Estimating Actual Evapotranspiration in Orchard Systems Using the ALARM Energy Balance Model and MODIS Data.
Saved in:
| Title: | Estimating Actual Evapotranspiration in Orchard Systems Using the ALARM Energy Balance Model and MODIS Data. |
|---|---|
| Authors: | Darouich, Hanaa1 (AUTHOR) hanaa.darouich@tecnico.ulisboa.pt, Derdar, Banan1,2 (AUTHOR), Oliveira, Ana R.1 (AUTHOR), Ramos, Tiago B.1,2 (AUTHOR) |
| Source: | Remote Sensing. Jul2026, Vol. 18 Issue 14, p2351. 21p. |
| Subjects: | Evapotranspiration, MODIS (Spectroradiometer), Irrigation management, Evaporative power, Irrigation water, Orchard management, Remote sensing |
| Geographic Terms: | Portugal |
| Abstract: | Highlights: The ALARM model demonstrated reliable performance in estimating actual evapotranspiration in fully irrigated, high-density orchard areas in southern Portugal. The model showed lower accuracy when estimating actual evapotranspiration in deficit-irrigated orchards. The model showed potential for regional-scale monitoring of orchard water use. Scaling challenges limit its applicability for field-level water management and irrigation scheduling. Energy balance models using remote sensing imagery can provide reliable, cost-effective estimates of actual evapotranspiration (ETa) over large areas. This study evaluated the Analytical Land Atmosphere Radiometer Model (ALARM), a one-source energy balance model, for estimating ETa in Mediterranean orchard systems. The model was applied to almond, olive, citrus, and pomegranate orchards during the 2019–2020 growing seasons using MODIS imagery. Calibration and validation were performed against ETa estimates from the SIMDualKc and HYDRUS-1D models. Sensitivity analysis showed canopy-related parameters had the greatest influence on ETa estimates. ALARM successfully reproduced seasonal ETa dynamics for almond, citrus, and pomegranate orchards, achieving R2 values ≥ 0.74 and normalized RMSE ≤ 34.1%. Performance was weaker for olive orchards (R2 = 0.47–0.85; NRMSE = 32.4–50.2%), where ETa was overestimated due to inadequate representation of deficit irrigation. The coarse spatial resolution of MODIS imagery also required an empirical adjustment parameter (β = 0.50–0.92) to address mixed land-cover conditions within pixels. Despite these limitations, ALARM proved promising for large-scale water resource assessments, although its suitability for detailed field-scale irrigation management remains limited. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| Abstract: | Highlights: The ALARM model demonstrated reliable performance in estimating actual evapotranspiration in fully irrigated, high-density orchard areas in southern Portugal. The model showed lower accuracy when estimating actual evapotranspiration in deficit-irrigated orchards. The model showed potential for regional-scale monitoring of orchard water use. Scaling challenges limit its applicability for field-level water management and irrigation scheduling. Energy balance models using remote sensing imagery can provide reliable, cost-effective estimates of actual evapotranspiration (ETa) over large areas. This study evaluated the Analytical Land Atmosphere Radiometer Model (ALARM), a one-source energy balance model, for estimating ETa in Mediterranean orchard systems. The model was applied to almond, olive, citrus, and pomegranate orchards during the 2019–2020 growing seasons using MODIS imagery. Calibration and validation were performed against ETa estimates from the SIMDualKc and HYDRUS-1D models. Sensitivity analysis showed canopy-related parameters had the greatest influence on ETa estimates. ALARM successfully reproduced seasonal ETa dynamics for almond, citrus, and pomegranate orchards, achieving R2 values ≥ 0.74 and normalized RMSE ≤ 34.1%. Performance was weaker for olive orchards (R2 = 0.47–0.85; NRMSE = 32.4–50.2%), where ETa was overestimated due to inadequate representation of deficit irrigation. The coarse spatial resolution of MODIS imagery also required an empirical adjustment parameter (β = 0.50–0.92) to address mixed land-cover conditions within pixels. Despite these limitations, ALARM proved promising for large-scale water resource assessments, although its suitability for detailed field-scale irrigation management remains limited. [ABSTRACT FROM AUTHOR] |
|---|---|
| ISSN: | 20724292 |
| DOI: | 10.3390/rs18142351 |
