- 1Department of Aquatic Ecosystem Analysis and Management, Helmholtz Centre for Environmental Research - UFZ, Magdeburg 39114, Germany (amir.rouhani@ufz.de, michael.rode@ufz.de, seifeddine.jomaa@ufz.de)
- 2Idrica (IDRICA), Valencia, Spain (ainhoa.mate@idrica.com, antonio.moya@idrica.com)
- 3Institute of Water and Environmental Engineering, Universitat Politècnica de València, Valencia, Spain (jaime@dihma.upv.es)
Digital twin, as a virtual representation of physical systems, is increasingly recognised as a core component of timely and accurate water management, particularly for interconnected and rapidly changing systems. Digital twin supports the simultaneous monitoring, simulation, and optimisation of real-world operations by integrating multiple data sources, including in-situ measurements, remote sensing and modelling data. By enabling a detailed characterisation of catchment functioning and its ecological boundary conditions, a digital twin facilitates equitable water allocation across sectors and supports timely and evidence-based decision-making.
Developing a digital twin requires extensive datasets, robust scientific evidence, and a clear grasp of ecological boundaries, reflecting the interconnected nature of multi-sectoral decision-making. The Bode River Basin, one of the best-monitored catchments in central Europe, serves as a showcase for designing and implementing a digital twin system for multi-sectoral and sustainable water management at catchment scale. The recent prolonged droughts (2017–2021) and their impacts on various water bodies offer a real-world “experiment” of extreme climate scenarios, highlighting the vulnerabilities and risks within the catchment and illustrating the complex trade-offs inherent in water resource management.
This study integrates long-term, high-resolution monitoring strategies with coupled surface water, groundwater, and water quality models into a unified framework that addresses both quantitative and qualitative aspects of water systems. Such a comprehensive approach enables forecasting climate change impacts and optimising water resource allocation across sectors. Overall, this work demonstrates the potential of digital twins to advance sustainable water resource management under changing climatic conditions.
Acknowledgment
This work was supported by the OurMED PRIMA Program project funded by the European Union’s Horizon 2020 research and innovation under grant agreement No. 2222.
How to cite: Rouhani, A., Mate Marin, A., Moya Diez, A., Gómez-Hernández, J. J., Rode, M., and Jomaa, S.: Transforming water resources management at river basin scale with digital twin technology, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17076, https://doi.org/10.5194/egusphere-egu25-17076, 2025.
