In this paper, we present the results of a large-scale numerical model of a generic nuclear waste repository situated in an argillaceous host rock formation. Modelling the evolution of an entire repository presents challenges due to the strong contrast in spatial and temporal scales at which the different processes take place, ranging from the centimetres to the kilometres and days to hundreds of thousands of years, respectively. From the view point of the physical processes, a further challenge originates from the different gas transport mechanisms: Gas advection as well as gas dissolution and diffusion jointly govern the efflux of gas from the repository and mitigate excess pore pressures, but there is a significant contrast between the rates of these two transport mechanisms. Using the TH2M implementation in the open-source finite element code OpenGeoSys-6 , we analyse the impact of gas transport via advection (in the partially saturated zones such as backfilled drifts, shafts and desaturated host rock) as well as gas transport via diffusion (in fully water-saturated media such as the undisturbed host rock and over- and underlying formations). Finally, this work outlines and discusses possible simplifications in modelling choices, such as mechanical surrogate models, geometrical simplifications as well as the impact of discretization. The work presented in this paper was carried out within the scope of the European Joint Programme EURAD, workpackage Gas, Task 4.
This dataset contains large-scale groundwater storage anomalies for the Sesan and Srepok catchments in the Central Highlands of Vietnam. The anomalies were derived from in-situ groundwater well water level time series and hydrogeological information. A detailed description of the datasets and methods can be found in Sayyadi et al 2025.
The dataset is comprised of three files: insitu_groundater_storage_anomalies.csv, GW_wells.csv and a shape file with the Thiessen polygones indicating the extent of the area for which the storage calculations were performed.
insitu_groundater_storage_anomalies.csv contains the groundwater storage variations, with the following columns:
1. gws_mm (Groundwater Storage in millimeters): The gws_mm data represent groundwater storage anomalies derived from in-situ well measurements. Groundwater levels were recorded monthly from a network of observation wells across the study area. Specific yield values were used to convert the groundwater level variations into storage anomalies, measured in millimeters of water equivalent.
2. seasonal_adjusted: The seasonal_adjusted data were obtained by removing the seasonal component from the raw groundwater storage time series (gws_mm). This was done by calculating the mean monthly anomalies and subtracting them from the original data to isolate non-seasonal variations.
3. trend: The trend data represent the linear trend component of the groundwater storage anomalies. The trend was calculated using a linear regression model applied to the seasonal-adjusted data, highlighting long-term groundwater storage changes over the study period.
4. detrended: The detrended data were created by removing both the seasonal and long-term trend components from the gws_mm data. This dataset captures short-term fluctuations and anomalies, free from the regular seasonal and trend influences.
GW_wells.csv contains a list of the griundwater wells used in the study, with information about their location and lithology, as well as the range of associated specific yields (sy).
Thiessen_polygones_GW_wells_2S.shp is a georeferenced shape sile containing the Thiessen polygones for the wells in GW_wells.csv.