Engineering topics

Wainwright, Haruko

Publications and source records attributed to Wainwright, Haruko.

At least 55 records · Page 3

DOE OSTI2020

Emerging technologies and radical collaboration to advance predictive understanding of watershed hydrobiogeochemistry

Increasing population and resource-intensive lifestyles are driving enhanced demands for clean water, food, and energy. In parallel, land-use change, climate change, and perturbations—including drought, floods, fires, and early snowmelt—are significantly reshaping interactions within watersheds throughout the world. While watersheds are the Earth's key functional unit for assessing and managing water resources, hydrological processes in watersheds also mediate biogeochemical interactions that support terrestrial life on Earth (Kaushal, Gold, Bernal, & Tank, 2018; National Research Council, 2012). Although society is dependent upon clean water availability, tractable prediction of watershed hydrobiogeochemical behavior, including watershed response to perturbations, remains a challenge. Central to the challenge are complex, multiscale interactions between plants, microorganisms, organic matter, minerals, dissolved constituents, and migrating fluids, which occur within and across bedrock-to-canopy compartments and along extensive lateral gradients of a watershed. Several recent community reports have synthesized formidable challenges associated with watershed science and technology (AGU, 2018; Blöschl et al., 2019). Here, we discuss emerging technologies and collaboration modes that are critical for developing generalizable insights about and predictive understanding of complex watershed hydrobiogeochemical behavior, which are important for underpinning optimized natural resource management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters

Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest surrounding Crested Butte, CO with remotely sensed data, including LiDAR. The flight box design encompassed the watersheds, surveying a total area of 334 km2 across 72 lines. The instrument used was an Optech Gemini, with a pulse density of 2-9 pulses m-2 across the study area (see final report document for detailed information (Goulden and Musinsky 2020). These LiDAR data are the primary data that were provided by NEON, and include both LiDAR source data and derived surface products. The source data are contained in 'crbu_laz.zip' and 'classified_point_cloud.zip. 'classified_point_cloud.zip' represents an additional processing level on 'crbu_laz.zip'. The derived products are 'dsm_mosaic_min_phase_me.tif', 'dtm_mosaic_min_phase_me.tif', and 'tch_mosaic_min_phase_me.tif'. These files are raster mosaics of a digital surface elevation model (DSM), digital terrain elevation model (DTM), and a canopy height model (CHM) at 1 m resolution with a height threshold of > 2 m, respectively, in geotiff (.tif) format. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. [UPDATE] On 06/26/2026 the files 'crbu_laz.zip' and 'classified_point_cloud.zip' were replaced with original output files from NEON to address zip file corruption and naming errors. No changes were made to the underlying data. (See Methods Step 2 for details).

2018 NEON and 2025 CHESS Campaigns↗

DOE OSTI2020

NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset

Lawrence Berkeley National Laboratory (LBNL) contracted the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) to observe watersheds of interest near Crested Butte, CO with remotely sensed data including imaging spectroscopy. The flight box design encompassed the watersheds, and flight design targeted a minimum of 30% overlap between adjacent flight lines. The total area surveyed was 334 km2 across 72 lines. Flight lines were oriented north-south for consistency in solar illumination geometry. Seven days were required to cover the flight area. Some areas were flown additional times to improve data quality or temporal coincidence between airborne acquisitions and field sampling. In total, 102 lines were collected and can be downloaded here: https://portal.nersc.gov/wfsfa/doi-10-15485-1617204/. The instrument used for the acquisition was an Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG), which records radiance within 426 contiguous spectral bands in the wavelength range from 380 to 2510 nm. The instrument was flown at a target aboveground altitude of 1000 m for a processed data spatial resolution of 1 m. These data are non-orthorectified, radiance data that require further processing prior to use as a surface reflectance data set.

2018 NEON and 2025 CHESS Campaigns↗

DOE OSTI2020

Genome-resolved metagenomics and metatranscriptomics of microbial communities in three meander-bound floodplain soils along the East River, Colorado.

This dataset comprises paired environmental and genomic data for soil samples collected across meander-bound floodplains G (ERMG), L (ERML) and Z (ERMZ). A total of 96 soil samples (32 per floodplain) from the ~ 10-25 cm layer were collected in September 2015, during base flow conditions. An additional 32 soil samples were collected from ERML in September 2016, including three samples from a depth just above the water table. A subset of samples (14) collected in 2016 were used for metatranscriptomics as well as metagenomics. The data package includes: 1) A spread sheet with sample names, location and depth by meander-bound floodplain. 2) Total organic carbon (TOC), total inorganic carbon (TIC), total carbon (TC = TOC + TIC), total nitrogen (TN), and the TOC to TN ratio (TOC:N) from 2015 subsamples. 3) Soil chemistry for 2016 subsamples. 4) A spread sheet with elevation, Easting, Northing, and topographic position index (TPI) for each site sampled in 2015. 5) A kml file, which can be viewed in Google Earth, with the locations of the 96 soil sampling sites along the East River Watershed Floodplain in Colorado. Metagenomics and metatranscriptomics data, as well as reconstructed genomes, are available elsewhere (see data package methods and bioRxiv preprint for links to the data). 6) Two sets of reconstructed genomes with overlapping members (see bioRxiv preprint for description and associated data). Metagenomes and metatranscriptomes are available elsewhere (see data package methods and bioRxiv preprint). To view tar.gz files, the following software can be used: https://www.gnu.org/software/tar/, https://www.7-zip.org/.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Gap-filled water quality, Normalized Differenced Vegetation Index, total nitrogen (nitrate and ammonia) deposition, and land cover data trends for the Continental United States

The purpose of this work was to quantify trends in water quality, total nitrogen deposition, vegetation, and land-use trends for the Continental United States (CONUS). This dataset contains gap-filled daily and yearly in-stream carbon (C) and nitrogen (N) concentrations, discharge, and calculated exports from United States Geological Survey (USGS) National Water Information System (NWIS) stations across the United States of six different nitrogen parameters (Supplementary Table A1), one carbon parameter, and temperature (USGS, 2016, 2018) (https://waterdata.usgs.gov/nwis). The final water quality dataset is merged with the normalized differenced vegetation index (NDVI), total deposition (TDEP), landcover, and elevation datasets. All data are available at the CONUS scale as well as at the scale of hydrologic unit codes: (HUC) HUC8, HUC6, HUC4, and HUC2 watersheds. There are two zip files associated with this data package. I split the data into two equal sized zip files to comply with the data size limits, however the datasets are the same within each zip file. All data files can be read in directly into the R software.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Time-domain reflectometer survey across the East River Watershed, Colorado

Lawrence Berkeley National Laboratory (LBNL) collected near-surface point-measurements of soil temperature (file variable TDR_T(C)), volumetric water content (file variable TDR_SM(VWC%)), and soil electrical conductivity (file variable TDR_EC(mS/m)) using a time-domain reflectometer (TDR) at a depth of 25 cm. The survey aimed to characterize the spatial heterogeneity of near-surface hydrological properties at the hillslope scale considering sites with different aspects and elevation within the watershed. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. These data were collected in early July 2019 over four hillslope sites: Pumphouse (north-east facing slope), Bradley (west and east-facing slopes), and Snodgrass (east-facing slope) within the East River watershed. Part of this survey was used to investigate soil-plant interactions at the hillslope scale in Jashvina et al. 2020.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Plant density and enhanced plant vigor estimation for high-resolution images v1

The package contains algorithms for the estimation of sprout/plant density and the corresponding enhanced plant vigor from remotely sensed (RS) images. These algorithms aim to improve the plant characterization and monitoring in the early season when the soil component is significant compared to the plant spatial coverage. In such a scenario, the identification of sprouts (or plants) and the estimation of plant vegetation indexes can be performed only using UAV-acquired images. Additionally, because of the extremely high resolution, gridding becomes necessary to improve visualization and provide more informative maps. However, to capture the real range of values of the VIs, it is important to avoid the inclusion of those pixels belonging to the soil component. The sprout/plant density estimation algorithm takes in input a classification map and uses the vegetation class to estimates the plant density within a user-defined grid using a floating window. Similarly, the enhanced plant vigor algorithm takes in input the vegetation index and the classification map. The enhanced vegetation index is computed for each pixel as the average value among those pixels that belong to the vegetation class within a floating window. The software is developed for the MATLAB environment.

Falco, Nicola↗

DOE OSTI2019

Optimizing Long-term Monitoring of Radiation Air Dose Rates - 19169

Radiation air dose rates near the Fukushima Daiichi Nuclear Power Plant (NPP) have been steadily decreasing over the past seven years since the accident in March 2011. After seven years, the radiation monitoring program is expected to transition from short-term emergency responses to long-term monitoring. The objectives of long-term monitoring are often different from early emergency responses, since extensive data accumulation has led to an understanding of contaminant distributions and mobility. The main long-term monitoring objectives are (1) to confirm system stability and the continuing reduction of contaminant and hazard levels, (2) to provide assurance for the public, (3) to accumulate the basic datasets for scientific knowledge and future preparation, and (4) to detect changes or anomalies in contaminant mobility (if they occur), or any unexpected processes or events. In this work, we have developed a methodology for optimizing the sampling locations of radiation air dose-rate monitoring. Three steps are taken in order to determine sampling locations in a systematic manner: (1) prioritizing the critical locations, such as schools or regulatory requirement locations, (2) diversifying locations across the key environmental controls that are known to influence contaminant mobility and distributions, and (3) capturing the heterogeneity of radiation air dose rates across the domain. In the second step, we use a Gaussian mixture model to identify the representative locations in multiple environmental variables, such as elevation and land-cover types. In the third step, we use a Gaussian process model to capture and estimate the heterogeneity of air dose rates across the domain. We use the integrated dose-rate map from the Bayesian geostatistical method as the reference map and distribute the sampling in such a way as to capture the heterogeneity of the reference map. Although we assume hypothetical sets of measurement locations to evaluate the performance of the methodology and algorithms, we have demonstrated this approach using real, spatially extensive datasets, including the integrated air-dose-rate map of 2016. Our results have shown that this approach allows us to add sampling locations in a systematic manner. Increasing the number of sampling locations can better capture the heterogeneity of dose rates, although the estimation error does not decrease further after a certain number of samples. We have also found that when there are restrictions such as pre-existing monitoring locations or the ones along roads, the spatial estimation becomes poor even with the same number of monitoring locations. (authors)

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DOE OSTI2019

Hydrological Controls on Residual Contaminants Under Sustainable Remediation - 19287

This paper investigates the impact of natural aquifer's recharge shifts induced by precipitation changes on residual contaminants located in soil and groundwater, subject to sustainable remediation techniques. We illustrate five climate change scenarios which mimic shifts in the natural recharge regime. We evaluate the impact on different performance metrics that include contaminant concentrations at observation wells and contaminant export to a creek. The approach is demonstrated by simulating the tritium plume migration within a U.S. Department of Energy's nuclear reservations: the Savannah River Site F-Area. Results show that increasing the aquifers' recharge initially causes a decrease in the well concentrations due to dilution, and subsequently an increase due to the mobilization of contaminants from the vadose zone. As the recharge shift increases, the peak concentration is higher and may occur at an earlier stage. The mobilized contaminants reach the wells or control planes several years or decades later than the precipitation events thus monitoring near the source zone is important for early detecting mobilized contaminants. Moreover, we observe that, even when the well concentrations are significantly affected, the export at the control planes may not be affected by shifts in the natural recharge regime therefore the risk of downgradient population may be under control even under significant hydrological changes. (authors)

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DOE OSTI2019

Climate change impact on residual contaminants under sustainable remediation

This study investigates the potential impact of climate change on residual contaminants in vadose zones and groundwater. We assume that the effect of climate changes can be represented by perturbations in the natural recharge through the aquifer system. We perform numerical modeling of unsaturated/saturated flow and transport and consider different performance metrics: contaminant concentrations at observation wells and contaminant export at the site's boundary. We evaluate the effect of increasing and decreasing recharge as well as the impact of potential failure of surface capping structures employed to immobilize vadose zone contaminants. Our approach is demonstrated in a real case study by simulating transport of non-reactive radioactive tritium at the U.S. Department of Energy's Savannah River Site. Results show that recharge changes significantly affect well concentrations: after an initial slight dilution we identify a significant concentration increase at different observation wells some years after the recharge increase and/or the cap failure, as a consequence of contaminants' mobilization. This effect is generally emphasized and occurs earlier as the recharge increases. Under decreased aquifers' recharge the concentration could slightly increase for some years, due to a decrease of dilution, depending on the magnitude of the negative recharge shift. We identify trigger levels of recharge above which the concentration/export breakthrough curves and the time of exceedance of the Maximum Contaminant Level for tritium are remarkably affected. Moreover, we observe that the contaminant export at the control plane, identified as the risk pathway to the downgradient population, may only be minimally affected by shifts in the natural recharge regime, except for some extreme cases. We conclude that more frequent sampling and in-situ monitoring near the source zone should be adopted to better explain concentrations' anomalies under changing climatic conditions. Moreover, the maintenance of the cap is critical not only to sequester residual contaminants in the vadose zone, but also to reduce the uncertainty associated with future precipitation changes. Finally, realistic flow and transport simulations achieved through proper calibration processes, rather than conservative modeling, should be adopted to identify non-trivial trade-offs which enable better allocation of resources towards reducing uncertainty in decision making.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Investigating Microtopographic and Soil Controls on a Mountainous Meadow Plant Community Using High-Resolution Remote Sensing and Surface Geophysical Data

Our study aims to explore the microtopographic controls that dictate the heterogeneity of plant communities in a mountainous floodplain-hillslope system, using remote sensing and surface geophysical techniques. Working within a lower montane floodplain-hillslope study site (750 m × 750 m) in the Upper Colorado River Basin, we developed a new data fusion framework, based on machine learning and feature engineering, that exploits remote sensing optical and light detection and ranging (LiDAR) data to estimate the distribution of key plant meadow communities at submeter resolution. We collected surface electrical resistivity tomography data to explore the variability in soil properties along a floodplain-hillslope transect at 0.50-m resolution and extracted LiDAR-derived metrics to model the rapid change in microtopography. Furthermore, we investigated the covariability among the estimated plant community distributions, soil information, and topographic metrics. Results show that our framework estimated the distribution of nine plant communities with higher accuracy (87% versus 80% overall; 85% versus 60% for shrubs) compared to conventional classification approaches. Analysis of the covariabilities reveals a strong correlation between plant community distribution, soil electric conductivity, and slope, indicating that soil moisture is a primary control on heterogeneous spatial distribution. At the same time, microtopography plays an important role in creating particular ecosystem niches for some of the communities. Such relationships could be exploited to provide information about the spatial variability of soil properties. This highly transferable framework can be employed within long-term monitoring to capture community-specific physiological responses to perturbations, offering the possibility of bridging local plot-scale observations with large landscape monitoring.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Remote sensing and geophysical characterization of a floodplain-hillslope system in the East River watershed, Colorado

This package is part of the Watershed Function SFA Data Collection and contains remote sensing data and geophysical measurements acquired at the Pumphouse hillslope-floodplain site, in the East River, Colorado. The remote sensing dataset includes: a) a WorldView-2 (WV-2) pan-sharpened multi-spectral remote sensing image, and b) LiDAR derived products. The WV-2 image was acquired on September 24th, 2015, and it is composed of eight spectral bands (coastal, blue, green, yellow, red, red edge, NIR1, and NIR2) with a spatial resolution of 0.5 m, covering an area of 750x750 m. The LiDAR products are a digital surface model (DSM), representing the top-of-canopy elevation, and a digital terrain model (DTM), representing the bare-ground elevation, at the spatial resolution of 0.5 m. Such data are extracted from the LiDAR point-cloud dataset acquired over the entire watershed on August 2015 (http://dx.doi.org/10.21952/WTR/1412542). The geophysical dataset is composed of the electrical resistivity tomography (ERT) data acquired along a 158.75 m long transect, spanning the hillslope topographical gradient with 1.25 m electrode spacing. The dataset also includes soil water content measured with a TDR system. The package provides also polygons of different vegetation communities, which were used as reference data for mapping plant community distributions. The spatial polygons are based on plant locations acquired during the field campaign of June-July 2017 using an RTK DGPS system. The reference dataset is composed by 11 vegetation classes, namely, deciduous forest, evergreen forest, riparian shrubland, sagebrush, shrubland, potentilla, frasera, lupine meadow, veratrum, bunchgrass meadow, and forb, as well as four non-vegetation classes, such as water-river, water-lake, man-made, bare area, and shadow. The vegetation classes are determined based on distinct spectral and/or structural signatures of dominant species. The package includes products derived by these datasets, such as: a) a plant height map, computed by subtracting the DTM from the DSM, and b) a plant community distribution map, obtained by using a data-fusion machine-learning-based framework that exploit the WV-2 image and plant height information.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Time domain-induced polarization geophysical data collected in the Rifle Floodplain, Colorado, USA

The IP data set was collected using a time domain-induced polarization (TDIP) method along 65 profiles of various lengths over the floodplain. Surface time domain?induced polarization (TDIP) data was collected to create the 3?D images of the complex electrical resistivity, in terms of magnitude and phase, which are associated with mineral precipitation and other lithological properties. The TDIP data was then used to estimate the spatial distribution of naturally reduced zones, which are known to be biogeochemical hotspots in floodplains having increased uranium and other redox-sensitive metal concentrations as well as high carbon contents. In the TDIP method, the transient decay of voltage is measured after current shut-off, typically in the form of an integral of decay curves over a predefined time window (so-called integral chargeability). TDIP measurements at the site were collected using the Syscal Iris Pro Switch equipment with a square-wave current injection, 50% duty cycle, and a pulse length of 2 s. The integral chargeability measurements were carried out using 20 windows during voltage decay between 240 and 1840 ms after current shut-off. Tomographic measurements were collected by deploying stainless steel electrodes with an electrode separation of 1.8 m and using a dipole-dipole ‘‘skip-2’’ and ‘‘skip-3’’ measuring protocol (i.e., for a dipoles length of 5.4 and 7.2 m, respectively). The sequence of dipole-dipole measurements was carefully arranged to (1) minimize unwanted electromagnetic coupling effects in the data, avoiding potential measurements with electrodes located inside the current dipole, (2) prevent voltage measurements using electrodes, which might be polarized due to previous current injection, and (3) increase the signal-to-noise ratio for an intended exploration depth of 8 m, i.e., the bottom of the aquifer. All measurements were collected as normal and reciprocal pairs for estimation of the data error. The IP measurements were collected with symmetric arrays (i.e., the measuring equipment placed at the center of the electrode array) with a maximum of 36 electrodes, considering that longer profiles revealed a significant increase in the normal-reciprocal misfit for the measurements of the decay curve, probably due to greater impact of electromagnetic coupling on the data. The TDIP data sets were inverted in a twodimensional domain along each transect using CRTomo, which is a smoothness-constraint inversion code based on a finite element algorithm. The resistivity and phase shift values at each pixel were then assigned at the corresponding point within the 3-D floodplain domain (the black rectangle Figure 1b) and used in the 3-D estimation. The TDIP inversion results provided the distribution of the complex resistivity, expressed in terms of its magnitude and phase-shift. The analysis of the normal-reciprocal misfit was used to estimate the relative error. We removed the measurement with smallest voltage difference (<2 mV), representing about 2% variations in the data. For the inversion of TDIP measurements, chargeability values were linearly converted to frequency domain phase values (at the fundamental frequency of 0.125 Hz), by assuming a constant-phase response. This approach has been demonstrated to provide consistent results in previous studies

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

The East River, Colorado, Watershed: A Mountainous Community Testbed for Improving Predictive Understanding of Multiscale Hydrological–Biogeochemical Dynamics

Core Ideas Development of a 300‐km 2 mountainous headwater testbed began in 2016 in the East River. The testbed can be used to explore how watershed changes impact downgradient water availability and quality. System‐of‐system, scale‐adaptive approaches can potentially improve watershed dynamics simulation. We have new approaches to monitor and simulate water partitioning and system responses. The East River watershed has been developed as a “community” testbed. Extreme weather, fires, and land use and climate change are significantly reshaping interactions within watersheds throughout the world. Although hydrological–biogeochemical interactions within watersheds can impact many services valued by society, uncertainty associated with predicting hydrology‐driven biogeochemical watershed dynamics remains high. With an aim to reduce this uncertainty, an approximately 300‐km 2 mountainous headwater observatory has been developed at the East River, CO, watershed of the Upper Colorado River Basin. The site is being used as a testbed for the Department of Energy supported Watershed Function Project and collaborative efforts. Building on insights gained from research at the “sister” Rifle, CO, site, coordinated studies are underway at the East River site to gain a predictive understanding of how the mountainous watershed retains and releases water, nutrients, carbon, and metals. In particular, the project is exploring how early snowmelt, drought, and other disturbances influence hydrological–biogeochemical watershed dynamics at seasonal to decadal timescales. A system‐of‐systems perspective and a scale‐adaptive simulation approach, involving the combined use of archetypal watershed subsystem “intensive sites” are being tested at the site to inform aggregated watershed predictions of downgradient exports. Complementing intensive site hydrological, geochemical, geophysical, microbiological, geological, and vegetation datasets are long‐term, distributed measurement stations and specialized experimental and observational campaigns. Several recent research advances provide insights about the intensive sites as well as aggregated watershed behavior. The East River “community testbed” is currently hosting scientists from more than 30 institutions to advance mountainous watershed methods and understanding.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

In Situ Monitoring of Groundwater Contamination for Sustainable Remediation Using the Kalman Filter - 18423

Groundwater monitoring is critical for nuclear-related facilities as well as radioactively contaminated sites. Recent advances in sensing, data analytics and simulation capabilities provide substantial opportunities to improve and change current monitoring procedures. In particular, we need a paradigm shift from contaminant-only or compliance-only monitoring programs to comprehensive monitoring, i.e., including other ancillary environmental variables for a holistic understanding of the groundwater systems and plume behaviors. Such new approaches are needed for the effective implementation of sustainable remediation (enhanced and natural attenuation), and they have great potential for cost reduction in site monitoring. This paper reviews recent developments for improving long-term monitoring, with focus on the effective use of in situ sensors, data analytics and simulation capabilities. In particular, we highlight a recent application of the Kalman filter algorithm to estimate contaminant concentrations continuously in real time, based on in-situ measured water quality parameters (e.g. electrical conductance and pH) and sparse groundwater sampling. The results show that we can reduce the groundwater sampling frequency significantly, while capturing the dynamics of short- and long-term contaminant concentration changes. Such advanced and integrated monitoring systems will be beneficial for local residents (e.g., to ensure the safety by detecting adverse events early, enabling a swift response) as well as for site operators (e.g., to gain/improve public acceptance, to be better prepared for litigations and false claims, and to reduce overall monitoring cost). (authors)

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DOE OSTI2018

Technical Advances for Sustainable Remediation: In Situ Monitoring and Climate Resiliency - 18436

Recent advances in sustainable remediation techniques show promise as solutions for contaminant removal in soil and groundwater media. Although passive remediation (or natural attenuation) has gained momentum as an acceptable technique, there are still challenges in regulatory frameworks as well as in public acceptance. Leaving contaminants in subsurface requires increased burden of proof to show that plumes are stable and residual contaminants do not pose a significant health risk. Climate changes and frequent extreme climate events contribute another level of complexity and make it difficult to demonstrate system stability and predict future plume conditions. In this study, we show two coupled approaches to tackle this challenge: (1) in situ groundwater monitoring based on advanced sensor and data analytics technologies (i.e., Big Data), and (2) state-of-art modeling for optimizing monitoring and site closure strategies. In the new monitoring approach, in situ sensors are used to continuously measure the key variables that control contaminant plume mobility and its spatial and temporal distribution (such as pH, redox potential, electrical conductivity, and groundwater level). Coupled with a limited number of groundwater sampling, the data analytics methods - data mining and machine learning - allow us to estimate contaminant concentrations, and also to detect any significant changes associated with the plume mobility. In parallel, the state-of-art numerical flow and reactive transport model - ASCEM software under DOE Office of Environmental Management - provides a physical and mechanistic understanding of the system behavior, and predicts the long-term plume migration for optimizing the monitoring and closure strategies. In particular, we focus on the effects of extreme precipitation or drought on the site closure as well as monitoring strategies. We demonstrate this approach at the Savannah River Site (SRS) F-Area, where groundwater is contaminated by various radionuclides, including uranium, tritium and technetium. (authors)

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DOE OSTI2018

Integrating Multiscale Datasets for Monitoring Air Dose Rates in Fukushima - 18437

Six years has passed since the radionuclide release occurred at the Fukushima Daiichi NPP. Measurements and monitoring of air dose rates (i.e., ambient dose equivalent rates) in the region around the Fukushima Daiichi NPP have been performed continuously since the accident. Such mapping efforts are essential to protect the public, to guide decontamination efforts, and to plan the return of evacuated residents. An extensive monitoring program has enabled to develop a data-driven environmental decay model for describing and predicting the decay of radiation air dose rates in the environment. However, it has been difficult to quantify the heterogeneity of environmental decay in the regional scale, since spatially extensive airborne survey datasets often have discrepancy with the ground-based measurements and have a larger uncertainty. Recently, a Bayesian hierarchical modeling approach was developed to integrate multiscale datasets (i.e., car, walk and airborne surveys), and also to estimate the spatial distribution of air dose rates in high resolution over space. The integrated air dose rate maps have been contributed to planning of the future decontamination and resident's return as well as associated cost. In this study, we aim to extend this approach and predict the area of the evacuation zone in the future. WE coupled the integrated map with the data-driven ecological decay model. Results show that the area of vacuation zone (i.e., the area above 3.8 micro-Sv/yr) will shrink significantly in the next twenty years, and it will be fully contained in the non-residential forested area by 2040. (authors)

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DOE OSTI2018

Climatic Controls on Residual Contaminants Under Sustainable Remediation - 18699

We investigate the impact of climate change on residual contaminants in soil and groundwater under sustainable remediation. We illustrate seven climate change scenarios which mimic shifts in the precipitation regime as well as the failure of the source-zone cap. We evaluate different performance metrics including contaminant concentrations at multiple wells and export to a creek. The approach is demonstrated by simulating the tritium plume migration at the Savannah River Site F-Area, USA. The cap integrity is critical not only to reduce the well concentrations and export but also to reduce the uncertainty associated with the climatic variability. Sampling or in situ monitoring near the source zone is important for the early detection of plume mobility changes. Realistic hydrological models are necessary to evaluate the trade-offs (mobility vs dilution)

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