Assessing SEBAL Model Performance under Center Pivot Irrigation for Efficient and Accurate Irrigation Management: A Case Study on Sugar Beet Cultivation | ||
| Egyptian Journal of Agronomy | ||
| Volume 47, Issue 3, September 2025, Pages 565-574 PDF (961.58 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/agro.2025.345755.1597 | ||
| Authors | ||
| Yousria Atef* 1; Ahmed Abou El-Hassan Abdel-Aziz1; Hazem Sayed Mehawed2; Abd El-Gany Mohamed EL-Gindy3 | ||
| 1Agricultural Engineering Department, Faculty of Agriculture, Ain Shams University, Cairo, Egypt | ||
| 2Agricultural Engineering Research Institute, Agricultural Research Center, Ministry of Agriculture | ||
| 3Faculty of Desert Agriculture, King Salman International University, El Tor, Egypt | ||
| Abstract | ||
| Accurate evapotranspiration (ET) estimation is crucial for effective irrigation management, particularly in water-stressed agricultural regions. This study evaluates and compares three ET models, SEBAL, Penman-Monteith, and Priestley-Taylor, in estimating ET for sugar beet (Beta vulgaris L.) under center-pivot irrigation. The results of Penman-Monteith generated the highest cumulative ET (875 mm), reflecting its sensitivity to meteorological inputs but risking overestimation in data-limited contexts. SEBAL estimated a moderate ET of 759.6 mm, closely matching expected water demands due to its use of satellite-derived energy balance data. Priestley-Taylor yielded the lowest ET (633.2 mm), underestimating peak water needs, risking water stress and yield reduction. Model accuracy metrics confirmed SEBAL’s reliability, with a Mean Absolute Error (MAE) of 0.437 mm/day and Root Mean Square Error (RMSE) of 0.541 mm/day. In comparison, Priestley-Taylor showed higher errors (MAE: 0.721 mm/day, RMSE: 0.856 mm/day). The spatial analysis highlighted SEBAL’s ability to detect dynamic ET variations, with peak demands of 4.0–5.0 mm/day during the late midseason. Regression analysis further supported SEBAL’s predictive accuracy, achieving an R-squared value of 0.95 when correlating ET with DMP. The SEBAL model, integrated with remote sensing, proves valuable for advancing sustainable water management practices in agriculture. | ||
| Keywords | ||
| Evapotranspiration (ET); SEBAL Model; Remote Sensing; Precision Irrigation; Agricultural Water Management | ||
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