苏打盐碱水灌溉的土壤添加石膏肥和有机肥后水溶性碳和微生物碳研究

Microbial biomass carbon (MBC), a small fraction of soil organic matter, has a rapid turnover rate and is a reservoir of labile nutrients. The water-extractable carbon pools provide a fairly good estimate of labile C present in soil and can be easily quantified. Changes in soil MBC and water-extractable organic carbon pools were studied in a 14-year long-term experiment in plots of rice-wheat rotation irrigated with canal water (CW), sodic water (SW, 10-12.5 mmol c L-1 residual sodium carbonate), and SW amended with gypsum with or without application of organic amendments including farmyard manure (FYM), green manure (GM), and wheat straw (WS). Irrigation with SW increased soil exchangeable sodium percentage by more than 13 times compared to irrigation with CW. Sodic water irrigation significantly decreased hot water-extractable organic carbon (HWOC) from 330 to 286 mg kg-1 soil and cold water-extractable organic carbon (CWOC) from 53 to 22 mg kg-1 soil in the top 0-7.5 cm soil layer. In the lower soil layer (7.5-15 cm), reduction in HWOC was not significant. Application of gypsum alone resulted in a decrease in HWOC in the SW plots, whereas an increase was recorded in the SW plots with application of both gypsum and organic amendments in both the soil layers. Nevertheless, application of gypsum and organic amendments increased the mean CWOC as compared with application of gypsum alone. CWOC was significantly correlated with MBC but did not truly reflect the changes in MBC in the treatments with gypsum and organic amendments applied. For the treatments without organic amendments, HWOC was negatively correlated with MBC (r = 0.57*) in the 0-7.5 cm soil layer, whereas for the treatments with organic amendments, both were positively correlated. Irrigation with SW significantly reduced the rice yield by 3 t ha-1 and the yield of rice and wheat by 5 t ha-1 as compared to irrigation with canal water. Application of amendments significantly increased rice and wheat yields. Both the rice yield and the yield of rice and wheat were significantly correlated with MBC (r = 0.49**-0.56**, n = 60). HWOC did not exhibit any relation with the crop yields under the treatments without organic amendments; however, CWOC showed a positive but weak correlation with the crop yields. Therefore, we found that under sodic water irrigation, HWOC or CWOC in the soils was not related to MBC.     

从连续的粒径大小分布数据估算土壤水分特征曲线

Soil moisture characteristic curve (SMC) is a fundamental soil property and its direct measurement is tedious and time consuming. Therefore, various indirect methods have been developed to predict SMC from particle-size distribution (PSD). However, the majority of these methods often yield intermittent SMC data because they involve estimating individual SMC points. The objectives of this study were 1) to develop a procedure to predict continuous SMC from a limited number of experimental PSD data points and 2) to evaluate model predictions through comparisons with measured values. In this study, an approach that allowed predicting SMC from the knowledge of PSD, parameterized by means of the closed-form van Genuchten model (VG), was used. Through using Mohammadi and Vanclooster (MV) model, the parameters obtained from fitting of VG to PSD data were applied to predict SMC curves. Since the residual water content (θ r ) could not be obtained through fitting of VG-MV integrated model to PSD data, we also examined and compared four different methods estimating θ r . Results showed that the proposed equation (MV-VG integrated model) provided an excellent fit to all the PSD data and the model could adequately predict SMC as measured in forty-two soils sampled from different regions of Iran. For all soils, the method in which θ r was obtained through parameter optimization procedure provided the best overall predictions of SMC. The two methods estimating θ r with Campbell and Shiozawa (CS) model resulted in less accuracy than the optimization procedure. Furthermore, the proposed model underestimated the moisture content in the dry range of SMC when the value of θ r was assumed to equal zero. θ r could be attributed to the incomplete desorption of water coated on soil particles and the accurate estimation of θ r was critical in prediction of SMC, especially for fine-textured soils at high suction heads. It could be concluded that the advantages of our approach were the continuity, robustness, and independency of model performance on soil type, allowing to improve predictions of SMC from PSD at the field and watershed scales.     

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.     

土壤类型和容重对离心机法测定土壤水分特征曲线的影响

本研究以杨凌塿土和嫩江黑土为研究对象,分别设置了4个土壤容重处理(1.0、1.1、1.2、1.3 g/cm³),利用离心机法测定土壤失水过程,以压力膜仪法为标准,对比不同吸力下的含水量实测值和van Genuchten模型参数的差异。结果表明,随着土壤容重的增加,离心机法测定土壤水分特征曲线准确度逐渐增加,获取黑土和塿土的van Genuchten模型参数α的准确度增幅分别为38.46% ~ 83.08% 和56.38% ~ 95.75%。离心机法测定土壤水分特征曲线的准确度在不同吸力段表现不同,近饱和段(0 ~ 10 kPa)离心机法测定值偏低,而高吸力段(10 ~ 1 500 kPa)测定值偏高,且高吸力段离心机法测定准确度较低,与压力膜仪法测定值具有极显著差异(P<0.01)。综上所述,为了提高离心机法测定土壤水分特征曲线的准确度,优先考虑应用于大容重和高有机质含量的土壤。     

黄淮海地区典型农业土壤中六六六(HCH)和滴滴涕(DDT)的残留量研究 Ⅱ.空间分布及垂直分布特征

主要研究了黄淮海地区7个县的典型农业土壤中六六六(HCH)和滴滴涕(DDT)在每个县的空间分布特征,及其在4个土壤剖面的垂直分布模式。空间分布图表明,HCHS(HCHS=-αHCH -βHCH γ-HCH -δHCH)和DDXS(DDXS=4,4-′DDE 4,4-′DDD 2,4-′DDT 4,4-′DDT)各浓度在每个县的分布基本上是随机的,DDT的变异性大于HCH。DDXS浓度超过国家规定的土壤环境质量一级标准(50μg kg-1)的区域集中在禹城县的东部。该研究同时表明在制定具体的土壤有机氯农药管理措施前研究它们的空间变异性的必要性。HCHS在剖面30 cm以下的含量水平与表层相似,其异构体中以-βHCH的含量最高;而DDXS则主要集中在土表0~30 cm,大于30 cm深度其值显著降低或低于检测限。结果表明在官方禁用20多年后,HCH和DDT在黄淮海地区0~100 cm土壤剖面的含量在绝大部分地点已经降至安全水平。     

4种湿地植物根系泌氧由根诱导的pH,Eh和Fe(II)变化和根际土壤中铅和锌的组分研究

A rhizobox experiment was conducted to compare iron (Fe) oxidation and changes of pH, redox potential (Eh) and fractions of zinc (Zn) and lead (Pb) in rhizosphere and non-rhizosphere soils of four emergent-rooted wetland plants (Echinodorus macrophyllus, Eleocharis geniculata, Hydrocotyle vulgaris and Veronica serpyllifolia) with different radial oxygen loss (ROL) from roots. The results indicated that all these wetland plants decreased pH and concentration of Fe(Ⅱ) but increased the Eh in the rhizosphere soils. Pb and Zn were transformed from unstable fractions to more stable fractions in the rhizosphere soils, so decreasing their potential metal mobility factors (MF). Among the four plants, E. macrophyllus, with the highest ROL and root biomass, possessed the greatest ability in formation of Fe plaque and in the reduction of heavy metal MFs in the rhizosphere soil. Wetland plants, with higher ROLs and root biomass, may thus be effective in decreasing potential long-term heavy metal bioavailabilities.     

长江三角洲地区土壤环境质量与修复研究Ⅰ.典型污染区农田土壤中多氯代二苯并二噁英/呋喃(PCDD/Fs)组成和污染的初步研究

通过同位素稀释高分辨率气相色谱-质谱方法(HRGC/HRMS)对长江三角洲地区某典型污染区农田土壤中多氯代二苯并二噁英(PCDDs)/呋喃(PCDFs)组成、含量及毒性当量进行了初步研究.结果表明,该地区农田土壤中PCDD/Fs总含量的平均值达2 639.1pg g-1dw,并检测出PCDD/Fs的四氯～八氯多种异构体.根据世界卫生组织毒性当量(TEQ,哺乳动物)计算结果显示,农田土壤中PCDD/Fs的毒性当量为TEQ20.8～21.3pg g-1 dw,超过加拿大国家居住环境土壤二噁英含量控制标准的5倍多,其中2,3,4,7,8-PCDF和1,2,3,7,8-PCDD对PCDD/Fs的TEQ值贡献最大.该地区农田土壤中已经出现一定程度的二噁英/呋喃污染.     

Pedotransfer functions for estimating soil water retention curve of Sicilian soils

Pedotransfer functions (PTFs) make use of routinely surveyed soil data to estimate soil properties but their application to soils different from those used for their development can yield inaccurate estimates. This investigation aimed at evaluating the water retention prediction accuracy of eight existing PTFs using a database of 217 Sicilian soils exploring 11 USDA textural classes. PTFs performance was assessed by root mean square differences (RMSD) and average differences (AD) between estimated and measured data. Extended Nonlinear Regression (ENR) technique was adopted to recalibrate or develop four new PTFs and Wind’s evaporation method was applied to validate the effectiveness of the relationships proposed. PTFs evaluation resulted in RMSD and AD values in the range 0.0630–0.0972 and 0.0021–0.0618 cm³ cm^–3, respectively. Best and worst performances were obtained respectively by PTF-MI and PTF-ZW. ENR allowed to recalibrate PTF-MI and PTF-ZW with improvements of RMSD (0.0594 and 0.0508 cm³ cm^–3) and to develop two relationships that improved RMSD by 75–78% as compared to PTF-MI. The results confirmed the potential of ENR technique in calibrating existing PTFs or developing new ones. Validation conducted with an independent dataset suggested that recalibrated/developed PTFs represent a viable alternative for water retention estimation of Sicilian soils.     

Evaluation of pedotransfer functions for estimating the soil water retention points

Direct measurement of soil moisture has been often expensive and time-consuming. The aim of this study was determining the best method to estimate the soil moisture using the pedotransfer functions in the soil par2 model. Soil samples selected from the database UNSODA in three textures include sandy loam, silty loam and clay. In clay soil, the Campbell model indicated better results at field capacity (FC) and wilting point (WP) with RMSE = (0.06, 0.09) and d = (0.65, 0.55) respectively. In silty loam soil, the Epic model had accurate estimation with MBE = 0.00 at FC and Campbell model had the acceptable result of WP with RMSE = 0.03 and d = 0.77. In sandy loam, Hutson and Campbell models had a better result to estimation the FC and WP than others. Also Hutson model had an acceptable result to estimation the TAW (Total Available Water) with RMSE = (0.03, 0.04, 0.04) and MBE = (0.02, 0.01, 0.01) for clay, sandy loam and silty loam, respectively. These models demonstrate the moisture points had the internal linkage with the soil textures. Results indicated that the PTFs models simulate the agreement results with the experimental observations.     

估计太湖地区水稻土水分特征曲线的物理-经验方法研究

为寻求适于太湖地区水稻土水分特征曲线估算的简便方法,本文以实测土壤基本性质和土壤水分特征曲线为基础,对13种物理-经验方法估计土壤水分特征曲线的效果进行综合评价。结果表明,基于形状相似性的物理-经验方法预测效果要优于多数分形方法,但均差于基于Kravchenko-Zhang分维方法和B rooks-Corey水分特征曲线方程的孔隙表面分形模型(简称KZBC模型)。物理-经验方法在不同压力水头段对含水量的预测精度有差异,在实际工作中不仅要考虑模型的适用性,还要考虑其适用的压力水头范围。KZBC模型估计土壤水分特征曲线精度最高,实用性也较强,是适用于本研究区水分特征曲线估计的最佳方法。     

土壤水分特征曲线的分形模拟

Many empirical models have been developed to describe the soil water retention curve （SWRC）. In this study, a fractal model for SWRC was derived with a specially constructed Menger sponge to describe the fractal scaling behavior of soil; relationships were established among the fractal dimension of SWRC, the fractal dimension of soil mass, and soil texture; and the model was used to estimate SWRC with the estimated results being compared to experimental data for verification. The derived fractal model was in a power-law form, similar to the Brooks-Corey and Campbell empirical functions. Experimental data of particle size distribution （PSD）, texture, and soil water retention for 10 soils collected at different places in China were used to estimate the fractal dimension of SWRC and the mass fractal dimension. The fractal dimension of SWRC and the mass fractal dimension were linearly related. Also, both of the fractal dimensions were dependent on soil texture, i.e., clay and sand contents. Expressions were proposed to quantify the relationships. Based on the relationships, four methods were used to determine the fractal dimension of SWRC and the model was applied to estimate soil water content at a wide range of tension values. The estimated results compared well with the measured data having relative errors less than 10% for over 60% of the measurements. Thus, this model, estimating the fractal dimension using soil textural data, offered an alternative for predicting SWRC.     

Point pedotransfer functions for prediction of water retention of selected soil series in a semi-arid region of western Iran

This study was conducted to derive point pedotransfer functions (PPTFs) for soil water retention (SWR) in western Iran. Topsoil and subsoil of 63 soil series, which were representative of different regions of Hamadan province, were sampled. Soil water retention was determined by the sand box and pressure plate at matric suctions (h _m) of 0, 1, 2, 5, 10, 25, 50, 100, 200, 500, 1000 and 1500 kPa. PPTFs were derived through multiple linear regressions for the topsoils and subsoils. These used particle size distribution, bulk density, organic matter, calcium carbonate and gravel contents as easily-available inputs. To increase the accuracy of the PPTFs, saturated water content was also included as an input variable in a group of PPTFs but they are not better as assessed using the Akaike Information Criterion. All of the PPTFs were statistically significant (p < 0.001) and could be used to predict the SWR. The absolute effect of bulk density on the SWR diminished as h _m increased. Bulk density decreased the SWR for low h _m and increased it for high h _m. In the wet range, organic matter increased the SWR. Clay and silt increased SWR whereas gravel decreased it. The effect of calcium carbonate on SWR was negligible.     

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.     

Performance of pedotransfer functions in predicting soil water characteristics of soils in Norway

Abstract

Pedotransfer functions (PTFs), predicting the soil water retention curve (SWRC) from basic soil physical properties, need to be validated on arable soils in Norway. In this study we compared the performance of PTFs developed by Riley (1996), Rawls and Brakensiek (1989), Vereecken et al. (1989), Wösten et al. (1999) and Schaap et al. (2001). We compared SWRCs calculated using textural composition, organic matter content (SOM) and bulk density as input to these PTFs to pairs of measured water content and matric potential. The measured SWRCs and PTF input data were from 540 soil horizons on agricultural land in Norway. We used various statistical indicators to evaluate the PTFs, including an integrated index by Donatelli et al. (2004). The Riley PTFs showed good overall performance. The soil specific version of Riley is preferred over the layer specific, as the latter may introduce a negative change in water content with increasing matric potential (h). Among the parameter PTFs, Wösten's continuous PTF showed the overall best performance, closely followed by Rawls&B and Vereecken. The ANN-based continuous PTF of Schaap showed poorer performance than its regression based counterparts. Systematic errors related to both particle size and SOM caused the class PTFs to perform poorly; these PTFs do not use SOM as input, and are therefore inappropriate for soils in Norway, being highly variable in SOM. The PTF performance showed little difference between soil groups. Water contents in the dry range of the SWRC were generally better predicted than water contents in the wet range. Pedotransfer functions that included both SOM and measured bulk density as input, i.e. Wösten, Vereecken and Rawls&B, performed best in the wet range.