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<p>To support a modal shift toward sustainable freight solutions, such as inland waterway transport (IWT), researchers and practitioners require long-term historical data on IWT freight flows. However, such comprehensive time series have been unavailable until now. This study addresses this gap by presenting a harmonized dataset encompassing 50 years (1970–2023) of IWT freight data across Europe, with a focus on the Rhine-Alpine Corridor. The dataset includes transport volumes (in tonnes) and transport performance (in ton-kilometers), classified according to NST-R, NST2007, and CCR nomenclatures. To ensure data continuity and completeness, processing techniques—including imputation and optical character recognition—were applied. The dataset offers valuable insights for researchers, policymakers, and transport planners aiming to comprehend and enhance the role of IWT in Europe’s freight transport landscape.</p>

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50-Years Inland Waterway Freight Data in the Rhine-Alpine Corridor

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月17日

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  • Bas Turpijn,
  • Fedor Baart,
  • Lóránt Tavasszy,
  • Mark van Koningsveld

摘要

To support a modal shift toward sustainable freight solutions, such as inland waterway transport (IWT), researchers and practitioners require long-term historical data on IWT freight flows. However, such comprehensive time series have been unavailable until now. This study addresses this gap by presenting a harmonized dataset encompassing 50 years (1970–2023) of IWT freight data across Europe, with a focus on the Rhine-Alpine Corridor. The dataset includes transport volumes (in tonnes) and transport performance (in ton-kilometers), classified according to NST-R, NST2007, and CCR nomenclatures. To ensure data continuity and completeness, processing techniques—including imputation and optical character recognition—were applied. The dataset offers valuable insights for researchers, policymakers, and transport planners aiming to comprehend and enhance the role of IWT in Europe’s freight transport landscape.