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ANNESI: Artificial Neural Network for Estuarine Salt Intrusion

Posted at 16/11/2022 by Gijs Hendrickx

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Gijs Hendrickx

Delft University of Technology

A screenshot of ANNESI

When developing nature-based solutions, understanding the system at hand is crucial. Within SALTISolutions, WP 7.1 addresses the development of nature-based solutions to mitigate salt intrusion; and therefore, an extensive sensitivity analysis has been executed focusing on which system-level parameters are governing the salt intrusion length in an estuary. Part of the output is an easy-accessible neural network, which is a quick tool to estimate salt intrusion in estuaries ranging from well-mixed to salt wedge types. This neural network is branded ANNESI – an Artificial Neural Network for Estuarine Salt Intrusion – and is open-source: https://doi.org/10.4121/19307693.

The following links leads you to the web-API that has been developed: https://annesi-web.netlify.app/. This provides low-level access to the neural network.

Last modified: 16/11/2022