How the National Capital Area's Park Trees Hold Back Stormwater Runoff

Surface runoff is water the land cannot absorb. In cities, where so much ground is paved, storm runoff is a particular worry: large volumes of it carry pollution, trash and excess nutrients off the streets into streams, wetlands, rivers, lakes and the ocean.

Trees and shrubs help. Their leaves and branches intercept rain, and their roots help water soak into and stay in the soil.

Runoff avoided by the parks' trees

The National Park Service's Urban Ecology Research Learning Alliance used the i-Tree software to estimate how much runoff the forests of the National Capital Area's parks prevent: about 2.9 million cubic metres a year. (Manassas National Battlefield Park was left out, because rainfall data for the reference dates were not available.)

Avoided runoff is the difference between the year's runoff with and without the vegetation, based on the rain intercepted by leaves only — branches and bark intercept rain too, but are not counted — and on weather data from a chosen NOAA station.

Total avoided runoff by park: Prince William Forest Park the most (about 1 million cubic metres a year), Wolf Trap the least (about 4,000). NPS, Urban Ecology Research Learning Alliance.

Avoided runoff per hectare: Rock Creek and Prince William the highest (240 cubic metres per hectare a year), Antietam the lowest (36). NPS, Urban Ecology Research Learning Alliance.

Why it matters

The canopy holds rain on its leaves and branches and delays it reaching the ground — especially useful where the ground is paved. Roots reduce erosion, open the soil so rain can soak in and recharge groundwater, and filter the water, catching pollutants.

Sources

• National Park Service, Urban Ecology Research Learning Alliance, "Avoided Runoff and Urban Forests," in Eco-Values of the Urban Forest: i-Tree Analysis. https://www.nps.gov/articles/000/uerla-trees-runoff.htm
• Urban Ecology Research Learning Alliance, i-Tree Ecosystem Analysis: Urban Forest Effects and Values, 2018. https://irma.nps.gov/DataStore/Reference/Profile/2290090