不同盆栽基质水分特征曲线的对比分析与模拟  

Comparative analysis and prediction of the potting media water retention curve with different proportional compositions

作　　者：朱钊岑 邵明安[1,2,3] 赵春雷 贾小旭 王娇[1,3] ZHU Zhaocen;SHAO Ming′an;ZHAO Chunlei;JIA Xiaoxu;WANG Jiao(Yellow River Delta Modern Agricultural Engineering Laboratory,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;College of Natural Resources and Environment,Northwest A&F University,Yangling 712100,China;College of Resources and Environment,University of Chinese Academy of Sciences,Beijing 100190,China)

机构地区：[1]中国科学院地理科学与资源研究所黄河三角洲现代农业工程实验室,北京100101 [2]西北农林科技大学资源环境学院,杨凌712100 [3]中国科学院大学资源与环境学院,北京100190

出　　处：《农业工程学报》2023年第8期197-204,共8页Transactions of the Chinese Society of Agricultural Engineering

基　　金：中国科学院A类战略性先导科技专项资助(XDA28130100);国家自然科学基金项目(41907009);黄土高原土壤侵蚀与旱地农业国家重点实验室开放基金项目(A314021402–2014)。

摘　　要：现有关于盆栽控水模拟土壤干旱条件的试验中多采用含水率作为水分胁迫阈值,然而由于基质配比不同导致含水率相同的基质的水分状况也不尽相同,这导致各研究间结果难以对比和参考。为快速获取盆栽基质水分特征曲线,建立基质水分特征曲线预测模型。该研究以盆栽控水试验常用的泥炭土、蛭石和珍珠岩为基质材料,测定了不同配比基质的水分特征曲线,通过不同方法(多元回归模型、人工神经网络)建立了其预测模型。结果表明,人工神经网络模型对泥炭土-蛭石复配基质水分特征曲线的预测精度高于多元回归;相较于人工神经网络,多元回归模型的稳定性更高。综合考虑模型的精度和稳定性,多元回归模型是预测作物盆栽基质水分特征曲线的最佳模型,预测精度R^(2)≥0.950,平均误差接近0。该模型为基质水分特征曲线快速获取以及相关作物干旱胁迫研究间的对比提供了方法和依据。The water stress threshold is one of the most important indexes to evaluate the response of crops to water stress.Water control in the pot culture is also a commonly-used way to simulate drought stress conditions.The absorption of soil water by crops is mainly decided by the soil water potential.And the relationship between soil water content and water potential varies with matric medias.However,the water stress threshold of a crop is usually given in the form of mass water content.However,there is some inconsistency in the matric media under previous pot experiments.This study aims to rapidly obtain the water retention curves of base materials in the pot experiments,in order to predict the potting soil water retention curves.The peat soil,vermiculite,and perlite were taken as matric materials in the pot experiments.The water retention curves of various media were measured,including three kinds of matric materials and eight different proportional compositions.The van Genuchten model was used to fit these water retention curves.After that,the pedotransfer functions(PTFs)of water retention curves were established using multiple regression and artificial neural network.The normalized root mean square error(SNRMSE),determination coefficient(R^(2)),and mean error(SMR)were selected as the accuracy indicators of the model.Furthermore,the model stability was verified through 30 cycles to finally determine the optimal modeling and the predicted water retention curve.The results showed that an ideal fitting effect of the van Genuchten model was achieved in the water retention curves of(R^(2)>0.99).There were some significant differences in the water retention curves of the three potting medias.Peat soil presented more invalid pores than vermiculite and perlite,resulting in a large water content in the high-water suction section(water suction>100 kPa).The high capillary pore content of vermiculite led to a high-water content in the middle and high-water suction sections(water suction 33-800 kPa).Pearlite shared the higher p

关 键 词：模型 基质 水分胁迫 盆栽试验 水分特征曲线 传递函数 

分 类 号：S152[农业科学—土壤学] S220.4[农业科学—农业基础科学]