Modelling the Inland Waterway Transportation Operations Supported by Navigation-Related Probabilistic Forecasts under Projected Drier Climate Conditions

16:15 Tuesday 28 May

SS019 • OC112

Room S13


Dmitry Kovalevsky (Germany) 1; María Máñez Costa (Germany) 1; David Williams (Germany) 1; Bastian Klein (Germany) 2

1 - Climate Service Center Germany (GERICS), Helmholtz-Zentrum Geesthacht; 2 - Bundesanstalt für Gewässerkunde (BfG)

In many regions of the world, including vitally important waterways of Central Europe, Inland Waterway Transport (IWT) is vulnerable to low stream flow events. The frequency and severity of low-flow events are likely to increase in many locations with projected changes towards possible drier regional and local climates. Therefore, reliable navigation-related forecasts, already in high demand by skippers, transport operators and other interested users, are likely to become even more important for IWT in the future.

Within the EU H2020 IMPREX project we are developing a system dynamics (SD) model of transportation of cargos for the energy sector for IWT on the river Rhine. The situation at bottlenecks becomes critical during periods of low-flow, as ships can only transport reduced amount of cargo to pass the bottleneck, or, in severe events, no transportation of goods is possible. The modelled decision-making might be supported by navigation-related forecasts. Two types of forecasts are considered: conventional deterministic and innovative probabilistic navigation-related forecasts. The modelling is performed for the cases of current climate conditions, and also for projected drier local climate. In hindcasting mode, the model runs are driven by observed data series of water level at bottlenecks, with real deterministic and probabilistic forecasts that were made available for users in the recent past driving the decision-making regarding transportation of cargos in the model world.

The added value of innovative probabilistic navigation-related forecasts versus conventional deterministic forecasts is assessed with model simulations. The SD model developed also addresses the issue of sustainability of supply chains in the energy sector dependent on IWT operations under the current and projected future climate.