Evapotranspiration Estimation Using a Water Balance Model for Urban Green Roof Vegetation in Portland, OR
Start Date
3-16-2026 2:20 PM
End Date
3-16-2026 2:29 PM
Abstract
Evapotranspiration (ET) plays a critical role in urban cooling and stormwater management, yet ET rates vary substantially across plant functional types, in large part due to differences in photosynthetic pathways. Quantifying these differences is essential for optimizing vegetation selection in green roofs and other urban green infrastructure systems. In this study, ET rates were estimated using a water balance model implemented in Python for three plant species representing distinct photosynthetic pathways: Idaho fescue (Festuca idahoensis, C₃), buffalo grass (Bouteloua dactyloides, C₄), and white stonecrop (Sedum album, CAM). The analysis was conducted for the period from September 14 to March 10 using precipitation, irrigation, runoff, and soil moisture measurements collected in Portland, Oregon. ET rates were calculated at both half-hourly and daily timescales. Results indicate that most estimated ET values fell within the expected range of 0–20 mm/day. Among the three plant types, the C₃ species generally exhibit the highest ET rates. Occasional negative ET values are observed, likely associated with increases in soil moisture storage during certain periods, highlighting potential uncertainties in water balance closure or data collection. Temporal patterns in ET closely follow total water inputs from precipitation and irrigation, with higher ET rates occurring during wetter periods. These findings demonstrate the utility of water balance modeling for evaluating species-specific ET behavior and provide insights for selecting vegetation that maximizes cooling and hydrologic benefits in urban green infrastructure applications.
Subjects
Hydrology, Land/watershed management, Plant ecology
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Evapotranspiration Estimation Using a Water Balance Model for Urban Green Roof Vegetation in Portland, OR
Evapotranspiration (ET) plays a critical role in urban cooling and stormwater management, yet ET rates vary substantially across plant functional types, in large part due to differences in photosynthetic pathways. Quantifying these differences is essential for optimizing vegetation selection in green roofs and other urban green infrastructure systems. In this study, ET rates were estimated using a water balance model implemented in Python for three plant species representing distinct photosynthetic pathways: Idaho fescue (Festuca idahoensis, C₃), buffalo grass (Bouteloua dactyloides, C₄), and white stonecrop (Sedum album, CAM). The analysis was conducted for the period from September 14 to March 10 using precipitation, irrigation, runoff, and soil moisture measurements collected in Portland, Oregon. ET rates were calculated at both half-hourly and daily timescales. Results indicate that most estimated ET values fell within the expected range of 0–20 mm/day. Among the three plant types, the C₃ species generally exhibit the highest ET rates. Occasional negative ET values are observed, likely associated with increases in soil moisture storage during certain periods, highlighting potential uncertainties in water balance closure or data collection. Temporal patterns in ET closely follow total water inputs from precipitation and irrigation, with higher ET rates occurring during wetter periods. These findings demonstrate the utility of water balance modeling for evaluating species-specific ET behavior and provide insights for selecting vegetation that maximizes cooling and hydrologic benefits in urban green infrastructure applications.