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.

scholarly journals Regional calibration and electromagnetic conductivity imaging for assessing the dynamics of soil salinity

2021 ◽  
Author(s):  
Maria Catarina Paz ◽  
Mohammad Farzamian ◽  
Ana Marta Paz ◽  
Nádia Luísa Castanheira ◽  
Maria Conceição Gonçalves ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Soil Salinity ◽  
Sea Water ◽  
Agricultural System ◽  
Soil Electrical Conductivity ◽  
Prediction Ability ◽  
Calibration Equation ◽  
Transient Nature ◽  
Salinity Levels ◽  
Conductivity Imaging

<p>Electromagnetic conductivity imaging (EMCI) is a state-of-the-art methodology for soil salinity assessment over large areas. It involves the following rationale: (1) use of the electromagnetic induction (EMI) geophysical technique to measure the soil apparent electrical conductivity (EC<sub>a</sub>, mS m<sup>−1</sup>) over an area; (2) inversion of EC<sub>a</sub> to obtain EMCI, which provides the spatial distribution of the soil electrical conductivity (σ, mS m<sup>−1</sup>); (3) calibration process consisting of a regression between σ and the electrical conductivity of the saturated soil paste extract (EC<sub>e</sub>, dS m<sup>−1</sup>), used as a proxy for soil salinity; and (4) conversion of EMCI into salinity maps using the obtained calibration equation.</p><p>In this study, we applied EMCI and a regional calibration in Lezíria Grande de Vila Franca de Xira, located in Portugal. The study area 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.</p><p>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. A regional calibration was developed and its ability to predict EC<sub>e</sub> from EMCI was evaluated. The validation analysis showed that EC<sub>e</sub> was predicted with a root mean square error of 3.14 dS m<sup>−1</sup> in a range of 52.35 dS m<sup>−1</sup>, slightly overestimated (−1.23 dS m<sup>−1</sup>), with a strong Lin’s concordance correlation coefficient of 0.94 and high linearity between measured and predicted data (R<sup>2</sup> = 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.</p><p>Because of the transient nature of data, it was also possible to perform a preliminary qualitative analysis of soil salinity dynamics in the study area, revealing salinity fluctuations related to the input of salts and water either through irrigation, precipitation, or level and salinity of groundwater.</p>

scholarly journals Linking Long-Term Changes in Soil Salinity to Paddy Land Abandonment in Jaffna Peninsula, Sri Lanka

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 211
Author(s):  
Tharani Gopalakrishnan ◽  
Lalit Kumar
Keyword(s):  
Sri Lanka ◽  
Soil Salinity ◽  
Agricultural Land ◽  
Sea Water ◽  
Land Use Changes ◽  
Soil Salinization ◽  
Landsat Images ◽  
Paddy Land ◽  
Semi Arid Region

Soil salinity is a serious threat to coastal agriculture and has resulted in a significant reduction in agricultural output in many regions. Jaffna Peninsula, a semi-arid region located in the northern-most part of Sri Lanka, is also a victim of the adverse effects of coastal salinity. This study investigated long-term soil salinity changes and their link with agricultural land use changes, especially paddy land. Two Landsat images from 1988 and 2019 were used to map soil salinity distribution and changes. Another set of images was analyzed at four temporal periods to map abandoned paddy lands. A comparison of changes in soil salinity with abandoned paddy lands showed that abandoned paddy lands had significantly higher salinity than active paddy lands, confirming that increasing salts owing to the high levels of sea water intrusion in the soils, as well as higher water salinity in wells used for irrigation, could be the major drivers of degradation of paddy lands. The results also showed that there was a dramatic increase in soil salinity (1.4-fold) in the coastal lowlands of Jaffna Peninsula. 64.6% of the salinity-affected land was identified as being in the extreme saline category. In addition to reducing net arable lands, soil salinization has serious implications for food security and the livelihoods of farmers, potentially impacting the regional and national economy.

scholarly journals Electromagnetic Induction Measurements for Investigating Soil Salinization Caused by Saline Reclaimed Water

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 73
Author(s):  
Lorenzo De Carlo ◽  
Gaetano Alessandro Vivaldi ◽  
Maria Clementina Caputo
Keyword(s):  
Electrical Conductivity ◽  
Soil Salinity ◽  
Electromagnetic Induction ◽  
Reclaimed Water ◽  
Soil Salinization ◽  
Repeated Measurements ◽  
Soil Electrical Conductivity ◽  
Geophysical Research ◽  
Soil Response ◽  
Short Period

This paper focused on the use of electromagnetic induction measurements in order to investigate soil salinization caused by irrigation with saline reclaimed water. An experimental activity was carried out during the growing season of tomato crop in order to evaluate expected soil salinization effects caused by different saline agro-industrial wastewaters used as irrigation sources. Soil electrical conductivity, strictly related to the soil salinity, has been monitored for three months by means of Electromagnetic Induction (EMI) measurements, and evident differences in the soil response have been observed. The study highlighted two aspects that can improve soil investigation due to the utilization of geophysical tools. First, EMI data can map large areas in a short period of time with an unprecedented level of detail by overcoming practical difficulties in order to massively sample soil. At the same time, repeated measurements over time allow updating real-time soil salinity maps by using accurate correlations with soil electrical conductivity. This application points out how integrated agro-geophysical research approaches can play a strategic role in agricultural saline water management in order to prevent soil salinization risks in medium to long-term periods.

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 Using Apparent Electrical Conductivity as Indicator for Investigating Potential Spatial Variation of Soil Salinity across Seven Oases along Tarim River in Southern Xinjiang, China

2020 ◽  
Vol 12 (16) ◽  
pp. 2601
Author(s):  
Jianli Ding ◽  
Shengtian Yang ◽  
Qian Shi ◽  
Yang Wei ◽  
Fei Wang
Keyword(s):  
Electrical Conductivity ◽  
Spatial Distribution ◽  
Water Resources ◽  
Soil Salinity ◽  
Soil Salinization ◽  
Mean Value ◽  
Land Evaluation ◽  
Bare Land ◽  
Apparent Electrical Conductivity ◽  
Southern Xinjiang

Soil salinization is a major soil health issue globally. Over the past 40 years, extreme weather and increasing human activity have profoundly changed the spatial distribution of land use and water resources across seven oases in southern Xinjiang, China. However, knowledge of the spatial distribution of soil salinization in this region has not been updated since a land survey in the 1970s to 1980s (the harmonized world soil database, HWSD) due to scarce observational data. Now, given the uncertainty raised by near future climate change, it is important to develop quick, reliable and accurate estimates of soil salinity at larger scales for a better manage strategy to the local fragile ecosystem that with limited land and water resources. This study collected electromagnetic induction (EMI) readings near surface soil to update on the spatial distribution and changes of water and salt in the region and to map apparent electrical conductivity (ECa, mS·m−1), in four coil configurations: vertical dipole in 1.50 m (ECav01) and 0.75 m (ECav05), so as the horizontal dipole in 0.75 m (ECah01) and 0.37 m (ECah05), then all the ECa coil configurations were modeled with random forest algorithm. The validation results showed an R2 range of 0.77–0.84 and an RMSE range of 115.17–142.76 mS·m−1. The validation accuracy of deep ECa dipole (ECah01, ECav05, and ECav01) was greater than that of shallow ECa (ECah05), as the former integrated a thicker portion of the subsurface. The range of EC spatial variability that can be explained by ECa is 0.19–0.36 (farmland, mean value is 0.28), grassland is 0.16–0.49 (shrub/grassland, mean value is 0.34), and bare land is 0.28–0.70 (bare land, mean value is 0.56). Among them, ECav01 has the best predictive ability. As the depth increased, the influence of soil-related variables decreased, and the contribution of climate-related variables increased. The main factor affecting ECa variation was climate-related variables, followed by vegetation-related variables and soil-related variables. Scatter plot show ECa was significantly correlated with ECe_HWSD_030 (0–30 cm, r = 0.482, p < 0.01) and ECe_HWSD_30100 (30–100 cm, r = 0.556, p < 0.01). The predicted spatial ECa maps were similar to the ECe values from HWSD, but also implies that the distribution of soil water and salt has undergone tremendous changes since 1980s. The study demonstrates that EMI data provide a reliable and cost-effective tool for obtaining high-resolution soil maps that can be used for better land evaluation and soil improvement at larger scales.

scholarly journals A REVIEW: IMPACT OF SOIL SALINITY ON ECOLOGICAL, AGRICULTURAL AND SOCIO-ECONOMIC CONCERNS

2021 ◽  
Vol 9 (07) ◽  
pp. 979-986
Author(s):  
Pooja N. Thaker ◽  
◽  
Nayana Brahmbhatt ◽  
Karishma Shah ◽  
◽  
...  
Keyword(s):  
Soil Salinity ◽  
Review Paper ◽  
Recent Literature ◽  
Human Life ◽  
Management Strategies ◽  
Crop Productivity ◽  
Soil Salinization ◽  
Climatic Conditions ◽  
Soil Conditions ◽  
Biodiversity Changes

In recent years, salinization of soil is one of the challenging environmental concerns occurring all over the world. The effects of concentration of salt can be detected in both natural (primary) as well as man-made (secondary) environment. This is due to massive urbanization and industrialization in coastal regions, Soil salinity may lead to degradative changes in the composition of natural water resources, loss of fertile soil, loss of biodiversity, changes in local climatic conditions which in turn affects many aspects like, increasing salinization (salt affected soil) of lands converted in to non-productive conditions which significantly affects human life and posing major interruption to the economic development of farmers and their economy in the country. Furthermore, the overview of salinization and its effects on ecology, agriculture and economic growth and development is presented in this paper. Purpose of this review paper represented is according to most recent literature and refines knowledge on consistent research efforts for the types of soil salinity, problems of soil salinization, effect on plant growth and management strategies in agriculture to mitigate soil conditions in the salinity affected areas as well as rise in crop productivity and suggests future perspectives for on-going salinity research in the country.

scholarly journals Quantitative Estimation of Soil Salinity Using UAV-Borne Hyperspectral and Satellite Multispectral Images

2019 ◽  
Vol 11 (7) ◽  
pp. 736 ◽  
Author(s):  
Jie Hu ◽  
Jie Peng ◽  
Yin Zhou ◽  
Dongyun Xu ◽  
Ruiying Zhao ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Soil Salinity ◽  
Quantitative Estimation ◽  
Arable Land ◽  
Cost Effective ◽  
Soil Salinization ◽  
Soil Samples ◽  
Soil Reclamation ◽  
Field Scale ◽  
Sparse Vegetation

Soil salinization is a global issue resulting in soil degradation, arable land loss and ecological environmental deterioration. Over the decades, multispectral and hyperspectral remote sensing have enabled efficient and cost-effective monitoring of salt-affected soils. However, the potential of hyperspectral sensors installed on an unmanned aerial vehicle (UAV) to estimate and map soil salinity has not been thoroughly explored. This study quantitatively characterized and estimated field-scale soil salinity using an electromagnetic induction (EMI) equipment and a hyperspectral camera installed on a UAV platform. In addition, 30 soil samples (0~20 cm) were collected in each field for the lab measurements of electrical conductivity. First, the apparent electrical conductivity (ECa) values measured by EMI were calibrated using the lab measured electrical conductivity derived from soil samples based on empirical line method. Second, the soil salinity was quantitatively estimated using the random forest (RF) regression method based on the reflectance factors of UAV hyperspectral images and satellite multispectral data. The performance of models was assessed by Lin’s concordance coefficient (CC), ratio of performance to deviation (RPD), and root mean square error (RMSE). Finally, the soil salinity of three study fields with different land cover were mapped. The results showed that bare land (field A) exhibited the most severe salinity, followed by dense vegetation area (field C) and sparse vegetation area (field B). The predictive models using UAV data outperformed those derived from GF-2 data with lower RMSE, higher CC and RPD values, and the most accurate UAV-derived model was developed using 62 hyperspectral bands of the image of the field A with the RMSE, CC, and RPD values of 1.40 dS m−1, 0.94, and 2.98, respectively. Our results indicated that UAV-borne hyperspectral imager is a useful tool for field-scale soil salinity monitoring and mapping. With the help of the EMI technique, quantitative estimation of surface soil salinity is critical to decision-making in arid land management and saline soil reclamation.

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