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植物生物条件下荒漠土壤水分预报的数学模型
引用本文:朱永华,吕海深,等.植物生物条件下荒漠土壤水分预报的数学模型[J].冰川冻土,2001,23(3):264-269.
作者姓名:朱永华  吕海深
作者单位:[1]中国科学院寒区旱区环境与工程研究所,甘肃兰州730000 [2]兰州大学数学系,甘肃兰州730000
基金项目:中国科学院知识创新工程项目;KZCX1-10-03;
摘    要:通过对生长了3a的荒漠植物骆驼刺的根系分布规律及不同深度土壤含水量分布资料的研究,利用动态模拟方程,分析了骆驼刺根系吸水的分布规律,以及根系吸水与其影响因素之间的关系,用多元回归分析方法拟合了骆驼刺根系吸水的数学模型,利用所得到的骆驼刺根系吸水模式对实验地的土壤水分动态进行了模拟,模拟值与实测值比较表明结果具有一定的精度。

关 键 词:荒漠土壤  含水量预测  数学模型  植物生长条件  骆驼刺  根系分布规律
文章编号:1000-0240(2001)03-0264-06
修稿时间:2000年11月20日

A Mathematical Model Predicting Water Content in Desert Soil with Plant Growth
Abstract:In the soil-plant-atmosphere continuum (SPAC), water transfer is an important process. How to describe water transfer in the SPAC is a key to know and understand the SPAC. But the key to describe water transfer in quantity is to determine how plant roots absorb soil water and to predict how soil moisture content changes in profile. Luotuoci is a typical kind of subshrub in inland desert regions of China and its lateral roots are very rich. A concept of plant root growth radius is developed in order to precisely describe the subshrub with rich lateral roots. The authors also studied the root distribution pattern of three-year-old Luotuoci and its volumetric soil water content in profile, and analyzed the relations between root water uptake and its restricted factors. Equation (5) for Lutuoci root water uptake is set up by multivariate regression analysis. Equations for calculation of evapotranspiration at time t (\%ET\%), change of roots growth radius (\%R\-h\%) and root depth at a given time (\%\%) are also worked out. At last, the authors simulated the soil water dynamics in the experimented Luotuoci growth site by the established root water uptake model. The comparison between the simulated and measured values shows that the accuracy of the established model is approving and realistic, and the method to establish the model of Luotuoci root water uptake can be useful to other kind of subshrub in inland desert regions.
Keywords:soil-plant-atmosphere continuum  desert plant  water content prediction  mathematical model
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