Spatial distribution of soil organic matter in a coal mining subsidence area
Underground mining has caused drastic disturbances to regional ecosystems and soil nutrients. Understanding the three-dimensional (3D) spatial distribution of soil nutrients in mining area farmland is crucial for agricultural production and environmental management. However, few studies have reporte...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-02-01
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| Series: | Acta Agriculturae Scandinavica. Section B, Soil and Plant Science |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/09064710.2019.1676916 |
| _version_ | 1797684387956916224 |
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| author | Huijuan Zhang Wenkai Liu Hebing Zhang Liangxin Fan Shouchen Ma |
| author_facet | Huijuan Zhang Wenkai Liu Hebing Zhang Liangxin Fan Shouchen Ma |
| author_sort | Huijuan Zhang |
| collection | DOAJ |
| description | Underground mining has caused drastic disturbances to regional ecosystems and soil nutrients. Understanding the three-dimensional (3D) spatial distribution of soil nutrients in mining area farmland is crucial for agricultural production and environmental management. However, few studies have reported the 3D spatial distribution of soil organic matter (SOM) in coal mining subsidence area. In our study, a sequential Gaussian simulation (SGS) algorithm was used to analyse the spatial distribution of SOM based on observations of 180 soil samples in the Zhaogu mine in China. The results showed that the SOM content had considerable variation in spatial distribution at different soil depths (0–20, 20–40, 40–60 cm) and decreased with the increase in soil depth. The spatial variability of surface organic matter was the largest, and the coefficient of variation was 29.38%, which was moderately mutated. The spatial distribution of SOM also varied among slope locations. The SOM content was higher upslope and downslope than on the middle slope. In addition, given a threshold, SGS can be used to calculate the probability that the organic matter content at any position is lower or higher than the given value. The research results provide a reference for land reclamation and precision agriculture. |
| first_indexed | 2024-03-12T00:28:59Z |
| format | Article |
| id | doaj.art-31e0c660bf194efaa759ba05b9dc8af1 |
| institution | Directory Open Access Journal |
| issn | 0906-4710 1651-1913 |
| language | English |
| last_indexed | 2024-03-12T00:28:59Z |
| publishDate | 2020-02-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Acta Agriculturae Scandinavica. Section B, Soil and Plant Science |
| spelling | doaj.art-31e0c660bf194efaa759ba05b9dc8af12023-09-15T10:26:25ZengTaylor & Francis GroupActa Agriculturae Scandinavica. Section B, Soil and Plant Science0906-47101651-19132020-02-0170211712710.1080/09064710.2019.16769161676916Spatial distribution of soil organic matter in a coal mining subsidence areaHuijuan Zhang0Wenkai Liu1Hebing Zhang2Liangxin Fan3Shouchen Ma4Henan polytechnic UniversityNorth China University of Water Resources and Electric PowerHenan polytechnic UniversityHenan polytechnic UniversityHenan polytechnic UniversityUnderground mining has caused drastic disturbances to regional ecosystems and soil nutrients. Understanding the three-dimensional (3D) spatial distribution of soil nutrients in mining area farmland is crucial for agricultural production and environmental management. However, few studies have reported the 3D spatial distribution of soil organic matter (SOM) in coal mining subsidence area. In our study, a sequential Gaussian simulation (SGS) algorithm was used to analyse the spatial distribution of SOM based on observations of 180 soil samples in the Zhaogu mine in China. The results showed that the SOM content had considerable variation in spatial distribution at different soil depths (0–20, 20–40, 40–60 cm) and decreased with the increase in soil depth. The spatial variability of surface organic matter was the largest, and the coefficient of variation was 29.38%, which was moderately mutated. The spatial distribution of SOM also varied among slope locations. The SOM content was higher upslope and downslope than on the middle slope. In addition, given a threshold, SGS can be used to calculate the probability that the organic matter content at any position is lower or higher than the given value. The research results provide a reference for land reclamation and precision agriculture.http://dx.doi.org/10.1080/09064710.2019.1676916soil organic matterunderground coal mine3d stochastic simulationsoil spatial variabilityprecision agriculture |
| spellingShingle | Huijuan Zhang Wenkai Liu Hebing Zhang Liangxin Fan Shouchen Ma Spatial distribution of soil organic matter in a coal mining subsidence area Acta Agriculturae Scandinavica. Section B, Soil and Plant Science soil organic matter underground coal mine 3d stochastic simulation soil spatial variability precision agriculture |
| title | Spatial distribution of soil organic matter in a coal mining subsidence area |
| title_full | Spatial distribution of soil organic matter in a coal mining subsidence area |
| title_fullStr | Spatial distribution of soil organic matter in a coal mining subsidence area |
| title_full_unstemmed | Spatial distribution of soil organic matter in a coal mining subsidence area |
| title_short | Spatial distribution of soil organic matter in a coal mining subsidence area |
| title_sort | spatial distribution of soil organic matter in a coal mining subsidence area |
| topic | soil organic matter underground coal mine 3d stochastic simulation soil spatial variability precision agriculture |
| url | http://dx.doi.org/10.1080/09064710.2019.1676916 |
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