Digital twins for inland waterways: Innovative approaches to monitoring and forecasting water levels, navigability, and infrastructure maintenance.
Author(s)
Märtens, Tammo
Krämer, Björn
Ehsanfar, Ebrahim
Dhavaleswarapu, Sohith
Advisor(s)
Editor(s)
Collections
Supplementary to:
Abstract
This paper deals with the application of digital twin technology in new and innovative ways for the upscaling of inland waterway management in terms of the monitoring and forecasting of water level, navigability, and infrastructures maintenance. Developed as part of the Horizon Europe project CRISTAL, the Water Level Twin, Buoy Twin, and Lock Twin were implemented. All bring forth important data insights from predictive modeling of water levels to real-time environmental monitoring by smart buoys and proactive maintenance management of locks by acoustic sensors. All of these developments aid improved decision-making for operators to improve security and efficiency in inland waterway transportation. Integration of machine learning models facilitates accurate forecasting of navigability, addressing challenges introduced by fluctuating water levels and environmental factors. This research reveils the potential for digital twins to transform inland waterway infrastructure management so that it is more climate change resilient and sustainable. The findings validate the effectiveness of digital twin systems in providing actionable intelligence for infrastructure operators, culminating in the creation of intelligent transport networks.
Sponsor
Date
2025-06
Extent
Resource Type
Text
Resource Subtype
Proceedings
Rights Statement
Unless otherwise noted, all materials are protected under U.S. Copyright Law and all rights are reserved