EGU24-12982, updated on 09 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Virtual Delta: a digital twin for real-time forecasting and management of saltwater intrusion in the Rhine-Meuse delta

Chanoknun Wannasin1,2, Bouke Biemond3, Bas Wullems4, Thies Blokhuijsen2, Meinard Tiessen2, Fedor Baart2,5, and Jaap Kwadijk1,2
Chanoknun Wannasin et al.
  • 1Faculty of Engineering Technology, University of Twente, Enschede, The Netherlands (
  • 2Deltares, Delft, The Netherlands
  • 3Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, The Netherlands
  • 4Hydrology and Environmental Hydraulics Group, Wageningen University, Wageningen, The Netherlands
  • 5Faculty of Civil Engineering and Geosciences, Delft University of Technology, The Netherlands

Estuarine saltwater intrusion poses a significant hydrological and environmental challenge in the Rhine-Meuse delta, amplified by human interventions (e.g., river engineering) and climate change impacts (e.g., droughts, storm surges, and sea-level rise). The more frequent and severe salt intrusion events, especially during droughts in 2018, 2020, and 2022, emphasize the need for accurate forecasting and effective management. This research aims to develop a digital twin for real-time forecasting and management of salt intrusion. The digital twin is part of the Virtual Delta, one of the main outputs that the SALTISolutions research project is working towards. As an operational modelling toolbox, this digital twin consists of four components: observed data analysis, real-time forecasting, early warning, and exploratory simulations. The observed data analysis component includes statistical information, such as return periods and exceedance exceedance probabilities of chloride concentration, river discharge, and water level. The forecasting component employs currently available salt intrusion models within the SALTISolutions project, including 1D, 2D, statistical, and machine learning models. The early warning component utilizes thresholds (e.g., maximum chloride concentrations at freshwater inlets). Exploratory simulations consider what-if scenarios (e.g., lower river discharge) and management options (e.g., combinations of different real-time measures). The research is ongoing, and the current development will be demonstrated. The digital twin is expected to assist water managers and stakeholders (e.g., drinking water companies) in decision-making, addressing impacts of saltwater intrusion, and ensuring a continuous supply of freshwater in the delta.

How to cite: Wannasin, C., Biemond, B., Wullems, B., Blokhuijsen, T., Tiessen, M., Baart, F., and Kwadijk, J.: Virtual Delta: a digital twin for real-time forecasting and management of saltwater intrusion in the Rhine-Meuse delta, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12982,, 2024.