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DOE OSTI2023

Establishing metrics to quantify spatial similarity in spherical and red blood cell distributions

As computational power increases and systems with millions of red blood cells can be simulated, it is important to note that varying spatial distributions of cells may affect simulation outcomes. Since a single simulation may not represent the ensemble behavior, many different configurations may need to be sampled to adequately assess the entire collection of potential cell arrangements. In order to determine both the number of distributions needed and which ones to run, we must first establish methods to identify well-generated, randomly placed cell distributions and to quantify distinct cell configurations. We utilize metrics to assess (1) the presence of any underlying structure to the initial cell distribution and (2) similarity between cell configurations. We propose the use of the radial distribution function to identify long-range structure in a cell configuration and apply it to a randomly distributed and structured set of red blood cells. To quantify spatial similarity between two configurations, we make use of the Jaccard index, and characterize sets of red blood cell and sphere initializations. As an extension to our work submitted to the International Conference on Computational Science, we significantly increase our data set size from 72 to 1048 cells, include a similar set of studies using spheres, compare the effects of varying sphere size, and utilize the Jaccard index distribution to probe sets of extremely similar configurations. Our results show that the radial distribution function can be used as a metric to determine long-range structure in both distributions of spheres and RBCs. We determine that the ideal case of spheres within a cube versus bi-concave shaped cells within a cylinder affects the shape of the Jaccard index distributions, as well as the range of Jaccard values, showing that both the shape of particle and the domain may play a role. Furthermore, we also find that the distribution is able to capture very similar configurations through Jaccard index values greater than 95% when appending several nearly identical configurations into the data set.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

The Influence of Nonlocal Metal–Dielectric Environments on Physical and Chemical Processes

Plasmonic nanolayers and laminar metallic/dielectric multilayers were originally developed for optical cloaking applications and lensing applications that could potentially image objects whose size was below the diffraction limit. These assemblies were initially formed from gold or silver nanorods grown within an alumina mesh. However, more recently, assemblies with similar properties have also been prepared by sequential thin-layer deposition of alternating layers of gold and magnesium fluoride (MgF 2 ). These metal/dielectric composite materials enable control of the dielectric constant in the directions perpendicular to the layers and balance the real and imaginary dielectric constants of the assembly such that the speed and the amplitude of the waves traveling through the assembly are not attenuated. In this Account, we will also focus on a few of the applications ranging from surface wetting to fluorescence quenching to enhancement of photochemical reactions. First, we will share an introduction to processes used to create these materials, which are combinations of low refractive index metals and transparent higher index materials arranged in a scalable repeating fashion. Two fabrication methods were employed: an electrochemical deposition of Ag nanorods into an anodized alumina matrix which produced materials with an anisotropic negative refractive index material within the plane of the film and lamellar metal/dielectric layers in which the negative index perpendicular to the growth direction. These alternating layers of plasmonic metals and dielectric materials were ultimately chosen to prepare films for further testing, because of their relative ease of fabrication. We will continue with a discussion of a few of the applications of both of these nonlocal dielectric composite materials including more specialized plasmonic, composite, and hyperbolic metamaterials including fluorescence quenching, photochemical reactions, and surface wetting. In each of these applications, the unique response caused by the enhancement of the electric field and the interface between hyperbolic materials and plasmonic materials as they interact photophysically with their near neighbors is presented. In each of the applications, the enhanced electric field extends from the composite substrate layer to interact with its near neighbors and beyond. Furthermore, the presence of this extended interaction can be observed in the form of decreased emission lifetime, enhancement of photochemical reaction rates, and changes in the surface energies measured by contact angle goniometry. In this Account, all of these situations will be addressed. Finally, we will conclude with a summary and vision for the future as well as a discussion of the unique challenges and opportunities available as research active faculty at an HBCU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Saharan Dust Transport Predictability Utilizing a Subseasonal Experiment (SubX) Model

Prediction of Saharan dust customarily requires complex aerosols models and observations. A previous study of the Miami, Florida dust record in conjunction to reanalysis data discovered a possible source of subseasonal predictability using a dust-transport-efficiency (DTE) index. Development of the Subseasonal Forecast Experiment (SubX) has expanded global forecast products; producing multi-model ensemble forecasts out to 45 days. Retrospective forecast data from the Community Climate System Model version 4.0 (CCSM4) is used in direct comparison to National Centers for Environmental Prediction (NCEP) reanalysis to evaluate the CCSM4 subseasonal forecast and DTE index prediction skill of weekly dust variability. Successful prediction of weekly dust transport using the DTE index is variable year-to-year. The DTE most successfully predicts dust when there is high variability in the tropical winds, likely due to a fluctuating subtropical high, and is not dependent on the overall mean flow or total dust mass transported. The CCSM4 SubX retrospective forecast well represents North Atlantic meteorology out to week-3 in both mean flow and variability. Dust transport can be predicted using the DTE index and CCSM4 SubX retrospective forecasts at week-1 leads to the same success as contemporaneous NCEP reanalysis.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Lower Urban Humidity Moderates Outdoor Heat Stress

Abstract Surface temperature is often used to examine heat exposure in multi‐city studies and for informing urban heat mitigation efforts due to scarcity of urban air temperature measurements. Cities also have lower relative humidity, traditionally not accounted for in large‐scale observational urban heat risk assessments. Here, using crowdsourced measurements from over 40,000 weather stations in ≈600 urban clusters in Europe, we show the moderating effect of this urbanization‐induced humidity reduction on outdoor heat stress during the 2019 heatwave. We demonstrate that daytime differences in heat index between urban clusters and their surroundings are weak, and associations of this urban‐rural difference with background climate, generally examined from the surface temperature perspective, are diminished due to moisture feedbacks. We also examine the spatial variability of surface temperature, air temperature, and heat index within these clusters—relevant for detecting hotspots and potential disparities in heat exposure—and find that surface temperature is a poor proxy for the intra‐urban distribution of heat index during daytime. Finally, urban vegetation shows much weaker (∼1/6th as strong) associations with heat index than with surface temperature, which has broad implications for optimizing urban heat stress mitigation strategies. These findings are valid for operational metrics of heat stress for shaded conditions (apparent temperature and humidex), thermodynamic proxies (wet‐bulb temperature), and empirical heat indices. Based on this large‐scale empirical evidence, surface temperature, used due to the lack of better alternatives, may not be suitable for accurately informing heat mitigation strategies within and across cities, necessitating more urban‐scale observations and better urban‐resolving models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Ozone mitigates extended growing season and enhanced vegetation greenness driven by environmental change

Rising temperature and elevated CO 2 concentrations lead to extended growing seasons and enhanced vegetation greenness in terrestrial ecosystems, especially across the Northern Hemisphere. However, whether and to what extent surface ozone, an anthropogenic environmental factor, affects vegetation phenology and greenness remains unexplored at a large scale. Integrating ground-based ozone observations with multiple satellite observations, we demonstrate that surface ozone significantly shortened the growing season by delaying start of season and advancing end of season. Additionally, ozone reduced growing-season vegetation greenness, as reflected in decreased annual accumulated Enhanced Vegetation Index and maximum Enhanced Vegetation Index. These impacts show pronounced spatial heterogeneity, varying in magnitude across the United States, Europe, and China over the past decade, highlighting ozone’s diverse impact on vegetation across regions. Our study predicts that continuously increasing surface ozone concentration will mitigate warming-driven lengthening the growing season by 2 to 4 days, reduce maximum Enhanced Vegetation Index by 0.4% to 8.3%, and reduce annual accumulated Enhanced Vegetation Index by 1.0% to 5.6% in 2050 under Shared Socioeconomic Pathway 5-8.5 scenario. Our findings highlight the imperative need for strategic surface ozone regulation to optimize vegetation health and maximize the capacity for carbon sequestration.

Yin, Hao [Vanderbilt Univ., Nashville, TN (United ↗

DOE OSTI2021

Graded Buffer Bragg Reflectors with High Reflectivity and Transparency for Metamorphic Optoelectronics

A graded buffer Bragg reflector (GBBR) is a bifunctional device component that provides the reflection of a distributed Bragg reflector and the adjustable lattice constant of a compositionally graded buffer. Prior work showed that these properties can be combined with low threading dislocation density and high reflectivity. Here, we design and demonstrate complex GBBRs for specific metamorphic solar cell applications. We design buffers that provide (1) high reflectivity over a narrow bandwidth, for quantum well solar cells, (2) reflectivity over a wide bandwidth, for optically thin solar cells, and (3) low sidelobe reflection, for multijunction devices that demand low out-of-band reflection. Apodized and triple GBBRs are demonstrated, and transparency is always considered, requiring designs with carefully engineered material combinations. A GBBR with a reflection of 99% is demonstrated, as well as a triple GBBR that has over 80% reflection for 100?nm of the spectrum around 800?nm. We also analyze potential deviations in a baseline GBBR from that of a perfect DBR using transmission electron microscopy to analyze imperfections in the material and modeling to analyze the impact of imperfect refractive index data for lattice-mismatched AlGaInAs. Minimal crosshatch roughness and unintentional thickness variation occur throughout the buffer, which likely influences reflection slightly. Small deviations between the calculated AlGaInAs and utilized AlGaAs refractive index exist, giving methods for future GBBR improvement. While the GBBR designs are intended for metamorphic solar cells, the broad and high reflection may also be useful for other optoelectronic devices such as light-emitting diodes or lasers.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2024

Voltage-induced modulation of interfacial ionic liquids measured using surface plasmon resonant grating nanostructures

We have used surface plasmon resonant metal gratings to induce and probe the dielectric response (i.e., electro-optic modulation) of ionic liquids (ILs) at electrode interfaces. Here, the cross-plane electric field at the electrode surface modulates the refractive index of the IL due to the Pockels effect. This is observed as a shift in the resonant angle of the grating (i.e., Δϕ), which can be related to the change in the local index of refraction of the electrolyte (i.e., Δnlocal). The reflection modulation of the IL is compared against a polar (D2O) and a non-polar solvent (benzene) to confirm the electro-optic origin of resonance shift. The electrostatic accumulation of ions from the IL induces local index changes to the gratings over the extent of electrical double layer (EDL) thickness. Finite difference time domain simulations are used to relate the observed shifts in the plasmon resonance and change in reflection to the change in the local index of refraction of the electrolyte and the thickness of the EDL. Simultaneously using the wavelength and intensity shift of the resonance enables us to determine both the effective thickness and Δn of the double layer. We believe that this technique can be used more broadly, allowing the dynamics associated with the potential-induced ordering and rearrangement of ionic species in electrode–solution interfaces.

Chemistry↗

DOE OSTI2021

The future evolution of energy-water-agriculture interconnectivity across the US

Abstract Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the ‘Interconnectivity Magnitude Index’ and the ‘Interconnectivity Spread Index’. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Khan, Zarrar (ORCID:0000000281478553)↗

DOE OSTI2022

Correlations between Texture Profile Analysis and Sensory Evaluation of Cured Largemouth Bass Meat (Micropterus salmoides)

Texture is an important factor in evaluating the quality of aquatic products. To evaluate the texture properties of cured large mouth bass, edible sodium chloride (0, 1.0, 2.0, and 3.0%) was smeared to the bass meat. Texture profile analysis (TPA) and sensory evaluation were performed to evaluate the quality of the cured samples, and the correlations of the indexes in the two methods were analyzed. Two principal components were obtained from the TPA indexes and sensory evaluation indexes, and the cumulative variance contribution rates were 73.87% and 72.99%, respectively. Results from the principal component analysis showed that the main indicators that affected the TPA were gumminess and springiness, while those that affected sensory evaluation were chewiness and adhesiveness. The TPA index and sensory evaluation could be effectively improved when the sodium chloride added to the bass meat was 1%. In the correlation analysis, sensory springiness was negatively correlated with TPA hardness ( P < 0.05 , r = −0.553) but positively correlated with TPA chewiness ( P < 0.05 , r = 0.596). After stepwise regression analysis, the prediction equation between the sensory springiness and TPA hardness was obtained as SSp=5.770−0.002Ha. These results provide a basis for predicting the quality of large mouth bass cured products.

Li, Meijin↗

DOE OSTI2022

Algorithms for Forward and Inverse Problem Solutions in Phase Contrast Tomography

PhaseTorch is a python package that implements algorithms for forward and inverse problem solutions in X-ray phase contrast tomography (XPCT). XPCT is useful to reconstruct the 3D distribution of the refractive index decrement and absorption index of an imaged object. PhaseTorch implements algorithms for simulation, reconstruction, and analysis of XPCT data. PhaseTorch provides algorithms for simulation of XPCT data of an object with known refractive and absorption indices. It contains algorithms for reconstructing the projections of the absorption index and refractive index decrement.

Sridhar, Venkatesh↗

DOE OSTI2023

Limited Role of Absolute Humidity in Intraurban Heat Variability

Abstract Monitoring and understanding the variability of heat within cities is important for urban planning and public health, and the number of studies measuring intraurban temperature variability is growing. Recognizing that the physiological effects of heat depend on humidity as well as temperature, measurement campaigns have included measurements of relative humidity alongside temperature. However, the role the spatial structure in humidity, independent from temperature, plays in intraurban heat variability is unknown. Here we use summer temperature and humidity from networks of stationary sensors in multiple cities in the United States to show spatial variations in the absolute humidity within these cities are weak. This variability in absolute humidity plays an insignificant role in the spatial variability of the heat index and humidity index (humidex), and the spatial variability of the heat metrics is dominated by temperature variability. Thus, results from previous studies that considered only intraurban variability in temperature will carry over to intraurban heat variability. Also, this suggests increases in humidity from green infrastructure interventions designed to reduce temperature will be minimal. In addition, a network of sensors that only measures temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location, allowing for lower-cost heat monitoring networks. Significance Statement Monitoring the variability of heat within cities is important for urban planning and public health. While the physiological effects of heat depend on temperature and humidity, it is shown that there are only weak spatial variations in the absolute humidity within nine U.S. cities, and the spatial variability of heat metrics is dominated by temperature variability. This suggests increases in humidity will be minimal resulting from green infrastructure interventions designed to reduce temperature. It also means a network of sensors that only measure temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location.

Meteorology & Atmospheric Sciences↗

DOE OSTI2023

Time-refraction optics with single cycle modulation

Abstract We present an experimental study of optical time-refraction caused by time-interfaces as short as a single optical cycle. Specifically, we study the propagation of a probe pulse through a sample undergoing a large refractive index change induced by an intense modulator pulse. In these systems, increasing the refractive index abruptly leads to time-refraction where the spectrum of all the waves propagating in the medium is red-shifted, and subsequently blue-shifted when the refractive index relaxes back to its original value. We observe these phenomena in the single-cycle regime. Moreover, by shortening the temporal width of the modulator to ∼5–6 fs, we observe that the rise time of the red-shift associated with time-refraction is proportionally shorter. The experiments are carried out in transparent conducting oxides acting as epsilon-near-zero materials. These observations raise multiple questions on the fundamental physics occurring within such ultrashort time frames, and open the way for experimenting with photonic time-crystals, generated by periodic ultrafast changes to the refractive index, in the near future.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Value-of-Information Analysis of a Fracture Prediction Method

A core-based fracture prediction method is used to illustrate a Value of Information (VOI) decision-analysis protocol to inform completion decisions in tight-gas sandstones. The ratio of late host-rock cement to available pore volume or degradation index uses petrographic observations of cement distributions in core (including sidewall cores) to predict whether nearby but unsampled fractures (widths > 0.5 to 1 mm) are sealed (non-conductive) or open (conductive). Measurements from four sandstone plays suggest that the index correctly predicts open vs. sealed fractures with an accuracy in excess of 80%. The value added is calculated using Bayesian inference in which accuracy of the index serves as the likelihood of the prior distribution of open fractures to assess the posterior probability that data represent a useful predictor of producibility. VOI of the prediction method is more than three times the cost to acquire the data. VOI is most sensitive to play-specific geologic and cost parameters including cost to drill, expected revenue from a successful well, cost of completion, cost of acquiring data for the index, and fracture probability distributions. The approach provides a way to value acquiring fracture data and points to a need for zone-specific production data in tight-gas sandstones.

02 PETROLEUM↗

DOE OSTI2021

Evaluation of Oxygen Consumption as a Sensitive Measure of Electrical Cable Polymer Insulation Degradation

Polymers used as dielectric materials in nuclear grade electrical cables, such as cross-linked polyethylene (XLPE) and ethylene-propylene rubber (EPR), are long-lived and durable. Estimating the decades-long useful service life of polymers experimentally in a feasible timeframe of weeks or months requires greatly accelerated aging in the laboratory at elevated temperatures and/or gamma dose rates. Many limitations of accelerated aging, such as due to artefacts of the process including diffusion limited oxidation and dose rate effects, have been identified that can make accurate lifetime prediction at service conditions challenging. This can be due to differences in degradation mechanisms between rapid and extended aging or to the presence of induction periods during which early aging is undetectable using common metrics of polymer insulation characterization such as tensile elongation at break. Conceptually, an ideal measure of aging would track clearly and predictably with material changes throughout the lifecycle of the evolving material state from early aging through end of useful life. With such a metric accelerated aging could be performed at much milder conditions, conditions closer to those found in long term service, and end of life calculated from the early data. Oxygen consumption has previously been proposed as a sensitive measure of insulation polymer oxidation that might meet such desirable characteristics. In this work, nuclear cable insulation samples of the two most common types, XLPE and EPR, from two of the most sourced manufacturers, RSCC and The Okonite Company, were subjected to gamma irradiation at dose rates of 100, 200, and 300 Gy/hr for up to 42 days at 26°C. The aged samples were used to evaluate oxygen consumption as a sensitive measure of aging for these materials and these conditions. For comparison and validation, the aged samples were also characterized using the more conventional tests of mass change, density, carbonyl index, and yellowness index. For both materials, oxygen consumption during irradiation was found to track consistently with applied dose—oxygen consumption rate was linear with time. Mass change and carbonyl index were also clearly proportional to exposure dose. Yellowness index, a surface sensitive measure, was observed to increase linearly with dose at low exposure levels before plateauing. Sample density was not observed to change under the conditions explored. Oxygen consumption was found to be a particularly sensitive metric to measure the degradation of polymeric cable insulation exposed to radiation. Oxygen consumption was compared to Arrhenius and time-temperature-superposition methods for activation energy calculation using literature date and found to be a useful and viable alternative for lifetime prediction. The techniques developed in this work are anticipated to be valuable in the estimation of insulation aging rates under mild conditions approaching service conditions. Direction comparison of useful life prediction by oxygen consumption with prediction via Arrhenius methodology for thermal aging and existing methods for radiation and combined thermal/radiation aging would serve to further validate this promising approach and refine our understanding of material-specific aging rates.

36 MATERIALS SCIENCE↗

DOE OSTI2024

The association between neighborhood obesogenic factors and prostate cancer risk and mortality: the Southern Community Cohort Study

Background: Prostate cancer is one of the leading causes of cancer-related mortality among men in the United States. We examined the role of neighborhood obesogenic attributes on prostate cancer risk and mortality in the Southern Community Cohort Study (SCCS). Methods: From the total of 34,166 SCCS male participants, 28,356 were included in the analysis. We assessed the relationship between neighborhood obesogenic factors [neighborhood socioeconomic status (nSES) and neighborhood obesogenic environment indices including the restaurant environment index, the retail food environment index, parks, recreational facilities, and businesses] and prostate cancer risk and mortality by controlling for individual-level factors using a multivariable Cox proportional hazards model. We further stratified prostate cancer risk analysis by race and body mass index (BMI). Results: Median follow-up time was 133 months [interquartile range (IQR): 103, 152], and the mean age was 51.62 (SD: ± 8.42) years. There were 1,524 (5.37%) prostate cancer diagnoses and 98 (6.43%) prostate cancer deaths during follow-up. Compared to participants residing in the wealthiest quintile, those residing in the poorest quintile had a higher risk of prostate cancer (aHR = 1.32, 95% CI 1.12–1.57, p = 0.001), particularly among non-obese men with a BMI < 30 (aHR = 1.46, 95% CI 1.07–1.98, p = 0.016). The restaurant environment index was associated with a higher prostate cancer risk in overweight (BMI ≥ 25) White men (aHR = 3.37, 95% CI 1.04–10.94, p = 0.043, quintile 1 vs. None). Obese Black individuals without any neighborhood recreational facilities had a 42% higher risk (aHR = 1.42, 95% CI 1.04–1.94, p = 0.026) compared to those with any access. Compared to residents in the wealthiest quintile and most walkable area, those residing within the poorest quintile (aHR = 3.43, 95% CI 1.54–7.64, p = 0.003) or the least walkable area (aHR = 3.45, 95% CI 1.22–9.78, p = 0.020) had a higher risk of prostate cancer death. Conclusion: Living in a lower-nSES area was associated with a higher prostate cancer risk, particularly among Black men. Restaurant and retail food environment indices were also associated with a higher prostate cancer risk, with stronger associations within overweight White individuals. Finally, residing in a low-SES neighborhood or the least walkable areas were associated with a higher risk of prostate cancer mortality.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Interplay of Topography, Fire History, and Climate on Interior Alaska Boreal Forest Vegetation Dynamics in the 21st Century: A Landsat Time-Series Analysis

This study investigates vegetation dynamics in boreal forests of Interior Alaska, focusing on topography, fire history, and climate influences. The study area includes Bonanza Creek Experimental Forest (BCEF) and surrounding region, categorized by topography (upland, floodplain, lowland) and fire history. Using Mann–Kendall trend and Theil–Sen slope analyses on Landsat-derived spectral metrics: Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR), we observed a shift from browning to greening trends, particularly in historically burned areas. The photosynthetic activity in burned upland converged with unburned areas ~30 years post-fire, coincident with a shift towards deciduous dominance during post-fire succession. Normalized Difference Moisture Index (NDMI) trends revealed a significant increase in vegetation moisture content across all topographies. We introduce Effective Seasonal Precipitation Index (ESPI), which combines prior-year annual precipitation with current-year spring snow depth. Its positive correlation with NDMI highlights its potential for monitoring vegetation moisture dynamics at the landscape scale. Furthermore, by correlating dendrochronology-based climate indices, we found strong correlation between NDMI and normalized Supplemental Precipitation Index (nSPI), across topographies. Overall, this research provides critical insights into how climate and fire influence interior boreal vegetation, highlighting the effects of increased precipitation, and topography on shaping differential vegetation responses across the landscape.

Google Earth Engine↗

DOE OSTI2022

Quantification of Off-Channel Inundated Habitat for Pacific Chinook Salmon ( Oncorhynchus tshawytscha ) along the Sacramento River, California, Using Remote Sensing Imagery

Off-channel areas are one of the most impacted aquatic habitats by humans globally, as extensive agricultural and urban development has limited them to roughly 10% of historical extent. This is also true for California’s Sacramento River Valley, where historically frequent widespread inundation has been reduced to a few off-channel water bodies along the mid-Sacramento River. This remaining shallow-water habitat provides crucial ecological benefits to multiple avian and fish species, but especially to floodplain-adapted species such as Chinook salmon (Oncorhynchus tshawytscha). Characterizing spatiotemporal off-channel dynamics, including inundation extent and residence time, is fundamental to better understanding the intrinsic value of such habitats and their potential to support recovery actions. Remote sensing techniques have been increasingly used to map surface water at regional and local scales, with improved resolutions. As such, this study maps off-channel inundation areas and describes their temporal dynamics by analyzing pixel-based time- series of multiple water indices, modified Normalized Difference Water Index (mNDWI) and the Automated Water Extraction Index (AWEI), generated from LandSat-8 and Sentinel-2 data between 2013–2021. Quantified off-channel area was similar with each water index and method used, but improved performance was associated with Sentinel-2 products and AWEI index to identify wetted areas under lower mainstem discharges. Results indicate an uneven distribution of off-channel habitat in the study area, with limited inundated areas in upstream reaches (<16% of total off-channel area for greater flows). In addition, much less habitat exists for flows under 400 m 3 /s, an important migration cue for endangered winter-run Chinook salmon, limiting juvenile access to areas with enhanced rearing conditions. Off-channel habitat residence times averaged between 7 and 16 days, primarily defined by the rate of receding flows, with rapid flow recession providing marginal off-channel habitat. This study shows reasonable performance of moderate resolution LandSat-8 and Sentinel-2 remote sensing imagery to characterize shallow-water inundated habitat in higher-order rivers, and as a method to inform restoration and native fish recovery efforts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

EcoSpec: Highly Equipped Tower-Based Hyperspectral and Thermal Infrared Automatic Remote Sensing System for Investigating Plant Responses to Environmental Changes

Despite an advanced ability to forecast ecosystem functions and climate at regional and global scales, little is known about relationships between local variations in water and carbon fluxes and large-scale phenomena. To enable data collection of local-scale ecosystem functions to support such investigations, we developed the EcoSpec system, a highly equipped remote sensing system that houses a hyperspectral radiometer (350–2500 nm) and five optical and infrared sensors in a compact tower. Its custom software controls the sequence and timing of movement of the sensors and system components and collects measurements at 12 locations around the tower. The data collected using the system was processed to remove sun-angle effects, and spectral vegetation indices computed from the data (i.e., the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Photochemical Reflectance Index (PRI), and Moisture Stress Index (MSI)) were compared with the fraction of photochemically active radiation (fPAR) and canopy temperature. The results showed that the NDVI, NDWI, and PRI were strongly correlated with fPAR; the MSI was correlated with canopy temperature at the diurnal scale. These correlations suggest that this type of near-surface remote sensing system would complement existing observatories to validate satellite remote sensing observations and link local and large-scale phenomena to improve our ability to forecast ecosystem functions and climate. The system is also relevant for precision agriculture to study crop growth, detect disease and pests, and compare traits of cultivars.

47 OTHER INSTRUMENTATION↗