| 我国东北黑土丘陵区小流域土壤有机质空间分布模拟 |
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| 引用本文： | 马泉来,高凤杰,张志民,单培明,韩文文,周军,曲茉莉.我国东北黑土丘陵区小流域土壤有机质空间分布模拟[J].环境科学研究,2016,29(3):382-390. |
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| 作者姓名： | 马泉来 高凤杰 张志民 单培明 韩文文 周军 曲茉莉 |
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| 作者单位： | 1.东北农业大学资源与环境学院, 黑龙江 哈尔滨 150030 |
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| 基金项目： | 国家水体污染控制与治理科技重大专项(2013ZX07201007-004)；东北农业大学青年才俊项目(14QC30) |
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| 摘 要： | 为探索小流域w(SOM)(SOM为土壤有机质)空间分布模拟的最佳方法,以我国东北黑土丘陵区海沟河小流域为例,借助地统计学和3S技术提取与w(SOM)显著相关的地形及环境因子,对海沟河小流域表层(0~20 cm)w(SOM)分别进行协同克里格插值、回归克里格插值和地理加权回归克里格空间插值模拟,并进行精度验证. 结果表明:我国东北黑土丘陵区海沟河小流域表层w(SOM)平均值为12.96 g/kg,空间变异程度为中等. 海拔、距水系距离均与w(SOM)显著相关,能够用来辅助w(SOM)的空间分布插值；与协同克里格插值结果相比,回归克里格对w(SOM)的插值精度提高了56.09%；地理加权回归克里格插值精度提高了90.87%；对地理加权回归克里格插值所产生的残差进行二次统计分析及合理插值,能够进一步提高插值模拟精度；将人类干扰因素纳入插值模型,是未来提高w(SOM)空间分布模拟精度的关键. 研究显示,地理加权回归克里格插值有效提高了w(SOM)空间插值模拟的精度,并且存在改进和提高的空间.
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| 关 键 词： | 黑土丘陵区 土壤有机质(SOM) 地理加权回归克里格 分布模拟 |
| 收稿时间： | 2015/10/10 0:00:00 |
| 修稿时间： | 2015/12/28 0:00:00 |
Simulation of Spatial Distribution of Soil Organic Matter in a Mollisol Watershed in Northeastern China |
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| MA Quanlai,GAO Fengjie,ZHANG Zhimin,SHAN Peiming,HAN Wenwen,ZHOU Jun and QU Moli.Simulation of Spatial Distribution of Soil Organic Matter in a Mollisol Watershed in Northeastern China[J].Research of Environmental Sciences,2016,29(3):382-390. |
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| Authors: | MA Quanlai GAO Fengjie ZHANG Zhimin SHAN Peiming HAN Wenwen ZHOU Jun and QU Moli |
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| Affiliation: | 1.College of Resource and Environment, Northeast Agricultural University, Harbin 150030, China2.Research Academy of Environmental Sciences of Heilongjiang Province, Harbin 150036, China |
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| Abstract: | Abstract: In order to find the best interpolation method of SOM distribution in the Mollisol watershed, 3S combined with geostatistics was used to extract topographic factors and analyze SOM distribution at the soil depth of 0-20 cm in the Haigouhe watershed of Heilongjiang province. CK (Co-Kriging), RK (Regression Kriging) and GWRK (Geographically Weighted Regression Kriging) were adopted to predict SOM distribution, and the accuracy of the interpolation was also investigated in the present study. The main results indicated that the mean SOM was 12.96 g/kg at 0-20 cm soil depth for the whole watershed, with a degree of variation at a moderate level. Altitude and distance from the river system were significantly correlated to SOM, and could be used as cofactors for SOM interpolation. Compared to CK, the accuracy of interpolation increased to 56.09% and 90.87% for RK and GWRK, respectively. The residual from GWR was calculated and interpolated, and also improved the accuracy of prediction. Furthermore, the accuracy of the prediction could also be improved effectively by including anthropomorphic factors into the interpolation; the method should be adopted in future research work. Therefore, GWR could be recognized as the best interpolation method, but could be improved in the future. |
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| Keywords: | mollisol hilly area soil organic matter Geographically Weighted Regression Kriging distributional simulation |
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