Spatial Distribution and Estimation Model of Soil pH in Coastal Eastern China

文献类型： 外文期刊

第一作者： Xie, Xiansheng

作者： Xie, Xiansheng;Hou, Yanlin;Wang, Shuojin;Jia, Shugang;Liu, Shutian;Hou, Xianda;Xie, Xiansheng;Qiu, Jianfei;Feng, Xinxin;Hou, Yanlin;Wang, Shuojin;Jia, Shugang;Liu, Shutian;Hou, Xianda;Hou, Yanlin;Wang, Shuojin;Jia, Shugang;Liu, Shutian;Hou, Xianda;Dou, Sen

作者机构：

关键词： soil health; mean annual precipitation; mean annual temperature; hydrothermal condition; estimation model

期刊名称：INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH （ 影响因子：4.614； 五年影响因子：4.798 ）

ISSN：

年卷期： 2022 年 19 卷 24 期

页码：

收录情况： SCI

摘要： Soil pH is an essential indicator for assessing soil quality and soil health. In this study, based on the Chinese farmland soil survey dataset and meteorological dataset, the spatial distribution characteristics of soil pH in coastal eastern China were analyzed using kriging interpolation. The relationships between hydrothermal conditions and soil pH were explored using regression analysis with mean annual precipitation (MAP), mean annual temperature (MAT), the ratio of precipitation to temperature (P/T), and the product of precipitation and temperature (P*T) as the main explanatory variables. Based on this, a model that can rapidly estimate soil pH was established. The results showed that: (a) The spatial heterogeneity of soil pH in coastal eastern China was obvious, with the values gradually decreasing from north to south, ranging from 4.5 to 8.5; (b) soil pH was significantly correlated with all explanatory variables at the 0.01 level. In general, MAP was the main factor affecting soil pH (r = -0.7244), followed by P/T (r = -0.6007). In the regions with MAP < 800 mm, soil pH was negatively correlated with MAP (r = -0.4631) and P/T (r = -0.7041), respectively, and positively correlated with MAT (r = 0.6093) and P*T (r = 0.3951), respectively. In the regions with MAP > 800 mm, soil pH was negatively correlated with MAP (r = -0.6651), MAT (r = -0.5047), P/T (r = -0.3268), and P*T (r = -0.5808), respectively. (c) The estimation model of soil pH was: y = 23.4572 - 6.3930 x lgMAP + 0.1312 x MAT. It has been verified to have a high accuracy (r = 0.7743, p < 0.01). The mean error, the mean absolute error, and the root mean square error were 0.0450, 0.5300, and 0.7193, respectively. It provides a new path for rapid estimation of the regional soil pH, which is important for improving the management of agricultural production and slowing down soil degradation.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序