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

Abstract

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. K E Y W O R D S bidimensional intrinsic mode function (BIMF), coal mining area, land use type, soil organic matter (SOM), two-dimensional empirical mode decomposition (2DEMD) 1 | INTRODUCTION Soil is one of the most valuable nonrenewable resources (Lal, 2015) and serves as an nexus for the atmosphere, hydrosphere, biosphere, and lithosphere (Alcañiz, Outeiro, Francos, & Úbeda, 2018). Previous studies indicated that minesoils undergo rapid changes in chemical, physical, and biological properties as a result of mining activities and pedogenic weathering processes (Shrestha & Lal, 2007; Skousen, 1995), and their spatial variation differed greatly compared with those in the non

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

“…The spatial distribution of the residual (Figure 4a5,b5) was closest to that of the original distribution (Figure 3a,b), which illustrated the overall spatial trend in soil salinity. These results are consistent with those of Huang et al (2017), Zhou et al (2021), and Zhu et al (2020). Wei et al (2021) decomposed soil salinity into seven scales using the WT algorithm in the region, while more than five scales were used in this study.…”

“…Future studies are required to clarify the effects of soil erosion on salinization. Our study found that removing the influence of the scale component of small‐scale variability (i.e., IMF1‐IMF4) enhanced the correlation between soil salinity and environmental factors (Tables 3 and 4), which is similar to the findings of other studies (Zhang et al, 2021; Zhu et al, 2020). Therefore, the adoption of scale‐specific environmental factors might improve the estimation of soil salinity or other soil properties and reduce the uncertainty in digital soil mapping.…”

“…Therefore, the BEMD algorithm is recommended for decomposing the scale variance of soil properties. The variation scale of the BEMD component gradually increased with decomposition (Table 2), which is analogous to the results reported in Tibet by Zhu et al (2020).…”

“…Wei et al (2021) decomposed soil salinity into seven scales using the WT algorithm in the region, while more than five scales were used in this study. This difference may be related to the artificial setting of 2), which is analogous to the results reported in Tibet by Zhu et al (2020).…”