Predict flood maps quickly and accurately when applying water on the site surface, all while leveraging new built-in artificial intelligence.
Tasked with strict drainage compliance requirements for a solar panel farm in the UK countryside, Project Centre used machine learning deluge to streamline design workflows and achieve the results they needed.
InfoDrainage’s ML Deluge tool can analyze and predict channeling and ponding, enabling more informed decision making in the drainage design process.
Machine learning algorithms are not vulnerable to hydraulic modelling instabilities as no equations are being solved to establish where the water is.
Enable iterative, interactive, and real-time modification, encouraging users to make a change, get instant feedback on the flood map, understand the impact, and implement improvements to the design.
Project Centre leveraged the Machine Learning Deluge Tool to determine stormwater controls placement on a large 42-hectare solar farm in the United Kingdom.
InfoDrainage 2025 delivers additional functionality to Machine Learning Deluge, allowing users to stamp ponds and swales directly onto the surface and generate updated flood maps within the deluge analysis.
