本文選題：土壤傳輸函數(shù) + BP神經(jīng)網(wǎng)絡(luò)��； 參考：《太原理工大學(xué)》2017年博士論文

【摘要】：土壤水分運(yùn)動(dòng)的入滲參數(shù)決定著地面徑流、灌溉水和降水轉(zhuǎn)換為土壤水的速度和分布,進(jìn)而也影響著灌水質(zhì)量和灌溉效果(灌水均勻度、儲(chǔ)水效果和灌水效率),它是合理確定不同灌水條件下技術(shù)參數(shù)的主要依據(jù)。因此,土壤水分入滲參數(shù)的研究便成為改進(jìn)地面灌水效果、提高灌溉水利用率等技術(shù)中迫切需要解決的關(guān)鍵問(wèn)題。文章以區(qū)域尺度上規(guī)�；魍寥来筇锶霛B試驗(yàn)為依據(jù),利用土壤傳輸函數(shù)理論,在系統(tǒng)地研究土壤入滲模型參數(shù)與容易獲得的土壤常規(guī)理化性狀參數(shù)間的定量關(guān)系基礎(chǔ)上,建立了土壤入滲參數(shù)與土壤常規(guī)理化性狀參數(shù)間的多元線性、非線性、BP神經(jīng)網(wǎng)絡(luò)模型傳輸函數(shù),實(shí)現(xiàn)了通過(guò)土壤基本理化參數(shù)預(yù)測(cè)土壤入滲參數(shù)的目的。其研究成果可以為實(shí)施優(yōu)化地面灌溉灌水技術(shù)參數(shù)提供強(qiáng)有力的技術(shù)支持,同時(shí),在一定程度上豐富了土壤傳輸函數(shù)理論的發(fā)展。文章的主要研究結(jié)果表明:(1)土壤水分入滲參數(shù)受多種因素的復(fù)雜影響,包括土壤結(jié)構(gòu)、質(zhì)地、含水量、有機(jī)質(zhì)含量、含鹽量等。土壤結(jié)構(gòu)、質(zhì)地、含水量、有機(jī)質(zhì)含量等常規(guī)理化參數(shù)與土壤入滲參數(shù)間存在線性或非線性的定量關(guān)系,其中土壤有機(jī)質(zhì)含量與入滲能力成正比,土壤干容重(結(jié)構(gòu))、初始含水量、黏粒含量(質(zhì)地)、含鹽量等與入滲能力成反比。(2)基于土壤常規(guī)理化參數(shù),采用傳輸函數(shù)預(yù)測(cè)土壤入滲參數(shù)是可行的。從預(yù)測(cè)結(jié)果來(lái)看,Kostiakov兩參數(shù)入滲模型、Kostiakov-Lewis三參數(shù)入滲模型和Philip入滲模型的顯著性檢驗(yàn)都是顯著的。引入每個(gè)自變量的顯著性檢驗(yàn)和回歸方程的顯著性檢驗(yàn)F值均大于相應(yīng)的F0.95,說(shuō)明傳輸函數(shù)的回歸系數(shù)是顯著的,回歸方程也是顯著的。隨著引入變量個(gè)數(shù)的增加,模型的復(fù)相關(guān)系數(shù)逐漸向1靠近,相關(guān)性越來(lái)越好,最終各個(gè)函數(shù)的多元線性回歸模型計(jì)算值與實(shí)測(cè)值之間的全相關(guān)系數(shù)R為0.9~0.95,R2均大于0.81,表明由實(shí)驗(yàn)數(shù)據(jù)所得的多元線性傳輸函數(shù)相關(guān)性較好,用土壤常規(guī)理化特征參數(shù)預(yù)測(cè)土壤入滲能力及其入滲參數(shù)是完全可行的。(3)Kostiakov兩參數(shù)、Kostiakov-Lewis三參數(shù)和Philip兩參數(shù)入滲模型的參數(shù)預(yù)報(bào)模型中合理的輸入變量為:土壤砂粒含量、黏粒含量、不均勻系數(shù)、曲率系數(shù)、體積含水量、重量含水量、干容重、有機(jī)質(zhì)含量等。(4)Kostiakov模型入滲參數(shù)的線性、非線性、BP預(yù)測(cè)模型相對(duì)誤差均較低,計(jì)算精度較高,相關(guān)性較好,擬合度高,均能實(shí)現(xiàn)對(duì)土壤入滲參數(shù)的預(yù)測(cè)。(5)Kostiakov-Lewis模型入滲參數(shù)的線性、非線性、BP預(yù)測(cè)模型的相對(duì)誤差都在合理范圍之內(nèi),相對(duì)誤差低,顯著性強(qiáng),相關(guān)性良好,擬合度高,也能夠?qū)崿F(xiàn)對(duì)土壤入滲參數(shù)的預(yù)測(cè)。(6)Philip模型入滲參數(shù)的線性、非線性、BP預(yù)測(cè)模型的相對(duì)誤差雖在合理范圍內(nèi),具有一定的可行性,但相對(duì)誤差值偏大,精度較低。(7)在Kostiakov、Kostiakov-Lewis和Philip模型參數(shù)的預(yù)測(cè)模型中,Kostiakov-Lewis模型參數(shù)的預(yù)測(cè)效果最好,能夠很好的反映土壤水分入滲的過(guò)程,特別是對(duì)于長(zhǎng)歷時(shí)水分入滲,較其它模型具有更高和更穩(wěn)定的預(yù)測(cè)精度;BP預(yù)測(cè)模型的精度要高于多元非線性預(yù)測(cè)模型,但模型的穩(wěn)定性不如多元非線性模型。
[Abstract]:The infiltration parameters of soil moisture movement determine ground runoff, irrigation water and precipitation conversion to the velocity and distribution of soil water, and also affect irrigation quality and irrigation effect (irrigation uniformity, water storage effect and irrigation efficiency). It is the main basis for the rational determination of technical parameters under different irrigation conditions. Therefore, soil water infiltration parameters The research has become the key problem to be solved urgently in improving the effect of ground irrigation and improving the utilization rate of irrigation water. The paper systematically studies the soil infiltration model parameters and the regular physical and chemical properties of soil obtained by soil infiltration function theory on the basis of regional scale tillage soil infiltration test on regional scale. On the basis of quantitative relationship between parameters of the soil, the multiple linear, nonlinear, nonlinear, BP neural network model transmission function between soil infiltration parameters and soil conventional physical and chemical parameters is established, and the purpose of predicting soil infiltration parameters through soil basic physical and chemical parameters is realized. The research results can be used to optimize the technical parameters of irrigation and irrigation. It provides strong technical support and, at the same time, enriches the development of soil transport function theory. The main research results of this article show that: (1) soil water infiltration parameters are complex influenced by various factors, including soil structure, texture, water content, organic matter content, salt content, soil structure, texture, water content, organic matter content. There is a linear or nonlinear quantitative relationship between the conventional physical and chemical parameters and the infiltration parameters of soil. The content of soil organic matter is proportional to the infiltration capacity. The dry bulk density (structure), initial water content, clay content (texture) and salt content are inversely proportional to the infiltration capacity. (2) based on the conventional physical and chemical parameters of soil, the transfer function is used to predict soil The soil infiltration parameters are feasible. From the prediction results, the Kostiakov two parameter infiltration model, the Kostiakov-Lewis three parameter infiltration model and the Philip infiltration model are all significant tests. The significance test of each independent variable and the significance test of the regression equation are greater than the corresponding F0.95, indicating the regression of the transfer function. The coefficient is significant, and the regression equation is also significant. With the increase of the number of variables introduced, the complex correlation coefficient of the model is gradually closer to 1, the correlation is getting better and better. Finally, the total correlation coefficient R between the calculated value and the measured value of the multiple linear regression model of each function is 0.9~0.95, and R2 is more than 0.81, indicating the diversity obtained from the experimental data. The correlation of linear transmission function is good. It is completely feasible to predict soil infiltration capacity and infiltration parameters with soil conventional physicochemical parameters. (3) Kostiakov two parameters, Kostiakov-Lewis three parameters and Philip two parameter infiltration model parameter prediction model, the reasonable input variation is: soil sand content, clay content, inhomogeneous system Number, curvature coefficient, volumetric water content, water content, dry bulk density, organic matter content and so on. (4) the linear, nonlinear, nonlinear, nonlinear, relative error of the Kostiakov model is low, the calculation precision is higher, the correlation is better, and the fitting degree is high. (5) the line of infiltration parameters of the Kostiakov-Lewis model. The relative error of the model is within a reasonable range, the relative error is low, the relative error is low, the correlation is strong, the correlation is good, the fitting degree is high, and the prediction of soil infiltration parameters can be realized. (6) the linear, nonlinear and the relative error of the BP prediction model of the Philip model is feasible, although the relative error of the BP model is in a reasonable range, but it is feasible, but it has certain feasibility, but the relative error of the model is reasonable. The relative error value is large and the precision is low. (7) in the prediction model of Kostiakov, Kostiakov-Lewis and Philip model parameters, the prediction effect of Kostiakov-Lewis model parameters is the best. It can reflect the infiltration process of soil moisture well, especially for long diachronic water infiltration, which has higher and more stable prediction accuracy than other models; BP The accuracy of the prediction model is higher than that of the multivariate nonlinear prediction model, but the stability of the model is not as good as that of the multivariate nonlinear model.

【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2017
【分類號(hào)】：S152.7

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