基于土壤质地数据估算土壤保水性能Van Genuchten参数

The van Genuchten (vG) function is often used to describe the soil water retention curve (SWRC) of unsaturated soils and fractured rock. The objective of this study was to develop a method to determine the vG model parameter m from the fractal dimension. We compared two approaches previously proposed by van Genuchten and Lenhard et al. for estimating m from the pore size distribution index of the Brooks and Corey (BC) model. In both approaches we used a relationship between the pore size distribution index of the BC model and the fractal dimension of the SWRC. A dataset containing 75 samples from the UNSODA unsaturated soil hydraulic database was used to evaluate the two approaches. The statistical parameters showed that the approach by Lenhard et al. provided better estimates of the parameter m. Another dataset containing 72 samples from the literature was used to validate Lenhard’s approach in which the SWRC fractal dimension was estimated from the clay content. The estimated SWRC of the second dataset was compared with those obtained with the Rosetta model using sand, silt, and clay contents. Root mean square error values of the proposed fractal approach and Rosetta were 0.081 and 0.136, respectively, indicating that the proposed fractal approach performed better than the Rosetta model.     

分形模型在利用颗粒分布数据评价土壤持水性质中的应用

Soil water retention characteristics are the key information required in hydrological modeling.Frac-tal models provide a practical alternative for indirectly estimating soil water retention characteristics from particle-size distribution data.Predictive capabilities of three fractal models,i.c.,Tylcr-Wheatcraft model,Rieu-Sposito model,and Brooks-Corey model,were fully evaluated in this work using experimental data from an international database and literature.Particle-size distribution data were firstly interpolated into 20 classes using a van Genuchten-type equation.Fractal dimensions of the tortuous pore wall and the pore surface were then calculated from the detailed particle-size distribution and incorporated as a parameter in fractal water retention models.Comparisons between measured and model-estimated water retention cha-racteristics indicated that these three models were applicable to relatively different soil textures and pressure head ranges.Tyler-Whcatcraft and Brooks-Corey models led to reasonable agreements for both coarse-and medium-textured soils,while the latter showed applicability to a broader texture range.In contrast,Rieu-Sposito model was more suitable for fine-textured soils.Fractal models produced a better estimation of water contents at low pressure heads than at high pressure heads.     

基于人工神经网络的数据处理和多目标群方法用土壤传递函数(PTFs)估算保水性

Pedotransfer functions(PTFs) have been developed to estimate soil water retention curves(SWRC) by various techniques.In this study PTFs were developed to estimate the parameters(θ s,θ r,α and λ) of the Brooks and Corey model from a data set of 148 samples.Particle and aggregate size distribution fractal parameters(PSDFPs and ASDFPs,respectively) were computed from three fractal models for either particle or aggregate size distribution.The most effective model in each group was determined by sensitivity analysis.Along with the other variables,the selected fractal parameters were employed to estimate SWRC using multi-objective group method of data handling(mGMDH) and different topologies of artificial neural networks(ANNs).The architecture of ANNs for parametric PTFs was different regarding the type of ANN,output layer transfer functions and the number of hidden neurons.Each parameter was estimated using four PTFs by the hierarchical entering of input variables in the PTFs.The inclusion of PSDFPs in the list of inputs improved the accuracy and reliability of parametric PTFs with the exception of θ s.The textural fraction variables in PTF1 for the estimation of α were replaced with PSDFPs in PTF3.The use of ASDFPs as inputs significantly improved α estimates in the model.This result highlights the importance of ASDFPs in developing parametric PTFs.The mGMDH technique performed significantly better than ANNs in most PTFs.     

基于土壤传递函数的土壤持水特性间接估计及其空间变异性研究

A total of 107 soil samples were taken from the city of Qingdao,Shandong Province,China.Soil water retention data at 2.5,6,10,33,100,300,and 1 500 kPa matric potentials were measured using a pressure membrane apparatus.Multiple linear regression (MLR) was used to develop pedotransfer functions (PTFs) for single point estimation and van Genuchten parameter estimation based on readily measurable soil properties,i.e.,MLR-based point (MLRP) PTF and MLR-based parametric (MLRV) PTF.The double cross-validation method was used to evaluate the accuracy of PTF estimates and the stability of the PTFs developed in this study.The performance of MLRP and MLRV PTFs in estimating water contents at matric potentials of 10,33,and 1 500 kPa was compared with that of two existing PTFs,the Rawls PTF and the Vereecken PTF.In addition,geostatistical analyses were conducted to assess the capabilities of these PTFs in describing the spatial variability of soil water retention characteristics.Results showed that among all PTFs only the Vereecken PTF failed to accurately estimate water retention characteristics.Although the MLRP PTF can be used to predict retention characteristics through traditional statistical analyses,it failed to describe the spatial variability of soil water retention characteristics.Although the MLRV and Rawls PTFs failed to describe the spatial variability of water contents at a matric potential of 10 kPa,they can be used to quantify the spatial variability of water contents at matric potentials of 33 and 1 500 kPa.     

作物根系层土壤水分模拟的经验-机理模型

To predict soil water variation in the crop root zone,a general exponential recession (GER) model was developed to depict the recession process of soil water storage.Incorporating the GER model into the mass balance model for soil water,a GER-based physicoempirical (PE-GER) model was proposed for simulating soil water variation in the crop root zone.The PE-GER model was calibrated and validated with experimental data of winter wheat in North China.Simulation results agreed well with the field experiment results,as well as were consistent with the simulation results from a more thoroughly developed soil water balance model which required more detailed parameters and inputs.Compared with a previously developed simple exponential recession (SER) based physicoempirical (PE-SER) model,PE-GER was more suitable for application in a broad range of soil texture,from light soil to heavy soil.Practical application of PE-GER showed that PE-GER could provide a convenient way to simulate and predict the variation of soil water storage in the crop root zone,especially in case of insufficient data for conceptual or hydrodynamic models.     

使用积分法估算原状土van Genuchten模型参数

The van Genuchten model is the most widely used soil water retention curve (SWRC) model. Two undisturbed soils (clay and loam) were used to evaluate the accuracy of the integral method to estimate van Genuchten model parameters and to determine SWRCs of undisturbed soils. SWRCs calculated by the integral method were compared with those measured by a high speed centrifuge technique. The accuracy of the calculated results was evaluated graphically, as well as by root mean square error (RMSE), normalized root mean square error (NRMSE) and Willmott’s index of agreement (l). The results obtained from the integral method were quite similar to those by the centrifuge technique. The RMSEs (4.61 × 10-5 for Eum-Orthic Anthrosol and 2.74 × 10-4 for Los-Orthic Entisol) and NRMSEs (1.56 × 10-4 for Eum-Orthic Anthrosol and 1.45 × 10-3 for Los-Orthic Entisol) were relatively small. The l values were 0.973 and 0.943 for Eum-Orthic Anthrosol and Los-Orthic Entisol, respectively, indicating a good agreement between the integral method values and the centrifuge values. Therefore, the integral method could be used to estimate SWRCs of undisturbed clay and loam soils.     

地膜覆盖滴灌棉田土壤上水分动态的数值模拟

Drip irrigation under plastic mulch has been widely applied in arid Northwest China as a water-saving irrigation technology.A comprehensive knowledge of the distribution and movement of soil water in root zone is essential for the design and management of irrigation regimes.Simulation models have been proved to be efcient methods for this purpose.In this study,the numerical model Hydrus -2D was used to simulate the temporal variations of soil water content in a drip irrigated cotton field under mulching.A concept of partitioning coefcient,calibrated to be 0.07,was introduced to describe the efect of plastic mulch on prevention of evaporation.The soil hydraulic parameters were optimized by inverse solution using the field data.At the optimized conditions,the model was used to predict soil water content for four field treatments.The agreements between the predictions and observations were evaluated using coefcient of determination (R2) and root mean square error (RMSE).The results suggested that the model fairly reproduced the variations in soil water content at all locations in four treatments,with R2 ranging from 0.582 to 0.826 and RMSE from 0.029 to 0.050 cm3 cm-3,indicating that the simulations agreed well with the observations.     

非饱和土壤一维水分入渗与再分布的解析解法

Soil infiltration and redistribution are important processes in field water cycle, and it is necessary to develop a simple model to describe the processes. In this study, an algebraic solution for one-dimensional water infiltration and redistribution without evaporation in unsaturated soil was developed based on Richards equation. The algebraic solution had three parameters, namely, the saturated water conductivity, the comprehensive shape coefflcient of the soil water content distribution, and the soil suction allocation coefficient. To analyze the physical features of these parameters, a relationship between the Green-Ampt model and the algebraic solution was established. The three parameters were estimated based on experimental observations, whereas the soil water content and the water infiltration duration were calculated using the algebraic solution. The calculated soil water content and infiltration duration were compared with the experimental observations, and the results indicated that the algebraic solution accurately described the unsaturated soil water flow processes.     

引入分维理论评价土壤对优势流的敏感性

Food dye Brilliant Blue was introduced as the tracer in a dye-tracing experiment to obtain dye profile patterns of sandy loam soil,aeolian sandy soil,percolating paddy soil and permeable paddy soil.The dyed soil profiles were then photographed and the photos were scanned into a computer.Edited with certain software,only the dyed areas were left on the profile photos,which indicted the preferential flow paths for water and solute transport.Fractal dimensions of the dye patterns were calculated according to Arnold‘s function.Soil particle size distribution was analyzed by pipette method.The regression analysis showed that there was significant relationship between soil clay content and fractal dimension D of the dye pattern of soil profile.Based on the experiment results,the possibility of introducing fractal dimension to estimation of soil sensitivity to preferential flow is discussed.     

沙漠非饱和风沙土壤水分特征曲线预测的分形模型

应用VanGenuchten提出的土壤水分特征曲线公式,推导出了沙漠风沙非饱和土壤水分特征曲线的分形模型。通过对古尔班通古特沙漠地9种不同土壤样本利用中子水分仪和负压计实测的水分特征曲线资料反求得到相应的分形维数,分析了分形维数与土壤质地之间的关系,结果表明随着土壤质地从流动风沙土、半固定风沙土到固定风沙土的变化,其分形维数呈逐渐增大。此外,基于土壤颗粒的重量与粒径分布求出了古尔班通古特沙漠地风沙土壤粒径的分形维数。通过对土壤水分特征曲线的分形维数与土壤粒径的分形维数的对比,得知它们之间存在着良好的线性关系。根据此关系,利用易测得的土壤粒径分形维数结合所推导的分形模型,对土壤水分特征曲线进行了预测,模型的预测结果很好地吻合了实测的土壤水分特征曲线。这一结果对于实际工作中根据风沙土壤颗粒大小分布的分形维数来预测沙漠风沙土壤水分特征曲线具有一定的指导意义。     

土壤颗粒的分形特征及其应用

本文应用土壤颗粒的质量分布原理来描述土壤颗粒的分形特征。通过对10种土壤颗粒的机械组成进行分析,分别计算出它们的分形维数（D=2.489～2.896）,并分析了其与土壤质地之间的关系。同时对土壤颗粒分形维数与所对应土壤的幂函数型水分特征曲线的拟合分形维数进行比较分析,建立了二者之间的相关关系。结果表明:分形维数的大小反映了土壤质地中粘粒、粉粒和砂粒含量的变化,随粘粒含量的增多分形维数增大,随砂粒含量的增多分形维数减小;同时土壤颗粒分形维数与所对应的水分特征曲线的拟合分形维数呈现出良好的一致性,因而对所研究的土壤而言,可应用土壤颗粒的质量分形维数结合幂函数模型来估算土壤水分特性曲线。     

土壤图像孔隙轮廓线分形特征及其应用

孔隙轮廓线分形维数是用来描述孔隙本身所具有的分形特征，它反映了土壤孔隙与固体颗粒接触界限的不规则性。该文采用数字图像处理技术研究了中国科学院封丘农业生态实验站内3种不同质地土壤样本图像的孔隙轮廓线分形特征。结果表明：土壤孔隙轮廓线分形特征与土壤质地之间存在着一定的相关关系，即土壤质地越细(黏粒含量越高)分形维数取值越大。同时，根据这3种土壤的孔隙轮廓线分形维数，结合不同分形方法分别预测了它们的水分特征曲线，并与实测的土壤水分特征曲线进行了比较。     

鲁中南山地典型植被土壤颗粒与土壤水分特征曲线的分形学特征

土壤粒径分布与水分特征曲线是土壤的重要物理性质,对土壤侵蚀状况和土壤肥力有显著影响。以鲁中南山地典型植被下土壤为研究对象,运用分形学理论研究5种典型植被土壤颗粒与水分特征曲线的分形学特征。结果表明:1)不同植被类型的土壤颗粒单重分形维数、多重分形参数和土壤水分特征曲线分形维数具有显著差异,均表现为麻栎+刺槐混交林>黑松+黄连木混交林>黑松林>核桃林>荒草地;2)土壤分形维数有林地大于荒草地,混交林大于纯林;3)土壤分形维数与黏粒体积分数、粉粒体积分数呈显著正相关,与砂粒体积分数呈显著负相关;4)土壤颗粒单重分形维数与土壤水分特征曲线分形维数呈显著的正相关关系。说明土壤颗粒分布与土壤水分特征曲线的分形参数可以作为反映土壤结构性状变化的定量指标,可利用土壤颗粒分形与土壤水分特征曲线分形维数的相关关系来描述对应的土壤水分特征曲线。研究成果可为鲁中南山地退耕还林与生态造林工程建设及其生态效益评价提供理论参考。     

土壤粒径分布单重分形与孔隙单重分形

土壤颗粒大小的分布是重要的土壤物理性质,对土壤水、气、热传导特性有着显著的影响。鉴于土壤颗粒分形在分析和描述岩土介质多孔结构的优势,本文通过对5种不同质地的土样进行颗粒分析与水分特征曲线的测试。结果表明:土壤结构定量化表征的方法就是确定土壤结构的分形维数,针对不同地区的土壤,可以通过土壤粒径分布分形维数体现土壤粒径分布的情况,分形维数越大,颗粒粒径越小,细粒含量越高,质地越发呈现不均匀性;且可利用土壤粒径分形维数估算土壤孔隙分形维数。为建立土壤粒径分布模型提供数据支持,同时也为推进土壤结构的研究进展提供了新的方向。     

灰色关联及非线性规划法构建传递函数估算黑土水力参数

土壤水分特征曲线和饱和导水率是重要的水力参数,为了简便准确获取这些参数,以松嫩平原黑土区南部为研究区域,采集136个采样点土样用于测定不同土层土壤水分特征曲线、饱和导水率以及土壤理化性质,并运用灰色关联分析确定影响土壤水力参数的主要土壤理化性质,采用非线性规划构建土壤分形维数、有机质、干容重、土壤颗粒组成与土壤水分特征曲线、饱和导水率之间的土壤传递函数,并通过与现有土壤传递函数对比分析进行精度验证。结果表明:1)土壤分形维数是估算土壤水分特征曲线模型参数和饱和导水率的主要参数之一,同时,干容重和有机质含量也在不同土层土壤传递函数中起到重要的作用;2)通过验证分析,不同土层各参数平均绝对误差接近于0,均方根误差值也都较小,其中在不同土层土壤传递函数估算的土壤含水率均方根误差分别为0.022、0.017cm~3/cm~3;3)对比分析其他已存的土壤水分特征曲线和饱和导水率的土壤传递函数,该文构建的土壤传递函数均方根误差值均较小,决定系数值都在0.66以上,表明估算精度较高,均好于其他方法估算精度,具有良好的区域适应性。综上,所构建的土壤水分特征曲线和饱和导水率土壤传递函数可以用于松嫩平原黑土区土壤水力参数估算。     

松嫩平原西部典型盐生景观土壤分形维数及盐碱化特征

为探究松嫩平原西部典型盐生景观土壤颗粒粒度组成及分形特征与土壤盐碱化之间的关系,采用体积分形维数模型计算了6种典型盐生景观土壤表层0—30 cm颗粒组成及分形维数,结合相关分析法分析了土壤分形维数与质地、盐碱特征之间的相关性。结果表明:(1)6种典型盐生景观中农田土壤分形维数值最小(2.35),碱蓬群落土壤最大(2.61),分形维数均值为2.48,分形维数随盐生景观土壤碱化程度增加而增大。(2)土壤质地越粗,砂粒含量越高,分形维数值越小;土壤质地越细,黏粒和粉粒含量越高,分形维数越大。(3)分形维数与盐分含量呈显著正相关(r=0.87,P0.05),尤其与盐分组成中HCO_3~-含量呈极显著正相关(r=0.89,P0.01),与养分中总磷含量呈极显著正相关(r=0.90,P0.01)。(4)土壤颗粒组成中砂粒、粉粒和黏粒与盐分、HCO_3~-及总磷含量也存在极显著相关性。不同盐生景观土壤分形维数与土壤颗粒组成和土壤盐分之间存在显著的相关性,因此可以用分形维数来反映土壤质地和指示土壤盐碱化特征。     

氨化秸秆还田对土壤孔隙结构的影响

【目的】土壤孔隙性质是土壤结构性的反映,直接影响着土壤的肥力和水分有效性。定量研究氨化秸秆还田对土壤不同大小等级孔隙数量和孔隙分布的影响,可以为土壤培肥提供科学依据。【方法】采用室内试验方法,设置氨化秸秆加入量为土壤总质量的 0(CK)、 0.384%(S1)、 0.575%(S2)、 0.767%(S3)4个处理,室内培养。在培养0、60、120和180 d,取样测定土壤水分特征曲线(SWRC)数据,利用双指数土壤水分特征曲线模型(DE模型,Double-exponential water retention equation),分析氨化秸秆对土壤剩余孔隙、基质孔隙和结构孔隙的影响; 基于DE模型的微分函数,探究不同氨化秸秆处理对土壤孔隙分布的影响。【结果】不同处理的土壤水分特征曲线SWRC实测值和DE模型模拟值之间的均方根误差介于0.0036和0.0041 cm3/cm3之间,R2介于0.998和0.999之间,土壤含水量模拟值和实测值非常接近1 ∶1,表明DE模型可以准确反映添加氨化秸秆后土壤含水量随吸力的变化规律,较准确地估算土壤不同大小等级孔隙数量变化。培养120 d内,氨化秸秆对土壤剩余孔隙、基质孔隙和结构孔隙影响不显著; 培养180 d时,各处理土壤结构孔隙度表现出随着氨化秸秆添加量的增加而增加的趋势; 此时S3对土壤剩余孔隙影响不显著,显著减小了土壤的基质孔隙度(P0.05),极显著地增加了土壤的结构孔隙度(P 0.01)。在孔隙分布中,氨化秸秆促进了土壤已有孔隙向较大孔隙的发育,显著增加了土壤结构孔隙分布数量; 随着氨化秸秆添加量的增加,土壤结构孔隙的分布数量越大,且峰值出现的越早。氨化秸秆增加了土壤中有机质含量; 土壤结构孔隙和总孔隙均与有机质含量呈显著的正相关关系(P 0.05); 有机质可以黏结团聚土壤的矿物颗粒,有效地促进了土壤结构孔隙的发育; 氨化秸秆对土壤孔隙的影响随着时间的进行越来越明显。【结论】氨化秸秆增加了土壤中有机质含量,促进了土壤孔隙结构的发育,增加了土壤的结构孔隙度和总孔隙度,这对改良和培肥土壤、改善土壤耕性具有重要意义。