Coupled heat-mass transport modelling of radionuclide migration from a nuclear waste disposal borehole

Disposal of radioactive waste originating from reprocessing of spent research reactor fuel typically includes stainless steel canisters with waste immobilised in a glass matrix. In a deep borehole disposal concept, waste packages could be stacked in a disposal zone at a depth of one to potentially several kilometres. This waste will generate heat for several hundreds of years. The influence of combining a natural geothermal gradient with heat from decaying nuclear waste on radionuclide transport from deep disposal boreholes is studied by implementing a coupled heat-solute mass transport modelling framework, subjected to depth-dependent temperature, pressure, and viscosity profiles. Several scenarios of waste-driven heat loads were investigated to test to what degree, if any, the additional heat affects radionuclide migration by generating convection-driven transport. Results show that the heat output and the calculated radioactivity at a hypothetical near-surface observation point are directly correlated; however, the overall impact of convection-driven transport is small due to the short duration (a few hundred years) of the heat load. Results further showed that the calculated radiation dose at the observation point was very sensitive to the magnitude of the effective diffusion parameter of the host rock. Coupled heat-solute mass transport models are necessary tools to identify influential processes regarding deep borehole disposal of heat-generating long-lived radioactive waste

The HPx software for multicomponent reactive transport during variably-saturated flow: Recent developments and applications

Abstract HPx is a multicomponent reactive transport model which uses HYDRUS as the flow and transport solver and PHREEQC-3 as the biogeochemical solver. Some recent adaptations have significantly increased the flexibility of the software for different environmental and engineering applications. This paper gives an overview of the most significant changes of HPx, such as coupling transport properties to geochemical state variables, gas diffusion, and transport in two and three dimensions. OpenMP allows for parallel computing using shared memory. Enhancements for scripting may eventually simplify input definitions and create possibilities for defining templates for generic (sub)problems. We included a discussion of root solute uptake and colloid-affected solute transport to show that most or all of the comprehensive features of HYDRUS can be extended with geochemical information. Finally, an example is used to demonstrate how HPx, and similar reactive transport models, can be helpful in implementing different factors relevant for soil organic matter dynamics in soils. HPx offers a unique framework to couple spatial-temporal variations in water contents, temperatures, and water fluxes, with dissolved organic matter and CO2 transport, as well as bioturbation processes

Hydrogeological conceptual model building and testing: A review

© 2018 Elsevier BV. This manuscript version is made available under the CC-BY-NC-ND 4.0 license: http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 24 month embargo from date of publication (December 2018) in accordance with the publisher’s archiving policyHydrogeological conceptual models are collections of hypotheses describing the understanding of groundwater systems and they are considered one of the major sources of uncertainty in groundwater flow and transport modelling. A common method for characterizing the conceptual uncertainty is the multi-model approach, where alternative plausible conceptual models are developed and evaluated. This review aims to give an overview of how multiple alternative models have been developed, tested and used for predictions in the multi-model approach in international literature and to identify the remaining challenges. The review shows that only a few guidelines for developing the multiple conceptual models exist, and these are rarely followed. The challenge of generating a mutually exclusive and collectively exhaustive range of plausible models is yet to be solved. Regarding conceptual model testing, the reviewed studies show that a challenge remains in finding data that is both suitable to discriminate between conceptual models and relevant to the model objective. We argue that there is a need for a systematic approach to conceptual model building where all aspects of conceptualization relevant to the study objective are covered. For each conceptual issue identified, alternative models representing hypotheses that are mutually exclusive should be defined. Using a systematic, hypothesis based approach increases the transparency in the modelling workflow and therefore the confidence in the final model predictions, while also anticipating conceptual surprises. While the focus of this review is on hydrogeological applications, the concepts and challenges concerning model building and testing are applicable to spatio-temporal dynamical environmental systems models in general

Centimeter-scale secondary information on hydraulic conductivity using a hand-held air permeameter on borehole cores

Saturated hydraulic conductivity (Ks) is one of the most important parameters determining groundwater flow and contaminant transport in both unsaturated and saturated porous media. Determining the small-scale variability of this parameter is key to evaluate implications on effective parameters at the larger scale. Moreover, for stochastic simulations of groundwater flow and contaminant transport, accurate models on the spatial variability of Ks are very much needed. While several well-established laboratory methods exist for determining Ks, investigating the small-scale variability remains a challenge. If several tens to hundreds of metres of borehole core has to be hydraulically characterised at the centimetre to decimetre scale, several hundreds to thousands of Ks measurements are required, which makes it very costly and time-consuming should traditional methods be used. With reliable air permeameters becoming increasingly available from the late 80’s, a fast and effective indirect method exists to determine Ks. Therefore, the use of hand-held air permeameter measurements for determining very accurate small-scale heterogeneity about Ks is very appealing. Very little is known, however, on its applicability for borehole cores that typically carry a small sediment volume. Therefore, the method was tested on several borehole cores of different size, originating from the Campine basin, Northern Belgium. The studied sediments are of Miocene to Pleistocene age, with a marine to continental origin, and consist of sand to clayey sand with distinct clay lenses, resulting in a Ks range of 7 orders of magnitude. During previous studies, two samples were taken from borehole cores each two meters for performing constant head lab permeameter tests. This data is now used as a reference for the air permeameter measurements that are performed with a resolution of 5 centimetres. Preliminary results indicate a very good correlation between the previously gathered constant head Ks data and the air permeability measurements, but a systematic bias seems to exist. A geostatistical analysis with cross-validation is performed to assess the predictive uncertainty on Ks, using both types of data. We conclude that performing hand-held air permeameter measurements on undisturbed borehole cores provides a very cost-effective way to obtain very detailed information in the framework of stochastic simulation and conditioning of heterogeneous hydraulic conductivity fields

Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks

peer reviewedaudience: researcher, professionalVarious approaches exist to relate saturated hydraulic conductivity (Ks) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods, i.e.multiple linear regression and artificial neural networks, that use the entire grain-size distribution data as input for Ks prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalized likelihood uncertainty estimation (GLUE) approach to predict Ks from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from literature demonstrates the importance of site specific calibration. The dataset used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size -Ks pairs. Finally, an application with the optimized models is presented for a borehole lacking Ks data

Development and analysis of the Soil Water Infiltration Global database

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements ( ∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type ( ∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it

Radionuclide and metal sorption on cement and concrete

Cementitious materials are being widely used as solidification/stabilisation and barrier materials for a variety of chemical and radioactive wastes, primarily due to their favourable retention properties for metals, radionuclides and other contaminants. The retention properties result from various mineral phases in hydrated cement that possess a high density and diversity of reactive sites for the fixation of contaminants through a variety of sorption and incorporation reactions. This book presents a state of the art review and critical evaluation of the type and magnitude of the various sorption and incorporation processes in hydrated cement systems for twenty-five elements relevant for a broad range of radioactive and industrial wastes. Effects of cement evolution or ageing on sorption/incorporation processes are explicitly evaluated and quantified. While the immobilisation of contaminants by mixing-in during hydration is not explicitly addressed, the underlying chemical processes are similar. A quantitative database on the solid/liquid distribution behaviour of radionuclides and other elements in hydrated cement systems is established on the basis of a consistent review and re-evaluation of literature data. In addition to recommended values, all underlying original experimental data and key experimental info rmation are provided, which allows users to trace the given recommendations or to develop their own set of key values. This database is closely tied to the safety analysis of near surface disposal of radioactive waste in Belgium. It focuses on radioelements, toxic stable elements and heavy metals, which makes it relevant for investigations involving the interaction of radioactive and conventional contaminants with cement-based barriers

Determining water quality requirements of coal seam gas produced water for sustainable irrigation

Coal seam gas production in Australia generates large volumes of produced water that is generally high in total dissolved solids and has a high sodium absorption ratio (SAR) which may affect soil structure, hydraulic conductivity, and crop production if used untreated for irrigation. By coupling major ion soil chemistry and unsaturated flow and plant water uptake, this study incorporates effects of salt concentrations on soil hydraulic properties and on root water uptake for soils irrigated with produced water featuring different water qualities. Simulations provided detailed results regarding chemical indicators of soil and plant health, i.e. SAR, EC and sodium concentrations. Results from a base scenario indicated that the use of untreated produced water for irrigation would cause SAR and EC values to significantly exceed the soil quality guide values in Australia and New Zealand (ANZECC). The simulations provided further useful insights in the type of coupled processes that might occur, and what the potential impacts could be on soil hydrology and crop growth. Calculations showed that the use of untreated produced water resulted in a decrease in soil hydraulic conductivity due to clay swelling causing water stagnation, additional plant-water stress and a reduction in plant transpiration. In case the produced water was mixed with surface water in a 1:3 ratio prior to irrigation, the calculated soil SAR values were much lower and generally acceptable for sandy to sandy-loam soil. The use of reverse osmosis treated produced water yielded an acceptable salinity profile not exceeding guide values for SAR and EC; the plant water stress was limited as there was no additional salinity stress associated with the low level of salts. Results further illustrated that accounting for coupled geochemical, hydrological and plant water uptake processes resulted in more accurate water balance calculations compared to an approach where such interactions were not implemented. Coupling unsaturated flow modelling with major ion chemistry solute transport using HYDRUS provides quantitative evidence to determine suitable water quality requirements for sustainable irrigation using coal seam gas produced water

Modeling the Rainfall-Runoff Process with a Bilinear State-Space Model

A fairly simple iterative algorithm for identifying mul-tivariable bilinear systems has been introduced, which uses input/output data directly. This new algorithm falls in the class of subspace methods and resembles well known Hankel based realization algorithms that identify a bilinear state space model on the basis of the Volterra kernels instead. Classical rainfall-runoff modeling has been limited to low order Volterra kernels due to the computational complexity involved in the identification. With the new algorithm this is no longer necessary since the parameters of the bilinear model are directly related to the Volterra kernels. The iterative subspace algorithm has been tested with a set of data from the Voer catchment in Belgium. The results indicate a better performance compared to a linear subspace algorithm, especially in tracking the base flow recession, which is where the nonlinearities are concentrtated