempts. This results in more efficient and effective monitoring, as inspectors will require little or no additional equipment and will be able to detect tamper without extensive time-consuming visual examination. Applications can include custom TIEs (cabinets or equipment enclosures), spray-coating onto facility-owned items, spray-coating of walls or structures, spray-coatings of circuit boards, and 3D-printed seal bodies. The paper describes research to-date on the sensor compounds and microspheres.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2024

Customer-Focused Key Performance Indicators for Electric Vehicle Charging

To systematically improve the public charging experience, EV charging industry stakeholders need to define and measure it precisely. Many stakeholders currently measure aspects of the charging experience, but they typically employ metrics that are either operational in nature, such as charger uptime and mean time between failures, or composite customer satisfaction indices. To improve the customer experience most effectively, the industry needs metrics that define the charging experience from the perspective of the customer, not business operations. Furthermore, industry practitioners need granular metrics to know what specific aspects of the charging experience need improvement. This report defines such customer-focused metrics, called key performance indicators (KPIs).

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Implementation Guide of Customer-Focused Key Performance Indicators for Electric Vehicle Charging

This report describes how individual and unique messages that are sent over in OCPP sessions and/or transactions are used to calculate the interim set of key performance indicators (KPI) established by ChargeX Consortium’s Working Group 1: Defining the Charging Experience in the report entitles “Customer-Focused Key Performance Indicators for Electric Vehicle Charging.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Implementation Guide of Customer-Focused Key Performance Indicators for Electric Vehicle Charging

33 - ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Customer-Focused Key Performance Indicators for Electric Vehicle Charging

33 - ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2018

A Comparison of Satellite Data-Based Drought Indicators in Detecting the 2012 Drought in the Southeastern US

The drought of 2012 in the North America devastated agricultural crops and pastures, further damaging agriculture and livestock industries and leading to great losses in the economy. The drought maps of the United States Drought Monitor (USDM) and various drought monitoring techniques based on the data collected by the satellites orbiting in space such as the Gravity Recovery and Climate Experiment (GRACE) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are inter-compared during the 2012 drought conditions in the southeastern United States. The results indicated that spatial extent of drought reported by USDM were in general agreement with those reported by the MODIS-based drought maps. GRACE-based drought maps suggested that the southeastern US experienced widespread decline in surface and root-zone soil moisture and groundwater resources. Disagreements among all drought indicators were observed over irrigated areas, especially in Lower Mississippi region where agriculture is mainly irrigated. Besides, we demonstrated that time lag of vegetation response to changes in soil moisture and groundwater partly contributed to these disagreements, as well.

drought indicators↗

DOE OSTI2020

Using yttrium as an indicator to estimate total rare earth element concentration: a case study of anthracite-associated clays from northeastern Pennsylvania

Abstract This study demonstrated using yttrium (Y) as an indicator to estimate the total rare earth element and Y contents (REY) in coal-associated samples and to facilitate selection of samples with high REY assays in a fast and inexpensive manner. More than 10 anthracite-associated samples were collected from each of three Pennsylvanian sites (sites B, J and C) based on Thorium gamma ray logging suggesting high REY content. Several samples from each site were analyzed by ICP-MS to determine the rare earth distribution patterns and to establish the site-specific linear equations of Y and REY. The Y contents of the remaining samples were measured by a portable X-ray fluorescence analyzer, and the REY values were estimated based on the site-specific linear equation developed earlier. R-squared values above 0.70 were obtained for all the estimation equations from all three sites on both a whole sample basis and an ash basis. Previously, ash content has been widely used as an indicator of high REY content. This may not be applicable for a specific site. Site B in this study is an example where ash contents could not be statistically correlated with REY, so using Y for estimation is more applicable. The demonstrated sample screening process is suitable for samples from sites that share more similar distribution patterns (either MREY or LREY or HREY) as well as for samples from sites that share multiple distribution patterns (LREY/MREY/HREY) depending on the desirable accuracy. The demonstrated process lowers the analytical cost from $70 to 80 dollars per sample to $10–15 per sample while significantly reducing the processing time and acid consumption for ICP digestion. This is particularly true when a relatively large sample size is involved, for example, 100 samples from one site analyzed by ICP-MS/OES.

Yang, Xiaojing↗

DOE OSTI2022

Multi-site assessment of the potential of fine resolution red-edge vegetation indices for estimating gross primary production

Gross primary production (GPP) models driven by fine resolution remote sensing data characterize the spatial and temporal heterogeneities in plant photosynthesis, which is largely dependent on biome-specific maximum photosynthetic capacity. The red-edge reflectance, sensitive to leaf chlorophyll content, is a good proxy of maximum photosynthetic capacity. More importantly, studies show that the red-edge reflectance-related chlorophyll content index (CIr) multiplied by the incident photosynthetic active radiation (PAR in ) strongly correlates to GPP estimated at carbon flux towers (GPP flux ). Yet, to the best of our knowledge, there is no systematic study investigating the general relationship between fine spatial resolution CIr and GPP among biomes and the relationship between CIr and maximum photosynthetic capacity in GPP models. To provide an overview on incorporating space-borne CIr into a GPP model, we applied fine resolution Sentinel-2-derived CIr and GPP flux over 57 flux sites representative of 10 biomes. We investigated the relationship between CIr and GPP flux , and the spatio-temporal relationship between CIr and ecosystem maximum photosynthetic capacity indicated by the potential ecosystem light use efficiency (LUE pot ). We also evaluated the relationship between other five vegetation indices (VIs) and GPP flux . Results showed that the CIr multiplied by PARin has a higher agreement (R 2 > 0.5) with GPP than other VIs. A universal relationship exists between the CIr multiplied by PARin and GPP, except for forest biomes. The CIr also strongly (R 2 > 0.5) relates to the LUE pot during the peak of the growing season. The CIr has a low spatial variance (CV = 0.25) among biomes, highlighting that CIr can be a proxy of maximum photosynthetic capacity in GPP models that do not require biome-dependent coefficients. This study provides insight for incorporating CIr into GPP models and better quantifying global terrestrial photosynthesis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Lacustrine leaf wax hydrogen isotopes indicate strong regional climate feedbacks in Beringia since the last ice age

The Late-Quaternary climate of Beringia remains unresolved despite the region's role in modulating glacial-interglacial climate and as the likely conduit for human dispersal into the Americas. In this work, we investigate Beringian temperature change using an ~32,000-year lacustrine record of leaf wax hydrogen isotope ratios (δ2Hwax) from Arctic Alaska. Based on Monte Carlo iterations accounting for multiple sources of uncertainty, the reconstructed summertime temperatures were ~3 °C colder (range: –8 to +3 °C) during the Last Glacial Maximum (LGM; 21-25 ka) than the pre-industrial era (PI; 2–0.1 ka). This ice-age summer cooling is substantially smaller than in other parts of the Arctic, reflecting altered atmospheric circulation and increased continentality which weakened glacial cooling in the region. Deglacial warming was punctuated by abrupt events that are largely synchronous with events seen in Greenland ice cores that originate in the North Atlantic but which are also controlled locally, such as by the opening of the Bering Strait between 13.4 and 11 ka. Our reconstruction, together with climate modeling experiments, indicates that Beringia responds more strongly to North Atlantic freshwater forcing under modern-day, open-Bering Strait conditions than under glacial conditions. Furthermore, a 2 °C increase (Monte Carlo range: –1 to +5 °C) over the anthropogenic era reverses a 6 °C decline (Monte Carlo range: –10 to 0 °C) through the Holocene, indicating that recent warming in Arctic Alaska has not surpassed peak Holocene summer warmth.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Prevalence of Americans reporting a family history of cancer indicative of increased cancer risk: Estimates from the 2015 National Health Interview Survey

The collection and evaluation of family health history in a clinical setting presents an opportunity to discuss cancer risk, tailor cancer screening recommendations, and identify people with an increased risk of carrying a pathogenic variant who may benefit from referral to genetic counseling and testing. National recommendations for breast and colorectal cancer screening indicate that men and women who have a first-degree relative affected with these types of cancers may benefit from talking to a healthcare provider about starting screening at an earlier age and other options for cancer prevention. The prevalence of reporting a first-degree relative who had cancer was assessed among adult respondents of the 2015 National Health Interview Survey who had never had cancer themselves (n = 27,999). We found 35.6% of adults reported having at least one first-degree relative with cancer at any site. Significant differences in reporting a family history of cancer were observed by sex, age, race/ethnicity, educational attainment, and census region. Nearly 5% of women under age 50 and 2.5% of adults under age 50 had at least one first-degree relative with breast cancer or colorectal cancer, respectively. We estimated that 5.8% of women had a family history of breast or ovarian cancer that may indicate increased genetic risk. A third of U.S. adults who have never had cancer report a family history of cancer in a first-degree relative. Furthermore, this finding underscores the importance of using family history to inform discussions about cancer risk and screening options between healthcare providers and their patients.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

13 C ENDOR Characterization of the Central Carbon within the Nitrogenase Catalytic Cofactor Indicates That the CFe 6 Core Is a Stabilizing “Heart of Steel”

Substrates and inhibitors of Mo-dependent nitrogenase bind and react at Fe ions of the active-site FeMo-cofactor [7Fe–9S–C–Mo–homocitrate] contained within the MoFe protein α-subunit. The cofactor contains a CFe 6 core, a carbon centered within a trigonal prism of six Fe, whose role in catalysis is unknown. Targeted 13 C labeling of the carbon enables electron-nuclear double resonance (ENDOR) spectroscopy to sensitively monitor the electronic properties of the Fe–C bonds and the spin-coupling scheme adopted by the FeMo-cofactor metal ions. Here this report compares 13 CFe 6 ENDOR measurements for (i) the wild-type protein resting state (E 0 ; α-Val 70 ) to those of (ii) α-Ile 70 , (iii) α-Ala 70 -substituted proteins; (iv) crystallographically characterized CO-inhibited “hi-CO” state; (v) E 4 (4H) Janus intermediate, activated for N 2 binding/reduction by accumulation of 4[ e– /H + ]; (vi) E 4 (2H)* state containing a doubly reduced FeMo-cofactor without Fe-bound substrates; and (vii) propargyl alcohol reduction intermediate having allyl alcohol bound as a ferracycle to FeMo-cofactor Fe6. All states examined, both S = 1/2 and 3/2 exhibited near-zero 13 C isotropic hyperfine coupling constants, $^Ca$ = [-1.3 ↔ +2.7] MHz. Density functional theory computations and natural bond orbital analysis of the Fe-C bonds show that this occurs because a (3 spin-up/3 spin-down) spin-exchange configuration of CFe 6 Fe-ion spins produces cancellation of large spin-transfers to carbon in each Fe–C bond. Previous X-ray diffraction and DFT both indicate that trigonal-prismatic geometry around carbon is maintained with high precision in all these states. The persistent structure and Fe–C bonding of the CFe 6 core indicate that it does not provide a functionally dynamic (hemilabile) “beating heart”-instead it acts as “a heart of steel”, stabilizing the structure of the FeMo-cofactor-active site during nitrogenase catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗