Publication
A Digital Twin Paradigm for Data-Driven Monitoring and Management of Lake Ecosystems
Janina Schneider; Daniel Lukats; Christoph Manss; Frederic Theodor Stahl
In: INFORMATIK 2025: The Wide Open - Offenheit von Source bis Science. Jahrestagung der Gesellschaft für Informatik (INFORMATIK-2025), September 16-19, Potsdam, Germany, Pages 1-6, Lecture Notes in Informatics (LNI), Vol. P-366, Gesellschaft für Informatik e.V. Bonn, 9/2025.
Abstract
The Digital Twins of Aquatic Environments (DiTAq) project investigates the use of digital twin technology for the management of lake ecosystems, targeting as a use case Lake Maschsee in Hanover, Germany. By integrating Artificial Intelligence ( AI ), specifically Machine Learning (ML), the project aims to predict aquatic plant growth, monitor ecological health, and optimize maintenance operations. The framework employs satellite, drone, and in-situ data, supplemented by validation techniques such as anomaly and concept drift detection. The study emphasizes the importance of interoperability and scalability in developing robust environmental Digital Twins (DTs), demonstrating their potential to provide real-time insights and support sustainable lake management practices.