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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effects of salinity and nutrients on metabolism and growth of Ulva lactuca : Implications for bioremediation of coastal watersheds

We studied Ulva lactuca to determine its potential for bioremediation of coastal watersheds. We cultured Ulva in orthogonal combinations of two salinities and three nutrient concentrations for six weeks, and then measured its growth, photosynthesis, chlorophyll fluorescence, nitrogen, carbon and phosphorus tissue concentrations, and carbon and nitrogen uptake pathways. Our findings show that Ulva was negatively affected by decreased salinity but these effects were ameliorated by the addition of nutrients to the water, such as would be expected from freshwater runoff during heavy rain events. Also, increased nutrients resulted in altered nitrogen (NH$_4^ +$ vs. NO$_3^-$) and carbon (HCO$_3^-$ vs. CO 2 ) uptake pathways, which can allow Ulva to retain its bloom potential even under reduced salinities. Together, our study suggests that Ulva is an ideal species to grow for the purpose of bioremediation of coastal bays and estuaries, even during storms that freshen the surface waters and increase nutrients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Determination of aquatic hazard concentrations for the oil spill response product class of surface washing agents using species sensitivity distributions

Surface washing agents (SWAs) are a diverse class of oil spill response products intended to facilitate removal of stranded oil from shorelines. This class of agents has high application rates relative to other categories of spill response products, but global toxicity data is generally limited to two standard test species: inland silverside and mysid shrimp. Here, in this study, we provide a framework to maximize the utility of limited toxicity data across a product class. To characterize species sensitivity to SWAs, the toxicity of three agents spanning a range of chemical and physical properties were tested in eight species. The relative sensitivity of mysids shrimp and inland silversides as surrogate test organisms was determined. Toxicity normalized species sensitivity distributions (SSDn) were used to estimate fifth centile hazard concentration (HC5) values for SWAs with limited toxicity data. Chemical toxicity distributions (CTD) of SWA HC5 values were used to compute a fifth centile chemical hazard distribution (HD5) to provide a more comprehensive assessment of hazard across a spill response product class with limited toxicity data than traditional single species or single agent approaches can give.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Evaluating the effectiveness of M-AMBI with other biotic indexes in a temperate estuary

Need for a scalable and widely applicable index has been increasingly important. This study evaluates the applicability of the M-AMBI, a potential comprehensive index, at small spatial scales. M-AMBI was compared to regional indices (EMAP-E and GOM B-IBI), assessing response to natural environmental gradients and low oxygen stress. Results indicate poor agreement between indices with M-AMBI and GOM B-IBI showing positive correlation but significant disagreement in habitat condition. EMAP-E had no agreement. Indices showed similar patterns of better habitat scores in higher salinities. M-AMBI also showed a negative relationship with sediment organic matter and total nitrogen. DO influenced all indices with M-AMBI the most sensitive. However, mismatches between DO and index score were observed further calibration may be needed before adoption into programs. Altogether, the M-AMBI demonstrates potential at smaller, local scales, but additional studies are needed to validate its performance in different coastal environments and under different conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

High-Resolution Measurement of Soil Thermal Properties and Moisture Content Using a Novel Heated Fiber Optics Approach

Hydrological parameters are scale dependent. Efficient monitoring techniques capable of measuring hydrological parameters, such as soil moisture content (θ), over a wide range of spatial scales are essential for understanding the complexity of water and energy movement across the landscape. Techniques to measure θ over spatial scales in the range from centimeters to thousands of meters, however, are sorely lacking. Recent improvements in the distributed temperature sensing (DTS) technology supported the development of novel techniques to fill that gap. However, improvements in the accuracy and applicability of DTS techniques are still needed. This study investigates the possibility of improving the accuracy of the fiber optics dual-probe heat-pulse (FO-DPHP) DTS technique by using a new design to maintain the spacing between the FO-DPHP probes and by introducing a novel data interpretation approach. The accuracy of the novel FO-DPHP design was tested at different θ in a sand column experiment. The FO-DPHP measurements obtained using traditional and novel data interpretation approaches were compared against independent measurements from several calibrated soil water content (EC5) sensors. Monte-Carlo analyses were also performed to assess the impact of DTS measurement errors on the accuracy achieved using the data interpretation approaches. The novel design and data interpretation approach allowed for accurate measurements of soil thermal properties and θ without the need to perform a hard-to-achieve soil-specific calibration. Measured θ had mean errors and standard deviations <0.03 and <0.01 m 3 m -3 , respectively, for moisture conditions ranging from dry to near saturation. The standard deviation in the measured heat capacity was <0.01 MJ m -3 K -1 .

42 ENGINEERING↗
DOE OSTI2019

Multiscale Feature-feature Interactions Control Patterns of Hyporheic Exchange in a Simulated Headwater Mountain Stream

Recent predictions of hyporheic exchange at the basin-scale assume individual features control exchange independently of each other, which has been demonstrated in relatively uniform, low-gradient rivers. However, this assumption may not hold in steep catchments where both the type and size of individual features may vary over short distances, leading to irregular patterns of feature dominance on hyporheic exchange flows. Also, steep longitudinal gradients support substantial downvalley flows in the subsurface, which may create feedbacks between adjacent features. In this study, we test the extent to which features interact with one another and whether they can be aggregated to make reach-scale predictions in a headwater mountain stream. Using systematic manipulations of a 2-D stream centerline model and spectral analyses, we test for the presence of both feature-feature and multiscale interactions. Our results show that changing the height of individual step-pool features can alter hyporheic flow fields in neighboring, and sometimes distant, features. Spectral analyses revealed two scales of streambed topography—a local scale of single features and an intermediate scale that spanned multiple local-scale features. All features produced hyporheic exchange, but turnover of deeper hyporheic water only occurred at a few key locations where local- and intermediate-scale features amplified each other. Further, shallow bedrock increases the ratio of local- and intermediate-scale flowpaths to regional-scale flowpaths. Conceptual models portraying hyporheic exchange as a series of nested flowpaths should include the interactions among streambed topographic features in mountain streams. These results have implications for upscaling, field experiments, and stream restoration in steep catchments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Hyporheic Exchange Driven by Submerged Rigid Vegetation: A Modeling Study

Flow-vegetation interaction affects fluid flow hydraulics and associated material transport in river corridors. Concomitant changes in pressure within the flow field due to the presence of vegetation may act as a driver for the formation of hyporheic flow across the sediment-water interface. This potentially important process, however, has yet to be studied. In order to investigate vegetation-induced hyporheic exchange, a series of numerical models of interlinked surface-subsurface flow modified by plant stems was conducted. Periodically staggered plant stem arrays on a flat sediment bed were considered within a coupled multiphysics computational fluid dynamics approach. Plants were idealized as rigid cylinders and arranged in different streamwise and spanwise spacing distances. Each vegetation array was then subjected to a broad range of flow Reynolds Numbers (Re). The results showed that hyporheic flow occurs in all conditions with the presence of vegetation. The vegetation-induced hyporheic flux is found to be a function of Re via a power law. The flux increases with interstem space until the space reaches the distance that rigid stems no longer affect the flow structures in the vicinity of each other. Larger intervegetation distances lead to a larger hyporheic zone. A direct comparison with bedforminduced hyporheic flow showed that vegetation can induce higher hyporheic flux through relatively shallower exchange zones. The results of all the simulations were synthesized into predictive models for hyporheic flux, bulk residence time and exchange depth based on drag coefficient, vegetation density, and Reynolds Number.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Enhancing Streamflow Forecast and Extracting Insights Using Long-Short Term Memory Networks With Data Integration at Continental Scales

Recent observations with varied schedules and types (moving average, snapshot, or regularly spaced) can help to improve streamflow forecasts, but it is challenging to integrate them effectively. Based on a long short-term memory (LSTM) streamflow model, we tested multiple versions of a flexible procedure we call data integration (DI) to leverage recent discharge measurements to improve forecasts. DI accepts lagged inputs either directly or through a convolutional neural network unit. DI ubiquitously elevated streamflow forecast performance to unseen levels, reaching a record continental-scale median Nash-Sutcliffe Efficiency coefficient value of 0.86. Integrating moving-average discharge, discharge from the last few days, or even average discharge from the previous calendar month could all improve daily forecasts. Directly using lagged observations as inputs was comparable in performance to using the convolutional neural network unit. Importantly, we obtained valuable insights regarding hydrologic processes impacting LSTM and DI performance. Before applying DI, the base LSTM model worked well in mountainous or snow-dominated regions, but less well in regions with low discharge volumes (due to either low precipitation or high precipitation-energy synchronicity) and large interannual storage variability. DI was most beneficial in regions with high flow autocorrelation: it greatly reduced baseflow bias in groundwater-dominated western basins and also improved peak prediction for basins with dynamical surface water storage, such as the Prairie Potholes or Great Lakes regions. However, even DI cannot elevate performance in high-aridity basins with 1-day flash peaks. Despite this limitation, there is much promise for a deep-learning-based forecast paradigm due to its performance, automation, efficiency, and flexibility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Coupled Time-Lapse Full-Waveform Inversion for Subsurface Flow Problems Using Intrusive Automatic Differentiation

We describe a novel framework for estimating subsurface properties, such as rock permeability and porosity, from time-lapse observed seismic data by coupling full-waveform inversion (FWI), subsurface flow processes, and rock physics models. For the inverse modeling, we handle the back propagation of gradients by an intrusive automatic differentiation strategy that offers three levels of user control: (1) At the wave physics level, we adopted the discrete adjoint method in order to use our existing high-performance FWI code; (2) at the rock physics level, we used built-in automatic differentiation operators from the TensorFlow backend; (3) at the flow physics level, we implemented customized partial differential equation (PDE) operators for the multiphase flow equations. The three-level coupled inversion strategy strikes a good balance between computational efficiency and programming efforts, and when the gradients are chained together, it constitutes a coupled inverse system. Our numerical experiments demonstrate that the three-level coupled inverse problem is superior in terms of accuracy to a traditional decoupled inversion strategy. Additionally, our method is able to simultaneously invert for parameters in empirical relationships such as the rock physics models. Our proposed inverted model can be used for reservoir performance prediction and reservoir management/optimization purposes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Evaluation of Methods for Causal Discovery in Hydrometeorological Systems

Understanding causal relations is of utmost importance in hydrology and climate research for systems identification, prediction, and understanding systems behavior in a changing climate. Traditionally, researchers in hydrometeorology attempted to study causal questions by conducting controlled experiments using numerical models. This approach, however, in most cases of interest provides uncertain results because the models are approximate representation of the natural system. An alternative approach that has recently drawn significant attention in several fields is to infer causal relations from purely observational data. It possesses several traits to its utility particularly in hydrometeorology due to the rapid accumulation of in situ and remotely sensed data records. The first objective of this study is to present a brief description of four causal discovery methods (Granger causality, Transfer Entropy, graph-based algorithms, and Convergent Cross Mapping) with special emphasis on the assumptions on which they are built. Second, using synthetic data generated from a hydrological model, we assess their performance in retrieving causal information taking into account sensitivity to sample size and presence of noise. Last, we use causal analysis to examine and formulate hypotheses on causal drivers of evapotranspiration in a shrubland region during summer and winter seasons. An interpretation of the hypotheses based on canopy seasonal dynamics and evapotranspiration processes is presented. It is hoped that the results presented here can be useful in guiding researchers studying hydrometeorological systems as to which causal method is most appropriate to the characteristics of the system under study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

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

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

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Characterizing Physical Properties of Streambed Interface Sediments Using In Situ Complex Electrical Conductivity Measurements

Streambed sediment physical properties such as surface area, are difficult to quantify in situ but exert a high-level control on a wide range of biogeochemical processes and sorption of contaminants. We introduce the use of complex electrical conductivity (CC) methods (also known as spectral-induced polarization (SIP)) that measure both real and imaginary conductivity to noninvasively and efficiently characterize shallow streambed sediments. We explore the method through synthetic modeling, laboratory, and field measurements to demonstrate the sensitivity of imaginary conductivity to sediment surface area, controlled in part by fine-grained iron oxides produced by anoxic groundwater discharge. Laboratory measurements verify expected relationships between CC parameters and sediment properties. Synthetic modeling using a 1D analytical model illustrates the influence of water layer depth and conductivity on the field CC measurements made at the streambed-stream water interface. Specifically, the inverted sediment imaginary conductivity is less impacted by uncertainty in the water layer depth and conductivity relative to the real conductivity and phase shift. Field CC measurements along a landfill-impacted river reveal discrete streambed zones with enhanced bulk surface area generally corresponding to anoxic groundwater discharge zones with high concentrations of fine-grained iron oxide precipitates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Influences on Discharge Partitioning on a Large River Delta: Case Study of the Mississippi-Atchafalaya Diversion, 1926-1950

The modern Mississippi River (M.R.) Delta is plumbed by the Mississippi and Atchafalaya rivers, setting water and sediment dispersal pathways for Earth’s fifth-largest river system. The Atchafalaya River’s (A.R.) partial annexation of discharge from the M.R., particularly between 1926 and 1950, prompted warnings of a rapid river avulsion and the construction of the Old River Control Structure to regulate flow. Natural and anthropogenic causes of this discharge annexation are difficult to disentangle. Here, we develop and validate a hydrodynamic model of flow partitioning through the historic channel network. We then isolate how several key changes to the system affected discharge partitioning and stage at the A.R.-M.R. diversion. Simulations show that erosion of the upper A.R. can account for 73% of the water discharge increase. Dredging in the lower A.R. between 1932 and 1950 can account for 35% of the water discharge increase, and was also an important control on shear stress distribution. The lower M.R. was slightly erosional during this period, and therefore hindered the A.R. discharge increase. Significant lacustrine delta deposition in A.R. had little effect on partitioning. These findings highlight the importance of A.R. enlargement processes on avulsion dynamics at this site. Given the essential nature of this river junction to the society, transportation, and commerce of the United States, improved attribution of discharge increases may lead to future management strategies that are broadly impactful.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Distributed Acoustic Sensing as a Distributed Hydraulic Sensor in Fractured Bedrock

Distributed acoustic sensing (DAS) was originally intended to measure oscillatory strain at frequencies of 1 Hz or more on a fiber optic cable. Recently, measurements at much lower frequencies have opened the possibility of using DAS as a dynamic strain sensor in boreholes. A fiber optic cable mechanically coupled to a geologic formation will strain in response to hydraulic stresses in pores and fractures. A DAS interrogator can measure dynamic strain in the borehole, which can be related to fluid pressure through the mechanical compliance properties of the formation. Because DAS makes distributed measurements, it is capable of both locating hydraulically active features and quantifying the fluid pressure in the formation. We present field experiments in which a fiber optic cable was mechanically coupled to two crystalline rock boreholes. The formation was stressed hydraulically at another well using alternating injection and pumping. The DAS instrument measured oscillating strain at the location of a fracture zone known to be hydraulically active. Rock displacements of less than 1 nm were measured. Laboratory experiments confirm that displacement is measured correctly. These results suggest that fiber optic cable embedded in geologic formations may be used to map hydraulic connections in three-dimensional fracture networks. A great advantage of this approach is that strain, an indirect measure of hydraulic stress, can be measured without beforehand knowledge of flowing fractures that intersect boreholes. The technology has obvious applications in water resources, geothermal energy, CO 2 sequestration, and remediation of groundwater in fractured bedrock.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Porosity-Permeability Evolution During Simultaneous Mineral Dissolution and Precipitation

Permeability in reactive porous media evolves in complex ways that are hard to predict. Macroscopic empirical equations are often used to estimate permeability evolution but fail to reflect the impact of pore scale reactions on permeability. This work aims to understand the evolution of permeability in systems where mineral dissolution and precipitation occur simultaneously. Pore network models are used for permeability simulation of a Paluxy sandstone using pore and pore-throat size distributions from the analysis of X-ray CT images. Pore and pore-throat radii are increased and decreased to reflect the effects of dissolution and precipitation reactions. Varying spatial distributions of reactions are simulated and the resulting porosity and permeability values compared with commonly used macroscopic equations. It is observed that when dissolution occurs at the inlet and precipitation at the outlet, porosity increases while permeability decreases. Similar results are also observed in the respective opposite scenario where precipitation occurs at the inlet and dissolution at the outlet. When dissolution and precipitation reactions are randomly distributed throughout the network, porosity increases with little change in permeability that is not captured by the empirical equations. When reactions are controlled by pore and pore-throat sizes, such as dissolution occurring in pores and pore-throats of small size and precipitation in pores and pore-throats of larger size, porosity and permeability decrease. When precipitation occurs in pores and pore-throats of smaller size and dissolution in pores and pore-throats of larger size, porosity and permeability increase and is described relatively well by the Verma-Pruess porosity-permeability equation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Potential Chemical Impacts of Subsurface CO 2 : An Integrated Experimental and Numerical Assessment for a Case Study of the Ogallala Aquifer

Leakage from geologic CO 2 sequestration (GCS) reservoirs to overlying underground sources of drinking water (USDW) is a tangible risk. This study is an integrated assessment that combines column experiments and reactive transport simulations of sediments sampled from the Ogallala aquifer above an active commercial-scale GCS site (the Farnsworth Unit in northern Texas). Experimental and simulation results suggest that carbonate mineral (calcite and dolomite) dissolution is the most significant reaction following CO 2 intrusion, and is also the dominant source of trace metal release. Cation exchange is another key mechanism controlling trace metal release by cation interference. Most of the trace metals, including Ba, Sr, As, Pb, and Zn, show a short-term release and quickly drop to the baseline values, suggesting low risk to the overlying USDW quality. Other trace metals, such as Mn and U, exhibit a tangible increase of their concentrations in the beginning, and drop to a higher level compared to the baseline, which may become a potential concern of long-term USDW quality change with CO2introduction. This study provides a comprehensive example of combining laboratory experiments and simulations for assessment of CO 2 -sediment interactions with combined release mechanisms in shallow groundwater aquifers. Data presented here provides useful insights for quantitative risk assessment and effective public education regarding CO 2 geological sequestration, and trace metal reactive transport studies in shallow groundwater aquifers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Using Complex Probability Amplitudes to Simulate Solute Transport in Composite Porous Media

Probability amplitudes are fundamental to quantum mechanics and offer robust descriptions of complicated systems, which have allowed physicists to explain behaviors inaccessible to classical physics. This article ponders how some of the same conceptual underpinnings of the mathematics used for modeling quantum systems might be applied to subsurface water resources problems and speculates how these tools could facilitate applications on quantum computers. A probability amplitude-based model for describing advective-dispersive transport in porous media using linear operators is investigated. The proposed complex valued model decomposes spreading into two “sub-continuum partial dispersion” coefficients, and this recovers classical spreading when the sum of these coefficients is the Fickian dispersion coefficient. However, the probability amplitudes have a manyto-one relationship to a probability distribution, so it embeds a level of heterogeneity into seemingly equivalent functions. Two propagators with different sub-continuum coefficients may have the same macroscopic behavior when either is considered in isolation, but when they act on the other the system’s behavior changes. Additionally, differences in the amplitudes cause a reduction in spreading as velocity correlations are disrupted, despite both propagators having identical dispersion coefficients, and this cannot be achieved using classical methods without changing the dispersion coefficient. The main point is that these amplitude-based models offer a way to embed information about the system into the propagators, instead of just “averaging it out” when making an upscaled model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Hyporheic Oxygen Dynamics in the East River, Colorado: Insights From an In–Situ, High Frequency Time Series During Two Distinct Flow Seasons

Dissolved oxygen (DO) is critical for aquatic ecosystems, however, few studies have focused on the long-term DO dynamics in hyporheic zones, which are a function of both transport (hydrologic exchange between river and hyporheic zone) and uptake by biogeochemical reactions or respiration. We explore the dynamics of temperature and DO at 10, 20, and 35 cm depth beneath the East River, Colorado, from July–October 2017 (relatively normal water year) and April to October 2018 (comparatively low flow year), enabled by distinctive, in-situ, high frequency (Δt = 5 min) sensors that provided continuous time-series from the undisturbed study site over 14 months. We expect that hyporheic DO, which has a regular daily fluctuation pattern, is supplied by the surface water (at all times we estimate downwelling) and that diurnal hyporheic DO temporal patterns should be aligned with diurnal hyporheic temperature patterns. However, this was not found to be the case. Hyporheic DO becomes depleted briefly at 20 and 35 cm depths in 2017, and at all three hyporheic depths for extended periods in 2018. Whereas diurnal temperature fluctuations have consistent timings of maxima and minima, hyporheic DO rarely has as regular a pattern, and daily ranges are inconsistent. Rainfall events caused some of these changes to diurnal hyporheic DO patterns without repeatable effects. Antecedent snowpack conditions influence streamflow dynamics and therefore hyporheic DO dynamics in this alpine river. These results also point to the strong and variable influence of hyporheic microbial communities regulating hyporheic DO.

54 ENVIRONMENTAL SCIENCES↗