Lezíria Grande de Vila Franca de Xira, located in Portugal, is an important agricultural system where soil faces the risk of salinization due to climate change, as the level and salinity of groundwater are likely to increase as a result of the rise of the sea water level and consequently of the estuary. These changes can also affect the salinity of the irrigation water which is collected upstream of the estuary. Soil salinity can be assessed over large areas by the following rationale: (1) use of electromagnetic induction (EMI) to measure the soil apparent electrical conductivity (EC_a, mS m⁻¹); (2) inversion of EC_a to obtain electromagnetic conductivity imaging (EMCI) which provides the spatial distribution of the soil electrical conductivity (σ, mS m⁻¹); (3) calibration process consisting of a regression between σ and the electrical conductivity of the saturated soil paste extract (EC_e, dS m⁻¹), used as a proxy for soil salinity; and (4) conversion of EMCI into salinity cross sections using the obtained calibration equation. In this study, EMI surveys and soil sampling were carried out between May 2017 and October 2018 at four locations with different salinity levels across the study area of Lezíria de Vila Franca. A previously developed regional calibration was used for predicting EC_e from EMCI. Using time-lapse EMCI data, this study aims (1) to evaluate the ability of the regional calibration to predict soil salinity and (2) to perform a preliminary qualitative analysis of soil salinity dynamics in the study area. The validation analysis showed that EC_e was predicted with a root mean square error (RMSE) of 3.14 dS m⁻¹ in a range of 52.35 dS m⁻¹, slightly overestimated (−1.23 dS m⁻¹), with a strong Lin's concordance correlation coefficient (CCC) of 0.94 and high linearity between measured and predicted data (R²=0.88). It was also observed that the prediction ability of the regional calibration is more influenced by spatial variability of data than temporal variability of data. Soil salinity cross sections were generated for each date and location of data collection, revealing qualitative salinity fluctuations related to the input of salts and water either through irrigation, precipitation, or level and salinity of groundwater. Time-lapse EMCI is developing into a valid methodology for evaluating the risk of soil salinization, so it can further support the evaluation and adoption of proper agricultural management strategies, especially in irrigated areas, where continuous monitoring of soil salinity dynamics is required.

中文翻译：

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使用延时电磁导率成像评估土壤盐分动力学

位于葡萄牙的LezíriaGrande de Vila Franca de Xira是重要的农业系统，由于气候变化，土壤可能面临盐碱化的风险，因为海水的上升可能会增加地下水的水平和盐碱度水平，因此河口。这些变化也可能影响在河口上游收集的灌溉水的盐度。可以通过以下原理在大范围内评估土壤盐度：（1）使用电磁感应（EMI）测量土壤的表观电导率（EC _a，mS m ^-1）；（2）对EC _a进行反演以获得电磁导率成像（EMCI），该成像可提供土壤电导率（σ，mS m ^-1）；（3）校准过程，包括在σ和饱和土膏提取物的电导率之间的回归（EC _e，dS m ^-1），用作土壤盐分的替代物；（4）使用获得的校准方程将EMCI转换为盐度截面。在这项研究中，于2017年5月至2018年10月在Lezíriade Vila Franca研究区的四个盐度不同的地点进行了EMI调查和土壤采样。先前开发的区域校准用于预测EC _e来自EMCI。本研究使用时移的EMCI数据，目的是（1）评估区域校准预测土壤盐分的能力，以及（2）对研究区域的土壤盐分动态进行初步的定性分析。验证分析表明，EC _Ë用的3.14 DS中的根均方误差（RMSE）预测中号^-1的范围内的52.35德尚中号^-1，略微高估（- 1.23德尚中号^-1），具有强烈的林的一致性相关系数（CCC）为0.94，实测数据与预测数据之间具有高度线性关系（R ² = 0.88）。还观察到，区域校准的预测能力受数据的空间变异性的影响要大于数据的时间变异性。针对数据收集的每个日期和位置生成了土壤盐分横截面，揭示了盐分的定性波动（通过灌溉，降水或地下水位和盐度与盐分和水的输入有关）。延时EMCI正在发展成为评估土壤盐渍化风险的有效方法，因此它可以进一步支持评估和采用适当的农业管理策略，尤其是在需要持续监测土壤盐分动态的灌溉地区。