State of the Dirt: 2025 in review

What Loam would have shown

We checked 24 riding areas once a day for all 365 days. That gave us 8,760 checks. Loam would have shown Prime on 6,327 of them and Dusty on 1,049. The rest were Caution, Stay off, or Frozen.

The Southwest was often too dry

Loam uses Dusty when the ground has drained but the surface has dried past the Prime range. It is the tan state in the app, labeled Rideable, very dry.

Most of those days came from the Southwest. Phoenix Mountains Preserve in Arizona had 284 Dusty days. Gooseberry Mesa in Utah had 213, and the Montrose/Uncompahgre area in Colorado had 134. Together, those three places made up 60 percent of all Dusty results in the report.

Dusty days were most common in midsummer. We counted 197 in July and 183 in August. A trail could be dry enough to ride without having the moisture that makes dirt feel firm and grippy.

Winter belonged to Quebec and New Brunswick

The strongest winter pattern came from eastern Canada. Mont-Sainte-Anne in Quebec had 110 Frozen days. Bromont, also in Quebec, had 85. Crabbe Mountain in New Brunswick had 82.

January and February accounted for 354 of the year's 592 Frozen results. Loam marks snow-covered ground as Frozen, even when there has not been much rain.

Oregon and Ohio had the most Stay off days

Mt. Hood in Oregon had 77 Stay off days, the most in the report. Caesar Creek in Ohio had 65. Bear Mountain Bike Park in British Columbia had 52, and Hardesty Portal in Oregon had 47.

Loam judged that enough water remained in the ground at those places for riding to damage the trail.

Colorado had a different pattern. Montrose/Uncompahgre, Colorado, had 231 Prime days and 134 Dusty days, with no Caution, Stay off, or Frozen days. These numbers tell us how the model behaves, not what riders found on the trail. Today's model sees that area as draining very quickly, and we should compare that result with real trail reports.

All 24 riding areas

Each line covers one place for one year, so the five numbers add up to 365. We included the state or province and grouped nearby parts of the country together.

How the replay worked

1. We chose 24 riding areas spread across the United States and Canada. Each one had the soil and terrain information Loam needs.
2. We downloaded the old hourly weather for each place, including rain, snow, temperature, and moisture in the soil.
3. We ran today's Loam model once a day from January 1 through December 31.
4. We checked that every hour and every daily result was present before using the numbers.

Altogether, the model read 217,152 hours of weather and produced all 8,760 daily results we expected.

What we can learn from this

This report shows how today's Loam model responds to one year of old weather. Clear patterns appear, including dry summers in the Southwest and long snowy stretches in eastern Canada.

Accuracy is a separate question. We do not have a matching diary of what the trails actually felt like on each day, and the replay does not include old park closures. These 24 places are also a sample, not every riding area in Loam.

Checking accuracy would require dated reports from people at the trails. We could then compare each report with what Loam said on the same day.

The science behind the estimate

Loam starts with a simple physical fact: a trail does not dry just because the rain stops. Water has to enter the ground, move through or across the soil, and leave the trail environment. How quickly that happens depends on the soil, terrain, vegetation, recent weather, and how wet the ground already was.

That is the problem Loam is designed to estimate. The model combines public soil and terrain information with recent weather and network characteristics to estimate how conditions are changing. It is a model of likely trail conditions, not a sensor embedded in the dirt, and it never overrides an official closure.

What the research says

USDA and USGS hydrology work treats infiltration, soil moisture, runoff, canopy, land cover, slope, and evapotranspiration as interacting parts of the water cycle. Recent trail research adds an important piece: rainfall intensity and accumulated rainfall can strongly affect runoff and sediment generation on recreational trails, while wet conditions make trail surfaces more vulnerable to degradation.

These sources describe the physical processes and research Loam draws from. They do not describe Loam's proprietary model or disclose its weights and thresholds.