Spatial distribution of salinity and heavy metals in surface soils on the Mugan Plain, the Republic of Azerbaijan

Han, Junho; Mammadov, Zaman; Kim, Minhee; Mammadov, Elton; Lee, Seo Yeon; Park, Jisuk; Mammadov, Garib; Elovsat, Guliyev; Ro, Hee‐Myong

doi:10.1007/s10661-021-08877-7

Cited by 12 publications

(10 citation statements)

References 34 publications

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“…The spatial distribution of soil water and salt also varies with time [40,41]. Our findings indicate that as water content decreases, the variability of soil water distribution initially increases under S1−3 and then decreases under S3−5 throughout the layer (Table 3 and Figure 4).…”

Section: Discussionmentioning

confidence: 65%

Spatial Distribution Mechanism of Soil Water-Salt Coupling Effect in Arid Saline-Alkali Farmland

Ke,

Ma,

Shen

2024

Preprint

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Revealing the spatial distribution mechanism of the coupling effect between soil water and salt is essential for managing saline-alkali farmland. This study utilized the multifractal method to analyze soil water and salt under varying water content levels in arid saline-alkali farmland. Soil samples were collected on the second (S1), fifth (S2), eighth (S3), eleventh (S4), and fourteenth (S5) days after a rainfall event. The findings showed that a significant decrease in soil water content, contrasting with an increase in soil salt content throughout the soil layers post-rainfall. As water content decreased, the spatial variability of soil water initially increased from S1-3 and then decreased, while the spatial variability of soil salt decreased. The spatial distribution between soil water and salt exhibited a high correlation at S3-4 (with relative water content of soil ranging from 0.52 to 0.75) due to their coupling effect. However, soil salt was unevenly leached by rainfall at high water content levels (S1-2) and precipitated at low water content levels (S5), resulting in low spatial variability correlations between soil water and salt. This study elucidated the coupling process of soil water and salt, identifying their spatiotemporal distribution mechanism in dryland agricultural areas.

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Section: Discussionmentioning

confidence: 65%

Spatial Distribution Mechanism of Soil Water-Salt Coupling Effect in Arid Saline-Alkali Farmland

Ke,

Ma,

Shen

2024

Preprint

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“…Regardless of the cause, the combined presence of high concentrations of soluble salts and HM is of concern given that both can harm crop plants, and salinity can increase bioavailability of HM like Cd and Pb (Acosta et al, 2011). Fortunately, others have reported opposite trends for HM like Cr, Ni, and As (Han J. et al, 2021). While we cannot predict how HM will behave in these soils, we can conclude that farms in the Indus Basin are at high risk for salinity and HM, so farmers should take steps to address these stress factors.…”

Section: Discussionmentioning

confidence: 99%

“…The presence of elevated concentrations of HM may be even more problematic in saline soils. For example, Cd bioavailability in soil and uptake into plants was increased in the presence of higher levels of soil salinity ( Wang et al, 2014 ; Han J. et al, 2021 ), which would be highly problematic in agricultural systems growing edible crop plants.…”

Section: Introductionmentioning

confidence: 99%

Diversity and functional traits of indigenous soil microbial flora associated with salinity and heavy metal concentrations in agricultural fields within the Indus Basin region, Pakistan

et al. 2022

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Soil salinization and heavy metal (HM) contamination are major challenges facing agricultural systems worldwide. Determining how soil microbial communities respond to these stress factors and identifying individual phylotypes with potential to tolerate these conditions while promoting plant growth could help prevent negative impacts on crop productivity. This study used amplicon sequencing and several bioinformatic programs to characterize differences in the composition and potential functional capabilities of soil bacterial, fungal, and archaeal communities in five agricultural fields that varied in salinity and HM concentrations within the Indus basin region of Pakistan. The composition of bacteria with the potential to fix atmospheric nitrogen (N) and produce the enzyme 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase were also determined. Microbial communities were dominated by: Euryarchaeota (archaea), Actinobacteria, Proteobacteria, Planctomycetota, Firimicutes, Patescibacteria and Acidobacteria (bacteria), and Ascomycota (fungi), and all soils contained phylotypes capable of N-fixation and ACC-deaminase production. Salinity influenced bacterial, but not archaeal or fungal communities. Both salinity and HM altered the relative abundance of many phylotypes that could potentially promote or harm plant growth. These stress factors also appeared to influence the potential functional capabilities of the microbial communities, especially in their capacity to cycle phosphorous, produce siderophores, and act as symbiotrophs or pathotrophs. Results of this study confirm that farms in this region are at risk due to salinization and excessive levels of some toxic heavy metals, which could negatively impact crop and human health. Changes in soil microbial communities and their potential functional capabilities are also likely to affect several critical agroecosystem services related to nutrient cycling, pathogen suppression, and plant stress tolerance. Many potentially beneficial phylotypes were identified that appear to be salt and HM tolerant and could possibly be exploited to promote these services within this agroecosystem. Future efforts to isolate these phylotypes and determine whether they can indeed promote plant growth and/or carry out other important soil processes are recommended. At the same time, identifying ways to promote the abundance of these unique phylotypes either through modifying soil and crop management practices, or developing and applying them as inoculants, would be helpful for improving crop productivity in this region.

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“…The phenomenon of cross-pollution between functional areas indicates that there is a major source of pollution risk in the functional areas, which requires an urgent response [ 11 , 12 ]. The accurate identification of pollution risk sources by classical statistical methods means using traditional full-scale sampling [ 13 , 14 ]. However, the disadvantage of the traditional method is the long time it takes to complete and the high expense, which is not an optimal choice for mining companies.…”

Section: Introductionmentioning

confidence: 99%

Pollution Risk Prediction for Cadmium in Soil from an Abandoned Mine Based on Random Forest Model

Cao

Guo

Lv³

et al. 2023

IJERPH

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It is highly uncertain as to the potential risk of toxic metal(loid)s in abandoned mine soil. In this study, random forest was used to predict the risk of cadmium pollution in the soils of an abandoned lead/zinc mine. The results showed that the random forest model is stable and precise for the pollution risk prediction of toxic metal(loid)s. The mean of Cd, Cu, Tl, Zn, and Pb was 6.02, 1.30, 1.18, 2.03, and 2.08 times higher than the soil background values of China, respectively, and their coefficients of variation were above 30%. As a case study, cadmium in the mine soil had “slope” hazard characteristics while the ore sorting area was the major source area of cadmium. The theoretical values of the random forest model are similar to the practical values for the ore sorting area, metallogenic belt, riparian zone, smelting area, hazardous waste landfill, and mining area. The potential risk of soil Cd in the ore sorting area, metallogenic belt, and riparian zone are extremely high. The tendency of pollution risk migrates significantly both from the ore sorting area to the smelting area and the mining area, and to the hazardous waste landfill. The correlation of soil pollution risk is significant between the mining area, the smelting area, and the riparian zone. The results suggested that the random forest model can effectively evaluate and predict the potential risk of the spatial heterogeneity of toxic metal(loid)s in abandoned mine soils.

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Spatial distribution of salinity and heavy metals in surface soils on the Mugan Plain, the Republic of Azerbaijan

Cited by 12 publications

References 34 publications

Spatial Distribution Mechanism of Soil Water-Salt Coupling Effect in Arid Saline-Alkali Farmland

Spatial Distribution Mechanism of Soil Water-Salt Coupling Effect in Arid Saline-Alkali Farmland

Diversity and functional traits of indigenous soil microbial flora associated with salinity and heavy metal concentrations in agricultural fields within the Indus Basin region, Pakistan

Pollution Risk Prediction for Cadmium in Soil from an Abandoned Mine Based on Random Forest Model

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