Monitoring Oxbow Lakes with Remote Sensing: Insights into Turbidity, Connectivity, and Fish Habitat

Abstract

In meandering river floodplain systems, remote sensing is a valuable tool for assessing connectivity processes relevant to fish ecological functions. This study used the Google Earth Engine platform and multispectral Landsat 7 imagery. A random forest classifier was used to evaluate water types and area changes in oxbow lakes of the Beni River in Bolivia. Water type dynamics were mainly associated with lake age and distance from the main channel. Seasonal variations highlighted the role of wind-driven sediment resuspension and overflow during high discharge conditions. Long-term lake area changes reflected typical oxbow lake evolution as well as alterations caused by the main channel. Multiannual changes showed a notable area decrease during years of low discharge. Relationships between discharge and lake area dynamics allowed the classification of three lake groups with different levels of connectivity and overbank flow influence. The ecological relevance of these groups was evaluated based on fish habitat preferences and migration patterns. Results emphasize the importance of preserving natural hydrologic variability, with flooding associated with increased habitat availability. Overall, this study demonstrates the usefulness of satellite remote sensing for detecting ecohydrological processes and offers insights to preserve ecological functions in data-scarce regions.