Is the InfoDrainage ML Deluge tool the future in drainage AI?

Autodesk AI inside InfoDrainage represents a leap forward in drainage design technology, bringing Machine Learning capabilities directly into the workflows that engineers use daily. This artificial intelligence integration, powered by the InfoDrainage Machine Learning Deluge tool, may transform how professionals approach overland flow analysis and stormwater control placement.

That is the set-up for Civil Tech Source’s latest YouTube video entitled “Is this the Future in Drainage AI? – AutoDesk InfoDrainage Deluge ML”. The channel is run by Ferdi Jafar, whose purpose in creating videos is to provide educational content to help new graduate engineers find appropriate solutions to common challenges at the start of their careers.

In the video, Ferdi focuses on the Machine Learning Deluge functionality inside InfoDrainage, how integrated SuDS modeling inside the app works, and how InfoDrainage integrates with Civil 3D, including a demo of the new Civil 3D 2026.2 pond design tools. Drainage engineers, civil engineers, and water management professionals will find practical insights in this video for streamlining their design process and saving substantial time on projects.

The foundation of the Machine Learning Deluge tool

The Machine Learning Deluge tool represents Autodesk’s first major step toward AI-powered drainage design. Rather than solving complex hydrodynamic equations for every triangle in a surface model, this technology uses pattern recognition from extensive training data to predict surface water behavior.

How the AI training works

The system learned from more than 10,000 traditional 2D hydraulic simulations, identifying patterns between ground surface characteristics and resulting flood extents. When users run the interactive Deluge, the AI applies these learned patterns to predict ponding locations, flow directions, and water accumulation zones almost instantaneously.

Interactive Deluge vs. traditional 2D analysis

Traditional 2D overland flow analysis examines every triangle in a surface model, solving hydraulic equations to determine water movement. This process requires significant computation time and can experience numerical instabilities on complex terrains.

The ML Deluge Tool takes a different approach. It processes contour-based surface data and applies Machine Learning predictions rather than solving equations. The result matches traditional 2D output closely while running in seconds instead of minutes. For engineers exploring drainage solutions early in the design process, this speed difference transforms how quickly they can evaluate options.

Takeaway #1: ML Deluge saves massive time on overland flow analysis

The first major breakthrough Ferdi demonstrates in the video is the sheer efficiency of the ML Deluge tool for surface water analysis. Engineers can now visualize flood risks and flow patterns in real time, enabling rapid iteration that was previously impossible.

Instant visualization of surface water behavior

When running the interactive Deluge on a custom terrain surface – complete with mounds, ditches, and varying slopes – the AI generates predictions that closely match traditional 2D analysis results. Flow arrows indicate water movement directions, ponding areas highlight accumulation zones, and the visualization updates almost immediately.

This functionality proves particularly valuable for master planning scenarios where professionals need high-level viability assessments without detailed 3D modeling. Teams can identify hotspots, evaluate general drainage patterns, and make informed decisions about infrastructure placement before committing to full design development.

Accurate pattern recognition

Ferdi says the ML Deluge predictions demonstrate remarkable accuracy because they draw from such extensive training data. While ML Deluge doesn’t analyze every individual triangle like traditional methods, it provides sufficient fidelity for preliminary design decisions and workflow optimization.

As he notes, engineers should understand that this tool excels at early-stage exploration and iterative testing. For final validation of critical projects, traditional 2D analysis remains the appropriate choice, but the AI-powered approach eliminates countless hours of preliminary investigation.

Takeaway #2: Integrated SuDS modeling eliminates export-import cycles

Ferdi thinks the second game-changing capability is how ML Deluge incorporates SuDS features directly within the analysis environment. This integration fundamentally changes drainage design workflows by removing the tedious back-and-forth between applications.

Direct pond and swale testing

InfoDrainage users can add ponds, swales, and other stormwater controls directly in the model and immediately see how these features affect surface water behavior, which Ferdi demonstrates in the video. In fact, InfoDrainage contains a long list of SuDS features inside the software like infiltration trenches, cellular storage, porous pavement, soakaways, bioretention systems, rain gardens, and wet ponds and infiltration basins, which can all be linked together to evaluate an entire site.

Ferdi shows how, when placing a 1-meter-deep pond at a specific location, ML Deluge instantly regenerates the flood map to show updated flow patterns being redirected into the new storage feature. The AI visualization showed reduced water accumulation in previously problematic areas, all without leaving the InfoDrainage interface or rebuilding surfaces in Civil 3D.

Workflow transformation

He says the traditional workflow starts to feel laborious after using the new InfoDrainage and Civil 3D integration. The old way required engineers to:

1. Bring the proposed model from Civil 3D into InfoDrainage
2. Run simulation analysis to verify performance
3. Export results back to Civil 3D
4. Model SuDS features with proper elevations
5. Create combined surfaces with all drainage components
6. Import the updated model back into InfoDrainage
7. Run 1D-2D analysis on the complete design

With integrated SuDS modeling, professionals can skip steps 3-6 entirely. The ML Deluge tool confirms whether stormwater control placement works before any external surface modeling occurs. This efficiency gain compounds across every design iteration throughout a project.

Takeaway #3: Civil 3D 2026.2 pond tools dramatically simplify surface design

Ferdi’s third major takeaway involves the new drainage design options introduced in Civil 3D 2026.2, which complement InfoDrainage AI workflows by dramatically simplifying pond creation and editing within the CAD environment.

Automated pond creaion with smart defaults

The updated pond creation tool streamlines what was previously a multi-step process. Engineers specify a starting elevation and depth, draw a single feature line, and Civil 3D automatically generates:

• Bottom surface at the correct elevation
• Top elevation with specified freeboard
• Storage volume calculations using surface volumetrics
• Complete pond geometry ready for further refinement

This automation replaces the previous workflow of creating surfaces, pasting feature lines, adjusting elevations manually, and running separate volumetric analyses. The time savings amount to 5-10 minutes per design iteration, which is a significant efficiency gain that accumulates across complex projects.

Seamless InfoDrainage integration

These Civil 3D improvements work in harmony with InfoDrainage AI workflows. Because there is an InfoDrainage toolbar directly inside Civil 3D, engineers who take advantage of InfoDrainage can go even further:

1. Design ponds quickly using the new automated tools
2. Export surfaces to InfoDrainage for ML Deluge analysis
3. Verify drainage performance in seconds
4. Return to Civil 3D for refinements if needed
5. Repeat the cycle with minimal friction

Ferdi’s verdict: The combination of fast pond design in Civil 3D and instant analysis in InfoDrainage creates an efficient feedback loop that accelerates the entire drainage design process.

Ferdi’s practical implementation advice

Understanding these features is valuable, but implementing them requires some practical considerations for teams transitioning to AI-enhanced workflows.

Getting started with Machine Learning Deluge

He recommends beginning by running the ML Deluge on familiar projects where you already know the expected drainage behavior. This builds confidence in the AI predictions and helps calibrate expectations for how the tool performs on different terrain types. The Machine Learning approach excels on typical residential and commercial sites – the scenarios well-represented in its training data.

Balancing AI speed with validation deeds

He recommends using the ML Deluge tool for preliminary design exploration, stormwater control placement optimization, and master planning assessments – but he says reserve traditional 2D analysis for final validation of critical drainage infrastructure. This balanced approach maximizes time savings while maintaining appropriate engineering rigor.

Updating your software environment

You can access the new pond design features by updating Civil 3D to version 2026.2 or later. The drainage tools appear in the ribbon interface and integrate with existing surface modeling workflows. InfoDrainage users with current subscriptions can access the ML Deluge functionality immediately through their existing installations, via an InfoDrainage toolbar inside Civil 3D. (Tip: Autodesk offers a free trial for InfoDrainage, with no credit card needed, so you can easily test it out.)

These AI tools lay the foundation for continued innovation in drainage design technology. As Autodesk expands Machine Learning capabilities across their water infrastructure platforms, engineers who build familiarity with these features now will be well-positioned for future developments in AI-powered design automation.

More on the latest InfoDrainage advances

• The power of polygons: Land use and soil type incorporated into sub-catchments in InfoDrainage 2025.4
• Let the app do it for you: New in InfoDrainage 2026.1: ‘AutoProfiling’ generates drainage profiles for you
• Stay up to date on what’s coming next with our high-level Water Infrastructure Roadmap.