Open AccessStatistical Analysis of Vegetation and Stormwater Runoff in an Urban Watershed During Summer and Winter Storms in Portland, Oregon, U.S.
Author(s) -
Geoffrey H. Donovan,
David T. Butry,
Megan Y. Mao
Publication year - 2016
Publication title -
arboriculture and urban forestry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.222
H-Index - 47
eISSN - 2155-0778
pISSN - 1935-5297
DOI - 10.48044/jauf.2016.028
Subject(s) - surface runoff , groundcover , stormwater , environmental science , hydrology (agriculture) , storm , vegetation (pathology) , watershed , runoff curve number , impervious surface , snowmelt , geography , ecology , meteorology , geology , medicine , geotechnical engineering , pathology , machine learning , computer science , biology
Past research has examined the effect of urban trees, and other vegetation, on stormwater runoff using hydrological models or small-scale experiments. However, there has been no statistical analysis of the influence of vegetation on runoff in an intact urban watershed, and it is not clear how results from small-scale studies scale up to the city level. Researchers address this gap in the literature by estimating random-effects regression models of the effect of trees and other vegetation on total runoff and peak runoff for a summer (15–16 June 2010) and a winter (18–19 December 2010) storm in Portland, Oregon, U.S. Researchers found that additional tree canopy cover was associated with lower runoff in the summer storm, but the significance of the tree coefficient was sensitive to model structure. Researchers found that additional groundcover (grass and shrubs) associated with lower peak flow in the summer, and this result was robust to model structure. Neither trees nor groundcover were significantly associated with winter stormwater runoff. Results suggest that trees and other vegetation can be effective at moderating stormwater runoff. However, vegetation is not as effective in the winter, which is consistent with past modeling and experimental studies.