H021-06
How high to fly? Evaluating different elevations for mapping evapotranspiration from remotely piloted aircrafts
Monday, 7 December 2020: 17:50
Virtual
Logan Austin Ebert1, Alex J Chisholm2, Jacob Prater3, Samuel C Zipper4, Ammara Talib5, Ankur R Desai5 and Mallika Arudi Nocco1, (1)University of California Davis, Department of Land, Air, and Water Resources, Davis, CA, United States, (2)Wysocki Farm Company, Stevens Point, WI, United States, (3)University of Wisconsin Stevens Point, Department of Soil and Waste Resources, Stevens Point, WI, United States, (4)University of Kansas, Kansas Geological Survey, Lawrence, United States, (5)University of Wisconsin Madison, Madison, WI, United States
Abstract:
A key challenge for bridging precision irrigation research and application is how best to monitor evapotranspiration (ET) and water stress in real-time. Eddy Covariance towers and lysimeters are vetted methods of monitoring ET and water stress but can lack field-size domains, spatial resolution, and be cost prohibitive. Remotely sensed data offer a potential solution to this problem. However, aerial and satellite imagery have the drawback of spatiotemporal resolution and cloud interference. Recent advancements in remotely piloted aircrafts (RPAs) have made frequent, low-flying optical and thermal imagery collection more economical and feasible than ever before. While low flight elevations improve image resolution and can reduce cloud interference, they require more imagery to cover a field and therefore increase battery usage and post-processing needs. In order to find the optimal RPA flight elevation for irrigation management, the goal of this study is to evaluate the influence of capture elevation on modeled ET values.
The goal of our project was to evaluate the influence of capture elevation on modeled evapotranspiration values. The optical and thermal data were collected from a commercially irrigated potato field in the Wisconsin Central Sands during the 2019 growing season. A total of eight mission sets were flown. Each mission set was flown using a quadcopter RPA system and combined multispectral/thermal camera. Mission sets included flights at 90, 60, and 30 m above ground level. Ground measurements of surface temperature and soil moisture were collected throughout the domain within 15 minutes of each RPA mission set. ET values were modeled from the flight data using the High-Resolution Mapping of Evapotranspiration (HRMET) model. HRMET-derived ET maps are compared to ET estimates from an Eddy Covariance system within the flight domain. Ongoing results will be used to develop best practices and assess trade-offs for integrating RPAs as decision support tools for irrigation and water management.
