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At least 253 records · Page 14

Time Series Analysis of Insar Data: Methods and Trends

Time series analysis of InSAR data has emerged as an important tool for monitoring and measuring the displacement of the Earth's surface. Changes in the Earth's surface can result from a wide range of phenomena such as earthquakes, volcanoes, landslides, variations in ground water levels, and changes in wetland water levels. Time series analysis is applied to interferometric phase measurements, which wrap around when the observed motion is larger than one-half of the radar wavelength. Thus, the spatio-temporal ''unwrapping" of phase observations is necessary to obtain physically meaningful results. Several different algorithms have been developed for time series analysis of InSAR data to solve for this ambiguity. These algorithms may employ different models for time series analysis, but they all generate a first-order deformation rate, which can be compared to each other. However, there is no single algorithm that can provide optimal results in all cases. Since time series analyses of InSAR data are used in a variety of applications with different characteristics, each algorithm possesses inherently unique strengths and weaknesses. In this review article, following a brief overview of InSAR technology, we discuss several algorithms developed for time series analysis of InSAR data using an example set of results for measuring subsidence rates in Mexico City.

InSAR↗

Spatio-Temporal Variability of Groundwater Storage in India

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Groundwater monitoring↗

Investigation of a Magma-Sediment Hydrothermal Dike System in Utah: Constraints on the Habitability Potential of Martian Noachian Hydrothermal Systems

The Martian crust is predominantly composed of basalt and hosts a large variety of alteration materials produced by wide-ranging processes from volcanic hydrothermal processes to sedimentary and post-magmatic (e.g., see [2] and reference within). High temperature hydrothermal systems from volcanic processes, as well as meteorite impacts, should have occurred through time. However, finding evidence of high-temperature hydrothermal activity has been challenging. To better understand how to detect such a system on Mars, Earth analogs can be used to constrain mineral changes in such a system, then applied to locations on Mars. Here we investigate a mafic dike and the surrounding metamorphic contact zone that has been hydrothermally altered from contact with ground water as it was emplaced.

R A Slank↗

Microbial sensor system for the assessment of subsurface environments

A microbial sensor, system, and method that can be used to determine a chemical environment and/or substrate concentrations in anaerobic or aerobic environments, such as soils, sediments and ground waters, are disclosed. An exemplary system uses one or more (e.g., inert) measurement electrodes and a reference electrode. The reference electrode can include an electrode exposed to atmospheric oxygen (e.g., a cathode) or an electrode exposed to stable anaerobic or aerobic conditions. The exemplary microbial sensor system measures open-circuit voltage to characterize the chemical (oxidizing or reducing) environment and/or recovery voltage to measure substrate concentrations in the subsurface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solid phase sampling device and methods for point-source sampling of polar organic analytes

Sampling devices for sampling an aqueous source (e.g., field testing of ground water) for multiple different analytes are described. Devices include a solid phase extraction component for retention of a wide variety of targeted analytes. Devices include analyte derivatization capability for improved extraction of targeted analytes. Thus, a single device can be utilized to examine a sample source for a wide variety of analytes. Devices also include an isotope dilution capability that can prevent error introduction to the sample analysis and can correct for sample loss and degradation from the point of sampling until analysis as well as correction for incomplete or poor derivatization reactions. The devices can be field-deployable and rechargeable.

Boggess, Andrew J.↗

Microbial sensor system for the assessment of subsurface environments

A microbial sensor, system, and method that can be used to determine a chemical environment and/or substrate concentrations in anaerobic or aerobic environments, such as soils, sediments and ground waters, are disclosed. An exemplary system uses one or more (e.g., inert) measurement electrodes and a reference electrode. The reference electrode can include an electrode exposed to atmospheric oxygen (e.g., a cathode) or an electrode exposed to stable anaerobic or aerobic conditions. The exemplary microbial sensor system measures open-circuit voltage to characterize the chemical (oxidizing or reducing) environment and/or recovery voltage to measure substrate concentrations in the subsurface.

Burge, Scott R.↗

Solid-phase sampling device and methods for point-source sampling of polar organic analytes

Sampling devices for sampling an aqueous source (e.g., field testing of ground water) for multiple different analytes are described. Devices include a solid phase extraction component for retention of a wide variety of targeted analytes. Devices include analyte derivatization capability for improved extraction of targeted analytes. Thus, a single device can be utilized to examine a sample source for a wide variety of analytes. Devices also include an isotope dilution capability that can prevent error introduction to the sample analysis and can correct for sample loss and degradation from the point of sampling until analysis as well as correction for incomplete or poor derivatization reactions. The devices can be field-deployable and rechargeable.

Boggess, Andrew J.↗

Probabilistic Groundwater Modeling of the RDX Plume at Los Alamos National Laboratory to Support Risk Assessment - 20359

A plume of the contaminant hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) with concentrations greater than the New Mexico tap water drinking standard (9.66 ppb) is present in the regional aquifer near the southwestern boundary of Los Alamos National Laboratory (LANL). A risk assessment is performed for exposure to regional aquifer groundwater, with long-term predictions of RDX concentrations provided by a calibrated, probabilistic, numerical fate and transport model. The structure of the model is hierarchical, with the RDX Regional Aquifer (RA) groundwater model acting as the primary tool for analysis of downgradient RDX concentrations. The RA model is deeply informed by the conceptual site model (CSM) and is calibrated using site RDX concentration data and hydraulic head measurements, along with other analyses. The model is calibrated using data through December 2019. Where data are scarce other lines of evidence are used to inform inputs, including the multiphase RDX Vadose Zone (VZ) model and Pipe and Disk analytical screening tool. Model inputs are described with informative prior distributions using a robust approach to development that incorporates all available lines of evidence for every parameter used as an input to the RA model. Calibration is performed using a classical nonlinear optimization routine, which is then used to initialize a Bayesian calibration. The Bayesian calibration constrains the uncertainty in the classical calibration, ultimately providing posterior distributions for all model parameters. The challenges of the calibration include high-dimensional parameter space, including spatially heterogeneous hydraulic conductivities, comparatively sparse data, and low RDX concentrations. Posterior parameter distributions developed in the calibration process are then used for stochastic predictive model runs into the future. The result of the forward runs is spatially and temporally explicit estimates of head and concentration with uncertainty at all points in space and time. The probabilistic modeling approach presented here includes innovative computational and statistical methods that leverage high-performance computing (HPC) resources. It makes use of prior modeling work performed at the chromium plume site in the central LANL area, with extensive updates. The risk assessment will ultimately be used to support decision-making at the site, using multiple appropriately weighted sources of information, as well as uncertainty, sensitivity, and value-of-information analyses. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Iodine Co-Precipitation with Calcium Carbonate in the Presence of Silica Ions - 20360

Historical releases of I-129 to the subsurface at the U.S. Department of Energy Hanford Site have resulted in large dilute plumes that cover an area of over 50 km{sup 2}. The most concentrated I-129 plume is associated with the 200 West Area in the 200-UP-1 operable unit of the Hanford Central Plateau, where peak concentrations have been measured up to 30 times the drinking water standard of 1 pCi/L. The mobility of iodine depends on many factors, including chemical speciation, pH, redox conditions, as well as the presence of organic matter, calcium carbonate minerals and microbial activities. Speciation measurements estimate that the majority of the iodine (∼76%) in Hanford groundwater exists as iodate. Information on processes that affect iodate mobility in the Hanford subsurface support evaluation of environmental management options for the I-129 plumes. Iodate can be incorporated into calcium carbonate, which is a potential mechanism of naturally attenuating radioiodine in groundwater. However, the silica content in porewater may impact the contaminant-calcium carbonate incorporation process. Silica is one of the most abundant elements in nature and can have an impact on chemical weathering of alkaline-earth carbonates in the environment. Hence, this research aims to advances knowledge of the iodine co-precipitation process with calcium carbonate in the presence of silica. This information supports the technical basis evaluation of natural attenuation for I-129. Samples for these studies were prepared using calcium carbonate-forming solutions that included certified grade sodium meta-silicate nonahydrate (Na{sub 2}SiO{sub 3}), calcium chloride dehydrate (CaCl{sub 2}.2H{sub 2}O), sodium carbonate (NaCO{sub 2}), and sodium hydroxide (NaOH) solutions for pH adjustments. Triplicate samples were prepared with silica concentrations in the solution of 0 mM, 0.5 mM and 20 mM, mixed with an iodate standard (1000 ppm of IO{sub 3}{sup -} in H{sub 2}O) and sampled over a one-week period. Preliminary data analyses suggest that less iodine remains in solution in the presence of silica (average remaining aqueous fraction 0.23±0.03 at 20 mM of Si) relative to samples without silica (0.52±0.06); an indication that more iodine has been sorbed or incorporated into precipitates. However, the mechanisms for this behavior are still under investigation and need to be interpreted relative to pore water compositions that are representative of Hanford site-specific conditions. Scanning electron microscope equipped with energy dispersive spectroscopy (SEM-EDS) analyses were performed to observe the solid phase morphology in these experiments and showed rhombohedral calcite crystals covered with amorphous Si floccules. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Emerging Contaminants: Identification, Life Cycle, and Key Challenges - 20415

The term 'emerging contaminants' and its multiple variants has come to refer to previously overlooked compounds discovered in the environment which represent a potential threat to human and ecological receptors. These compounds may be discovered in the environment as new analytical techniques are developed and/or as new monitoring programs for drinking water and groundwater are implemented, while the threat to receptors may be realized through advances in understanding of toxicology and pathways to receptors. Emerging contaminants present unique and considerable challenges as demands to address them can outpace the understanding of their toxicity, their need for regulation, their occurrence, and techniques for treating the environmental media they affect. With these challenges in mind, this paper serves as a primer for understanding emerging contaminants. The paper will lay a foundation for understanding emerging contaminants through three key topics: 1. Who identifies emerging contaminants? An overview of the various stakeholder groups around the world working on identifying potential emerging contaminants and developing systems for screening potential candidates, prioritizing, and ultimately generating regulations will be provided. 2. How Chemicals Rise into Awareness as Emerging Contaminants. The process by which contaminants emerge through a cycle of awareness, characterization, management and regulation will be discussed. Current emerging contaminants will be discussed in the context of the life cycle: emerging contaminants where impacts to drinking water supplies are driving public awareness (e.g. per and polyfuoroalkyl substances (PFASs) and 1,4-dioxane), emerging contaminants impacted by changing regulatory standards or development and debate on toxicity (e.g., hexavalent chromium, 1,2,3-trichloropropane, trichloroethylene in vapor intrusion), and those with evolving understanding of impacts and usage (e.g., microplastics). 3. Key Challenges. Unique challenges associated with emerging contaminants, including visibility and public sensitivity, uncertainty and vulnerability, will be discussed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Comparison of Aerosol Optical Properties and Water Vapor Among Ground and Airborne Lidars and Sun Photometers During TARFOX

We compare aerosol optical thickness (AOT) and precipitable water vapor (PWV) measurements derived from ground and airborne lidars and sun photometers during the Tropospheric Aerosol Radiative Forcing Observational Experiment. Such comparisons are important to verify the consistency between various remote sensing measurements before employing them in any assessment of the impact of aerosols on the global radiation balance. Total scattering ratio and extinction profiles measured by the ground-based NASA Goddard Space Flight Center scanning Raman lidar system, which operated from Wallops Island, Virginia (37.86 deg N, 75.51 deg W); are compared with those measured by the Lidar Atmospheric Sensing Experiment (LASE) airborne lidar system aboard the NASA ER-2 aircraft. Bias and root-mean-square differences indicate that these measurements generally agreed within about 10%. Aerosol extinction profiles and estimates of AOT are derived from both lidar measurements using a value for the aerosol extinction/backscattering ratio S(sub a) = 60 sr for the aerosol extinction/backscattering ratio, which was determined from the Raman lidar measurements. The lidar measurements of AOT are found to be generally within 25% of the AOT measured by the NASA Ames Airborne Tracking Sun Photometer (AATS-6). However, during certain periods the lidar and Sun photometer measurements of AOT differed significantly, possibly because of variations in the aerosol physical characteristics (e.g., size, composition) which affect S(sub a). Estimates of PWV, derived from water vapor mixing ratio profiles measured by LASE, are within 5-10% of PWV derived from the airborne Sun photometer. Aerosol extinction profiles measured by both lidars show that aerosols were generally concentrated in the lowest 2-3 km.

Ferrare, R.↗

Comparison of Aerosol Optical Properties and Water Vapor Among Ground and Airborne Lidars and Sun Photometers During TARFOX

We compare aerosol optical thickness (AOT) and precipitable water vapor (PWV) measurements derived from ground and airborne lidars and Sun photometers during TARFOX (Tropospheric Aerosol Radiative Forcing Observational Experiment). Such comparisons are important to verify the consistency between various remote sensing measurements before employing them in any assessment of the impact of aerosols on the global radiation balance. Total scattering ratio and extinction profiles measured by the ground-based NASA/GSFC Scanning Raman Lidar (SRL) system, which operated from Wallops Island, Virginia (37.86 deg N, 75.51 deg W), are compared with those measured by the Lidar Atmospheric Sensing Experiment (LASE) airborne lidar system aboard the NASA ER-2 aircraft. Bias and rms differences indicate that these measurements generally agreed within about 10%. Aerosol extinction profiles and estimates of AOT are derived from both lidar measurements using a value for the aerosol extinction/backscattering ratio S(sub a)=60 sr for the aerosol extinction/backscattering ratio, which was determined from the Raman lidar measurements.

Ferrare, R.↗

The Discrepancy Between Measured and Modeled Downwelling Solar Irradiance at the Ground: Dependence on Water Vapor

Moderate resolution spectra of the downwelling solar irradiance at the ground in north central Oklahoma were measured during the Department of Energy Atmospheric Radiation Measurement Program Intensive Observation Period in the fall of 1997. Spectra obtained under-cloud-free conditions were compared with calculations using a coarse resolution radiative transfer model to examine the dependency of model-measurement bias on water vapor. It was found that the bias was highly correlated with water vapor and increased at a rate of 9 Wm per cm of water. The source of the discrepancy remains undetermined because of the complex dependencies of other variables, most notably aerosol optical depth, on water vapor.

Pilewski, P.↗

The Discrepancy Between Measured and Modeled Downwelling Solar Irradiance at the Ground: Dependence on Water Vapor

Moderate resolution spectra of the downwelling solar irradiance at the ground in north central Oklahoma were measured during the Department of Energy Atmospheric Radiation Measurement Program Intensive Observation Period in the fall of 1997. Spectra obtained under cloud-free conditions were compared with calculations using a coarse resolution radiative transfer model to examine the dependency of model-measurement bias on water vapor. It was found that the bias was highly correlated with water vapor and increased at a rate of 9 Wm(exp -2) per cm of water. The source of the discrepancy remains undetermined because of the complex dependencies of other variables, most notably aerosol optical depth, on water vapor.

Pilewskie, P.↗

Geophysical and Environmental Monitoring Data, and Subsurface Flow Modelling Results for Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO

This dataset includes geoelectrical monitoring data acquired between October 2021 and November 2022, soil moisture and temperature data, groundwater data obtained from borehole SNIB covering the period from June 2021 to September 2022, and hydrological modelling results. The data were acquired to investigate how variations in bedrock type and topography, and vegetation cover control subsurface flow dynamics. To provide insights into the subsurface flow dynamics and their controls, a monitoring transect was installed at the Chicken Bone Meadow, Mt. Snodgrass, Crested Butte, CO, measuring the spatio-temporal variations of soil moisture, soil and snow temperature, subsurface electrical resistivity variations, and groundwater dynamics. Field data are organized in a folder structure, with Electrical Resistivity Tomography (ERT) data being provided as one file per measurement, and data of the soil moisture and temperature sensors being provided as text files covering the entire monitoring period. The ‘Locations.csv’ file contains the location of all sensors, given in NAD83 – UTM Zone 13N. ERT monitoring data has been processed to filter data based on reciprocal errors (data with errors > 30% were removed), a linear error model was fitted to each survey, and to ensure a constant set of measurements for time-lapse inversion, filtered data were interpolated and assigned a 100% measurement error. Soil moisture and temperature data were acquired at 15 min intervals, and averaged to provide 1h data. Weather data and borehole data (groundwater depth, conductivity and temperature) were acquired at 30 min intervals, and are provided as daily measurements; all measurements are averaged, except of precipitation values, which are given as daily accumulation. The hydrological model was set up along the ERT monitoring transect, and net infiltration was used as surface boundary condition and derived from the weather data. Four different results are provided, (1) results for a parameterization using hydraulic permeability and porosity as derived from the ERT data through petrophysical relationships, and (2) three simplified model results, using 1 to 3 geological layers above the bedrock. Modelling was performed using PFLOTRAN, and for each model the PFLOTRAN input files are provided. The result files include weekly hydrological modelling results (e.g., saturation, velocities, pressures), as well as the model parameterization. The dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.

54 ENVIRONMENTAL SCIENCES↗

Retrieval Assimilation and Modeling of Atmospheric Water Vapor from Ground- and Space-Based GPS Networks: Investigation of the Global and Regional Hydrological Cycles

Uncertainty over the response of the atmospheric hydrological cycle (particularly the distribution of water vapor and cloudiness) to anthropogenic forcing is a primary source of doubt in current estimates of global climate sensitivity, which raises severe difficulties in evaluating its likely societal impact. Fortunately, a variety of advanced techniques and sensors are beginning to shed new light on the atmospheric hydrological cycle. One of the most promising makes use of the sensitivity of the Global Positioning System (GPS) to the thermodynamic state, and in particular the water vapor content, of the atmosphere through which the radio signals propagate. Our strategy to derive the maximum benefit for hydrological studies from the rapidly increasing GPS data stream will proceed in three stages: (1) systematically analyze and archive quality-controlled retrievals using state-of-the-art techniques; (2) employ both currently available and innovative assimilation procedures to incorporate these determinations into advanced regional and global atmospheric models and assess their effects; and (3) apply the results to investigate selected scientific issues of relevance to regional and global hydrological studies. An archive of GPS-based estimation of total zenith delay (TZD) data and water vapor where applicable has been established with expanded automated quality control. The accuracy of the GPS estimates is being monitored; the investigation of systematic errors is ongoing using comparisons with water vapor radiometers. Meteorological packages have been implemented. The accuracy and utilization of the TZD estimates has been improved by implementing a troposphere gradient model. GPS-based gradients have been validated as real atmospheric moisture gradients, establishing a link between the estimated gradients and the passage of weather fronts. We have developed a generalized ray tracing inversion scheme that can be used to analyze occultation data acquired from space- or land-based receivers. The National Center for Atmospheric Research mesoscale model (version MM5) has been adapted for Southern California, and assimilation studies are underway. Additional information is contained in the original.

Dickey, Jean O.↗

Modeling the impact of riparian hollows on river corridor nitrogen exports, Frontiers in Water: Dataset

This package contains all reactive transport simulation outputs used in "Modeling the impact of riparian hollows on river corridor nitrogen exports" (Rogers, D.B., et al., 2021). The simulation outputs reflect hydrological and biogeochemical behavior of a single, generalized riparian hollow located in the intra-meander region of a sub-alpine floodplain under transient hydrological conditions. The context for, purpose of, and conclusions drawn from this model are detailed in Rogers, D.B., et al., 2021.The .zip file contains simulation outputs for each of the five time periods analyzed (see metadata for specific dates), with each folder representing one continuous simulation period. Within each folder are the raw simulation outputs, which are comprised of hundreds of files. Files ending in ".vtk" are best visualized and analyzed using ParaView (https://www.paraview.org). All other files are best viewed or analyzed using R. For a detailed description of the meaning of each file, refer to the ".fls" file located in each folder.

54 ENVIRONMENTAL SCIENCES↗

Groundwater table elevation and temperature from 2015 to 2024 at the Lower Montane site in the East River Watershed, Colorado.

This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells with Location ID's ER-DOW (alias DO1West), ER-DOE (alias DO2East), ER-MBA1 (alias M1Bend1), ER-MBA2 (alias M1Bend2), ER-UPW (alias UP1West), ER-UPM (alias UP2), ER-UPE (alias UP3East). Another dataset contains the data from wells with Location ID's ER-CPA1 to ER-CPA6. Each file contains the water level elevation and the water temperature. Water level elevation has been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file Well_Location.csv). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements were initially added to the archive for the period 2015 to 2019, and later updated with time-series until 2024 (end of data collection). The dataset contains 8 *.csv data files, and 3 *.csv metadata files. Feel free to contact the author with any questions or collaboration interests. The publication year was updated from "2020" to "2025" to reflect the revised version of this dataset.

54 ENVIRONMENTAL SCIENCES↗