Predictive mapping of soil electrical conductivity as a Proxy of soil salinity in south-east of Algeria

Abdennour, Mohamed Amine; Douaoui, Abdelkader; Piccini, Chiara; Pulido, Manuel; Bennacer, Amel; Bradaï, Abdelhamid; Barrena, Jesús; Yahiaoui, Itheri

doi:10.1016/j.indic.2020.100087

Cited by 13 publications

(9 citation statements)

References 54 publications

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“…The soil salinity exhibited a moderate variation in our study. The soil EC was also found to exhibit a moderate variation (CV of EC was 47.4%) in the southeastern part of Algeria [21] and in the Manas River watershed in northern China (CV of EC was 33.1-63.0%) [10], but their CV values were higher than those in our study (Table 1). Another study reported a strong variation (CVs of 1.31-1.57) in the different soil layers [35].…”

Section: Soils Salinity Of the Different Soil Layers And Its Correlation With The Other Propertiescontrasting

confidence: 63%

“…For EC, pH, SAR, and other soil properties in a reclaimed area of the Behera Governorate of Egypt, the IDW method had a higher prediction efficiency than the kriging method [20]. For the soil EC in a representative rural community located in the western part of Biskra, Algeria, the CK method performed better than the OK method, with RMSE values of 0.92 and 1.53, respectively [21]. As can be seen, the most suitable method for the spatial prediction of soil salinity and the related indexes is still under debate, and further study is needed in specific regions.…”

Section: Introductionmentioning

confidence: 92%

“…Ordinary kriging is a widely used interpolation method, which can be used to obtain an optimal, linear, and unbiased prediction for a nonsampled point based on the values of neighboring sample points. The OK method assigns weights to these points based on their distances from the point being estimated and the spatial variability structure, and the formula is as follows [21,33]:…”

Section: Ordinary Kriging Interpolationmentioning

confidence: 99%

“…Soil salinity can exhibit a positive [21] or negative [36] correlation with pH, but the correlation is generally not significant. In our study, a significant negative correlation was found between TSC and pH in both soil layers.…”

Section: Soils Salinity Of the Different Soil Layers And Its Correlation With The Other Propertiesmentioning

confidence: 99%

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Comparison of Different Interpolation Methods for Prediction of Soil Salinity in Arid Irrigation Region in Northern China

Gao

Liu

2021

Agronomy

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Numerous methods have been used in the spatial prediction of soil salinity. However, the most suitable method is still unknown in arid irrigation regions. In this paper, 78 locations were sampled in salt-affected land caused by irrigation in an arid area in northern China. The geostatistical characteristics of the soil pH, Sodium Adsorption Ratio (SAR), Total Salt Content (TSC), and Soil Organic Matter (SOM) of the surface (0–20 cm) and subsurface (20–40 cm) layers were analyzed. The abilities of the Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and CoKriging (CK) interpolation methods were compared, and the Root Mean Square Error (RMSE) was used to justify the results of the methods. The results showed that the spatial distributions of the soil properties obtained using the different interpolation methods were similar. However, the surface layer exhibits more spatial heterogeneity than the subsurface layer. Based on the RSME, the nugget/sill value and range significantly affected which method was the most suitable. Lower nugget/sill values and lower ranges can be fitted using the IDW method, but higher nugget/sill values and higher ranges can be fitted using the OK method. These results provide a valuable reference for the prediction of soil salinity.

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Section: Soils Salinity Of the Different Soil Layers And Its Correlation With The Other Propertiescontrasting

confidence: 63%

Section: Introductionmentioning

confidence: 92%

Section: Ordinary Kriging Interpolationmentioning

confidence: 99%

Section: Soils Salinity Of the Different Soil Layers And Its Correlation With The Other Propertiesmentioning

confidence: 99%

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Comparison of Different Interpolation Methods for Prediction of Soil Salinity in Arid Irrigation Region in Northern China

Gao

Liu

2021

Agronomy

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“…Soil salinity is considered worldwide as one of the most important soil health threats contributing to soil degradation and halting agricultural productivity (Rengasamy, 2016). Soil salinization is a restricting factor of agricultural production, especially in arid and semi-arid areas, as the high concentration of salts affect soils' quality, vegetation growth, crop diversity, and food production (Abdennour et al, 2020). The development of soil salinity in an area is closely linked to its topographic and climatic characteristics, unsustainable agricultural management practices, and insufficient drainage (Dagar et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Exploring the spatial patterns of soil salinity and organic carbon in agricultural areas of Lesvos Island, Greece, using geoinformation technologies

Lekka

Petropoulos

Triantakonstantis

et al. 2023

Environ Monit Assess

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The salt-affected soils national map of Greece was recently made available within the initiative of the Global Soil Partnership (GSP) of Food and Agriculture Organization of the United Nations FAO. The present study explores the development of higher resolution soil property maps included in this national scale product adopting a modified version of the FAO methodology and a logistic regression (LR) method based on ground and satellite data. Furthermore, it also investigates the correlation between saline soils and soil organic carbon (SOC) using geospatial analysis methods. The island of Lesvos in Greece has been selected as a case study. A probabilistic model for saline soils in the agricultural land of Lesvos is produced by exploiting geoinformation technologies. As a result, the spatial distribution of saline soils in the croplands of Lesvos was obtained. Indicatively, areas with p > 0.80 for the occurrence of saline soils accounting for ∼20% of a total area of 169.51 km2 of the croplands in Lesvos. The Nagelkerke R2 coefficient showed that the probabilistic model interprets 11.3% of the variance of the dependent variable from the independent factors. The model accuracy was assessed adopting the receiver operating characteristic (ROC) curve, which showed a reasonable adaptability with area under curve (equal to 0.73). The methodological approach proposed herein can support decision-making on agricultural land protection and planning activities which are key priority today due to environmental instability, food security, and climate change.

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Characterization of the water bodies of Extremadura (SW Spain)

Abdennour

Contador

Barrena-González

et al. 2023

Environ Monit Assess

Self Cite

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Extremadura is the region that stores the greatest amount of fresh water in Spain. Such water is mainly used for power generation, irrigation in agriculture, biodiversity conservation, tourism, recreation, and human and livestock consumption. Nevertheless, crucial information on the total number of water bodies and their geometrical characteristics and spatial distribution patterns are still missing. Thus, our main goal was to characterize the Extremenian water bodies geometrically and spatially through different statistical techniques such as kernel density, Moran’s index, the Getis-Ord Gi*, and principal component analysis (PCA). Firstly, all existing hydrological information was gathered, and using aerial aircraft imagery and satellite images, each water body (WB) was then carefully collected, checked, and corrected. We have inventoried 100,614 WBs (mean density: 2.45 WB km2), irregularly distributed on the territory. WBs with an area < 0.01 km2 (100 ha) represent 64.5% of the total. A multivariate statistical study was conducted, showing that livestock, aridity of the climate, and topography are the main factors controlling the density of water bodies (WBs) in this area. It can be concluded that monitoring of small bodies is crucial to understand their spatial distribution, since they are spread over areas in which extensive farming and commercial crops such as tobacco strongly influence the way of living of many families.

show abstract

Predictive mapping of soil electrical conductivity as a Proxy of soil salinity in south-east of Algeria

Cited by 13 publications

References 54 publications

Comparison of Different Interpolation Methods for Prediction of Soil Salinity in Arid Irrigation Region in Northern China

Comparison of Different Interpolation Methods for Prediction of Soil Salinity in Arid Irrigation Region in Northern China

Exploring the spatial patterns of soil salinity and organic carbon in agricultural areas of Lesvos Island, Greece, using geoinformation technologies

Characterization of the water bodies of Extremadura (SW Spain)

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