Depth-Specific Soil Electrical Conductivity and NDVI Elucidate Salinity Effects on Crop Development in Reclaimed Marsh Soils

Agricultural management decision-making in salinization-prone environments requires efficient soil salinity monitoring methods. This is the case in the B-XII irrigation district in SW Spain, a heavy clay reclaimed marsh area where a shallow saline water table and intensively irrigated agriculture cr...

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Veröffentlicht in:Remote sensing (Basel, Switzerland) Switzerland), 2022-07, Vol.14 (14), p.3389
Hauptverfasser: Gómez Flores, José Luis, Ramos Rodríguez, Mario, González Jiménez, Alfonso, Farzamian, Mohammad, Herencia Galán, Juan Francisco, Salvatierra Bellido, Benito, Cermeño Sacristan, Pedro, Vanderlinden, Karl
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Sprache:eng
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Zusammenfassung:Agricultural management decision-making in salinization-prone environments requires efficient soil salinity monitoring methods. This is the case in the B-XII irrigation district in SW Spain, a heavy clay reclaimed marsh area where a shallow saline water table and intensively irrigated agriculture create a fragile balance between salt accumulation and leaching in the root zone, which might be disrupted by the introduction of new crops and increasing climate variability. We evaluated the potential of electromagnetic induction (EMI) tomography for field-scale soil salinity assessment in this hyper-conductive environment, using EMI and limited analytical soil data measured in 2017 and 2020 under a processing tomato–cotton–sugar beet crop rotation. Salinity effects on crop development were assessed by comparing Sentinel 2 NDVI imagery with inverted depth-specific electrical conductivity (EC). Average apparent electrical conductivity (ECa) for the 1-m depth signal was 20% smaller in 2020 than in 2017, although the spatial ECa pattern was similar for both years. Inverted depth-specific EC showed a strong correlation (R ≈ 0.90) with saturated paste extract EC (ECe), [Na+] and sodium absorption ratio (SAR), resulting in linear calibration equations with R2 ≈ 0.8 for both years and leave-one-out cross validation Nash–Sutcliffe Efficiency Coefficient, ranging from 0.57 to 0.74. Overall, the chemical parameter estimation improved with depth and soil wetness (2017), yielding 0.83 < R
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14143389