Faint old singletrack descending steeply 500 feet from the CDT two track road to Gucci-Polaski Spring. The 1.6 km trail is marked at the south end with a faded wooden Water sign; follow rock cairns from there as the trail improves approaching the spring. At the north end, locate an old cairn where the road emerges from woods, then connect cairns across open hillside until the trail becomes visible. Gucci-Polaski Spring lies roughly one mile south with easier access.
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Strava Integration
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What you'll get
Automatic trail detection. Your ride's GPS is matched against MudWatch's catalogue via polyline overlap, not a proximity check. Trails you only passed at the trailhead don't get listed; trails you actually rode do.
Your preferred level of detail. New connections start with Short summary. Choose Full details for the longer trail, ride and weather breakdown, or No description for title-only updates.
Conditions from the time of your ride. Summaries use conditions at your activity's start, rather than the weather when it uploads.
Optional ride titles. Use names from matched trails. Default titles and timestamp-style device names can change; custom titles stay yours.
Preview before saving. See your latest activity with each option. Previewing and saving settings never change that activity or rewrite older rides.
Permissions needed: Read your activities and update descriptions and, only when enabled, default activity titles.
Changes apply to future uploads only. Your personal notes and custom titles are preserved.
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Overall ride conditions
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About MudWatch
Built for riders who care about more than yesterday's rain.
Generic weather apps tell you whether it's going to rain. That's not the question riders ask. MudWatch turns soil physics, terrain data, and live atmospheric models into a per-trail score and specific recommendations you can act on.
MudWatch for iPhoneTry the beta through TestFlight. Requires iOS 17 or later.
UnitsDistance, elevation, temperature, rain and wind.
Mountain accuracy
Elevation-adjusted temperature
Standard weather forecasts read the temperature at a low-elevation grid point, not at the trail. For a high-altitude trail, that gap can be 1,000m or more. Without correction, you get the valley temperature instead of the trail temperature.
Aiguille du Midi above Chamonix. Standard lapse rate: 6.5°C per km of altitude.
Every trail in MudWatch has a real GPS track with elevation. We compute the trail's actual altitude from those coordinates and lapse-rate-correct the displayed temperature, the apparent ("feels like") temperature, and the soil temperature. The conditions panel shows "(adjusted for trail altitude)" whenever the correction is meaningful. The cold-and-hot rules in the recommendation engine fire on the corrected number, so alpine trails get accurate frost warnings even when the valley is shirt-sleeve weather.
Looking forward
When will the trail dry out?
Knowing the trail is wet now is half the question. The other half: when will it be back in prime condition?
Soil moisture trajectory after a wet week. The trail crosses back into rideable territory mid-Friday afternoon.
MudWatch reads soil moisture forward through a 7-day window and combines it with evapotranspiration (the rate the soil loses moisture to sun, wind, and dry air) to predict when conditions will recover. If today is too wet, the conditions panel shows you when the next dry window opens. If the soil never drops back to a rideable level inside the forecast horizon, you'll see "stays wet through forecast window" instead of getting your hopes up.
Trail-specific drying
The atmospheric forecast tells half the story. The trail's own terrain tells the other half. MudWatch analyses each trail's GPS polyline to compute its dominant aspect (which compass direction the slopes face) and its average steepness, then biases the drying prediction accordingly:
North-facing trails in the northern hemisphere stay shaded longer and dry slower. We extend the recovery window for trails whose slopes predominantly face north or north-east. (Mirrored for the southern hemisphere.)
South-facing trails get more direct sun and dry faster. We pull recovery in for trails with strong south-facing exposure.
Steep terrain sheds water quickly. Steep trails recover faster than the local average; low-angle, flat trails hold puddles in low spots and dry slower.
The bias surfaces in the trail's recommendations as an extra line beneath the dry-by prediction, e.g. "Slopes face north; expect drying to lag the forecast by 12-24h on shaded sections".
3D view
The trail in three dimensions, with weather you can see
Every trail page renders the GPS track as a 3D ribbon coloured by gradient. Easy spinning stays cool blue, mid-steep ramps shift through green and amber, and the punchy double-digit pitches glow red. Drag to rotate, scroll to zoom, hover to read the gradient and elevation at any point.
Slanted rain, drifting cloud cover and a ground-plane wind arrow over the trail's actual GPS track.
The same atmospheric model that scores the ride drives the view's weather. Live drizzle slants in the wind direction at the rider's location. Snow drifts at a gentler angle. Fog softens the scene into low cloud. Thunderstorms darken the ceiling and fire jagged lightning bolts that briefly light up the entire model. A wind arrow rotates with the ground plane so you can see which way you'll be fighting on the climb.
Trail-state modelling
How wet is the trail, really?
The grip curve is a hump, not a slope
Grip peaks at "tacky". Moist but not wet. Both directions away from there reduce the score.
A bone-dry trail is dusty hardpack: corners blow out, dust over the surface eats grip. A waterlogged trail is mud: tyres pump, lines wash out, riders erode the trail. The sweet spot is tacky. Moist enough to bind, not so wet that it pumps. The score is shaped to match that physical reality, not "more rain equals worse."
Surface-aware grip curves
The grip curve shifts per surface type. Rock and pavement barely care about moisture. Roots get genuinely dangerous when wet. Clay turns gluey from the first sign of damp. Sand prefers slightly moist over bone-dry.
Rock / pavedLoam, dirt (default)RootsClay
Different surfaces, different penalties. A wet rocky descent and a wet rooty descent are scored very differently.
Surface
How it behaves
Rock
Drains fast. Almost no wetness sensitivity until properly saturated.
Roots
Fine when dry, treacherous when damp. Heavy penalty from "damp" onwards.
Clay
Sticky and slippery in equal measure once damp. Penalised earlier than other surfaces.
Sand
Loose and slow when bone-dry. Firm and grippy when slightly damp. Mud when wet.
Loose
Surface fails when wet. Dust over hardpack a different problem when dry.
Hardpack, gravel
Drains fast, peak at tacky, dust at the dry end of the curve.
Loam, dirt
The default curve. Standard MTB sweet spot at 18-28% saturation.
So a "wet rocky descent" and a "wet rooty descent" get scored very differently, even though the underlying soil moisture reading is the same.
Two-layer soil moisture
Most apps glance at recent rain. MudWatch reads the soil at two depths and uses whichever is wetter during your likely riding window. The shallow layer responds in minutes. The deeper layer takes days. Reading both lets us tell the difference between "rain just stopped, surface is slick" and "soaked through to the bones".
Cross-section: rain hits the tread, the surface layer responds first, the root zone slowly tracks. We score the worse of the two during your likely riding window.
Smart timing
The best window today, not just "today is fine"
"8/10 today" doesn't help you plan. MudWatch scores the next 12 hours individually, weighing soil state, rain timing, temperature comfort, and the daylight budget for a trail of this length. The recommendation comes back as a specific time: "around 09:00".
In tropical climates, that's early morning or late afternoon. Midday gets pushed down by heat. In northern winter, it's mid-day. The cold ends of the day get penalised instead. Same model, opposite advice, no climate switch needed.
Sunset-aware. A window that wouldn't leave enough daylight to safely finish the ride gets hard-cut. Lost-light-on-the-mountain is a real risk we don't pretend otherwise.
Beyond the score
Conditions that matter, surfaced when they matter
Air quality
Real PM2.5 readings and US AQI. Recommendations soften or escalate based on whether sensitive groups should be cautious.
UV index
Flags very high and extreme UV days where sun protection genuinely matters, especially on long climbs without canopy.
Pollen
Per-species counts for grass, birch, ragweed, alder, mugwort, and olive. Allergy-prone riders get a heads-up before they're out on the trail.
Freezing level
When the trail tops out above the day's freezing line, expect frost on north-facing rock, slick timber bridges, and ice in the shade. Even when the valley feels mild.
Thunderstorm risk
We watch atmospheric instability (CAPE), not just rain forecasts. High CAPE on a warm afternoon means storms can pop up from a clear sky. Hazard-level alerts before the first lightning strike.
Sun glare
We compute the sun's azimuth at low-light hours and compare to the trail's start-to-end bearing. East-running trails get a "low sun until 06:42" callout. North-south trails get the all-clear.
Headwind detection
Wind direction vs trail direction. If the climb out is into a cold headwind at 25 km/h, you'll know to bring a wind layer before you set off.
Recent rain
Real measured precipitation over the last 24, 48, and 72 hours. Not estimated from cloud cover or humidity. Actual rainfall.
Trail intelligence
Every trail is a real GPS track
The mini-map on a trail page is the trail's actual shape. The elevation profile is its actual climb and descent. Length, max altitude, start and end heights are all derived from the GPS, not from metadata that might be wrong. Hover the elevation chart and a synchronised dot moves on both, with distance and altitude at that point.
The trail's bearing falls out of the same data and powers the sun-glare and headwind features. Without a real GPS track, none of those would exist.
MudWatch Beta. Mountain bike trail conditions, modelled.
Trail matrix
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