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Assessment of Water Depth Variability and Rice Farming Using Remote Sensing
Rubén Simeón1, Constanza Rubio2, Antonio Uris2
1Centro Valenciano de Estudios sobre el Riego (CVER), Universitat Politècnica de València, Camí de Vera s/n, 46022 València, Spain.
None:
Remote sensing is a widely used tool for crop monitoring to improve water management. Rice, a crop traditionally grown under flooded conditions, requires farmers to understand the relationship between crop reflectance, water depth and final yield. This study focused on seven commercial rice fields in 2022 and six in 2023, analyzing the correlations between water depth and Sentinel-2 reflectance over two growing seasons in Valencia, Spain. During the tillering stage across both seasons, water depth showed positive correlations with visible bands and negative correlations with NIR and SWIR bands. There were no correlations with the indices NDVI, GNDVI, NDRE and NDWI. The NIR band showed significant correlations across both seasons, with R2 values of 0.69 and 0.71, respectively. In addition, the calculation of NIR anomalies for each field proved to be a good indicator of final yield anomalies. In 2022, anomalies above 10% corresponded to yield deviations above 500 kg·ha-1, while in 2023, anomalies above 15% were associated with yield deviations above 1000 kg·ha-1. The response of final yield to water level was positive up to average values of 9 cm. The use of the NIR band during the rice crop tillering stage can support farmers in improving irrigation management.
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