Testing the Accuracy of QWaterModel Against Eddy Covariance Evapotranspiration Data of Almond Orchards Located in California Using Landsat Imagery

The paper investigates the efficacy of the QWaterModel, a QGIS plugin designed for estimating evapotranspiration (ET) in almond orchards located in California's water-scarce San Joaquin Valley. Given the anticipated 25% rise in global water requirements for agriculture by 2080 and the increasing drought pressures, the need for innovative water management practices is paramount (Nikolaou et al., 2020). ​The research aims to compare ET estimates from QWaterModel with eddy covariance ET measurements (ECET) across two almond orchards (WWF and OLA) to assess the model's reliability in real-world agricultural applications.​ Utilizing Landsat imagery and ground-based ECET data, the study finds a strong correlation (r = 0.87, R² = 0.75) between QWaterModel estimations and actual ET measurements, indicating that the model effectively captures the dynamics of water usage in almond cultivation. The QWaterModel's user-friendly interface and integration with satellite data highlight its potential as a practical tool for water management, especially for farmers lacking advanced technical skills. Nevertheless, variability in estimates suggests that the model may oversimplify complex ET processes affected by local conditions, urging the need for further calibration and validation against diverse data sources. The findings underscore the importance of accurate ET estimation for sustainable agricultural practices amidst growing water scarcity and point out ways to enhance QWaterModel's applicability.

Publication Details

Journal
Furman University Scholar Exchange (Furman University)
Published
2025-04-05
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
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article

Testing the Accuracy of QWaterModel Against Eddy Covariance Evapotranspiration Data of Almond Orchards Located in California Using Landsat Imagery

Furman University Scholar Exchange (Furman University)
Plant Water Relations and Carbon Dynamics
article

Testing the Accuracy of QWaterModel Against Eddy Covariance Evapotranspiration Data of Almond Orchards Located in California Using Landsat Imagery

article en

Abstract

The paper investigates the efficacy of the QWaterModel, a QGIS plugin designed for estimating evapotranspiration (ET) in almond orchards located in California's water-scarce San Joaquin Valley. Given the anticipated 25% rise in global water requirements for agriculture by 2080 and the increasing drought pressures, the need for innovative water management practices is paramount (Nikolaou et al., 2020). ​The research aims to compare ET estimates from QWaterModel with eddy covariance ET measurements (ECET) across two almond orchards (WWF and OLA) to assess the model's reliability in real-world agricultural applications.​ Utilizing Landsat imagery and ground-based ECET data, the study finds a strong correlation (r = 0.87, R² = 0.75) between QWaterModel estimations and actual ET measurements, indicating that the model effectively captures the dynamics of water usage in almond cultivation. The QWaterModel's user-friendly interface and integration with satellite data highlight its potential as a practical tool for water management, especially for farmers lacking advanced technical skills. Nevertheless, variability in estimates suggests that the model may oversimplify complex ET processes affected by local conditions, urging the need for further calibration and validation against diverse data sources. The findings underscore the importance of accurate ET estimation for sustainable agricultural practices amidst growing water scarcity and point out ways to enhance QWaterModel's applicability.

Furman University Scholar Exchange (Furman University)
Zero hunger
Openalex Percentile: Top 49%
Plant Water Relations and Carbon Dynamics
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Testing the Accuracy of QWaterModel Against Eddy Covariance Evapotranspiration Data of Almond Orchards Located in California Using Landsat Imagery · Furman University Scholar Exchange (Furman University) (2025) | TGRS Research Map | TGRS