【作者】 胡小宁；

【导师】 郭满才； 袁志发； 赵忠；

【作者基本信息】 西北农林科技大学 ， 应用数学， 2010， 硕士

【摘要】 建立根系生长的数学模型,定量地研究人工植被根系的分布特征及其与土壤水分的相互作用机制,弄清人工植被根系对深层土壤水分的影响及其范围,对揭示黄土高原林地土壤干层的形成机理,科学地指导造林树种和人工草种的选择,加快西北山川秀美工程的建设速度具有十分重要的意义。本论文采用2007年6月、8月、10月和2008年4月在陕西省安塞县（半干旱区）和甘肃省泾川县（半湿润区）获得的刺槐人工林细根和土壤水分调查数据,建立了刺槐细根生长模型及刺槐细根生长与土壤水分的耦合关系模型。主要结论如下:1.验证了垂直生长模型S = h^B（ M + Nh + Uh² + Vh³）能很好地拟合刺槐细根的垂直分布,其中,S为细根表面积密度(cm²·dm^-3),h为土层深度（cm）,B反映了细根分布的最大值在土壤中出现的深度,M、N、U、V为经验系数,并计算得出刺槐最大扎根深度及土壤入渗水对细根生长的贡献率。在此基础上,采用室分析方法建立了细根表面积密度随土层深度变化的房室模型S₂（h） = b(e^-k₂h- e^k₁h),从数值上验证了垂直生长模型是房室模型的简化形式,为垂直生长模型提供了理论基础。2.建立了刺槐细根的动态生长模型S （t , h ） = e^-βt·h^B(e^α₁- e^α₂ h + e^α₃h² - e^α₄h³),其中,β为细根表面积密度随时间的衰减率,α₁、α₂、α₃、α₄为经验参数。模型可以表达细根生长随土层深度和时间两个因素的变化状况,并且可以很好地预测黄土高原不同土层深度和时间下刺槐细根生长状况。3.建立了细根表面积密度随土壤水含量（W/%）、土层深度和时间变化的耦合模型,其中0﹤a﹤1。该模型能够很好的描述黄土高原地区刺槐细根生长与土壤水分之间的耦合关系,反映了细根生长和土壤水分随时间的周期性变化;模型参数a的值介于0和1之间,表明土壤水分只是部分供给了刺槐根系的生长,刺槐根系生长对土壤水分的利用是有限的,不会造成研究区域刺槐林地土壤的干化;参数m反映了土壤水分对根系生长10-20天的滞后效应;参数p、b、m反映了刺槐生长地区的差异,a反映了刺槐根系生长需水量的生物学特性。更多还原

【Abstract】 It is very important to establish the mathematical model of fine root growth, study the distribution of artificial vegetation roots and its relationship with soil moisture in quantitative method, and research the influence of deep soil moisture by artificial vegetation roots, for revealing the cause of soil desiccation layer in the Loess Plateau woodland, guiding the species choice of artificial tree or grass scientifically, speeding up the construction of Northwest Landscape Beautification Project.The paper established a model for fine root growth of Robinia pseudoacacia and a coupled model for the relationship between fine root growth and soil moisture, based on the data of artificial R.pseudoacacia fine root and soil moisture, investigated in Ansai county of Shaanxi province（semi-arid region） and Jingchuan county of Gansu province（sub-humid region）. The main conclusions are as follows:1. The paper tested and verified that the model S = h^B（ M + Nh + Uh² + Vh³）can good fit the fine root vertical distribution for R.pseudoacacia (where, S is fine root surface area density/cm²·dm^-3; h is soil depth/cm; B shows the soil depth where the values of fine root are the most; M,N,U,V are empirical coefficients), and calculated the maximum depth of fine root and the contribution rate of soil moisture to fine root growth. Based on the above, it established a compartment model S₂（h） = b(e^-k₂h- e^k₁h) for fine root surface area density, with the change of soil depth, verified its equivalence with the vertical growth model using numerical method, and offered the theoretical basis for the vertical growth model.2. The paper established a dynamic model S （t , h ） = e^-βt·h^B(e^α₁- e^α₂ h + e^α₃h² - e^α₄h³)for fine root growth （where,βis the attenuation rate of fine root surface area density with time;α₁ ,α₂,α₃,α₄ are empirical coefficients）. The dynamic model could show the changes of fine root growth with soil depth and time, and can predict the state of fine root growth for R.pseudoacacia in different soil depth and time, in the Loess Plateau.3. The paper established a coupled model , 0<a<1, described the relationship between fine root surface area density (S/cm²·dm^-3) and soil moisture （W/%）, with the change of soil depth （h/cm） and time （t/month）. It is proved that the model could reflect the coupling relationship exactly. It displays the annual cyclical changes about fine root growth and soil moisture; the value of parameter a falls in between 0 and 1, which shows the root growth of R.pseudoacacia just absorbs part of the soil moisture and could not cause soil desiccation in the investigative area; parameter m indicates the hysteresis effect of soil moisture and root growth, which is between 10 to 20 day; parameters p, b and m reflect the difference of region where R.pseudoacacia grow, and parameter a reflects the biological characteristics of R.pseudoacacia - water demand of root growth.更多还原