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(the final reports and corresponding slide deck of WP3 can be downloaded by clicking the images below)
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| name | 11208811-006-ZKS-0001_v1.0-TKI PRISMA3_WP3_Beneficial sediment reuse in the port of Rotterdam from a logistical point of view.pdf |
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| height | 250 |
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| name | 11208811-006-ZKS-0001_v1.0-TKI PRISMA3_WP3_Beneficial Sediment Re-use_marineworms-study.pdf |
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| height | 250 |
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| name | TKI PRISMA3_WP3_FinalResults_MScThesis_Floris_vd_Heijde.pdf |
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| height | 250 |
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To reduce its dredging load, the Port of Rotterdam has set a target to re-use at least 1 million m³ of dredged sediment annually. In the third work package, we explored how beneficial use on this large scale may become a reality.
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WP4: Data science for more efficient dredging trips
(the final reports and corresponding slide deck of WP4 can be downloaded by clicking the images below)
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| name | TKI PRISMA3_WP4_Executive Summary Work Package 4.pdf |
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| height | 250 |
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| name | TKI PRISMA3_WP4_PetraBardocz_Internship_Report.pdf |
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| height | 250 |
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| name | TKI PRISMA3_WP4_Finalpresentation_Petra_Bardocz.pdf |
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| height | 250 |
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The aim of the fourth work package was to explore if weekly dredging volumes can be forecasted based on relevant hydro-meteo variables through a machine learning approach. This can enable more efficient dredging, thereby resulting in less dredging trips and thus reduced emissions. We compiled dredging volumes from the dredging database for the port area, while hydro-meteo data were taken from publicly available sources such as Waterinfo.
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