Author(s): Katarzyna Suska; Dominik Kopec; Janek Niedzielko; Jakub Charyton; Karol Lawniczak; Agnieszka Napiorkowska-Krzebietke; Piotr Parasiewicz

Linked Author(s):

Keywords: Prymnesium parvum; Oder River; Hyperspectral data; MesoHABSIM; Fish habitat modelling; Environmental management

Abstract: The 2022 ecological crisis in the Oder River, triggered by an extreme bloom of Prymnesium parvum, underscored the need for advanced analytical tools to evaluate water quality and fish habitat vulnerability. This study integrates extensive field sampling, laboratory analyses, hyperspectral aerial imagery, satellite data, and statistical modelling to assess the spatial risk of P. parvum occurrence. Approximately 500 water samples collected in 2022–2023 were used to construct a decision-tree model predicting golden algae presence based on physicochemical parameters. Additional sampling conducted in October 2024, combined with high-resolution hyperspectral data, enabled the creation of detailed raster and vector maps illustrating the spatial variability of water parameters across the Oder River, Gliwice Canal, and connected lakes. Comparison of hyperspectral and Sentinel-2–based modelling demonstrated high predictive performance (R² > 0.7 for 11 parameters). Applying the decision tree to spatial datasets revealed distinct areas of elevated P. parvum probability, particularly in low-flow zones such as the Gliwice Canal and Big Dzierzno Lake. The integrated approach, including remote sensing, hydrodynamic context, and MesoHABSIM habitat modelling, provides a robust framework for evaluating ecological impacts, supporting restoration planning, and improving risk assessments for future harmful algal events in the Oder River system.

DOI: https://doi.org/10.64697/iahr.proc.ise2026.abs.246

Year: 2026