A multi-scale remote sensing approach for assessing drought impacts on rainfed and irrigated cereal yields in Lleida, Spain

This study evaluates the performance of agricultural drought indices at provincial and field scales, as well as their ability to explain the variability of wheat and barley yields under rainfed and irrigated conditions. The analysis was conducted in the Lleida region (northeastern Spain) from 2010 to 2024 using high-resolution (30 m) multi-source remote sensing data and yield information from 5030 cereal fields. Five drought indices representing vegetative stress, thermal stress, soil moisture conditions, and their combination were evaluated: the Vegetative Condition Index (VCI), the Thermal Condition Index (TCI), the Soil Moisture Condition Index (SMCI), the Vegetative Health Index (VHI), and the Combined Drought Anomaly Index (CDAI). The analysis of drought index–yield relationships reveal a strong dependence on crop type, phenological stage, spatial scale, and water management practices. Barley exhibits greater sensitivity to drought than wheat and responds earlier in the growing season. Correlations are generally weak during early growth stages but become much stronger during the reproductive and maturation phases. Using high spatial resolution data (30 m) significantly enhances the performance of drought indices. Under rainfed conditions, most indices perform well except for the TCI, with the CDAI standing out as the most effective, achieving correlation values of r = 0.85 (p < 0.01) at the provincial scale and a median of r = 0.52, with a maximum of r = 0.95 (p < 0.01) at the field scale. In contrast, drought index–yield correlations in irrigated areas are consistently lower, highlighting the buffering role of irrigation in mitigating drought impacts. In irrigated fields across the study area, yield variability is primarily driven by heat stress rather than water or vegetation stress. Overall, composite drought indices such as the CDAI are particularly well suited for monitoring agricultural drought in rainfed conditions, whereas indices specifically designed for irrigated agriculture remain essential.

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Publication Details

Journal
Agricultural Water Management
Published
2026-09-29
DOI
https://doi.org/10.1016/j.agwat.2026.110826
Primary Topic
Hydrology and Drought Analysis
Type
article
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article

A multi-scale remote sensing approach for assessing drought impacts on rainfed and irrigated cereal yields in Lleida, Spain

Saïd Khabba, Abdelhakim Amazirh, El Houssaine Bouras, Maria‐José Escorihuela et al.
Agricultural Water Management
Hydrology and Drought Analysis
article

A multi-scale remote sensing approach for assessing drought impacts on rainfed and irrigated cereal yields in Lleida, Spain

Saïd Khabba, Abdelhakim Amazirh, El Houssaine Bouras, Maria‐José Escorihuela, Salah Er‐Raki, Youness Ablila, Zaineb Bouswir, Jose Antonio Martinez Casasnovas
article en

Abstract

This study evaluates the performance of agricultural drought indices at provincial and field scales, as well as their ability to explain the variability of wheat and barley yields under rainfed and irrigated conditions. The analysis was conducted in the Lleida region (northeastern Spain) from 2010 to 2024 using high-resolution (30 m) multi-source remote sensing data and yield information from 5030 cereal fields. Five drought indices representing vegetative stress, thermal stress, soil moisture conditions, and their combination were evaluated: the Vegetative Condition Index (VCI), the Thermal Condition Index (TCI), the Soil Moisture Condition Index (SMCI), the Vegetative Health Index (VHI), and the Combined Drought Anomaly Index (CDAI). The analysis of drought index–yield relationships reveal a strong dependence on crop type, phenological stage, spatial scale, and water management practices. Barley exhibits greater sensitivity to drought than wheat and responds earlier in the growing season. Correlations are generally weak during early growth stages but become much stronger during the reproductive and maturation phases. Using high spatial resolution data (30 m) significantly enhances the performance of drought indices. Under rainfed conditions, most indices perform well except for the TCI, with the CDAI standing out as the most effective, achieving correlation values of r = 0.85 (p < 0.01) at the provincial scale and a median of r = 0.52, with a maximum of r = 0.95 (p < 0.01) at the field scale. In contrast, drought index–yield correlations in irrigated areas are consistently lower, highlighting the buffering role of irrigation in mitigating drought impacts. In irrigated fields across the study area, yield variability is primarily driven by heat stress rather than water or vegetation stress. Overall, composite drought indices such as the CDAI are particularly well suited for monitoring agricultural drought in rainfed conditions, whereas indices specifically designed for irrigated agriculture remain essential.

Agricultural Water ManagementVol. 336
Cadi Ayyad University (MA), Universitat de Lleida (ES), Université Mohammed VI Polytechnique (MA)
Zero hunger
Openalex Percentile: Top 14%
Hydrology and Drought Analysis
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