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<p>Remote sensing has become a strategic tool for monitoring irrigation systems, especially in regions with a lack of local agroclimatic and field-scale management data. This study evaluated the water productivity and irrigation performance of soybean cultivation in Pratânia, in the midwestern region of São Paulo State, Brazil, comparing a center pivot system (72.77&#xa0;ha) and three rainfed areas (with an area of 53.74&#xa0;ha) over three consecutive seasons (2022–2025). Local data, including crop yield, applied irrigation depth, and climatic variables, were compared with remote sensing products from the WaPOR v3.0 database (precipitation—P, reference—ET<sub>o</sub> and actual evapotranspiration and interception – AETI, and net primary production - NPP) Irrigation performance was assessed using equity (EqD), relative water deficit (RWD), and Water Productivity (WP) as a key performance indicator. Results showed that local yields in irrigated fields were 5.16, 4.63, and 4.12 t ha⁻¹ for the 2022–2023, 2023–2024, and 2024–2025 cropping seasons, respectively. In comparison, WaPOR-based estimates for the same periods were 7.15, 5.79, and 7.00 t ha⁻¹, indicating a consistent trend of yield overestimation by the platform, although it successfully captured seasonal variability. WUP ranged between 1.24 and 1.66&#xa0;kg m⁻³ in irrigated cultivation, with similar values under rainfed conditions. RWD values (&lt; 0.13) indicated low exposure to water stress in both systems. However, EqD indicator effectively distinguished the two management systems; irrigated fields maintained high uniformity (CV: 3.31–5.68%), whereas rainfed areas exhibited significantly higher spatial heterogeneity (CV: 8.13–10.36%) due to irregular precipitation distribution. This demonstrates the leverage of the WaPOR dataset in capturing field-scale water status. While absolute yields were overestimated compared to local data, the platform proved robust in identifying spatial performance gaps and monitoring irrigation impacts. Therefore, WaPOR is recommended as a reliable proxy for irrigation auditing and strategic decision-making in regions where in-situ monitoring is limited.</p>

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Evaluation of water productivity and irrigation performance in center pivot and rainfed systems using the WaPOR database

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月21日

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  • Valdemiro Simão João Pitoro,
  • José Rafael Franco,
  • Pedro Vitor Soares Adrien,
  • Victor Crespo de Oliveira,
  • Rodrigo Máximo Sánchez-Román

摘要

Remote sensing has become a strategic tool for monitoring irrigation systems, especially in regions with a lack of local agroclimatic and field-scale management data. This study evaluated the water productivity and irrigation performance of soybean cultivation in Pratânia, in the midwestern region of São Paulo State, Brazil, comparing a center pivot system (72.77 ha) and three rainfed areas (with an area of 53.74 ha) over three consecutive seasons (2022–2025). Local data, including crop yield, applied irrigation depth, and climatic variables, were compared with remote sensing products from the WaPOR v3.0 database (precipitation—P, reference—ETo and actual evapotranspiration and interception – AETI, and net primary production - NPP) Irrigation performance was assessed using equity (EqD), relative water deficit (RWD), and Water Productivity (WP) as a key performance indicator. Results showed that local yields in irrigated fields were 5.16, 4.63, and 4.12 t ha⁻¹ for the 2022–2023, 2023–2024, and 2024–2025 cropping seasons, respectively. In comparison, WaPOR-based estimates for the same periods were 7.15, 5.79, and 7.00 t ha⁻¹, indicating a consistent trend of yield overestimation by the platform, although it successfully captured seasonal variability. WUP ranged between 1.24 and 1.66 kg m⁻³ in irrigated cultivation, with similar values under rainfed conditions. RWD values (< 0.13) indicated low exposure to water stress in both systems. However, EqD indicator effectively distinguished the two management systems; irrigated fields maintained high uniformity (CV: 3.31–5.68%), whereas rainfed areas exhibited significantly higher spatial heterogeneity (CV: 8.13–10.36%) due to irregular precipitation distribution. This demonstrates the leverage of the WaPOR dataset in capturing field-scale water status. While absolute yields were overestimated compared to local data, the platform proved robust in identifying spatial performance gaps and monitoring irrigation impacts. Therefore, WaPOR is recommended as a reliable proxy for irrigation auditing and strategic decision-making in regions where in-situ monitoring is limited.