Prof. Dr. Andras Bardossy | Spatial Statistics | Excellence in Research Award
University of Stuttgart | Germany
Prof. Dr. András Bardossy is a distinguished expert in hydrology with research contributions spanning stochastic hydrology, geostatistics, surface and subsurface hydrology, hydroclimatology, climate change, and fuzzy computations. His professional career includes leading academic and research roles in prominent international institutions, focusing on hydrology, geohydrology, and water management. He has conducted extensive research in precipitation modeling, GCM downscaling, regionalization of hydrological models and parameters, groundwater and soil moisture evaluation, infiltration modeling, and environmental decision-making under uncertainty. His work further covers groundwater pollution modeling, multivariate statistical modeling, sediment transport, water quality analysis, and geostatistical investigation of environmental systems. Prof. Bardossy has held honorary and invited professorships at several globally recognized universities and has supervised 56 PhD scholars, with a strong publication record comprising 231 scientific papers. His core expertise also includes spatial statistics and advanced data analysis techniques.
Profiles: Scopus | Orcid | Google Scholar
Baste, S., Klotz, D., Acuña Espinoza, E., Bardossy, A., & Loritz, R. (2025). Unveiling the limits of deep learning models in hydrological extrapolation tasks. Hydrology and Earth System Sciences, 29(21), 5871–5891.
Zhang, Q., Zhang, K., Bárdossy, A., Li, Y., & Wu, N. (2025). Improving representation of hydrological process heterogeneity in grid-Xin’anjiang model through a stepwise approach. Journal of Hydrology, 655, 132897.
El Hachem, A., Seidel, J., & Bárdossy, A. (2025). Probabilistic downscaling of EURO-CORDEX precipitation data for the assessment of future areal precipitation extremes for hourly to daily durations. Hydrology and Earth System Sciences.
Hörning, S., & Bárdossy, A. (2025). Simulation of conditional non-Gaussian random fields with directional asymmetry. Spatial Statistics, 65, 100872.
El Hachem, A., Seidel, J., O'Hara, T., Villalobos Herrera, R., Overeem, A., Uijlenhoet, R., Bárdossy, A., & de Vos, L. (2024). Technical note: A guide to using three open-source quality control algorithms for rainfall data from personal weather stations. Hydrology and Earth System Sciences.