Invasive aquatic species pose a threat to ecosystems worldwide. Their spread between watersheds occurs mainly during flood events, when natural boundaries become temporarily passable. A research team has developed an innovative method to identify connection points between basins during heavy rainfall. Using satellite data and statistical models, they created an index combining elevation, watershed size, and geological characteristics. This approach accurately predicts (94%) where water connections will form during extreme events. The research focused on invasive fish in the United States, but the method is applicable globally. This technology provides environmentalists with a powerful tool to prevent the spread of non-native species, protecting aquatic biodiversity. The data is freely available and easy to use, making risk zone mapping accessible to everyone.
The study uses a multidisciplinary approach combining hydrology, ecology, and remote sensing. The developed connectivity index is based on three fundamental parameters: the point elevation relative to the minimum elevations of adjacent basins (HUC-12), watershed size, and local geological characteristics. Researchers used Landsat data to validate surface water presence during events with more than 20 mm of precipitation in 3 days. The statistical model achieves exceptional prediction margin (R2 = 0.94) thanks to the analysis of interactions between different environmental factors. This allows identification of even temporary connections that last few hours, but sufficient for aquatic species passage. The methodology is scalable and can be applied to different geographical regions, offering a valuable tool for conservation planning.
