With higher evapotranspiration (ET) rates compared to other urban land covers, urban forests can play an important role in stormwater flood reduction. Effective incorporation of urban forests into stormwater planning and green infrastructure design requires methods that can quantify ET across mixed-land use landscapes but with sufficient spatial resolution for parcel-specific rates. We used Landsat-derived ET from 2000 to 2018 to estimate 30-m annual ET rates across the City of Virginia Beach, USA, a large urban landscape with increasing flood concerns. Our objectives were to compare ET rates across land covers and then identify land attributes and models to explain spatial ET variation. Upland and wetland forests had higher ET compared to urban areas, where wetland forest had annual ET rates 3–4 times that of urban and contributed ca. 40% of total landscape ET despite covering only 20% of the area. These quantified ET rates highlight the disproportional role that urban forests may play in stormwater runoff reduction, and can inform scenarios of land use change to prioritize forest conservation efforts. Relationships between ET rates and aggregated, higher resolution land attribute data indicated key drivers, where ET increased with canopy cover and decreased with impervious cover and water table depth. A regression model combining these drivers explained approximately 70% of ET variation, providing means to downscale ET estimates to further guide stormwater planning at finer spatial scales. Our findings emphasize the importance of urban forests as green infrastructure elements and point to potential approaches to better incorporate them in stormwater planning decisions.

与其他城市土地覆盖相比，具有更高的蒸发蒸腾（ET）率，城市森林可以在减少暴雨洪水方面发挥重要作用。要有效地将城市森林纳入雨水规划和绿色基础设施设计中，就需要能够对混合土地利用景观中的ET进行量化的方法，但要有足够的空间分辨率来满足特定地块的费率。我们从2000年至2018年使用Landsat衍生的ET来估算美国弗吉尼亚海滩市的3,000万年ET率，这是一个充满洪水担忧的大城市景观。我们的目标是比较整个土地覆盖层的ET率，然后确定土地属性和模型以解释空间ET的变化。与城市地区相比，旱地和湿地森林的ET较高，而城市地区的湿地森林的年ET速率是城市的3-4倍，约占城市的ET。尽管仅占该地区的20％，但占总景观ET的40％。这些量化的ET比率突显了城市森林可能在减少雨水径流中所起的不成比例的作用，并且可以为土地利用变化的情况提供依据，从而优先进行森林保护工作。ET率与更高分辨率的土地属性数据之间的关系表明了主要驱动力，其中ET随着冠层的覆盖而增加，而随着不透水层和地下水位的降低而降低。结合这些驱动因素的回归模型解释了大约70％的ET变化，为缩减ET估算值提供了手段，以进一步指导更精细的空间尺度上的雨水规划。我们的发现强调了城市森林作为绿色基础设施要素的重要性，并指出了将其更好地纳入雨水规划决策的潜在方法。