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William Avery

Publications and source records attributed to William Avery.

4 recordsLinked to original sources
USGS2022

Loss of street tree canopy increases stormwater runoff

Urban forests have largely been overlooked for the role they play in reducing stormwater runoff volume by using hydrologic processes such as interception (rainfall intercepted by tree canopy), evapotranspiration (the transfer of water from vegetation into the atmosphere) and infiltration (percolation of rainwater into the Earth’s soil). Early research into the effects of trees on urban stormwater runoff used simple estimates based on assumptions of canopy coverage and design storm criteria. In a review of available literature on how capable urban trees are at reducing runoff, the Center for Watershed Protection (2017) found only six studies; three of them used measured data from a single plot, and the other three used models. When identifying gaps in research on the role of trees in stormwater management, Kuehler and others (2017) highlighted the need for studies that scale the local effects of urban trees to the larger sewershed catchment area, allowing a more holistic understanding of the urban tree canopy effects on hydrology. For these reasons, the U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency, U.S. Forest Service, and the University of Wisconsin, quantified the effect of removing urban street trees and their canopy on stormwater generation in a medium-density residential area. Using a paired-catchment experimental design, rainfall-runoff relations were characterized in two medium-density residential catchments in Fond du Lac, Wisconsin, during May through September in 2018–20. Results of the study are detailed in Selbig and others (2022). During the calibration phase, hydrograph metrics from paired runoff events were used to develop the relation between the control and test catchments with street trees in place. The ability to measure changes to the rainfall-runoff response after removal of tree canopy was made possible by an aggressive tree removal program by the city as a response to rapid infestation from the Agrilus planipennis (emerald ash borer). In March 2020, a total of 31 street trees were removed at the onset of the treatment period, resulting in a loss of 2,990 square meters of canopy over streets, driveways, sidewalks, and grassed areas.

Wisconsin↗
USGS2022

Quantifying the stormwater runoff volume reduction benefits of urban street tree canopy

Trees in the urban right-of-way areas have increasingly been considered part of a suite of green infrastructure practices used to manage stormwater runoff. A paired-catchment experimental design (with street tree removal as the treatment) was used to assess how street trees affect major hydrologic fluxes in a typical residential stormwater collection and conveyance network. The treatment consisted of removing 29 green ash (Fraxinus pennsylvanica) and two Norway maple (Acer platanoides) street trees from a medium-density residential area. Tree removal resulted in an estimated 198 m3 increase in surface runoff volume compared to the control catchment over the course of the study. This increase accounted for 4% of the total measured runoff after trees were removed. Despite significant changes to runoff volume (p ≤ 0.10), peak discharge was generally not affected by tree removal. On a per-tree basis, 66 L of rainfall per m2 of canopy was lost that would have otherwise been intercepted and stored. Runoff volume reduction benefit was estimated at 6376 L per tree. These values experimentally document per-capita retention services rendered by trees over a growing season with 42 storm events. These values are within the range reported by previous studies, which largely relied on simulation. This study provides catchment scale evidence that reducing stormwater runoff is one of many ecosystem services provided by street trees. This study quantifies these services, based on site conditions and a mix of deciduous species, and serves to improve our ability to account for this important yet otherwise poorly constrained hydrologic service. Engineers, city planners, urban foresters, and others involved with the management of urban stormwater can use this information to better understand tradeoffs involved in using green infrastructure to reduce urban runoff burden.

Wisconsin↗
USGS2022

Loss of street trees predicted to cause 6000 L/tree increase in leaf-on stormwater runoff for Great Lakes urban sewershed

Urban forests are recognized as a nature-based solution for stormwater management. This study assessed the underlying processes and extent of runoff reduction due to street trees with a paired-catchment experiment conducted in two sewersheds of Fond du Lac, Wisconsin. Computer models are flexible, fast, and low-cost options to generalize and assess the hydrologic processes determined in field studies. A state-of-the-art, public-domain model, which explicitly simulates urban tree hydrology, i-Tree Hydro, was used to simulate the paired-catchment experiment, and results from field observations and simulation predictions were compared to assess model validity and suitability as per conditions in the broader Great Lakes basin. Model parameters were aligned with observed conditions using automatic and manual calibration. Model performance metrics were used to quantify the weekly performance of calibration and to validate predictions. Those calibration metrics differed substantially between the two periods simulated, but most calibration metrics remained positive, indicating the model was not fitting only the period used for calibration. Predicted avoided runoff for a five-month leaf-on period was 64 L/m2 of canopy, 4 % lower than the field-estimated avoided runoff of 66 L/m2 of canopy. Interception was the most directly comparable process between the model and field observations. Based on 5 storms sampled, field estimation of precipitation intercepted and retained on trees averaged 63 % and ranged from 22 % to 81 %, while model estimation averaged 61 % and ranged from 36 % to 99 %. This model was able to fit predictions to observed catchment discharge but required extensive manual calibration to do so. The i-Tree Hydro model predicted avoided runoff comparable with the field study and earlier assessments. Additional field studies in similar settings are needed to confirm findings and improve transferability to other tree species and environmental settings.

Wisconsin↗