| 黄土高原南北样带不同土层土壤容重变异分析与模拟 |
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| 引用本文： | 易小波,邵明安,赵春雷,张晨成.黄土高原南北样带不同土层土壤容重变异分析与模拟[J].农业机械学报,2017,48(4):198-205. |
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| 作者姓名： | 易小波 邵明安 赵春雷 张晨成 |
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| 作者单位： | 西北农林科技大学,西北农林科技大学,西北农林科技大学,西北农林科技大学 |
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| 基金项目： | 国家自然科学基金项目（41530854、41501233） |
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| 摘 要： | 为探明黄土高原南北样带土壤容重空间分布特征,为土壤水文过程模拟与预测提供水力参数,采用经典统计学方法,分析了样带不同土层深度(0~10 cm、10~20 cm、20~40 cm)土壤容重的空间变异特征,并用多元逐步回归、传递函数方程和一阶自回归状态空间模型方法分别对土壤容重的空间分布进行了模拟。结果表明:样带0~20 cm深度土壤容重的变异为中等程度变异,20~40 cm为弱变异。状态空间方程转换系数表明,不同土层深度土壤容重的影响因素不同,0~10 cm主要为有机碳含量、黏粒和砂粒体积分数,10~20 cm为有机碳含量、黏粒和砂粒体积分数和降水量,20~40 cm为黏粒和砂粒体积分数、降水量和土地利用。状态空间模型的模拟效果均优于经典统计的多元逐步回归方程和传递函数方程,基于黏粒和砂粒体积分数、降水量和土地利用的状态空间模型可以解释样带20~40 cm容重92.3%的变异。一阶自回归状态空间模型可用于田间条件下土壤容重分布特征的预测。
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| 关 键 词： | 容重 状态空间 传递函数 模拟 空间变异 |
| 收稿时间： | 2016/8/14 0:00:00 |
Variation Analysis and Simulation of Soil Bulk Density within Different Soil Depths along South to North Transect of Loess Plateau |
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| Affiliation: | Northwest A&F University,Northwest A&F University,Northwest A&F University and Northwest A&F University |
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| Abstract: | To provide soil hydraulic parameters for simulating soil hydrological processes, classical statistics were used to characterize the spatial distribution of soil bulk density (BD) within different soil depths (0~10cm, 10~20cm and 20~40cm) along south to north transect of the Loess Plateau. Furthermore, the multiple stepwise regressions, pedotransfer functions and the first order autoregressive state space models were applied to simulate the distribution of BD. The magnitude of BD variability in the 0~20cm soil layer was moderate according to the coefficient of variations, while the BD variability in the 20~40cm soil layer was weak. The key factors affecting the spatial distribution of BD differed in different soil depths. Soil organic carbon, clay and sand contents were the key factors in the 0~10cm soil layer;soil organic carbon content, clay and sand contents and precipitation were the key factors in the 10~20cm soil layer;while in the 20~40cm soil layer, clay and sand contents, precipitation and land use were the key factors to affect the spatial distribution of BD along south to north transect. State-space models were consistently more effective than multiple stepwise regression functions and pedotransfer functions for estimating spatial distribution of BD. State-space model that included clay and sand contents, precipitation and land use factors showed the best simulation result, and the combination of such variables explained 92.3% of the total variation of BD. State-space models were recommended for studying spatial relations between soil bulk density and other variables on the Loess Plateau. |
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| Keywords: | bulk density state-space pedotransfer function simulation spatial variation |
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