scholarly journals Assessing the dynamics of soil salinity with time-lapse inversion of electromagnetic data guided by hydrological modelling

2020 ◽  
Author(s):  
Mohammad Farzamian ◽  
Dario Autovino ◽  
Angelo Basile ◽  
Roberto De Mascellis ◽  
Giovanna Dragonetti ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Water Content ◽  
Soil Salinity ◽  
Time Lapse ◽  
Solute Concentration ◽  
Hydrological Modelling ◽  
Irrigated Agriculture ◽  
Field Assessment ◽  
The World ◽  
Spatio Temporal

Abstract. Irrigated agriculture is threatened by soil salinity in numerous arid and semiarid areas of the world, chiefly caused by the use of highly salinity irrigation water, compounded by excessive evapotranspiration. Given this threat, efficient field assessment methods are needed to monitor the dynamics of soil salinity in salt-affected irrigated lands and evaluate the performance of management strategies. In this study, we report on the results of an irrigation experiment with the main objective of evaluating time-lapse inversion of electromagnetic induction (EMI) data and hydrological modelling in field assessment of soil salinity dynamics. Four experimental plots were established and irrigated 12 times during a two-month period, with water at four different salinity levels (1, 4, 8 and 12 dS m−1) using a drip irrigation system. Time-lapse apparent electrical conductivity (σa) data were collected 6 times during the experiment period using a CMD Mini-Explorer. Prior to inversion of time-lapse σa data, a numerical experiment was performed by 2D simulations of the water and solute infiltration and redistribution process. The obtained potential spatio-temporal distributions of water content, solute concentration and bulk electrical conductivity (σb) assisted in understanding of how solute concentration and water content changes during the experiment influence σb distribution as well as optimizing the time-lapse inversion parameters for resolving σb changes in this experiment. Finally, we inverted the time-lapse field σa data and interpreted the results in terms of concentration distributions over time. Our investigation shows that EMI measurements and suitable modelling techniques allow for rapid and non-invasive investigation of spatio-temporal variability in soil salinity over large areas. Their effectiveness and relatively low cost make them appealing for management of water irrigation in salinity-threatened regions of the world.

scholarly journals Assessing the dynamics of soil salinity with time-lapse inversion of electromagnetic data guided by hydrological modelling

2021 ◽  
Vol 25 (3) ◽  
pp. 1509-1527
Author(s):  
Mohammad Farzamian ◽  
Dario Autovino ◽  
Angelo Basile ◽  
Roberto De Mascellis ◽  
Giovanna Dragonetti ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Soil Salinity ◽  
Electromagnetic Induction ◽  
Irrigation System ◽  
Time Lapse ◽  
Hydrological Modelling ◽  
Irrigated Agriculture ◽  
Field Assessment ◽  
Apparent Electrical Conductivity ◽  
Spatio Temporal

Abstract. Irrigated agriculture is threatened by soil salinity in numerous arid and semi-arid areas of the world, chiefly caused by the use of highly salinity irrigation water, compounded by excessive evapotranspiration. Given this threat, efficient field assessment methods are needed to monitor the dynamics of soil salinity in salt-affected irrigated lands and evaluate the performance of management strategies. In this study, we report on the results of an irrigation experiment with the main objective of evaluating time-lapse inversion of electromagnetic induction (EMI) data and hydrological modelling in field assessment of soil salinity dynamics. Four experimental plots were established and irrigated 12 times during a 2-month period, with water at four different salinity levels (1, 4, 8 and 12 dS m−1) using a drip irrigation system. Time-lapse apparent electrical conductivity (σa) data were collected four times during the experiment period using the CMD Mini-Explorer. Prior to inversion of time-lapse σa data, a numerical experiment was performed by 2D simulations of the water and solute infiltration and redistribution process in synthetic transects, generated by using the statistical distribution of the hydraulic properties in the study area. These simulations gave known spatio-temporal distribution of water contents and solute concentrations and thus of bulk electrical conductivity (σb), which in turn were used to obtain known structures of apparent electrical conductivity, σa. These synthetic distributions were used for a preliminary understanding of how the physical context may influence the EMI-based σa readings carried out in the monitored transects as well as being used to optimize the smoothing parameter to be used in the inversion of σa readings. With this prior information at hand, we inverted the time-lapse field σa data and interpreted the results in terms of concentration distributions over time. The proposed approach, using preliminary hydrological simulations to understand the potential role of the variability of the physical system to be monitored by EMI, may actually allow for a better choice of the inversion parameters and interpretation of EMI readings, thus increasing the potentiality of using the electromagnetic induction technique for rapid and non-invasive investigation of spatio-temporal variability in soil salinity over large areas.

scholarly journals Field-Scale Characterization of Spatio-Temporal Variability of Soil Salinity in Three Dimensions

2020 ◽  
Vol 12 (24) ◽  
pp. 4043
Author(s):  
Hongyi Li ◽  
Xinlu Liu ◽  
Bifeng Hu ◽  
Asim Biswas ◽  
Qingsong Jiang ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Soil Salinity ◽  
Three Dimensions ◽  
Soil Core ◽  
Arid Areas ◽  
Field Scale ◽  
Natural Factors ◽  
Secondary Salinity ◽  
Spatio Temporal ◽  
Semi Arid

Information on spatial, temporal, and depth variability of soil salinity at field and landscape scales is important for a variety of agronomic and environment concerns including irrigation in arid and semi-arid areas. However, challenges remain in characterizing and monitoring soil secondary salinity as it can largely be impacted by managements including irrigation and mulching in addition to natural factors. The objective of this study is to evaluate apparent electrical conductivity (ECa)-directed soil sampling as a basis for monitoring management-induced spatio-temporal change in soil salinity in three dimensions. A field experiment was conducted on an 18-ha saline-sodic field from Alar’s Agricultural Science and Technology Park, China between March, and November 2018. Soil ECa was measured using an electromagnetic induction (EMI) sensor for four times over the growing season and soil core samples were collected from 18 locations (each time) selected using EMI survey data as a-priori information. A multi-variate regression-based predictive relationship between ECa and laboratory-measured electrical conductivity (ECe) was used to predict EC with confidence (R2 between 0.82 and 0.99). A three-dimensional inverse distance weighing (3D-IDW) interpolation clearly showed a strong variability in space and time and with depths within the study field which were mainly attributed to the human management factors including irrigation, mulching, and uncovering of soils and natural factors including air temperature, evaporation, and groundwater level. This study lays a foundation of characterizing secondary salinity at a field scale for precision and sustainable management of agricultural lands in arid and semi-arid areas.

A tracer test in a shallow heterogeneous aquifer monitored via time-lapse surface electrical resistivity tomography

Geophysics ◽  
2010 ◽  
Vol 75 (4) ◽  
pp. WA61-WA73 ◽  
Author(s):  
Martina Monego ◽  
Giorgio Cassiani ◽  
Rita Deiana ◽  
Mario Putti ◽  
Giulia Passadore ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Transport Model ◽  
Time Lapse ◽  
Solute Concentration ◽  
Tracer Test ◽  
Groundwater Velocity ◽  
Fine Sediments ◽  
Heterogeneous Aquifer ◽  
Surface Time ◽  
Over Time

We illustrate a case study of a saline tracer test in a shallow, highly heterogeneous aquifer, monitored by means of surface time-lapse ERT. The test was aimed at identifying the system’s hydraulic properties. Some of the expected limitations of the method — particularly caused by the strong decrease in ERT resolution with depth — and the consequent problems with mass balance and moment calculation could be partly balanced by the use of direct measurements of groundwater electrical conductivity and tracer concentration at one selected location. The vast heterogeneity of the system, ranging in lithology from clay to gravel at a scale of meters to tens of meters, reflects itself in the tracer migration and distribution over time: The tracer is trapped in the low-permeability regions and from these it is slowly released over time. High-resolution surface ERT proves effective at picturing this system behavior over time. The extreme heterogeneity is also a challenge in the attempt to translate bulk electrical conductivity into estimates of groundwater electrical conductivity and, hence, solute concentration because surface conductivity in fine sediments has an important role. The test results could be used to identify some of the key parameters for solute transport, namely, mean groundwater velocity and aquifer dispersivity at the scale of the test by means of transport model calibration.

Estimating Topsoil Water Content of Clay Soils With Data From Time-Lapse Electrical Conductivity Surveys

Soil Science ◽  
2012 ◽  
Vol 177 (6) ◽  
pp. 369-376 ◽  
Author(s):  
Gonzalo Martínez García ◽  
Karl Vanderlinden ◽  
Yakov Pachepsky ◽  
Juan Vicente Giráldez Cervera ◽  
Antonio Jesús Espejo Pérez
Keyword(s):  
Electrical Conductivity ◽  
Water Content ◽  
Time Lapse ◽  
Clay Soils

scholarly journals Assessing soil salinity dynamics using time-lapse electromagnetic conductivity imaging

SOIL ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. 499-511
Author(s):  
Maria Catarina Paz ◽  
Mohammad Farzamian ◽  
Ana Marta Paz ◽  
Nádia Luísa Castanheira ◽  
Maria Conceição Gonçalves ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Cross Sections ◽  
Soil Salinity ◽  
Sea Water ◽  
Management Strategies ◽  
Time Lapse ◽  
Soil Salinization ◽  
Agricultural System ◽  
Prediction Ability ◽  
Conductivity Imaging

Abstract. 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 (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, mS m−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 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.

scholarly journals Monitoring soil salinity using time-lapse electromagnetic conductivity imaging

2020 ◽  
Author(s):  
Maria Catarina Paz ◽  
Mohammad Farzamian ◽  
Ana Marta Paz ◽  
Nádia Luísa Castanheira ◽  
Maria Conceição Gonçalves ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Soil Salinity ◽  
Management Strategies ◽  
Time Lapse ◽  
Soil Salinization ◽  
Spatiotemporal Variability ◽  
Coefficient Of Determination ◽  
Agricultural System ◽  
Soil Electrical Conductivity ◽  
Salinity Levels

Abstract. Lezíria Grande of Vila Franca de Xira, located in Portugal, is an important agricultural system where soil faces the risk of salinization, being thus prone to desertification and land abandonment. 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 (ECa, dS m−1); (2) inversion of ECa to obtain electromagnetic conductivity images (EMCI) which provide 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 (ECe, dS m−1), used as a proxy for soil salinity; and (4) conversion of EMCI into salinity maps 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. This study aims to evaluate the potential of time-lapse EMCI and the regional calibration to predict the spatiotemporal variability of soil salinity in the study area. The results showed that ECe was satisfactorily predicted, with a root mean square error (RMSE) of 3.22 dS m−1 in a range of 52.35 dS m−1 and a coefficient of determination (R2) of 0.89. Results also showed strong concordance with a Lin’s concordance correlation coefficient (CCC) of 0.93, although, ECe was slightly overestimated with a mean error (ME) of −1.30 dS m−1. Soil salinity maps for each location revealed salinity fluctuations related to the input of salts and water either through irrigation, precipitation or groundwater level and salinity. Time-lapse EMCI has proven to be a valid methodology for evaluating the risk of soil salinization, and 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.

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