Remote sensing-based evapotranspiration modeling for several land uses using SETMI model for Nebraska

I. Z. Goncalves; C. M. U. Neale; S. Akasheh; B. Barker

doi:10.1117/12.2684084

17 October 2023 Remote sensing-based evapotranspiration modeling for several land uses using SETMI model for Nebraska

I. Z. Goncalves, C. M. U. Neale, S. Akasheh, B. Barker

Proceedings Volume 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV; 127270Z (2023) https://doi.org/10.1117/12.2684084
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Abstract

Daily evapotranspiration (ET) estimation using remote sensing procedures is important for proper irrigation management based on crop type and at field scales. This research aimed to estimate daily ET for grassland, bare soil, corn, soybeans, cottonwood, and red cedar through the hybrid modelling approach named Spatial EvapoTranspiration Modeling Interface (SETMI) applied in southwest Nebraska, USA, based on two source model using satellite image inputs, and weather datasets. Multispectral and thermal infrared imagery from satellite sensors joined with climate, crop cover classification image, and weather datasets were used to estimate ET for the period 2008-2013. SETMI was applied using multispectral and thermal infrared imagery from Landsat 7 and 8. SETMI model considers the ET obtained from the two-source energy balance model at satellite overpass time and was validated using latent heat fluxes measured with an Eddy covariance system (EC) on grassland. Crop coefficient (Kc) was estimated using modeled ET and daily reference ET over the season. Modeled ET showed a strong correlation to the ground data from EC, with ET presenting R² equal to 0.96. Overall, the maximum average Kc over the period was satisfactory for all land uses ranging from 0.45 for bare soil to 1.2 for corn. On average, bare soil showed the lowest Kc, while corn and soybeans had the highest values. The SETMI model produced adequate estimated daily Kc values over the years through the TSEB model, confirming the applicability of the model in estimating ET.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

I. Z. Goncalves, C. M. U. Neale, S. Akasheh, and B. Barker "Remote sensing-based evapotranspiration modeling for several land uses using SETMI model for Nebraska", Proc. SPIE 12727, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV, 127270Z (17 October 2023); https://doi.org/10.1117/12.2684084

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