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Environmental contamination by radioactive materials can be characterized by in situ gamma surface measurements. During such measurements, the field of view of a gamma detector can be tens of meters wide, resulting in a count rate that integrates the signal over a large measurement support volume/area. The contribution of a specific point to the signal depends on various parameters, such as the height of the detector above the ground surface, the gamma energy and the detector properties, etc. To improve the spatial resolution of the activity concentration, contributions of a radionuclide from nearby areas to the count rate of a single measurement should be disentangled. The experiments described in this paper, deployed 2D inversion of in situ gamma spectrometric measurements using a non-negative least squares-based Tikhonov regularization method. Data were acquired using a portable LaBr3 gamma detector. The detector response as a function of the distance of the radioactive source, required for the inversion process, was simulated using the Monte Carlo N-Particle (MCNP) transport code. The uncertainty on activity concentration was calculated using the Monte Carlo error propagation method. The 2D inversion methodology was first satisfactorily assessed for 133Ba and 137Cs source activity distributions using reference pads. Secondly, this method was applied on a 137Cs contaminated site, making use of above-ground in-situ gamma spectrometry measurements, conducted on a regular grid. The inversion process results were compared with the results from in-situ borehole measurements and laboratory analyses of soil samples. The calculated 137Cs activity concentration levels were compared against the activity concentration value for exemption or clearance of materials which can be applied by default to any amount and any type of solid material. Using the 2D inversion and the Monte Carlo error propagation method, a high spatial resolution classification of the site, in terms of exceeding the exemption limit, could be made. The137Cs activity concentrations obtained using the inversion process agreed well with the results from the in-situ borehole measurements and those from the soil samples, showing that the 2D inversion is a convenient approach to deconvolute the contribution of radioactive sources from nearby areas within a detector's field of view, and increases the resolution of spatial contamination mapping.

Heat is a naturally occurring, widespread groundwater tracer that can be used to identify flow patterns in groundwater systems. Temperature measurements, being relatively inexpensive and effortless to gather, represent a valuable source of information which can be exploited to reduce uncertainties on groundwater flow, and, for example, support performance assessment studies on waste disposal sites. In a lowland setting, however, hydraulic gradients are typically small, and whether temperature measurements can be used to inform us about catchment-scale groundwater flow remains an open question. For the Neogene Aquifer in Flanders, groundwater flow and solute transport models have been developed in the framework of safety and feasibility studies for the underlying Boom Clay formation as a potential host rock for geological disposal of radioactive waste. However, the simulated fluxes by these models are still subject to large uncertainties as they are typically constrained by hydraulic heads only. In the current study, we use a state-of-the-art 3D steady-state groundwater flow model, calibrated against hydraulic head measurements, to build a 3D transient heat transport model, for assessing the use of heat as an additional state variable, in a lowland setting and at the catchment scale. We therefore use temperature–depth (TD) profiles as additional state variable observations for inverse conditioning. Furthermore, a Holocene paleo-temperature time curve was constructed based on paleo-temperature reconstructions in Europe from several sources in combination with land surface temperature (LST) remotely sensed monthly data from 2001 to 2019 (retrieved from NASA's Moderate Resolution Imaging Spectroradiometer, MODIS). The aim of the research is to understand the mechanisms of heat transport and to characterize the temperature distribution and dynamics in the Neogene Aquifer. The simulation results clearly underline advection/convection and conduction as the major heat transport mechanisms, with a reduced role of advection/convection in zones where flux magnitudes are low, which suggests that temperature is also a useful indicator in a lowland setting. Furthermore, the performed scenarios highlight the important roles of (i) surface hydrological features and withdrawals driving local groundwater flow systems and (ii) the inclusion of subsurface features like faults in the conceptualization and development of hydrogeological investigations. These findings serve as a proxy of the influence of advective transport and barrier/conduit role of faults, particularly for the Rauw fault in this case, and suggest that solutes released from the Boom Clay might be affected in similar ways.

We present three methodological improvements of the "SCK CEN approach" for Bayesian inference of the radionuclide inventory in radioactive waste drums, from radiological measurements. First we resort to the Dirichlet distribution for the prior distribution of the isotopic vector. The Dirichlet distribution possesses the attractive property that the elements of its vector samples sum up to 1. Second, we demonstrate that such Dirichlet priors can be incorporated within an hierarchical modeling of the prior uncertainty in the isotopic vector, when prior information about isotopic composition is available. Our used Bayesian hierarchical modeling framework makes use of this available information but also acknowledges its uncertainty by letting to a controlled extent the information content of the indirect measurement data (i.e., gamma and neutron counts) shape the actual prior distribution of the isotopic vector. Third, we propose to regularize the Bayesian inversion by using Gaussian process (GP) prior modeling when inferring 1D spatially-distributed quantities. As of uncertainty in the efficiencies, we keep using the same stylized drum modeling approach as proposed in our previous work to account for the source distribution uncertainty across the vertical direction of the drum. A series of synthetic tests followed by application to a real waste drum show that combining hierarchical modeling of the prior isotopic composition uncertainty together with GP prior modeling of the vertical Pu profile across the drum works well. We also find that our GP prior can handles both cases with and without spatial correlation. The computational times involved by our proposed approach are on the order of a few hours, say about 2, to provide uncertainty estimates for all variables of interest in the considered inverse problem. This warrants further investigations to speed up the inference., arXiv admin note: text overlap with arXiv:2101.02112

Heat is a naturally occurring widespread groundwater tracer that can be used to identify flow patterns in groundwater systems. Temperature measurements, being relatively inexpensive and effortless to gather, represent a valuable source of information which can be exploited to reduce uncertainties on groundwater flow, and e.g. support performance assessment studies on waste disposal sites. In a lowland setting, however, hydraulic gradients are typically small, and whether temperature measurements can be used to inform us about catchment-scale groundwater flow remains an open question. For the Neogene aquifer in Flanders, groundwater flow and solute transport models have been developed in the framework of safety and feasibility studies for the underlying Boom Clay Formation as potential host rock for geological disposal of radioactive waste. However, the simulated fluxes by these models are still subject to large uncertainties, as they are typically constrained by hydraulic heads only. In the current study we use a state-of-the-art 3D steady-state groundwater flow model, calibrated against hydraulic head measurements, to build a 3D transient heat-transport model, for assessing the use of heat as an additional state variable, in a lowland setting, at the catchment scale. We therefore use temperature-depth (TD) profiles as additional state variable observations for inverse conditioning. Furthermore, a Holocene paleo-temperature time curve was constructed based on paleo-temperature reconstructions in Europe from several sources in combination with land-surface temperature (LST) imagery remote sensing monthly data from 2001 to 2019 (retrieved from NASA’s MODIS). The aim of the research is to understand the mechanisms of heat transport and to characterize the temperature distribution and dynamics in the Neogene aquifer. The simulation results clearly underline advection/convection and conduction as the major heat transport mechanisms, with a reduced role of advection/convection in zones where flux magnitudes are low, which suggests temperature is a useful indicator also in a lowland setting. Furthermore, performed scenarios highlight the important roles of i) surface hydrological features and withdrawals driving local groundwater flow systems, and ii) the inclusion of subsurface features like faults in the conceptualization and development of hydrogeological investigations. These findings serve as a proxy of the influence of advective transport and barrier/conduit role of faults, particularly the Rauw Fault in this case, and suggest that solutes released from the Boom Clay might be affected in similar ways.

Within the H2020 INSIDER project, the main objective of work package 3 (WP3) is to draft a sampling guide for initial nuclear site characterization in constraint environments, before decommissioning, based on a statistical approach. The second task of WP3 aims at developing a strategy for sampling in the field of initial nuclear site characterization in view of decommissioning, with the most important goal to guide the end user to appropriate statistical methods (including, but not limited to those identified during the first overview task) to use for data analysis and sampling design. To aid the end user in applying this strategy, a user-friendly application for guiding the end user through the contents of the strategy and the initial characterization process is also developed.

Aiming at economical optimization, the characterisation of the biological shield of the Belgian Reactor 3 is one of the three use cases intended to validate the integrated characterization methodology developed within the INSIDER project. Pre-existing data were used to define the sampling design strategy. The additional sampling and analysis program consisted of total gamma measurements at the inner surface of the biological shield (secondary data) and gamma spectrometry measurements on drill core samples (primary data). The newly acquired data is supplemented with the historical available data. The full data set currently consists of a total of 283 secondary and 379 primary data points. Preliminary calculations already provide a clear-cut representation of the three different end-stage classes: unconditional clearance, conditional clearance and radioactive waste. On the short term, the current model will be further refined and completed with proper risk evaluation. On the longer term, we envisage a global uncertainty calculation and sensitivity analysis of the entire process.

Cone penetration testing (CPT) is one of the most efficient and versatile methods currently available for geotechnical, lithostratigraphic and hydrogeological site characterization. Currently available methods for soil behaviour type classification (SBT) of CPT data however have severe limitations, often restricting their application to a local scale. For parameterization of regional groundwater flow or geotechnical models, and delineation of regional hydro- or lithostratigraphy, regional SBT classification would be very useful. This paper investigates the use of model-based clustering for SBT classification, and the influence of different clustering approaches on the properties and spatial distribution of the obtained soil classes. We additionally propose a methodology for automated lithostratigraphic mapping of regionally occurring sedimentary units using SBT classification. The methodology is applied to a large CPT dataset, covering a groundwater basin of ~60 km2 with predominantly unconsolidated sandy sediments in northern Belgium. Results show that the model-based approach is superior in detecting the true lithological classes when compared to more frequently applied unsupervised classification approaches or literature classification diagrams. We demonstrate that automated mapping of lithostratigraphic units using advanced SBT classification techniques can provide a large gain in efficiency, compared to more time-consuming manual approaches and yields at least equally accurate results. ispartof: PLoS One vol:12 issue:5 ispartof: location:United States status: published

Outcropping sediments can be used as easily accessible analogues for studying subsurface sediments, especially to determine the small-scale spatial variability of hydrogeological parameters. The use of cost-effective in situ measurement techniques potentially makes the study of outcrop sediments even more attractive. We investigate to what degree air-permeameter measurements on outcrops of unconsolidated sediments can be a proxy for aquifer saturated hydraulic conductivity (K) heterogeneity. The Neogene aquifer in northern Belgium, known as a major groundwater resource, is used as the case study. K and grain-size data obtained from different outcropping sediments are compared with K and grain-size data from aquifer sediments obtained either via laboratory analyses on undisturbed borehole cores (K and grain size) or via large-scale pumping tests (K only). This comparison shows a pronounced and systematic difference between outcrop and aquifer sediments. Part of this difference is attributed to grain-size variations and earth surface processes specific to outcrop environments, including root growth, bioturbation, and weathering. Moreover, palaeoenvironmental conditions such as freezing–drying cycles and differential compaction histories will further alter the initial hydrogeological properties of the outcrop sediments. A linear correction is developed for rescaling the outcrop data to the subsurface data. The spatial structure pertaining to outcrops complements that obtained from the borehole cores in several cases. The higher spatial resolution of the outcrop measurements identifies small-scale spatial structures that remain undetected in the lower resolution borehole data. Insights in stratigraphic and K heterogeneity obtained from outcrop sediments improve developing conceptual models of groundwater flow and transport.

The rate at which low-lying sandy areas in temperate regions, such as the Campine Plateau (NE Belgium), have been eroding during the Quaternary is a matter of debate. Current knowledge on the average pace of landscape evolution in the Campine area is largely based on geological inferences and modern analogies. We performed a Bayesian inversion of an in situ-produced 10Be concentration depth profile to infer the average long-term erosion rate together with two other parameters: the surface exposure age and the inherited 10Be concentration. Compared to the latest advances in probabilistic inversion of cosmogenic radionuclide (CRN) data, our approach has the following two innovative components: it (1) uses Markov chain Monte Carlo (MCMC) sampling and (2) accounts (under certain assumptions) for the contribution of model errors to posterior uncertainty. To investigate to what extent our approach differs from the state of the art in practice, a comparison against the Bayesian inversion method implemented in the CRONUScalc program is made. Both approaches identify similar maximum a posteriori (MAP) parameter values, but posterior parameter and predictive uncertainty derived using the method taken in CRONUScalc is moderately underestimated. A simple way for producing more consistent uncertainty estimates with the CRONUScalc-like method in the presence of model errors is therefore suggested. Our inferred erosion rate of 39 ± 8. 9 mm kyr−1 (1σ) is relatively large in comparison with landforms that erode under comparable (paleo-)climates elsewhere in the world. We evaluate this value in the light of the erodibility of the substrate and sudden base level lowering during the Middle Pleistocene. A denser sampling scheme of a two-nuclide concentration depth profile would allow for better inferred erosion rate resolution, and including more uncertain parameters in the MCMC inversion., Earth Surface Dynamics, 5 (2), ISSN:2196-632X, ISSN:2196-6311

Decommissioning of nuclear building structures usually leads to large amounts of low level radioactive waste. Using a reliable method to determine the contamination depth is indispensable prior to the start of decontamination works and also for minimizing the radioactive waste volume and the total workload. The method described in this paper is based on geostatistical modeling of in situ gamma-ray spectroscopy measurements using the multiple photo peak method. The method has been tested on the floor of the waste gas surge tank room within the BR3 (Belgian Reactor 3) decommissioning project and has delivered adequate results. ispartof: Applied Radiation and Isotopes vol:79 pages:25-36 ispartof: location:England status: published