
Discover the recent research within the Sustainable Development and Technologies project, where we conducted a multi-step modeling approach integrating unsupervised and deep learning algorithms to improve the interpretation of geophysical well-logging data for a more thorough characterization of the Quaternary aquifer system in the Debrecen area, Hungary. This approach facilitated the mapping of lithofacies and variations in hydraulic conductivity across the primary hydrostratigraphical units. Through this integration, we enhanced the understanding of the groundwater system, providing reliable inputs for groundwater modeling in a cost-effective and time-efficient manner.





The starting point of the study is that, even though the discourse related to the revitalization of brownfield areas has a long history in Hungarian development policy practice, its role in promoting the circular economy and environmental sustainability has appeared with little emphasis in Hungary so far, for which the article presents a few theoretical and practical arguments. In the study, the authors introduce a framework presenting the environmental, social and economic benefits of brownfield areas’ redevelopment, highlighting sustainability benefits along concrete examples.