AI-Powered
Trail Intelligence
MudWatch goes beyond weather data — it models how trails actually behave after rain, using surface type, gradient, drainage, and elevation to forecast rideable conditions day by day.
How it works
Accumulated Rainfall Modeling
Trails don't recover the moment the rain stops. MudWatch analyzes 72-hour accumulated rainfall and applies time-decay algorithms that simulate natural drying — weighting recent precipitation more heavily and accounting for how different substrates hold and release moisture over time.
Surface Intelligence
Material-Specific Scoring
Each surface type behaves differently in wet conditions. The model applies independent wetness curves per material:
- Clay — Becomes extremely slippery; penalized heavily after rain
- Dirt & earth — Holds moisture longest; extended drying window
- Rock & gravel — Drains fast; recovers within hours
- Grass — Deceptively slippery despite apparent drainage
Risk Assessment
Grade-Based Adjustments
Technical terrain carries higher risk when wet. MudWatch applies grade multipliers to condition scores:
- Green — 40% more resilient to rain impact
- Blue — Baseline rain sensitivity
- Black / Double Black — 40–60% additional wet-condition penalty
Steeper trails become dangerous, not just unpleasant — the scoring reflects that distinction.
Environmental Factors
Microclimate Awareness
Beyond rainfall, the model incorporates sun exposure and shade (canopy trails dry slower), elevation-adjusted precipitation, humidity-influenced drying rates, wind patterns on exposed ridgelines, and drainage quality per trail segment. These variables combine into a single rideable score, updated daily.
The Bottom Line
Smarter Than a Weather App
A light drizzle after three dry weeks is nothing. The same drizzle after a saturated fortnight closes the trail. MudWatch knows the difference — so you can stop guessing and start riding on the right days.
