基于人工神经网络的比水容量模型参数预测模型研究
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摘要
为了探索获取比水容量的简便方式,以山西省黄土高原区农耕土壤为实验对象,进行了土壤水分特征曲线与比水容量的相关试验,拟合得到比水容量模型参数,并配套测定了相关的土壤基本理化参数。在研究分析各个土壤基本理化参数与比水容量模型参数的影响关系的基础上,建立了关于土壤质地、土壤容重、土壤有机质含量、土壤无机盐含量的BP神经网络预报模型。研究表明:以土壤质地、土壤容重、土壤有机质含量、土壤无机盐含量为输入因子的BP神经网络预报模型是可行的,比水容量模型参数实测值与预测值之间的平均相对误差均低于10%,预测效果较好,精度较高。该研究结果为黄土高原地区获取比水容量提供了理论与技术上的支持,同时可促进土壤传输函数理论的发展。
In order to explore a simple and convenient method for obtaining specific water capacity,the relevant basic physical and chemical parameters of the soil,the soil water characteristic curve and specific water capacity are tested in the soil of the Loess Plateau in Shanxi Province. The parameters of the specific water capacity model are fitted and measured. Based on an analysis of the relationship between the basic physical and chemical parameters of each soil and the parameters of the water capacity model,a BP neural network prediction model is established on the soil texture,soil bulk density,soil organic matter content,and soil inorganic salt content. The results show that the BP neural network prediction model based on soil texture,soil bulk density,soil organic matter content and soil inorganic salt content are feasible,and the average relative error between the measured and predicted values of the water capacity model parameters is lower than 10%,prediction and accuracy are better. The research results provide theoretical and technical supports for obtaining specific water capacity,and promoting the development of soil transfer function theory.
In order to explore a simple and convenient method for obtaining specific water capacity,the relevant basic physical and chemical parameters of the soil,the soil water characteristic curve and specific water capacity are tested in the soil of the Loess Plateau in Shanxi Province. The parameters of the specific water capacity model are fitted and measured. Based on an analysis of the relationship between the basic physical and chemical parameters of each soil and the parameters of the water capacity model,a BP neural network prediction model is established on the soil texture,soil bulk density,soil organic matter content,and soil inorganic salt content. The results show that the BP neural network prediction model based on soil texture,soil bulk density,soil organic matter content and soil inorganic salt content are feasible,and the average relative error between the measured and predicted values of the water capacity model parameters is lower than 10%,prediction and accuracy are better. The research results provide theoretical and technical supports for obtaining specific water capacity,and promoting the development of soil transfer function theory.
引文
[1]张航,徐明岗,张富仓,等.陕西农业土壤持水性能及其与土壤性质的关系[J].干旱地区农业研究,1994,(2):32-37.
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[4] Vereecken H J,Maes J,Feyen J,et al. Estimating the Soil Moisture Retention Characteristic From Texture,Bulk Density,and Carbon Content[J]. Soil Science,1989,148(6):389-403.
[5]王欢元,韩霁昌,罗林涛,等.两种土壤传递函数在预测砒砂岩与沙复配土的水力学参数中的应用[J].土壤通报,2013,(6):1 351-1 355.
[6]韩勇鸿,樊贵盛,孔令超.田间持水率土壤传输函数研究[J].农业机械学报,2013,44(9):62-67.
[7]李昊哲,樊贵盛.冻融土壤Philip入渗模型参数的BP预报模型[J].节水灌溉,2017,(5):5-10.
[8] Van Genuchten M Th. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils[J].Soil Science Society of America Journal,1980,44:892-898.
[9] Brooks RH,Corey AT. Hydraulic Properties of Porous Media. Hydrology Paper[D]. Fort Collins,Colorado:Colorado State Univ,1964:3-27.
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[11]舒凯民,樊贵盛.砂壤黄土比水容量对土壤容重变异敏感性分析[J].土壤通报,2016,47(4):814-819.
[2]雷志栋,杨诗秀,谢传森.土壤水动力学[M].北京:清华大学出版社,1988.
[3]刘建立,徐绍辉,刘慧.估计土壤水分特征曲线的间接方法研究进展[J].水利学报,2004,35(2):68-76.
[4] Vereecken H J,Maes J,Feyen J,et al. Estimating the Soil Moisture Retention Characteristic From Texture,Bulk Density,and Carbon Content[J]. Soil Science,1989,148(6):389-403.
[5]王欢元,韩霁昌,罗林涛,等.两种土壤传递函数在预测砒砂岩与沙复配土的水力学参数中的应用[J].土壤通报,2013,(6):1 351-1 355.
[6]韩勇鸿,樊贵盛,孔令超.田间持水率土壤传输函数研究[J].农业机械学报,2013,44(9):62-67.
[7]李昊哲,樊贵盛.冻融土壤Philip入渗模型参数的BP预报模型[J].节水灌溉,2017,(5):5-10.
[8] Van Genuchten M Th. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils[J].Soil Science Society of America Journal,1980,44:892-898.
[9] Brooks RH,Corey AT. Hydraulic Properties of Porous Media. Hydrology Paper[D]. Fort Collins,Colorado:Colorado State Univ,1964:3-27.
[10] Gardner W R,Hillel D,Benyamini Y. Post-irrigation movement of soil water:I. Redistribution[J]. Water Resources Research,1970,6(3):851-861.
[11]舒凯民,樊贵盛.砂壤黄土比水容量对土壤容重变异敏感性分析[J].土壤通报,2016,47(4):814-819.