The LEGACY project aims to address the complex issue of groundwater pollution and its impact on European coastal waters, focusing on submarine groundwater discharge (SGD). This project seeks to quantify pollutant transport via SGD, understand the driving forces behind this transport, assess the attenuation of legacy contaminants in subterranean estuaries, and predict future changes due to climate change and land use intensification. By employing innovative tracer techniques, advanced hydrological modeling, and comprehensive laboratory investigations, the project will generate crucial insights into the dynamics of groundwater pollution. The outcomes of the LEGACY project will significantly enhance our understanding of pollutant pathways and their long-term impacts on coastal ecosystems. This will inform the development of large-scale pollutant budgets and predictive models essential for effective environmental management and policy formulation, aiming to mitigate the adverse effects of groundwater pollution on coastal water quality. Currently, I am conducting preliminary work that involves collecting and analyzing monthly precipitation and runoff data from 1980 to 2024 from more than 10000 stations within Baltic Sea catchments. The datasets are extensive and require curation and calculations, which is computationally intensive and beyond the capacity of standard computing resources. High performance computing (HPC) resources are indispensable for this project for several reasons: Data Handling and Processing: The project involves handling large time series datasets spanning over four decades, which require substantial computational power for efficient processing and analysis. Additionally, the curation of big data in running Python programs for data analysis is essential. Advanced Modeling: The development of high-resolution hydrological and pollutant transport models necessitates significant computational resources to ensure accuracy and reliability. Calculations and Operations in ArcGIS: Defining catchment boundaries and calculating values for each catchment require complex operations in ArcGIS. HPC resources will facilitate these calculations, ensuring efficiency and accuracy. Uploading Large Data to ArcGIS Online: The creation of interactive maps in ArcGIS Online using large datasets demands substantial computational power for processing and visualization. The LEGACY project’s ambition to resolve groundwater pollution pathways on a continental scale necessitates the use of HPC resources. The data-intensive nature of this research, coupled with the need for advanced modeling techniques and complex operations in ArcGIS, requires computational capabilities that exceed standard desktop computing. With HPC, the project will be able to process large datasets, run complex simulations, and perform intricate operations in ArcGIS effectively. HPC resources will enable the development of detailed pollutant budgets, predictive models, and interactive maps, essential for understanding and managing the impact of groundwater pollution on coastal ecosystems. The results will inform sustainable development goals, providing a scientific basis for improved water quality management and policy decisions. In conclusion, the allocation of HPC resources is critical for the success of the LEGACY project. It will provide the necessary computational power to analyze extensive environmental data, develop accurate models, and create interactive visualizations. This research has the potential to revolutionize our approach to global water quality management by illuminating a hidden but crucial source of pollution.