Integrating remote sensing and ion balance to predict yield losses under saline irrigation in rice

Rice cultivation in the Guadalquivir River marshes of southern Spain is increasingly constrained by irrigation water salinity, exacerbated by drought and seawater intrusion. This study assessed the agronomic, physiological, and spectral responses of indica and japonica cultivars under commercial farming conditions across a natural salinity gradient (mean electrical conductivity of irrigation water ranging from 3.1 to 6.9 dS m⁻¹). Field measurements included yield, growth traits, and leaf ion concentrations, complemented with Sentinel-2 vegetation indices and integrated using Generalized Additive Models (GAMs). Rice yield declined steeply with salinity, with up to 70 % losses between 3 and 7 dS m⁻¹ . Rice grown in medium-salinity fields maintained Na/K ratios comparable to low-salinity fields, suggesting that compensatory K⁺ uptake mitigated yield penalties. By contrast, high salinity led to marked ionic imbalance, particularly in japonica cultivars, which consistently exhibited higher Na/K ratios than indica . Spectral data revealed that broad-band greenness indices (NDVI, GNDVI, EVI, SAVI, NDRE) effectively captured early osmotic effects (<60 DAS), while MCARI uniquely detected late-stage ionic stress during reproductive phases. GAM analysis confirmed two phenological windows of higher sensitivity to salinity—vegetative establishment and reproductive development—while demonstrating the predictive utility of combined physiological and spectral indicators (LOOCV R² = 0.867). These findings underscore the need for growth phase-specific management and the potential of integrating physiological and remote sensing data to support adaptation strategies in Mediterranean rice systems. • Remote sensing and ion balance predict rice yield under saline irrigation. • Medium salinity fields maintained Na/K ratios, mitigating yield penalties. • High salinity caused ionic imbalance, stronger in japonica than indica . • GAMs identified vegetative and reproductive stages as salinity-sensitive. • Stage-specific management is key for rice under saline irrigation.

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Publication Details

Journal
Agricultural Water Management
Published
2026-01-21
DOI
https://doi.org/10.1016/j.agwat.2026.110164
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
31.91
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article

Integrating remote sensing and ion balance to predict yield losses under saline irrigation in rice

Shyam Pariyar, M. Becker, José Rodolfo Quintana-Molina, Gregorio Egea et al.
1 citations
Agricultural Water Management
Remote Sensing in Agriculture
31.91
article

Integrating remote sensing and ion balance to predict yield losses under saline irrigation in rice

Shyam Pariyar, M. Becker, José Rodolfo Quintana-Molina, Gregorio Egea, Annkathrin Rosenbaum
article en
1 citations

Abstract

Rice cultivation in the Guadalquivir River marshes of southern Spain is increasingly constrained by irrigation water salinity, exacerbated by drought and seawater intrusion. This study assessed the agronomic, physiological, and spectral responses of indica and japonica cultivars under commercial farming conditions across a natural salinity gradient (mean electrical conductivity of irrigation water ranging from 3.1 to 6.9 dS m⁻¹). Field measurements included yield, growth traits, and leaf ion concentrations, complemented with Sentinel-2 vegetation indices and integrated using Generalized Additive Models (GAMs). Rice yield declined steeply with salinity, with up to 70 % losses between 3 and 7 dS m⁻¹ . Rice grown in medium-salinity fields maintained Na/K ratios comparable to low-salinity fields, suggesting that compensatory K⁺ uptake mitigated yield penalties. By contrast, high salinity led to marked ionic imbalance, particularly in japonica cultivars, which consistently exhibited higher Na/K ratios than indica . Spectral data revealed that broad-band greenness indices (NDVI, GNDVI, EVI, SAVI, NDRE) effectively captured early osmotic effects (<60 DAS), while MCARI uniquely detected late-stage ionic stress during reproductive phases. GAM analysis confirmed two phenological windows of higher sensitivity to salinity—vegetative establishment and reproductive development—while demonstrating the predictive utility of combined physiological and spectral indicators (LOOCV R² = 0.867). These findings underscore the need for growth phase-specific management and the potential of integrating physiological and remote sensing data to support adaptation strategies in Mediterranean rice systems. • Remote sensing and ion balance predict rice yield under saline irrigation. • Medium salinity fields maintained Na/K ratios, mitigating yield penalties. • High salinity caused ionic imbalance, stronger in japonica than indica . • GAMs identified vegetative and reproductive stages as salinity-sensitive. • Stage-specific management is key for rice under saline irrigation.

Agricultural Water ManagementVol. 325
University of Bonn (DE), Universidad de Sevilla (ES)
Life below water
Openalex Percentile: Top 2%
Remote Sensing in Agriculture
31.91
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