Radioactive waste disposal and management presents a unique problem at the Krško nuclear power plant as it is built and co-owned by the Republic of Croatia and the Republic of Slovenia. Each country is responsible for the management of half of the low- and intermediate-level radioactive waste (LILW) and spent nuclear fuel (SNF). So far, Slovenia has officially selected the site for LILW disposal and the Croatian programme has a single location left (since 1999), not officially approved as acceptable. This paper contains a new approach to site selection related to the implementation of GIS technology and presents a map of potential areas for LILW disposal including only the remaining Croatian location. It was constructed based on eleven layers that include natural characteristics and anthropogenic pressures. For the construction of the main map, detailed topological checks and spatial analysis of polygons have been made, reducing potential areas to be further evaluated.

The basic principles of geological risk calculation through probability of success (PoS) are mostly applied to numerical estimation of additional hydrocarbon existence in proven reservoirs or potential hydrocarbon discoveries in selected geological regional subsurface volumes. It can be adapted and validated for a comprehensive input dataset collected in the selected petroleum province, by dividing up geological events into several probability categories and classes. Such methodology has been widely developed in the last decades in the Croatian subsurface—mostly in the Croatian Pannonian Basin System (CPBS). Through the adaptation of geological categories, it was also applied in hybrid, i.e., stochastic, models developed in the CPBS (Drava Depression), mostly for inclusion of porosity values. As the robustness of this methodology is very high, it was also modified to estimate the influence of water-flooding in increasing oil recovery in some proven Neogene sandstone reservoirs in the CPBS (Sava Depression). This new modification is presented to be applied to geological risk calculation, intending to assess the safety of geological environment storage in deep wells, where spent nuclear fuel (SPN) would be disposed, a subject of great importance. The conceptual study encompassed the magmatic and metamorphic rocks in the pre-Neogene basement of the CPBS, intended to be used for such purpose. Regionally distributed lithologies are considered for nuclear waste disposal purpose, in order to detect the safest ones, considering petrophysical values, water saturation, recent weathering and tectonic activity.

Coal fly ash and slag waste residuals from coal combustion are an issue of importance as one of the possible sources of environmental contamination and exposure to NORM. This study compares the results of different radiological risk assessment scenarios targeting terrestrial biota at a legacy site in Croatia that contains large quantities of coal ash with an enhanced content of radionuclides originating from previous industrial activities. The ERICA assessment tool was used for a risk assessment, which included data from borehole samples with a maximum depth of 6 m and trees as the primary reference organisms. The results of the risk assessments from various depth ranges found the radiological risk to the reference organisms to be negligible, regardless of the depth range, since the screening dose rate of 10 µGyh⁻¹ was not exceeded in any of the assessments. The risk assessment results from all depth ranges show higher total dose rate predictions when the tool’s default CR values are used, compared to the site-specific ones, which is in agreement with previous studies on the application of the ERICA tool. A comparison of results from different spatial radiological risk assessments showed that sample depth does not affect the estimated total dose rate to biota.

After the adoption of the National Program for the Implementation of the Strategy for the Management of Radioactive Waste Used Resources and Spent Nuclear Fuel, by the Government of the Republic of Croatia, the issue of radioactive waste management in Croatia became current. Slovene-Croatian co-ownership over the Krgko nuclear power plant (KNPP) means that half of the operational and decommissioning waste, as well as spent nuclear fuel (SNF) belongs to Croatia. Until now, SNF has been kept in a pool at KNPP, and dry storage before disposal is also planned. A generic project of a SNF repository has been developed and has already undergone a second revision and review. The project idea involves site selection in both countries and the conceptual solution of the SKB-3V type in crystalline rock. This paper presents an estimate of the thermal-hydro-mechanical effects (THME) of the SNF repository in crystalline rock (granodiorite) of SKB-3V concept by developing a numerical model in the SIGMA/W, SEEP/W and TEMP/W software. Simulations have shown that it is possible to construct a SNF repository in the crystalline rocks of Croatia or Slovenia, that the generic repository project is well-designed and that a model of hydro-thermo-mechanical effects of spent nuclear fuel on the rock in Croatia/Slovenia can be produced, which proves the suitability of the rock mass for this purpose.

The basic principles of geological risk calculation through Probability of Success (PoS) are mostly applied for numerical estimation of additional hydrocarbon existence in proven reservoirs or potential hydrocarbon discoveries in selected geological regional subsurface volume. It can be tailored and validated for a comprehensive input dataset collected in the selected petroleum province, adapted by dividing up geological events into several probability categories and classes. The most applied categories are (existence of) reservoir rocks, traps and isolators, source rocks, migration pathways and preservation conditions for hydrocarbons The methodology results in unique probability values as multiplication of independent statistical events, which can also be applied in the assessment of a potential hydrocarbon discovery of desired minimal volume and its value in any virtual currency like risk-neutral dollars. Such methodology has been extensively developed in the last decades in the Croatian subsurface, mostly in the Croatian part of the Pannonian Basin System (CPBS). Through the adaptation of geological categories, it was also applied in hybrid, i.e., stochastical, models developed in the CPBS (Drava Depression). Stochastically estimation of porosity was already applied. As the robustness of this methodology is very high, it was also modified to estimate the influence of water-flooding in increasing oil recovery in some proven Neogene sandstone reservoirs in the CPBS (Sava Depression). This new modification is being presented to be applied to geological risk calculation, intending to assess the safety of geological environment in deep wells, where depleted radioactive fuel would be disposed, a subject of great importance. The case study encompassed the magmatic and metamorphic rocks in the pre-Neogene basement of the CPBS. For disposal purpose, these are regionally lithologies considered as to be the safest ones considering petrophysical values, water saturation, recent weathering and tectonic activity.

Radon (²²²Rn) is a chemically inert (noble) gas, naturally occurring α-emitter radionuclide, and the direct progeny of ²²⁶Radium; it is produced in the uranium (²³⁸U) decay chain. Short-term measurements of the concentration of radon can be performed to identify locations and objects with potentially increased concentrations. The goal of this study is to present a comparison of models for the seasonal prediction of ²²²Rn active concentration variations from the results of ²²²Rn short-term measurements acquired by active instruments. Several predictive models are compared in this study, with estimation and validation datasets from ²²²Rn concentration measurements from two significant micro-locations: the St. Barbara mine and a ground-floor room of the University of Zagreb Faculty of Mining, Geology and Petroleum engineering (UNIZG-FMGPE) building, in Zagreb, Croatia. MATLAB version R2025b System identification and a Signal multiresolution analyzer were used for the estimation of predictive models and validation for mid-term prediction. This research provides one method for estimating the concentration variations from a smaller number of observations from 8 days of measurements. It shows that the best models for the estimation and prediction of radon concentration time series are the auto-regressive non-linear ARX model (NLarx), with a one-step-ahead prediction fit of up to around 90% for a minimum measurement duration of 8 days, 192 samples, and a 1 h floating mean for the estimation and ARMAX estimation from the reconstructed signal as a simple polynomial approximation of the original measurement signal, with a one-step-ahead prediction fit of almost 100%. The ARMAX model with a one-step-ahead predicted output gives excellent estimation of the MODWT and EMD reconstructed signal, which has approximately the same mean as the original signal and, thus, can be used for indirect prediction of the Rn mean. The NLarx model showed good results in the validation of Rn concentration variations; thus, this model is selected as the preferred model to predict Rn concentration variations from short-term measurements.