Browsing by Author "Santos, Fernando Monteiro"
Now showing 1 - 5 of 5
Results Per Page
Sort Options
- Assessing soil salinity dynamics using time-lapse electromagnetic conductivity imagingPublication . Paz, Maria Catarina; Farzamian, Mohammad; Paz, Ana Marta; Castanheira, Nádia Luísa; Gonçalves, Maria Conceição; Santos, Fernando MonteiroLezíriaGrandedeVilaFrancadeXira,locatedinPortugal,isanimportantagriculturalsystemwhere 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 appar- ent electrical conductivity (ECa, mS m−1); (2) inversion of ECa to obtain electromagnetic conductivity imaging (EMCI) which provides the spatial distribution of the soil electrical conductivity (σ,mSm−1); (3) calibration process consisting of a regression between σ and the electrical conductivity of the saturated soil paste extract (ECe, 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 ECe 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 ECe 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 overesti- mated (−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.
- Comparison of electromagnetic induction and electrical resistivity tomography in assessing soil salinity: Insights from four plots with distinct soil salinity levelsPublication . Paz, Maria Catarina; Castanheira, Nádia Luísa; Paz, Ana Marta; Gonçalves, Maria Conceição; Santos, Fernando Monteiro; Farzamian, MohammadElectromagnetic induction (EMI) and electrical resistivity tomography (ERT) are geophysical techniques measuring soil electrical conductivity and providing insights into properties correlated with it to depths of several meters. EMI measures the apparent electrical conductivity (ECa, dS m−1) without physical contact, while ERT acquires apparent electrical resistivity (ERa, ohm m) using electrodes. Both involve mathematical inversion to obtain models of spatial distribution for soil electrical conductivity (σ, mS m−1) and electrical resistivity (ρ, ohm m), respectively, where ρ is the reciprocal of σ. Soil salinity can be assessed from σ over large areas using a calibration process consisting of a regression between σ and the electrical conductivity of the saturated soil paste extract (ECe, dS m−1), used as a proxy for soil salinity. This research aims to compare the prediction abilities of the faster EMI to the more reliable ERT for estimating σ and predicting soil salinity. The study conducted surveys and sampling at four locations with distinct salinity levels in Portugal, analysing the agreement between the techniques, and obtained 2D vertical soil salinity maps. In our case study, the agreement between EMI and ERT models was fairly good in three locations, with σ varying between 50 and 500 mS m−1. However, this was not the case at location 4, where σ exceeded 1000 mS m−1 and EMI significantly underestimated σ when compared to ERT. As for soil salinity prediction, both techniques generally provided satisfactory and comparable regional-level predictions of ECe, and the observed underestimation in EMI models did not significantly affect the overall estimation of soil salinity. Consequently, EMI demonstrated an acceptable level of accuracy in comparison to ERT in our case studies, supporting confidence in utilizing this faster and more practical technique for measuring soil salinity over large areas
- Integrated Geophysical Methods for Shallow Aquifers Characterization and ModellingPublication . Alcalá, Francisco Javier; Paz, Maria Catarina; Martínez-Pagán, Pedro; Santos, Fernando Monteiro
- Integrated Geophysical Methods for Shallow Aquifers Characterization and ModellingPublication . Alcalá, Francisco Javier; Paz, Maria Catarina; Martínez-Pagán, Pedro; Santos, Fernando Monteiro
- Regional calibration and electromagnetic conductivity imaging for assessing the dynamics of soil salinityPublication . Paz, Maria Catarina; Farzamian, Mohammad; Paz, Ana Marta; Castanheira, Nádia Luísa; Gonçalves, Maria Conceição; Santos, Fernando Monteiro