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

Abstract

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 <0.98 at 0.9 m. The observed spatial EC distributions showed a steadily increasing inverse correlation with NDVI during the growing season, particularly for processing tomato and cotton, reaching R values of −0.71 and −0.85, respectively. These results confirm the potential of EMI tomography for mapping and monitoring soil salinity in the B-XII irrigation district, while it allows, in combination with NDVI imagery, a detailed spatial assessment of soil salinity impacts on crop development throughout the growing season. Contrary to the popular belief among farmers in the area, and despite non-saline topsoil conditions, spatial EC and subsoil salinity patterns were found to affect crop development negatively in the studied field.

Improving the monitoring of root zone soil salinity under vegetation cover conditions by combining canopy spectral information and crop growth parameters

“…Therefore, exploring the method for eliminating vegetation cover area or enhancing soil spectral characterization by collaborating with vegetation spectral information is of great significance for improving the accuracy of soil attribute inversion by remote sensing ( Zhang et al., 2021a ). Differences in soil salinity can lead to differences in landscape (vegetation), and many studies have used hyperspectral reflectance of vegetation canopy or derived vegetation indices such as normalized difference vegetation index (NDVI) ( Garajeh et al., 2021 ; Gómez Flores et al., 2022 ), photochemical reflectance index (PRI) ( Ivushkin et al., 2019 ; Kim et al., 2020 ) etc., to indirectly estimate soil salinity. However, the vegetation canopy reflectance spectrum is mixed with the spectrum of ground objects, and affected by factors such as leaf characteristics, canopy structure, soil properties, and atmospheric conditions ( Guo et al., 2017 ).…”

Influence of Thermal Desorption Technology on Removal Effects and Properties of PAH-Contaminated Soil Based on Engineering Experiments

“…EC can be used to evaluate the ease of water and nutrient uptake by plant roots [41,42]. The conductivity of S1 soil changed mainly due to the fact that the increase in temperature below 500 • C causes the release of salt-based ions from the organic matter, leading to an increase in conductivity [43].…”

Sentinel-2, Herramienta en La Seguridad Agroalimentaria Y Agricultura De Precisión

“…En España se determinó la CE en predios con tomate, algodón y remolacha azucarera encontraron relación inversa entre CE y NDVI y los resultados indicaron que en tomate el valor de correlación (R) fluctuó por debajo de -0.66 hasta -0.73 en todas las profundidades (0.1, 0.3, 0.5, 0.7 y 0.9 m); respecto a NDVI a partir del día 50 después de siembra (dds) hasta el 60, teniendo al algodón como referencia, los valores de R estuvieron entre -0.70 a -0.90 a partir de los 35 dds en todas las profundidades. Estos resultados coinciden con el cultivo de remolacha azucarera, donde el R oscilo ente -0.53 a -0.57 desde el dds 70 (Gómez-Flores et al, 2022). Los sitios con mayor CE presentaron menor desarrollo del cultivo, así mismo decrece el NDVI lo cual indica que conforme aumenta la CE el cultivo se estresa y ralentiza su desarrollo (Gómez-Flores et al, 2022).…”