Description
The dataset contains the processed data of 1252 simulations using Delft3D Flexible Mesh (DFM) in which estuaries were designed using a parametric design. Every estuary design is based on thirteen (13) input parameters: three (3) boundary conditions, and ten (10) geomorphological characteristics. The output is represented by two (2) variables: (1) the salt intrusion length, 'L'; and (2) the salt variability, 'V'. Simulations are carried out over a span of nine (9) days of which the first eight (8) are considered spin-up; i.e., one (1) day of the simulation is used for further post-processing. The salt intrusion length is a depth- and tide-averaged estimation of the salt intrusion of this last day; and the salt variability an estimate of the difference between the maximum salinity and the minimum salinity over the tide, depth- and spatially- averaged. The various settings of the simulations are drawn using machine learning techniques.
| Date made available | 20 Mar 2023 |
|---|---|
| Publisher | TU Delft - 4TU.ResearchData |
| Date of data production | 2023 |
Datasets
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ANNESI: An open-source artificial neural network for estuarine salt intrusion
Hendrickx, G. (Creator), TU Delft - 4TU.ResearchData, 13 Sept 2022
DOI: 10.4121/19307693
Dataset/Software: Software
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Nature-based solutions to mitigate salt intrusion
Hendrickx, G. G., 2024, 240 p.Research output: Thesis › Dissertation (TU Delft)
Open AccessFile84 Downloads (Pure) -
Predicting the response of complex systems for coastal management
Hendrickx, G. G., Antolínez, J. A. A. & Herman, P. M. J., 2023, In: Coastal Engineering. 182, 11 p., 104289.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile12 Link opens in a new tab Citations (Scopus)141 Downloads (Pure)
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