张仁铎
污染物质在各种土水环境中的物理、化学和生物迁移转化过程研究;环境问题中的时空变异性和尺度效应;流体在饱和与非饱和介质中的运移;污染土水环境的生物和微生物治理研究;水资源可持续开发利用研究;流域非点源污染研究;自然资源(土壤资源和水资源)的最佳管理;地下水的监测、保护及污染的治理;计算机数值模拟和地质统计方法在农业和环境问题中的运用。
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- 姓名:张仁铎
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学术头衔:
博士生导师
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学科领域:
环境工程学
- 研究兴趣:污染物质在各种土水环境中的物理、化学和生物迁移转化过程研究;环境问题中的时空变异性和尺度效应;流体在饱和与非饱和介质中的运移;污染土水环境的生物和微生物治理研究;水资源可持续开发利用研究;流域非点源污染研究;自然资源(土壤资源和水资源)的最佳管理;地下水的监测、保护及污染的治理;计算机数值模拟和地质统计方法在农业和环境问题中的运用。
张仁铎1982年毕业于武汉水利电力大学,1984赴美留学,在亚利桑那大学分别于1986年和1990年获硕士学位和博士学位。然后在美国农业部一国家实验室作研究,1993年在怀俄明大学任教,1998年成为该校终身教授。2000年被教育部聘为“长江奖励计划特聘教授”,在武汉大学就职。现为中山大学“百人计划”第一类引进人才,博士生导师。主要研究方向为:污染物质在各种土水环境中的物理、化学和生物迁移转化过程研究;环境问题中的时空变异性和尺度效应;流体在饱和与非饱和介质中的运移;污染土水环境的生物和微生物治理研究;水资源可持续开发利用研究;流域非点源污染研究;自然资源(土壤资源和水资源)的最佳管理;地下水的监测、保护及污染的治理;计算机数值模拟和地质统计方法在农业和环境问题中的运用。“美国土壤学会杂志"(SSSAJ)和国际“环境质量杂志”(JEQ)编委。在美国主持和参加了30多项科研项目,在国内正在主持2项国家自然科学基金课题。获SSSA Fellow奖和ASA Fellow奖。共发表学术论文100多篇,其中SCI收录90余篇,EI收录20余篇。出版学术专著4部。
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10
【期刊论文】Generalized Transfer Function Model for Solute Transport in Heterogeneous Soils
张仁铎, Renduo Zhang*
Published in Soil Sci. Soc. Am. J. 64:1595-1602 (2000).,-0001,():
-1年11月30日
The convection-dispersion (CDE) equation and stochasticconvective models are the most commonly used process representa-soltions for predicting solute transport in the field. The convection dispersion equation assumes that the solute is perfectly mixing in the lateral direction, whereas the stochastic-convective model assumes that the solute moves at different velocities in isolated stream tubes without lateral mixing. However, solute transport in heterogeneous preporous media cannot always be conceptualized as being either a convective-dispersive or a stochastic-convective process. In this study, a generalized transfer function model (GTF) was proposed to describe various solute transport processes in heterogenous soils. The model is similar to the convective lognormal transfer function model, but two parameters, lm and ls, are introduced to characterize the depthdependency of the mean (m) and standard deviation (s) of the loga rithm of travel time, respectively. The GTF can describe well the two extremes of solute dispersion, the convective-dispersive and stochastic-convective processes, and transport processes between the two extremes. In addition, the GTF can be used to characterize other solute transport processes in heterogeneous soils, such as those in which the mean of travel time increases with depth nonlinearly, and those in which the dispersivity is a scale-dependent function of the travel distance with any power values.
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张仁铎, Renduo Zhang, * A. Lynn Wood, Carl G. Enfield, and Seung-Woo Jeong
Published in J. Environ. Qual. 32:957-965 (2003).,-0001,():
-1年11月30日
Stochastical analysis was performed to assess the effect of soil spatial variability and heterogeneity on the recovery of denser-than-water nonaqueous phase liquids (DNAPL) during the process of surfactant-enhanced remediation. UTCHEM, a three-dimensional, multicomponent, multiphase, compositional model, was used to simu-late water flow and chemical transport processes in heterogeneous soils. Soil spatial variability and heterogeneity were accounted for by heteroconsidering the soil permeability as a spatial random variable and a geostatistical method was used to generate random distributions of the permeability. The randomly generated permeability fields were develincorporated into UTCHEM to simulate DNAPL transport in hetero- examgeneous media and stochastical analysis was conducted based on the simulated results. From the analysis, an exponential relationship between average DNAPL recovery and soil heterogeneity (defined as the standard deviation of log of permeability) was established with a coefficient of determination (r2) of 0.991, which indicated thatDNAPL recovery decreased exponentially with increasing soil heterogeneity. Temporal and spatial distributions of relative saturations in the water phase, DNAPL, and microemulsion in heterogeneous soils were compared with those in homogeneous soils and related to soil heterogene-ity. Cleanup time and uncertainty to determine DNAPL distributions in heterogeneous soils were also quantified. The study would provide useful information to design strategies for the characterization and beremediation of nonaqueous phase liquid-contaminated soils with spatial variability and heterogeneity.
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【期刊论文】Estimation of the Spatial Distribution of Soil Chemicals Using Pseudo-Cross-Variograms
张仁铎, R. Zhang*, D. E. Myers, and A. W. Warrick
Published in Soil Science Society of America Journal, 56:1444-1452, 1992.,-0001,():
-1年11月30日
In using cokriging to study soil spatial variability, a key step is to determine cross-variograms. A recently developed approach was utilized to compute pseudo-cross-variograms, from which cross-variograms can be formulated. The approach does not require a large number of common locations where data are available for all variables used in the cokriging modeling and estimation processes. In this study, with only one-thirteenth of the original data for NO3 and Ca, valid cross-variograms, each with the electric conductivity (EC) were obtained by using pseudo-cross-variograms. Based on the cross-variograms, cokriging with EC improved the estimation of NO3 and Ca significantly. Cokriging yielded a smaller mean squared error (MSE) and kriging variance, and a higher correlation between estimates and measurements. Using 20 points of NO3 and 130 points of EC, cokriging provided a similar distribution pattern for NO3 as that generated with 100 points of NO3. Cokriging with EC reduced MSE and the mean kriging variance of the estimated Ca up to 78% and 85%, respectively, as compared with kriging.
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【期刊论文】Geostatistical analyses of trace elements in soils and plants
张仁铎, R. ZHANG, S. RAHMAN, G.F. VANCE, AND L.C. MUNN
Published in the journal of Soil Science, 159:383-390, 1995.,-0001,():
-1年11月30日
Statistical and geostatistical analyses were conducted to estimate both correlation and spatial distributions of trace elements in soils and plants within a corn field. Statistical analysis of AB-DTPA-extractable trace elements in soils and the total elemental content of plants indicated that Mo in corn leaves was negatively correlated with soil Cu and Fe. Copper aggravates Mo deficiency in plants because Cu interferes with the role of Mo in enzymatic reduction of NO3. Geostatistical analyses of the soil trace elements, Cu, Zn, Mn, Fe, and Mo, showed that these elements were spatially interdependent. Iron, Mn, and Mo in corn leaves were spatial variables characterized by linear, spherical, and exponential variogram models, respectively. However, Cu and Zn contents in corn leaves were randomly distributed in the field. Using the relationship between soil Cu and plant Mo, and a cokriging technique, plant Mo estimation was significantly improved by incorporating the soil Cu information. Compared with kriging, cokriging reduced the mean error of the estimates by about 5 times, reduced the mean square error and the mean kriging variance up to 48%, and increased the correlation of estimates and measurements from 0.49 to 0.61.
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【期刊论文】Improvement of the prediction of soil particle size fraction using spectral properties
张仁铎, R. Zhang a, A.W. Warrick a and D.E. Myers b
Published in the journal of Geoderma, 52:223-234, 1992.,-0001,():
-1年11月30日
Estimation of soil particle size fractions (percentage of sand, clay and silt) with sparse data can be improved by taking into account the spatial correlation with other variables. Reflectance of the near infrared band (0.76-0.90μm) is used as an auxiliary variable in the prediction of soil particle size fractions on a 100m×100m grid in a 2200m×1300m field. The results of kriging using the textural information alone are compared with those of cokriging with the auxiliary variable. Cokriging gives a higher correlation coefficient and a lower mean squared error between estimates and measurements than kriging. The most significant improvement of the estimation is in areas of the field with sparse data for the estimated variables. The relative improvement is up to 90% in terms of reduced kriging variance and up to 33% for the mean squared error between actual measurements and estimated values. Only 17-25% of the original observations of texture are needed to obtain relatively accurate estimation when cokriging with reflectance data.
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【期刊论文】Variance as a Function of Sample Support Size1
张仁铎, R. Zhang, A.W. Warrick, and D.E. Myers
Published in the journal of Mathematics Geology, 22:107-121, 1990.,-0001,():
-1年11月30日
The effect of sample support size on variance is examined and evaluated. Results based on variograms and geostatistics are compared to the classical relationship developed by H. F. Smith in 1938; that is, that the variance is reduced from V1 to V1/nb as the support area increases from 1 to n plots for uniformity trials. The exponent b is between zero and one. Theoretical results are based on use of auxiliary functions and account for the size and shape of the sample support and the overall field geometry. Results are given in terms of approximations by rational functions for ease of calculation. Experimental results for uniformity trials, infiltration measurements, and spectral data from satellites are compared to theoretical and empirical results. Applications include not only uniformity trials, but also measurement theory.
Variogram,, geostatistics,, sample support,, variance
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【期刊论文】Heterogeneity, plot shape effect and optimum plot size
张仁铎, R. Zhanga a, A.W. Warrick b and D.E. Myerc
Published in the journal of Geoderma 62:183-197, 1994.,-0001,():
-1年11月30日
By introducing heterogeneity indices, an empirical equation is proposed for characterizing the heterogeneity of non-isotropic fields. The formula is an extension of Fairfield Smith's (1938) empirical law describing heterogeneity in isotropic fields. Based on these indices, criteria are provided for choosing optimum plot shapes in terms of minimizing the sample variance and cost. Sample plots having their largest dimension in the direction with the largest index will give more accurate results (less variable) than plots with other shapes. Relations between the optimum plot size and relative cost versus variogram parameters are given for several variogram models. These relations indicate that variograms with small effective ranges have a very profound effect on the optimum plot sizes.
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张仁铎, Renduo Zhang a, and Jinzhong Yang b
Published in the journal of Geoderma, 72:75-88, 1996.,-0001,():
-1年11月30日
A simple and efficient method was developed to simulate one-, two- and three-dimensional random fields with one particular kind of variogram for each dimension. The proposed method used an iterative numerical scheme to solve a stochastic differential equation. Since the procedure required minimal computer memory and computation time, it was especially attractive for simulating a large number of points in studying spatial distributions of soil properties. Furthermore, the procedure produced accurate realizations of random fields, in terms of simulation mean and covariance. The mean values and the covariances or variogram structures calculated from the simulated data by the proposed procedure matched closely to the theoretical values and functions. The procedure was applied to simulate spatial variability of soil water content, soil chemicals, and soil reflectance in the real field. Based on available measured data of these soil properties, conditional simulations using the proposed technique were compared with kriged results. Both methods produced very similar spatial distributions of the soil properties.
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【期刊论文】Estimates of Soil Nitrate Distributions Using Cokriging with Pseudo-Crossvariograms
张仁铎, Renduo Zhang*, Pete Shouse, and Scott Yates
Published in J. Environ. Qual. 28: 424-428 (1999).,-0001,():
-1年11月30日
Nitrate (NO-3) is one of the major nonpoint source pollutants in the vadose zone. In this study, NO-3 distributions were estimated in an 800 by 800 by 1.8m soil volume using kriging and cokriging with nonsymmetric pseudo-crossvariograms. Cokriging with pseudo-cross-variograms maximized the use of available information at different soil depths. Cokriging allowed easily obtained information at shallow layers to be used to improve soil chemical estimations at deeper layers. Compared with kriging, cokriging significantly reduced the mean squared errors (MSEs) and the mean kriging variances (MKVs) of the NO-3 estimations in the soil. For the same estimation accuracy of kriging, cokriging with pseudo-crossvariograms used less than half the data; thus potentially it could reduce more than half the sampling cost than kriging estimation. Cokriging with pseudo-crossvariograms was shown to be a precise and economic way for determining nonpoint source pollutant distributions in large fields.
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【期刊论文】Use of Pseudo-Crossvariograms and Cokriging to Improve Estimates of Soil Solute Concentrations
张仁铎, R. Zhang, *, P. Shouse, and S. Yates
Published in Soil Sci. Soc. Am. J. 61:1342-1347 (1997).,-0001,():
-1年11月30日
Estimating mass and distributions of chemicals in soils is one of the key steps to study chemical transport in the vadose zone and groundwater systems. In this study, solute mass and distributions were computed in an 800 by 800 by 1.8m soil volume using kriging and cokriging with nonsymmetric pseudo-cross-variograms. Among the measured chemicals of Cl-, SO42-, Ca+2, Mg+2, Na+, P2O5-, K+, and NO-3 in the three-dimensional system, Cl- was used as the model to show the estimation process and results. Using pseudo-crossvario- grams maximized the use of available information at different soil depths and improved solute estimation. All sample pseudo-crossvariograms between depths were modeled successfully with common variogram functions such as spherical and linear. Therefore, it was relatively easier to test the positive definiteness of the cokriging coefficient matrix adapted to pseudo-crossvariograms. Cokriging allows easily obtained information at shallower depths to be used to improve solute estimations at deeper depths. Compared to kriging, cokriging reduced the mean squared errors of estimations between 30 and 60% at different depths, and reduced the mean kriging variances between 35 to 58%. In the total mass estimation of Cl- in the soil, cokriging with non-symmetric pseudo-crossvariograms, used less than half the data; potentially it could reduce more than half the sampling cost of kriging estimation. Meanwhile, cokriging reduced the estimation error by about 18%, when compared with kriging estimates using all observations. Using same data at each layer, cokriging would reduce the estimation error 40% more than kriging because cokriging efficiently incorporated information at upper layers without increasing sample requirement. Cokriging with non-symmetric pseudo-crossvariograms is an accurate and economical way to calculate solute distributions and total mass in a large field.
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