This paper presents the integration of pipeline transport into the Dutch national freight transport model BasGoed.

This paper first provides a general overview of freight transport in the Netherlands. This overview covers all modes of transport, shipping, road transport, rail transport, inland navigation and pipelines. This overview is followed by a more detailed description of pipeline transport. We address the current use of pipelines, looking at the operational range, the existing infrastructure and the types of goods currently transported via pipelines, such as liquids and gases. With a SWOT analysis, we evaluate the strengths, weaknesses, opportunities and threats of pipeline transport. This analysis helped to prepare the functional and technical design of a pipeline module for BasGoed.

We then present the conceptual design and technical implementation of the pipeline transport module in BasGoed. The considerations behind the architecture and design are described. Modelling challenges include limited data availability, forecasting potential modal shift and potential demand for new transport due to energy transition (hydrogen, CO2). Use cases have been developed to ensure that the model properly reflects these developments in pipeline transport demand.

We further describe the technical integration into BasGoed, addressing the aspects of data integration and ensuring data accuracy and consistency. The paper discusses how the integration of pipeline transport leads to a better representation of freight transport within the Netherlands, by improving the BasGoed model.

The paper concludes with some conclusions and recommendations for including freight transport via pipelines in freight transport models.
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In 2020 hebben Rijkswaterstaat en ProRail in opdracht van het Nederlandse Ministerie van Infrastructuur en Waterstaat de ReferentiePrognose Goederenvervoer 2021 (kort: RPGV2021) laten uitvoeren. In deze paper geven we een korte toelichting over het model BasGoed in het algemeen en het project RPGV2021 specifiek. Het vernieuwing van het model BasGoed bevat onder ander een meer gedetailleerde kostenfunctie waarmee de transportkosten wordt berekend, de implementatie van een nieuwe containerketenmodule en de inclusie van een nieuw energiescenario. Om de werking van deze vernieuwing te analyseren, wordt in deze paper de plausibiliteit van de modelelasticiteiten getoetst. Verder vergelijken we de modeluitkomsten voor een prognose voor het jaar 2018 met realisatiecijfers. Deze vergelijking laat zien dat het weggoederenvervoer inclusief bestelauto op hetzelfde niveau uitkomt als de realisatie, maar dat op een gedetailleerder niveau de verdeling over de voertuigtypen afwijkt. In het algemeen geven de analyseresultaten vertrouwen in de resultaten uit de RPGV2021, welke in hoofdlijn in dit paper worden omschreven en visualiseert.@en

Strategic freight transport models can be used for a quantitative analysis of long term forecasts. This paper discusses an analysis of the bandwidth of freight transport forecasts for The Netherlands with the strategic freight transport model ‘BasGoed’. This model was developed over the past years as a basic model, satisfying the needs of policy making, based on proven knowledge and available transport data. Starting point for the analysis are the long-term scenarios for The Netherlands developed recently by CPB Netherlands Bureau for Economic Policy Analysis and PBL Netherlands Environmental Assessment Agency (WLO scenarios: Future outlook on welfare, prosperity and the human environment). The scenarios describe two base cases: The High and Low scenario. Both scenarios include a consistent set of assumptions on economic development (domestic growth by industry sector and international trade), infrastructure development, fuel prices, and logistic efficiency. The bandwidth of freight forecasts is further explored in five distinctive sensitivity analyses: different development in fuel prices, energy markets, CO2-pricing, dematerialization and modal shift in the port of Rotterdam. The sensitivity analysis provides more insight in the level of importance of each scenario assumption and it can be useful in estimating a bandwidth for freight transport demand. This is valuable in providing insight in the robustness of the freight transport forecasts for policy studies.@en