Estimation of Evapotranspiration of Urban Turfgrass Using Eddy Covariance Flux Measurements and Remote Sensing-Based Models
Location
Logan, UT
Start Date
3-29-2022 4:15 PM
End Date
3-29-2022 7:00 PM
Description
Green urban areas are increasingly affected by water scarcity and climate change. The combination of warmer temperatures and increasing drought poses substantial challenges for management of urban landscapes in the western US. Evapotranspiration (ET) is the main use of water in urban landscapes. Eddy Covariance (EC) measurements allows quantitative estimates of actual ET in turfgrass. The two-source energy balance (TSEB) remote sensing-based model offers the capability to deliver spatial maps of actual ET. We hypothesize that currently satellite spatial resolutions may not be adequate to discriminate spectral features of trees, grasses, shrubs, etc. Under such a hypothesis, this work proposes to address the heterogeneity and scale issues by using high-resolution imagery data acquired from multispectral and thermal cameras mounted on unmanned aircraft systems (UAS); and wavelet analysis to identify spatial scales at which biomass and surface energy balance components can be adequately quantified. The goal of this research is to quantify ET of turfgrass and connect the findings with the TSEB ET model and variations of weather and climate. The study location is a golf course in Roy, Utah, USA. We estimate hourly, daily, and seasonal ET of the turfgrass surface using eddy covariance flux measurements; evaluate the ability of the TSEB model to estimate instantaneous and daily ET by using remotely sensed images from unmanned aircraft system and Landsat satellites; and determine how ET responds to variations of temperature, humidity, and advection of heat from the surrounding lands. This presentation will show the preliminary results on EC data processing and TSEB model outputs.
Estimation of Evapotranspiration of Urban Turfgrass Using Eddy Covariance Flux Measurements and Remote Sensing-Based Models
Logan, UT
Green urban areas are increasingly affected by water scarcity and climate change. The combination of warmer temperatures and increasing drought poses substantial challenges for management of urban landscapes in the western US. Evapotranspiration (ET) is the main use of water in urban landscapes. Eddy Covariance (EC) measurements allows quantitative estimates of actual ET in turfgrass. The two-source energy balance (TSEB) remote sensing-based model offers the capability to deliver spatial maps of actual ET. We hypothesize that currently satellite spatial resolutions may not be adequate to discriminate spectral features of trees, grasses, shrubs, etc. Under such a hypothesis, this work proposes to address the heterogeneity and scale issues by using high-resolution imagery data acquired from multispectral and thermal cameras mounted on unmanned aircraft systems (UAS); and wavelet analysis to identify spatial scales at which biomass and surface energy balance components can be adequately quantified. The goal of this research is to quantify ET of turfgrass and connect the findings with the TSEB ET model and variations of weather and climate. The study location is a golf course in Roy, Utah, USA. We estimate hourly, daily, and seasonal ET of the turfgrass surface using eddy covariance flux measurements; evaluate the ability of the TSEB model to estimate instantaneous and daily ET by using remotely sensed images from unmanned aircraft system and Landsat satellites; and determine how ET responds to variations of temperature, humidity, and advection of heat from the surrounding lands. This presentation will show the preliminary results on EC data processing and TSEB model outputs.