基于通用陆面模式(Common Land Model,CoLM),首次评估了两套最新的全球土壤数据集GSDE(Global Soil Dataset for Earth System Model)和SG(SoilGrids)对全球陆面过程模拟的影响。比较分析了两套数据中砂粒、粘粒、砾石、有机碳的含量和...基于通用陆面模式(Common Land Model,CoLM),首次评估了两套最新的全球土壤数据集GSDE(Global Soil Dataset for Earth System Model)和SG(SoilGrids)对全球陆面过程模拟的影响。比较分析了两套数据中砂粒、粘粒、砾石、有机碳的含量和容重这五个土壤属性在全球分布上的差异以及这种差异造成的对模式估计的土壤特性参数、水力热力变量的影响。结果表明,土壤特性参数在全球的空间分布主要受土壤粒径分布(砂粒、粉粒和粘粒)影响,同时也受砾石、有机碳和容重的影响。土壤资料对全球模拟结果影响主要体现在区域差异,对水文学变量的影响(Re最大达到±100%)大于对土壤热力学变量的影响(Re<±10%),对地表辐射变量的影响较小(Re<±5%)。其中,土壤体积含水量在加拿大中部及西北部、俄罗斯东南部及中西部和澳大利亚中部地区模拟结果相差较大,总径流在低纬地区模拟结果出现较大的差异,热力学变量在非洲北部、加拿大西北部以及俄罗斯中北部的差异稍大。将模拟的土壤体积含水量与站点观测相比,两套数据的表现接近,与站点观测相比都存在一定的偏差,但SG更接近观测,其中在Molly Caren站点(39°57′N,83°27′W)上SG相比GSDE整体提高约0.01~0.02。本研究表明,模式模拟结果受不同土壤数据集的影响显著,可优先考虑诸如SG较准确的土壤数据。土壤属性对陆面模拟的影响需进一步研究。展开更多
A simple semi-empirical analysis method for predicting the group effect of pile group under dragload embedded in clay was described assuming an effective influence area around various locations of pile group. Various ...A simple semi-empirical analysis method for predicting the group effect of pile group under dragload embedded in clay was described assuming an effective influence area around various locations of pile group. Various pile and soil parameters such as the array of pile group, spacing of the piles (S), embedment length to diameter ratio of piles (L/D) and the soil properties such as density (γ), angle of internal friction (φ) and pile-soil interface friction coefficient (μ) were considered in the analysis. Model test for dragload of pile group on viscosity soil layer under surface load consolidation conditions was studied. The variations of dragload of pile, resistance of pile tip and the layered settlement of soil with consolidation time were measured. In order to perform comparative analysis, single pile was tested in the same conditions. The predicted group effect values of pile group under dragload were then compared with model test results carried out as a part of the present investigation and also with the values reported in literatures. The predicted values were found to be in good agreement with the measured values, validating the developed analysis method. The model test results show that negative skin friction of pile shaft will reach 80%-90% of its maximum value, when pile-soil relative displacement reaches 2 mm.展开更多
Characterization of soil hydraulic properties is important to environment management; however, it is well recognized that it is laborious, time-consuming and expensive to directly measure soil hydraulic properties. Th...Characterization of soil hydraulic properties is important to environment management; however, it is well recognized that it is laborious, time-consuming and expensive to directly measure soil hydraulic properties. This paper reviews the development of pedotransfer functions （PTFs） used as an alternative tool to estimate soil hydraulic properties during the last two decades. Modern soil survey techniques like satellite imagery/remote sensing has been used in developing PTFs. Compared to mechanistic approaches, empirical relationships between physical properties and hydraulic properties have received wide preference for predicting soil hydraulic properties. Many PTFs based on different parametric functions can be found in the literature. A number of researchers have pursued a universal function that can describe water retention characteristics of all types of soils, but no single function can be termed generic though van Cenuchten （VG） function has been the most widely adopted. Most of the reported parametric PTFs focus on estimation of VG parameters to obtain water retention curve （WRC）. A number of physical, morphological and chemical properties have been used as predictor variables in PTFs. Conventionally, regression algorithms/techniques （statistical/neurM regression） have been used for calibrating PTFs. However, there are reports of utilizing data mining techniques, e.g., pattern recognition and genetic algorithm. It is inferred that it is critical to refine the data used for calibration to improve the accuracy and reliability of the PTFs. Many statistical indices, including root mean square error （RMSE）, index of agreement （d）, maximum absolute error （ME）, mean absolute error （MAE）, coefficient of determination （r2） and correlation coefficient （r）, have been used by different researchers to evaluate and validate PTFs. It is argued that being location specific, research interest in PTFs will continue till generic PTFs are developed and validated. In future studies, improved methods will be required to extract information from the existing database.展开更多
文摘基于通用陆面模式(Common Land Model,CoLM),首次评估了两套最新的全球土壤数据集GSDE(Global Soil Dataset for Earth System Model)和SG(SoilGrids)对全球陆面过程模拟的影响。比较分析了两套数据中砂粒、粘粒、砾石、有机碳的含量和容重这五个土壤属性在全球分布上的差异以及这种差异造成的对模式估计的土壤特性参数、水力热力变量的影响。结果表明,土壤特性参数在全球的空间分布主要受土壤粒径分布(砂粒、粉粒和粘粒)影响,同时也受砾石、有机碳和容重的影响。土壤资料对全球模拟结果影响主要体现在区域差异,对水文学变量的影响(Re最大达到±100%)大于对土壤热力学变量的影响(Re<±10%),对地表辐射变量的影响较小(Re<±5%)。其中,土壤体积含水量在加拿大中部及西北部、俄罗斯东南部及中西部和澳大利亚中部地区模拟结果相差较大,总径流在低纬地区模拟结果出现较大的差异,热力学变量在非洲北部、加拿大西北部以及俄罗斯中北部的差异稍大。将模拟的土壤体积含水量与站点观测相比,两套数据的表现接近,与站点观测相比都存在一定的偏差,但SG更接近观测,其中在Molly Caren站点(39°57′N,83°27′W)上SG相比GSDE整体提高约0.01~0.02。本研究表明,模式模拟结果受不同土壤数据集的影响显著,可优先考虑诸如SG较准确的土壤数据。土壤属性对陆面模拟的影响需进一步研究。
基金Project(50679015) supported by the National Natural Science Foundation of China
文摘A simple semi-empirical analysis method for predicting the group effect of pile group under dragload embedded in clay was described assuming an effective influence area around various locations of pile group. Various pile and soil parameters such as the array of pile group, spacing of the piles (S), embedment length to diameter ratio of piles (L/D) and the soil properties such as density (γ), angle of internal friction (φ) and pile-soil interface friction coefficient (μ) were considered in the analysis. Model test for dragload of pile group on viscosity soil layer under surface load consolidation conditions was studied. The variations of dragload of pile, resistance of pile tip and the layered settlement of soil with consolidation time were measured. In order to perform comparative analysis, single pile was tested in the same conditions. The predicted group effect values of pile group under dragload were then compared with model test results carried out as a part of the present investigation and also with the values reported in literatures. The predicted values were found to be in good agreement with the measured values, validating the developed analysis method. The model test results show that negative skin friction of pile shaft will reach 80%-90% of its maximum value, when pile-soil relative displacement reaches 2 mm.
文摘Characterization of soil hydraulic properties is important to environment management; however, it is well recognized that it is laborious, time-consuming and expensive to directly measure soil hydraulic properties. This paper reviews the development of pedotransfer functions （PTFs） used as an alternative tool to estimate soil hydraulic properties during the last two decades. Modern soil survey techniques like satellite imagery/remote sensing has been used in developing PTFs. Compared to mechanistic approaches, empirical relationships between physical properties and hydraulic properties have received wide preference for predicting soil hydraulic properties. Many PTFs based on different parametric functions can be found in the literature. A number of researchers have pursued a universal function that can describe water retention characteristics of all types of soils, but no single function can be termed generic though van Cenuchten （VG） function has been the most widely adopted. Most of the reported parametric PTFs focus on estimation of VG parameters to obtain water retention curve （WRC）. A number of physical, morphological and chemical properties have been used as predictor variables in PTFs. Conventionally, regression algorithms/techniques （statistical/neurM regression） have been used for calibrating PTFs. However, there are reports of utilizing data mining techniques, e.g., pattern recognition and genetic algorithm. It is inferred that it is critical to refine the data used for calibration to improve the accuracy and reliability of the PTFs. Many statistical indices, including root mean square error （RMSE）, index of agreement （d）, maximum absolute error （ME）, mean absolute error （MAE）, coefficient of determination （r2） and correlation coefficient （r）, have been used by different researchers to evaluate and validate PTFs. It is argued that being location specific, research interest in PTFs will continue till generic PTFs are developed and validated. In future studies, improved methods will be required to extract information from the existing database.
