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CC BY V4.0, Open Access
Thesis
SCALING ENERGY BALANCE EVAPOTRANSPIRATION MODELS, METRIC, SEBAL, AND SSEB, TO HIGH RESOLUTION sUAS IMAGERY
Washington State University
Master of Science (MS), Washington State University
07/2024
DOI:
https://doi.org/10.7273/000006916
Abstract
A point measurement of evapotranspiration (ET) is usually not enough to capture the spatiotemporal variability within an irrigated field for precision irrigation management. Therefore, the key goal of this thesis was to study the suitability and scalability of high-altitude remote sensing driven ET estimation models for generating high resolution ET maps of irrigated field crops, with tall wheatgrass as a model crop. To realize this goal, three satellite-based surface energy balance (SEB) ET models have been adapted to work with sUAS (small Unmanned Aerial Systems) imagery. Mapping Evapotranspiration at high Resolution with Internalized Calibration (METRIC), Surface Energy Balance Algorithm for Land (SEBAL), and Simplified Surface Energy Balance (SSEB) were the models used for producing ET maps using sUAS aerial imagery. For the growing season of 2023, sUAS multispectral and thermal images of a drip irrigated tall wheatgrass field were captured with a GSD of 2 cm. Since solar radiation is the primary driver of the ET process, the first objective was focused on the estimation of net radiation from sUAS imagery. The broadband albedo, a parameter critical for estimating the net radiation, was computed through the weighted average of narrow-band reflectance. The weighted average was obtained by simulating the incoming solar radiation and the narrow-band reflectance maps obtained from the sUAS multispectral imagery. The comparison of the computed albedo with the measured albedo yielded a root mean square error (RMSE) of 0.02, a mean absolute error (MAE) of 0.01, and a mean absolute percentage error (MAPE) of 5.92%. As for the computed and measured net radiation the RMSE was 32.77 W/m2, the MAE was 23.03 W/m2 and the MAPE was 3.91%. The second objective assessed how the three ET models' estimation values correlate with one another. The model specific ET maps were correlated on a pixel-by-pixel basis. The ET estimates from the three models were then ensembled to come up with a single ET estimate. Upon comparison of the ensembled ET with the amount of water use in the 25, 50, 75% water-stressed and control (100% of required water based on WHAT?) irrigated plots, an MAE value of 0.70 mm/day, RMSE of 0.79 mm/day, and MAPE value of 2.15% was observed. Overall, results suggest that ET maps derived from sUAS imagery, can be used to help make informed irrigation decisions.
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Details
- Title
- SCALING ENERGY BALANCE EVAPOTRANSPIRATION MODELS, METRIC, SEBAL, AND SSEB, TO HIGH RESOLUTION sUAS IMAGERY
- Creators
- Elda Yitbarek Bezuayene
- Contributors
- Lav Khot (Chair)Troy R. Peters (Committee Member)Kirti Rajagopalan (Committee Member)Bernardita Sallato (Committee Member)
- Awarding Institution
- Washington State University
- Academic Unit
- Department of Biological Systems Engineering
- Theses and Dissertations
- Master of Science (MS), Washington State University
- Publisher
- Washington State University
- Number of pages
- 81
- Identifiers
- 99901152439001842
- Language
- English
- Resource Type
- Thesis