Spatial distribution of soil nutrients in reclamation dump sites based on subdivision IDW

Authors

ZHAO Yanling, Institute of Land Reclamation and Ecological Restoration, China University of Mining and Technology, Beijing 100083, China
ZHAO Bincheng, Institute of Land Reclamation and Ecological Restoration, China University of Mining and Technology, Beijing 100083, China
WANG Xin, Institute of Land Reclamation and Ecological Restoration, China University of Mining and Technology, Beijing 100083, China
XIAO Wu, Department of Land Management, Zhejiang University, Hangzhou 310058, China
LIU Huifang, China ENFI Engineering Co. Ltd, Beijing 100083, China

Abstract

Accurately grasping the spatial distribution of soil nutrients is of great significance for evaluating the soil quality of reclamation dumps and formulating corresponding reclamation measures. The general interpolation method of the complex terrain of the dump site has a poor prediction effect. The northern dump of Shengli No.1 open-pit mine in Xilinhot, Inner Mongolia was selected as an example in the paper. The soil nutrients(available nitrogen, available potassium, available phosphorus and organic matter) were spatially interpolated using the inverse distance weighting method based on terrain partitioning, and compared with the conventional inverse distance weighting method and kriging interpolation method. The results show that the cross-validation accuracy obtained by using the partitioned inverse distance weighting method was higher than that of the kriging interpolation method and the inverse distance weighting method. In addition, the R² value of available phosphorus was 0.22, and the R² value of available nitrogen was 0.37. The R² values of available potassium and organic matter were 0.34 and 0.14, respectively. They were also higher than Kriging interpolation and inverse distance weighting. In addition, the partitioned inverse distance interpolation method could accurately estimate the extreme points of the measured points, and could better reflect the details of the spatial distribution of soil nutrients in the dump.

Keywords

dump, soil nutrients, spatial distribution, subdivision IDW, Shengli mining area

DOI

10.3969/j.issn.1001-1986.2020.04.027

Recommended Citation

ZHAO Yanling, ZHAO Bincheng, WANG Xin, et al. (2020) "Spatial distribution of soil nutrients in reclamation dump sites based on subdivision IDW," Coal Geology & Exploration: Vol. 48: Iss. 4, Article 28.
DOI: 10.3969/j.issn.1001-1986.2020.04.027
Available at: https://cge.researchcommons.org/journal/vol48/iss4/28

Reference

[1] 王金满,郭凌俐,白中科,等. 黄土区露天煤矿排土场复垦后土壤与植被的演变规律[J]. 农业工程学报,2013,29(21):223-232. WANG Jinman,GUO Lingli,BAI Zhongke,et al. Succession law of reclaimed soil and vegetation on opencast coal mine dump of loess area[J]. Transactions of the Chinese Society of Agricultural Engineering,2013,29(21):223-232.

[2] 肖礼,赵俊峰,黄懿梅,等. 永利露天煤矿排土场不同植被类型下土壤理化性质和酶活性研究[J]. 水土保持研究,2016,23(4):89-93. XIAO Li,ZHAO Junfeng,HUANG Yimei,et al. Study on soil enzyme activities and physical and chemical properties under different vegetation types in Yongli opencast coal mine[J]. Research of Soil and Water Conservation,2016,23(4):89-93.

[3] 王党朝,刘慧芳,肖武,等. 胜利一号露天煤矿北排土场土壤物理性质空间分布研究[J]. 中国煤炭,2018,44(11):135-140. WANG Dangchao,LIU Huifang,XIAO Wu,et al. Research on spatial distribution of soil physical properties in north dump of Shengli No.1 opencast coal mine[J]. China Coal,2018,44(11):135-140.

[4] 郭凌俐,王金满,白中科,等. 黄土区露天煤矿排土场复垦初期土壤颗粒组成空间变异分析[J]. 中国矿业,2015,24(2):52-59. GUO Lingli,WANG Jinman,BAI Zhongke,et al. Analysis of spatial variability of soil granules in early stage of reclamation at opencast coal mine dump in loess area[J]. China Mining Magazine,2015,24(2):52-59.

[5] 王子良. 空间数据预处理及插值方法对比研究:以铜陵矿区土壤元素为例[D]. 合肥:合肥工业大学,2010. WANG Ziliang. Comparison and research of spatial data pretreatment and interpolation:Taking the example of soil elements in Tongling mining area[D]. Hefei:Hefei University of Technology,2010.

[6] 胡刚,赵刚,宋慧. 不同插值方法对降水量空间不确定性的影响[J]. 济南大学学报(自然科学版),2012,26(4):428-432. HU Gang,ZHAO Gang,SONG Hui. Influence of different interpolation methods on spatial uncertainty of rainfall[J]. Journal of Jinan University(Natural Science and Technology Edition),2012,26(4):428-432.

[7] MISHRA U,LAL R,SLATER B,et al. Predicting soil organic carbon stock using profile depth distribution functions and ordinary Kriging[J]. Soil Science Society of America Journal,2009,73(2):614-621.

[8] 徐艳,王曙光,李娟. 生物炭对矿区重金属污染土壤养分影响及修复效果[J]. 西部大开发(土地开发工程研究),2019,4(11):33-37. XU Yan,WANG Shuguang,LI Juan. The nutrient and remediation effect of biochar on heavy metal contaminated soil in mining areas[J]. Western Development(Land Development and Engineering Research),2019,4(11):33-37.

[9] 王颖,冯仲科. 平朔矿区开采受损及治理区土壤养分特征对比分析[J]. 水土保持通报,2019,39(1):91-97. WANG Ying,FENG Zhongke. Comprehensive study on soil nutrient in damaged and controlled areas in Pingshuo mining area[J]. Bulletin of Soil and Water Conservation,2019,39(1):91-97.

[10] 徐薇涵. 丹棱金藏芒硝矿区土壤盐分空间分布特征研究[D]. 成都:四川农业大学,2013. XU Weihan. Study of spatial distribution feature of soil salinity in the Glauber's salt mining area of Danling County[D]. Chengdu:Sichuan Agricultural University,2013.

[11] 徐占军,张媛,张绍良,等. 基于GIS与分区Kriging的采煤沉陷区土壤有机碳含量空间预测[J]. 农业工程学报,2018,34(10):253-259. XU Zhanjun,ZHANG Yuan,ZHANG Shaoliang,et al. Spatial prediction of soil organic carbon content in coal mining subsidence area based on GIS and partition Kriging[J]. Transactions of the Chinese Society of Agricultural Engineering,2018,34(10):253-259.

[12] 于伟宣,赵明松,王萌,等. 采样数量与空间插值方法对土壤属性预测精度的影响[J]. 科学技术与工程,2017,17(25):186-191. YU Weixuan,ZHAO Mingsong,WANG Meng,et al. Effects of sampling sizes and spatial interpolation methods on prediction accuracy of soil properties[J]. Science Technology and Engineering,2017,17(25):186-191.

[13] 张世文,王胜涛,刘娜,等. 土壤质地空间预测方法比较[J]. 农业工程学报,2011,27(1):332-339. ZHANG Shiwen,WANG Shengtao,LIU Na,et al. Comparison of spatial prediction method for soil texture[J]. Transactions of the Chinese Society of Agricultural Engineering,2011,27(1):332-339.

[14] 黄利燕. 基于ArcGIS不同空间插值方法的降雨量预测效果对比[J]. 北京测绘,2019,33(7):759-762. HUANG Liyan. A comparison of precipitation prediction effect based on different spatial interpolation methods in ArcGIS[J]. Beijing Surveying and Mapping,2019,33(7):759-762.

[15] 郭李娜,樊贵盛. 基于网格搜索和交叉验证支持向量机的地表土壤容重预测[J]. 土壤通报,2018,49(3):512-518. GUO Lina,FAN Guisheng. Support vector machines for surface soil density prediction based on grid search and cross validation[J]. Chinese Journal of Soil Science,2018,49(3):512-518.

[16] 陈慕松,范晓晖,吴寿华. 基于不同空间插值类型的耕地土壤有机质空间变异性分析[J]. 江西农业学报,2018,30(10):55-59. CHEN Musong,FAN Xiaohui,WU Shouhua. Analysis of spatial variation of soil organic matter content in cultivated land based on different spatial interpolation styles[J]. Acta Agriculturae Jiangxi,2018,30(10):55-59.

[17] 李素萃,赵艳玲,肖武,等. 巢湖流域景观生态质量时空分异评价[J]. 农业机械学报,2020,51(1):203-213. LI Sucui,ZHAO Yanling,XIAO Wu,et al. Spatial and temporal differentiation of landscape ecological quality in Chaohu river basin[J]. Transactions of The Chinese Society of Agricultural Machinery,2020,51(1):203-213.

[18] 高宏艳,索全义,郑海春,等. 内蒙古平原灌区耕地土壤肥力评价方法研究:以土默川平原灌区为例[J]. 土壤通报,2019,50(4):794-799. GAO Hongyan,SUO Quanyi,ZHENG Haichun,et al. Soil fertility evaluation methods of cultivated land in the irrigation district of Inner Mongolia plain:A case study of Tumochuan plain[J]. Chinese Journal of Soil Science,2019,50(4):794-799.

[19] 李小文,曹春香,常超一. 地理学第一定律与时空邻近度的提出[J]. 自然杂志,2007,29(2):69-71. LI Xiaowen,CAO Chunxiang,CHANG Chaoyi. The first law of geography and spatial-temporal proximity[J]. Chinese Journal of Nature,2007,29(2):69-71.

[20] 吴子豪,刘艳芳,陈奕云,等. 综合土地利用及空间异质性的土壤有机碳空间插值模型[J]. 应用生态学报,2018,29(1):238-246. WU Zihao,LIU Yanfang,CHEN Yiyun,et al. Spatial interpolation model of soil organic carbon density considering land-use and spatial heterogeneity[J]. Chinese Journal of Applied Ecology,2018,29(1):238-246.