Development of actionable salt intrusion forecasts

We address the need for improved forecasts of saltwater intrusion in estuaries. Estuaries worldwide face problems with saltwater intrusion, which threatens the freshwater supply for drinking, agriculture and industry. The Rhine-Meuse delta is taken as a case study. This is a complex multi-branched system that is highly influenced by hydraulic management structures. Problems with saltwater intrusion occur regularly in this delta (e.g. 2003, 2005, 2006, 2011, 2013, 2018). These problems are most likely to occur when high sea levels due to storm swell coincide with low river discharge. We aim to provide water managers with better forecasts, so they can take mitigating measures in a timely fashion. Two modelling approaches will be investigated on how they can be applied to forecast salt intrusion on a timescale of days to weeks. These approaches are a machine learning model and several improvements (e.g. parameters, data assimilation, postprocessing) to the existing hydrodynamic SOBEK 1D model forecasts. In both approaches, the probabilistic nature of the input data will be processed to yield a probabilistic forecast of salt intrusion. Finally, we will test the developed models, or a combination thereof, in a scenario analysis of several water management decisions. The aim of this presentation is to exchange ideas on the various methods of (salt intrusion) forecasting, their advantages and limitations, and their application for deriving actionable forecasts.