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1.
Development and use of a database of hydraulic properties of European soils   总被引:17,自引:0,他引:17  
J. H. M. W  sten  A. Lilly  A. Nemes  C. Le Bas 《Geoderma》1999,90(3-4):169-185
Many environmental studies on the protection of European soil and water resources make use of soil water simulation models. A major obstacle to the wider application of these models is the lack of easily accessible and representative soil hydraulic properties. In order to overcome this apparent lack of data, a project was initiated to bring together the available hydraulic data which resided within different institutions in Europe into one central database. This information was then used to derive a set of pedotransfer functions applicable to studies at a European scale. These pedotransfer functions predict the hydraulic properties from parameters collected during soil surveys and can be a good alternative for costly and time-consuming direct measurement of these properties. A total of 20 institutions from 12 European countries collaborated in establishing the database of draulic operties of uropean oils (HYPRES). This database has a flexible relational structure capable of holding a wide diversity of both soil pedological and hydraulic data. As these data were contributed by 20 different institutions it was necessary to standardise both the particle-size and the hydraulic data. A novel similarity interpolation procedure was successfully used to achieve standardization of particle-sizes according to the FAO clay, silt and sand particle-size ranges. Standardization of hydraulic data was achieved by fitting the Mualem-van Genuchten model parameters to the individual θ(h) and K(h) hydraulic properties stored in HYPRES. The HYPRES database contains information on a total of 5521 soil horizons (including replicates). Of these, 4030 horizons had sufficient data to be used in the derivation of pedotransfer functions. Information on both water retention and hydraulic conductivity was available for 1136 horizons whereas 2894 horizons had only information on water retention. Each soil horizon was allocated to one of 11 possible soil textural/pedological classes derived from the six FAO texture classes (five mineral and one organic) and the two pedological classes (topsoil and subsoil) recognised within the 1:1 000 000 scale Soil Geographical Data Base of Europe. Next, both class and continuous pedotransfer functions were developed. By using the class pedotransfer functions in combination with the 1:1 000 000 scale Soil Map of Europe, the spatial distribution of soil water availability within Europe was derived.  相似文献
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基于ANN的复垦土壤水分特征曲线的预测研究   总被引:8,自引:5,他引:3       下载免费PDF全文
为能较容易且更准确地获取复垦土壤水分特征曲线,将易测定的土壤特性如土壤质地、容重和饱和含水量作为输入变量,采用基于bagging算法的神经网络法建立了用于预测土壤水分特征曲线的土壤转换函数法(PTFs)模型,并对徐州矿区复垦土壤的水分特征曲线进行了预测,同时与普通BP算法预测精度进行了比较.研究结果表明所建立的PTFs参数模型具有较高的估计精度,bagging算法均方根预测误差比普通BP算法减少了7.5%~27.0%,说明该模型的建立与求解为复垦土壤水分特征曲线的预测研究提供了一条新途径.  相似文献
3.
封丘地区土壤传递函数的研究   总被引:6,自引:1,他引:5       下载免费PDF全文
以黄淮海平原封丘地区的潮土和风沙土为研究对象 ,试图寻求解决土壤水动力学特性参数问题的更加实用可行的方法。根据大量的土壤基本物理性质和土壤持水数据 ,利用多元逐步回归分析方法 ,分别建立了vanGenuchten模型的参数θr、θs、a、n的土壤传递函数模型 ,并通过统计分析和数学模拟进行模型验证。研究结果表明 ,vanGenuchten模型参数与土壤的质地、有机质含量及容重等基本物理性质有一定的线性相关性。vanGenuchten模型的参数估计模型对粘性土壤的拟合效果较好 ,而拟合砂性土壤时误差较大。  相似文献
4.
A method for prediction of soil penetration resistance   总被引:3,自引:2,他引:1  
A new equation for predicting penetration resistance of soil is presented. The equation contains two main additive terms: the first is a measure of the degree of compactness of the soil and the second gives the contribution of pore water to the soil strength. It is proposed that these terms are applicable to soils of different texture, at different bulk densities and at different water contents. The equation is calibrated and tested using values of penetrometer resistance measured in the field at a range of locations in Poland. Predictions from the equation are compared with predictions from two other published equations. It is shown that the performance of the proposed equation is superior to the other two, at least for the Polish data set used in this work. On the basis of the assumption that the proposed equation is correct, predictions of penetrometer resistance are made using pedotransfer functions to illustrate typical effects of soil texture, bulk density and water content.  相似文献
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Modeling water flow and solute transport in vadose zone requires knowledge of soil hydraulic properties, which are water retention and hydraulic conductivity curves. As an alternative to direct measurement, indirect determination of these functions from basic soil properties using pedotransfer functions (PTFs) has attracted the attention of researchers in a variety of fields such as soil scientists, hydrologists, and agricultural and environmental engineers. In this study, PTFs for point and parametric (van Genuchten's parameters) estimation of soil hydraulic parameters from basic soil properties such as particle-size distribution, bulk density, and three different pore sizes were developed and validated using artificial neural network (ANN) and multiple-linear regression methods and the predictive capabilities of the two methods was compared using some evaluation criteria. Total of 195 soil samples was divided into two groups as 130 for the development and 65 for the validation of PTFs. Although the differences between the two methods were not statistically significant (p > 0.05), regression predicted point and parametric variables of soil hydraulic parameters better than ANN. Both methods had lower accuracy in parametric predictions than in point predictions. Accuracy of the predictions was evaluated by the coefficient of determination (R2) and the root mean square error (RMSE) between the measured and predicted parameter values. The R2 and RMSE varied from 0.637 to 0.979 and from 0.013 to 0.938 for regression, and varied from 0.444 to 0.952 and from 0.020 to 3.511 for ANN, respectively. Even though regression performs insignificantly better than ANN in this case, ANN produces promising results and its advantages can be utilized by developing or using new algorithms in future studies.  相似文献
8.
The unsaturated soil hydraulic functions involving the soil–water retention curve (SWRC) and the hydraulic conductivity provide useful integrated indices of soil quality. Existing and newly devised methods were used to formulate pedotransfer functions (PTFs) that predict the SWRC from readily available soil data. The PTFs were calibrated using a large soils database from Hungary. The database contains measured soil–water retention data, the dry bulk density, sand, silt and clay percentages, and the organic matter content of 305 soil layers from some 80 soil profiles. A three-parameter van Genuchten type function was fitted to the measured retention data to obtain SWRC parameters for each soil sample in the database. Using a quasi-random procedure, the database was divided into “evaluation” (EVAL) and “test” (TEST) parts containing 225 and 80 soil samples, respectively. Linear PTFs for the SWRC parameters were calculated for the EVAL database. The PTFs used for this purpose particle-size percentages, dry bulk density, organic matter content, and the sand/silt ratio, as well as simple transforms (such as logarithms and products) of these independent variables. Of the various independent variables, the eight most significant were used to calculate the different PTFs. A nonlinear (NL) predictive method was obtained by substituting the linear PTFs directly into the SWRC equation, and subsequently adjusting the PTF parameters to all retention data of the EVAL database. The estimation error (SSQ) and efficiency (EE) were used to compare the effectiveness of the linear and nonlinearly adjusted PTFs. We found that EE of the EVAL and the TEST databases increased by 4 and 7%, respectively, using the second nonlinear optimization approach. To further increase EE, one measured retention data point was used as an additional (concomitant) variable in the PTFs. Using the 20 kPa water retention data point in the linear PTFs improved the EE by about 25% for the TEST data set. Nonlinear adjustment of the concomitant variable PTF using the 20 kPa retention data point as concomitant variable produced the best PTF. This PTF produced EE values of 93 and 88% for the EVAL and TEST soil data sets, respectively.  相似文献
9.
利用土壤理化性质数据建立转换函数是间接获得土壤水力参数的重要手段之一。基于测定的土壤理化性质和土壤水分常数数据,本文采用回归分析、BP神经网络和基于BP神经网络的Rosetta模型3种方式分别建立了青海三江源地区土壤饱和含水量、毛管持水量和田间持水量的转换函数,并对其预测精度进行了比较。结果表明:(1)回归分析方法总体预测效果比较理想,特别是田间持水量的平均误差(ME)和均方根误差(RMSE)都在3.397%以下,决定系数(R2)高达0.868;(2)BP神经网络方法的预测效果非常理想,各土壤水分常数平均误差和均方根误差都在4.685%以下,并且决定系数均在0.857以上;(3)Rosetta模型的预测效果相对较差,特别是饱和含水量和毛管持水量,平均误差(ME)和均方根误差(RMSE)相对较大,决定系数(R2)相对较小。3种方式中,BP神经网络方法所建立的毛管持水量和饱和含水量转换函数均为最佳,回归方法所建立的田间持水量的转换函数要好于BP神经网络方法和Rosetta模型,Rosetta模型对土壤水分常数的预测效果不如其他两种方式。研究可为青海三江源地区土壤水力特性参数研究以及区域尺度上土壤水分估算提供科学依据。  相似文献
10.
Ferralsols under native vegetation have a weak to moderate macrostructure and a well-developed microstructure corresponding to subrounded microaggregates that are usually 80 to 300 μm in size. The aim of this study was to analyze how the hydraulic properties of a clay Ferralsol were affected by a change of structure when the native vegetation is cleared for pasture. We studied the macrostructure in the field and microstructure in scanning electron microscopy. The water retention properties were determined by using pressure cell equipment. We determined the saturated hydraulic conductivity, Ks, by applying a constant hydraulic head to saturated core samples, and the unsaturated hydraulic conductivity, K(Ψ), by applying the evaporation method to undisturbed core samples. Results showed a significant decrease in the water retained at −1 and −10 hPa from 0- to 40-cm-depth when the native vegetation is cleared for pasture. That decrease in the water retained was related to a smaller development of microaggregation and greater proportion of microaggregates in close packing. For smaller water potential, there was no difference of water retained at every depth between native vegetation and pasture. Pedotransfer functions established earlier for Brazilian Ferralsols and using clay content as single predictor gave pretty good results but the precision of the estimation decreased when the water potential increased. This decrease in the precision was related to the lack of predictor taking structure into account. Ks and K(Ψ) showed an upward trend with depth under native vegetation and pasture. Except at 0–7-cm depth between the Brachiaria clumps in the pasture where smaller Ks and K(Ψ) than at the other depth was recorded whatever land use, we did not record any significant difference of Ks and K(Ψ) at every depth between native vegetation and pasture. The upward trend shown by the hydraulic conductivity with depth was related to the increase in the development of microaggregation with depth.  相似文献
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