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Probabilistic Shipping Forecast

  • Dennis MeißnerEmail author
  • Bastian Klein
Reference work entry

Abstract

Inland waterway transport is an important even though often neglected economic sector relying on hydrological forecasts in order to increase its operating efficiency. Besides river ice and floods, low stream flow is the main hydrological impact for shipping along the European inland waterways as it sustainably affects the load capacity of vessels and thus transportation costs several times a year. For this reason, inland waterway transport benefits from water-level forecasts in order to take preventive action and adjust the draft, especially during stream flow droughts.

Although most navigation-related water-level forecasts are still deterministic, the waterway transport sector is a well-suited customer of probabilistic forecast products for several reasons: The number of decisions to be taken is quite high, especially in comparison to the operation of protection measures against rare flood events. Furthermore, in waterway transport, the user’s costs and losses associated with possible forecast-based decisions are well known and monetary valuation of losses, like nonoperation times or additional effort due to lighterage, is more feasible as it is for example with regard to human lives or environmental pollution. Last but not least shipping is an inhomogeneous stakeholder as different vessel types and routes cause different cost structures and sensitivities due to navigation conditions. Selecting one “best-guess” forecast, being optimal for all users, is impossible.

In this chapter, hydrological forecasts as one component to support inland waterway transport are presented and the added value of probabilistic forecasts is demonstrated applying a simulation based cost model for the River Rhine, being one of the world’s most frequented inland waterways.

Keywords

Cost structure model Flood Inland waterway Inland waterway transport Low stream flow Navigation River ice River Information Service (RIS) River Rhine Seasonal forecast Shipping Traffic Water-level forecast 

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.German Federal Institute of Hydrology (BfG)KoblenzGermany
  2. 2.Department Water Balance, Forecasting and PredictionsFederal Institute of Hydrology (BfG)KoblenzGermany

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