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Revealing the 2D –scale, location–specific variations of soil properties in the coal mining area of Changhe watershed, China

Bibliographic Data

ID21648338
AuthorsHongfen Zhu (0000-0002-9220-9017, College of Resources and Environment Shanxi Agricultural University Taigu 030801 PR China), Rutian Bi (0000-0002-1395-7579, College of Resources and Environment Shanxi Agricultural University Taigu 030801 PR China), Ruipeng Sun (College of Resources and Environment Shanxi Agricultural University Taigu 030801 PR China), Zhanjun Xu (0000-0002-1902-5270, College of Resources and Environment Shanxi Agricultural University Taigu 030801 PR China), Chunjuan Lv (College of Resources and Environment Shanxi Agricultural University Taigu 030801 PR China), Jason Yang (0000-0002-7156-5872, College of Resources and Environment Shanxi Agricultural University Taigu 030801 PR China, corresponding author)
Year2020
Volume31
Issue18
Pages2775-2788
Publication date2020-12-01
Open AccessYes
TypeARTICLE
VenueLand Degradation and Development (JOURNAL)
Journal identifiersISSN: 1085-3278 • E-ISSN: 1099-145X
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ldr.3639
OpenAlexW3022686553
LanguageEN
Citations received1
References cited35

Many researches have been conducted to understand the scale–location specific variations of soil properties in one‐dimensional soil samples. However, these results did not enable us to properly understand the 2D (two‐dimensional) distributions of soil characteristics, especially in the coal mining areas. Therefore, the objective of this study is to reveal the scale–location dependent variation of two‐dimensional patterns for soil properties and to develop a soil organic matter (SOM) prediction based on those scale–location effects in the coal mining area. To this end, SOM, porosity, and silt were measured in the top (0–20 cm), middle (20–40 cm), and bottom (40–60 cm)layers of soil in Changhe watershed, China. The scale‐specific spatial patterns of soil properties were extracted using two‐dimensional empirical mode decomposition (2DEMD), and SOM was predicted using stepwise multiple linear regression (SMLR) and 2DEMD GS . It was found that the spatial distributions of SOM residue (>24 km) at middle layer and porosity residue at top and bottom layers could reveal the differentiation between coal mining and non‐coal mining areas. The scale‐effects on the relationships between SOM and its covariates was stronger than that of land uses, and the relationships of SOM with the covariates in different land use types were distinctive at top layer, and were similar at bottom layer. 2DEMD GS performed better than SMLR on SOM prediction for its involvement of scale and location effects. Therefore, the relationship between SOM and influencing factors is a function of scale, location, and land uses activities, and the scale‐ and location‐dependent method should be considered for SOM prediction

Cartography · Coal · Geography · Geomorphology · Silt · Spatial ecology · Spatial variability · Statistics · Watershed · Computer Science · Environmental Science · Geochemistry and Geologic Mapping · Mathematics · Soil and Unsaturated Flow · Soil Geostatistics and Mapping · Ecology · Geology · Soil Science

  • Revealing the scale‐ and location‐specific variation and control factors of soil salinity using bi‐dimensional empirical modal decomposition

    Open Access•Chuanmei Zhu, Jianli Ding et al.•Land Degradation and Development•2022

  • Restoring Soil Quality to Mitigate Soil Degradation

    Open Access•Rattan Lal•Sustainability•2015

Citations per year0.25
Citation span2022 - 2022 (1)
Highly citedNo

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