草覆盖影响了沙地土壤的水文物理学参数和水流的异质性

Vegetation cover has a major effect on water flow in soils.Two sites,separated by distance of about 50 m,were selected to quantify the influence of grass cover on hydrophysical parameters and heterogeneity of water flow in a sandy soil emerging during a heavy rain following a long hot,dry period.A control soil(pure sand)with limited impact of vegetation or organic matter was obtained by sampling at 50 cm depth beneath a glade area,and a grassland soil was covered in a 10 cm thick humic layer and colonised by grasses.The persistence of water repellency was measured using the water drop penetration time test,sorptivity and unsaturated hydraulic conductivity using a mini disk infiltrometer, and saturated hydraulic conductivity using a double-ring infiltrometer.Dye tracer experiments were used to assess the heterogeneity of water flow,and both the modified method for estimating effective cross section and an original method for assessing the degree of preferential flow were used to quantify this heterogeneity from the images of dyed soil profiles.Most hydrophysical parameters were substantially different between the two surfaces.The grassland soil had an index of water repellency about 10 times that of pure sand and the persistence of water repellency almost 350 times that of pure sand. Water and ethanol sorptivities in the grassland soil were 7% and 43%,respectively,of those of the pure sand.Hydraulic conductivity and saturated hydraulic conductivities in the grassland soil were 5% and 16%of those of the pure sand, respectively.Dye tracer experiments revealed a stable flow with"air-draining"condition in pure sand and well-developed preferential flow in grassland soil,corresponding to individual grass tussocks and small micro-depressions.The grassland soil was substantially more water repellent and had 3 times the degree of preferential flow compared to pure sand.The results of this study reinforce our view that the consequences of any change in climate,which will ultimately influence hydrology,will be markedly different between grasslands and bare soils.     

单环压力渗透仪两个积水深度程序的数值模拟及试验验证

The two-ponding depth （TPD） analysis procedure of single-ring infiltrometer data can yield invalid results, i.e., negative values of the field-saturated soil hydraulic conductivity or the matric flux potential, denoting failure of the two-level run. The objective of this study was to test the performance of the TPD procedure in analyzing the single-ring infiltrometer data of different types of soils. A field investigation carried out in western Sici]y, Italy, yielded higher failure rates （40%） in two clay loam soils than in a sandy loam soil （25%）. A similar result, i.e., fine-textured soils yielding higher failure rates than the coarse-textured one, was obtained using numerically simulated infiltration rates. Soil heterogeneity and reading errors were suggested to be factors determining invalid results in the field. With the numerical data, allowing a less generic definition of soil heterogeneity, invalid TPD results were occasionally obtained with the simultaneous occurrence of a high random variation （standard deviation ≥ 0.5） and a well developed structural correlation for saturated hydraulic conductivity （correlation length 〉 20 cm）. It was concluded that a larger number of replicated runs should be planned to characterize fine-textured soils, where the risk to obtain invalid results is relatively high. Large rings should be used since they appeared more appropriate than the small ones to capture and average soil heterogeneity. Numerical simulation appeared suitable for developing improved strategies of soil characterization for an area of interest, which should also take into account macropore effects.     

Hydrological Responses and Flow Pathways in an Acrisol on a Forested Hillslope with a Monsoonal Subtropical Climate

The nature of subsurface flow depends largely on hydraulic conductivity of the vadoze zone, permeability of the underlying bedrock, existence of soil layers differing in hydraulic properties and macropore content, soil depth, and slope angle.Quantification of flow pathways on forested hillslopes is essential to understand hydrological dynamics and solute transport patterns.Acrisols, with their argic Bt horizons, are challenging in this respect.To further elucidate flow pathways of water and short-term variability of soil moisture patterns in Acrisols, a field study was conducted on a forested hillslope in a sub-catchment of the Tie Shan Ping(TSP)watershed, 25 km northeast of Chongqing City, China.This catchment is covered by a mixed secondary forest dominated by Masson pine(Pinus massoniana).Soil saturated hydraulic conductivity(K sat) was significantly reduced at the interface between the AB and Bt horizons(2.6 × 10~(-5) vs.1.2 × 10~(-6) m s~(-1)), which led to that the flow volume generated in the Bt horizon was of little quantitative importance compared to that in the AB horizon.There was a marked decrease in porosity between the OA and AB horizons, with a further decrease deeper in the mineral subsoil.Especially, the content of soil pores 300 μm was higher in the AB horizon(14.3%)than in the Bt horizon(6.5%).This explained the difference in soil K sat values.This study showed that Bt horizon had limited water transport capability, forcing part of the infiltrated rainwater as interflow through the OA and AB horizons.Thus, the topsoil responded quickly to rainfall events, causing frequent cycles of saturation and aeration of soil pores.     

可耕种坡地的土壤水力参数非均质性变化

The spatial variations of the soil hydraulic properties were mainly considered in vertical direction. The objectives of this study were to measure water-retention curves, θ（ψ）, and unsaturated hydraulic conductivity functions, K（ψ）, of the soils sampled at different slope positions in three directions, namely, in vertical direction, along the slope and along the contour, and to determine the effects of sampling direction and slope position of two soil catenas. At the upper slope positions, the surface soils （0-10 cm） sampled in the vertical direction had a lower soil water content, 0, at a certain soil water potential （-1 500 kPa 〈 ψ 〈 -10 kPa） and had the greatest unsaturated hydraulic conductivity, K, at ψ 〉 -10 kPa. At the lower slope positions, K at ψ〉 -10 kPa was smaller in the vertical direction than in the direction along the slope. The deep soils （100 110 cm） had similar soil hydraulic properties in all the three directions. The anisotropic variations of the hydraulic properties of the surface soils were ascribed to the effects of natural wetting and drying cycles on the structural heterogeneity. These results suggested that the anisotropy of soil hydraulic properties might be significant in influencing soil water movement along the slope and need to be considered in modeling.     

基于地形属性使用回归, 克里格和人工神经网络方法估算饱和导水率空间分布

Several methods,including stepwise regression,ordinary kriging,cokriging,kriging with external drift,kriging with varying local means,regression-kriging,ordinary artificial neural networks,and kriging combined with artificial neural networks,were compared to predict spatial variation of saturated hydraulic conductivity from environmental covariates.All methods except ordinary kriging allow for inclusion of secondary variables.The secondary spatial information used was terrain attributes including elevation,slope gradient,slope aspect,profile curvature and contour curvature.A multiple jackknifing procedure was used as a validation method.Root mean square error (RMSE) and mean absolute error (MAE) were used as the validation indices,with the mean RMSE and mean MAE used to judge the prediction quality.Prediction performance by ordinary kriging was poor,indicating that prediction of saturated hydraulic conductivity can be improved by incorporating ancillary data such as terrain variables.Kriging combined with artificial neural networks performed best.These prediction models made better use of ancillary information in predicting saturated hydraulic conductivity compared with the competing models.The combination of geostatistical predictors with neural computing techniques offers more capability for incorporating ancillary information in predictive soil mapping.There is great potential for further research and development of hybrid methods for digital soil mapping.     

土壤物理性质对供水能力的影响

The water-supplying capacity of two agricltural soils red soil in Jiangxi Province and meadow sol in Henan Province,was assessed mainly using physical investigations.The reticulated mottling horizon in the red soil was a horizon limiting roots distribution due to its high density and hardness in structure and low pH(pH5.05),The reistance of the red soil to drought hazard was poor because of its low water-supply capacity and poor hydraulic conductivity.The meadow soil had superior profile infiltration to that of the red soil and great available water-storage capacity,which resulted in low run-off loss,espectially in the wheat-growth season.It was difficult for water stored in the deep layers of the meadow soil to reach the surface due to the low unsaturated hydraulic conductivity of its clay-rich horizon in subsoil,Howver,water stored in deep layers was still available because the roots could extend to the deep layers due to the relatively low density in soil structure.     

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.     

模拟降雨条件下土壤结皮的发展和聚丙烯酰胺对黄土上结皮形成的影响

This study evaluated the morphological characteristics and dynamic variation in characteristics of soil crust and iden-tified the relationships between soil crust and splash erosion under simulated rainfall.The effect of polyacrylamide (PAM) on soil aggregate stabilization and crust formation was also investigated.A laboratory rainfall simulation experiment was carried out using soil sample slices.The slices were examined under a polarized light microscopy and a scanning electron microscope (SEM).The results revealed that the soil crusts were thin and were characterized by a greater density,higher shear strength,finer porosity,and lower saturated hydraulic conductivity than the underlying soil.Two types of crusts,i.e.,structural and depositional crusts,were observed.Soil texture was determined to be the most important soil variable influ-encing surface crust formation;depositional crust formation was primarily related to the skeleton characteristics of the soil and happened when the soil contained a high level of medium and large aggregates.The crust formation processes observed were as follows:1) The fine particles on the soil surface became spattered,leached,and then rough in response to raindrop impact and 2) the fine particles were washed into the subsoil pores while a compact dense layer concurrently formed at soil surface due to the continual compaction by the raindrops.Therefore,the factors that influenced structural crust formation were a large amount of fine particles in the soil surface,continual impact of raindrops,dispersion of aggregates into fine particles,and the formation of a compact dense layer concurrently at the soil surface.It was concluded that the most important factor in the formation of soil crusts was raindrop impact.When polyacrylamide (PAM) was applied,it restored the soil structure and greatly increased soil aggregate stabilization.This effectively prevented crust formation.However,this function of PAM was not continuously effective and the crust reformed with long-term rainfall.In conclusion,this study showed that soil micromorphological studies were a useful method for evaluating soil crust formation.     

依据传统土壤数据应用数字土壤制图法对香港山地地区土壤建立土纲信息

Based on legacy soil data from a soil survey conducted recently in the traditional manner in Hong Kong of China, a digital soil mapping method was applied to produce soil order information for mountain areas of Hong Kong. Two modeling methods (decision tree analysis and linear discriminant analysis) were used, and their applications were compared. Much more eflort was put on selecting soil covariates for modeling. First, analysis of variance (ANOVA) was used to test the variance of terrain attributes between soil orders. Then, a stepwise procedure was used to select soil covariates for linear discriminant analysis, and a backward removing procedure was developed to select soil covariates for tree modeling. At the same time, ANOVA results, as well as our knowledge and experience on soil mapping, were also taken into account for selecting soil covariates for tree modeling. Two linear discriminant models and four tree models were established finally, and their prediction performances were validated using a multiple jackknifing approach. Results showed that the discriminant model built on ANOVA results performed best, followed by the discriminant model built by stepwise, the tree model built by the backward removing procedure, the tree model built according to knowledge and experience on soil mapping, and the tree model built automatically. The results highlighted the importance of selecting soil covariates in modeling for soil mapping, and suggested the usefulness of methods used in this study for selecting soil covariates. The best discriminant model was finally selected to map soil orders for this area, and validation results showed that thus produced soil order map had a high accuracy.     

由降雨事件引起的坡面产流和土壤侵蚀的元胞自动机模拟

A novel quantitative cellular automata (CA) model that simulates and predicts hillslope runoff and soil erosion caused by rainfall events was developed by integrating the local interaction rules and the hillslope surface hydraulic processes. In this CA model, the hillslope surface was subdivided into a series of discrete spatial cells with the same geometric features. At each time step, water and sediment were transported between two adjacent spatial cells. The flow direction was determined by a combination of water surface slope and stochastic assignment. The amounts of interchanged water and sediment were computed using the Chezy-Manning formula and the empirical sediment transport equation. The water and sediment discharged from the open boundary cells were considered as the runoff and the sediment yields over the entire hillslope surface. Two hillslope soil erosion experiments under simulated rainfall events were carried out. Cumulative runoff and sediment yields were measured, respectively. Then, the CA model was applied to simulate the water and soil erosion for these two experiments. Analysis of simulation results indicated that the size of the spatial cell, hydraulic parameters, and the setting of time step and iteration times had a large impact on the model accuracy. The comparison of the simulated and measured data suggested that the CA model was an applicable alternate for simulating the hillslope water flow and soil erosion.     

Predicting unsaturated hydraulic conductivity of soil based on some basic soil properties

Soil hydraulic conductivity is a crucial parameter in modeling flow process in soils and deciding water management. In this study, by combining the non-similar media concept (NSMC) to the one-parameter model of Brooks and Corey, a new NSMC-based model for estimating unsaturated hydraulic conductivity of various soils was presented. The main inputs are soil bulk density, particle-size distribution, soil water retention characteristic and saturated hydraulic conductivity of soil. The results indicated that the NSMC-based model could generally more accurately predict unsaturated hydraulic conductivity of soils, as compared to four one-parameter models and van Genuchten–Mualem model. This study, by introducing NSMC, provided a new way to incorporate soil physical heterogeneity into soil hydraulic simulation, and hence NSMC-based approach is expected to improve efficiency of the existing models in the simulation of soil water flow.     

滩涂围垦农田土壤饱和导水率的影响因素及转换函数研究

确定苏北沿海滩涂围垦农田耕层土壤饱和导水率的影响因素,构建适合该区的土壤转换函数,是研究该区田间土壤水盐运动和盐渍化防控的重要前提。本文在该区典型地块实测土壤饱和导水率和相关土壤基本理化性质,探讨了该区土壤饱和导水率的剖面分布特点,对影响饱和导水率的土壤基本性质进行了主成分分析,并建立了用于该区饱和导水率间接估算的土壤转换函数。结果表明:滩涂围垦农田土壤饱和导水率随剖面深度增加呈表土层高、亚表层低、底土层又升高的趋势,20~40 cm土层饱和导水率最小,介于2.75~6.73 cm·d-1,属低透水强度;土壤容重随剖面深度增加表现出与饱和导水率相反的变化特点。除了容重、孔隙度、质地等物理因素外,土壤肥力、盐分等化学性质也是影响饱和导水率的重要因素;影响滩涂围垦农田土壤饱和导水率的因素可由持水特性、盐碱状况、养分特征和土壤质地4个主成分反映,其累计贡献率达78.17%。在Vereecken转换函数中引入土壤盐分后可提高预测精度,修正函数Vereecken_1是最适合滩涂围垦农区土壤、具有最佳预测精度的转换函数。本文构建的土壤转换函数,可通过较易获得的砂粒、黏粒、容重、盐分和有机质对耕层土壤饱和导水率进行较高精度的预测,其结果可为滩涂盐渍化农区田间尺度土壤饱和导水率间接估算以及水盐运动数值模拟提供支持。     

应用土壤质地预测干旱区葡萄园土壤饱和导水率空间分布

田间表层土壤饱和导水率的空间变异性是影响灌溉水分入渗和土壤水分再分布的主要因素之一,研究土壤饱和导水率的空间变化规律,有助于定量估计土壤水分的空间分布和设计农田的精准灌溉管理制度。为了探究应用其他土壤性质如质地、容重、有机质预测土壤饱和导水率空间分布的可行性,试验在7.6 hm2的葡萄园内,采用均匀网格25 m×25 m与随机取样相结合的方式,测定了表层(0～10 cm)土壤饱和导水率、粘粒、粉粒、砂粒、容重和有机质含量,借助经典统计学和地统计学,分析了表层土壤饱和导水率的空间分布规律、与土壤属性的空间相关性,并对普通克里格法、回归法和回归克里格法预测土壤饱和导水率空间分布的结果进行了对比。结果表明:1)土壤饱和导水率具有较强的变异性,平均值为1.64 cm/d,变异系数为1.17;2)表层土壤饱和导水率60%的空间变化是由随机性或小于取样尺度的空间变异造成;3)土壤饱和导水率与粘粒、粉粒、砂粒和有机质含量具有一定空间相关性,而与土壤容重几乎没有空间相关性;4)在中值区以土壤属性辅助的回归克里格法对土壤饱和导水率的预测精度较好,在低值和高值区其与普通克里格法表现类似。研究结果将为更好地描述土壤饱和导水率空间变异结构及更准确地预测其空间分布提供参考。     

基于遗传算法的土壤水分运动参数识别

土壤水分运动参数的识别是研究土壤水分运动的基础。该文以反映土壤含水率实测值和计算值吻合程度的均方差最小为优化目标,以土壤导水率和扩散率经验参数上下限为约束条件,建立了土壤水分运动参数识别的优化计算模型。采用遗传算法和田间均质土壤一维非饱和运动数值计算相结合的方法,获得土壤导水率和扩散率经验参数最优值。经验证计算,土壤含水率实测值和计算值吻合程度较高,表明这一方法是可行的。     

紫色砂岩区不同植被类型土壤优先流特征及其影响因素

以三峡库区内的重庆市四面山针阔混交林、竹林和草地3种不同植被类型土地为研究对象,应用亮蓝染色示踪法和图像分析法,同时结合SPSS软件对比研究紫色砂岩区针阔混交林、竹林和草地3种不同植被类型下的土壤优先流特征及其影响因素。结果表明：1）3种植被类型下土壤优先流的主要发生区域不同,竹林和草地的土壤优先流主要发生在0~20 cm土壤表层,而针阔混交林的土壤优先流主要发生在10~40 cm土层;2）针阔混交林的土壤优先路径数量较竹林和草地多,优先路径发育程度表现为针阔混交林〉竹林〉草地;3）根系直径d影响土壤中优先流的发生,     

波涌灌间歇入渗饱和-非饱和土壤水分运动数值模拟及试验

考虑到地下水浅埋对上层包气带水分分布造成一定影响,该研究结合波涌灌技术,对地下水浅埋下间歇入渗的土壤水分分布特征和运动规律进行了分析,建立了基于饱和-非饱和土壤条件下一维间歇入渗水分运动模型,根据试验实测资料采用Hydrus-1D软件反推土壤水分运动参数,并对入渗过程进行了模拟。在此基础上,确定了饱和导水率的估算模型。结果表明:所建参数估算模型较好地反映了饱和导水率与间歇周期数、循环率以及周期时间之间的相关关系,所建水分运动模型模拟值与实测值比较,累计入渗量、土壤含水率以及湿润体运移距离总体相关系数高于0.96,均方差在0.5以内,吻合度较高,能够较好地描述了地下水影响条件下波涌灌间歇入渗饱和-非饱和土壤水分运动特征。该研究为波涌灌技术进一步发展奠定了科学基础。     

土壤大孔隙饱和导水率的数值模拟及实验研究

原状土壤饱和导水率的确定将直接影响水及溶质在原状土壤中运动的模拟,进而影响到水文模型及溶质运移模型的模拟精度。为此,将原状土壤分为基质域和大孔隙域,以南京市栖霞区的土壤为例,通过CT扫描结合经验公式法、室内原状土柱实验法分别得到了原状土壤大孔隙的饱和导水率,并对其结果进行了详细的对比分析。结果表明:两种测定大孔隙饱和导水率的方法得到结果的相对偏差在10%以内。     

基于三维Copula函数的滴灌硝态氮淋失风险评估方法

硝态氮淋失是滴灌系统设计和运行管理需要考虑的重要因素。该研究构建了滴灌条件下的水氮运移模型,利用HYDRUS-2D软件进行了求解,模拟分析了田间尺度砂壤土饱和导水率和初始含水率空间变异对NO₃^--N淋失率的影响,并利用三维Gumbel-Hougaard Copula函数构建了土壤饱和导水率、初始含水率和NO₃^--N淋失率的联合分布函数,分析了给定土壤饱和导水率和初始含水率条件下NO₃^--N淋失率超过某一阈值的条件概率。结果表明,NO₃^--N淋失率概率密度函数可用指数函数表示;土壤饱和导水率和初始含水率的空间变异会明显增加NO₃^--N淋失风险;NO₃^--N淋失率超过给定阈值（6.4%,均质土壤条件下的NO₃^--N淋失率）的条件概率基本随土壤饱和导水率和初始含水率的增大而增大。构建田间尺度土壤特性参数（如饱和导水率、初始含水率等）与NO₃^--N淋失率的联合分布函数为研究多变量空间变异条件下NO₃^--N淋失风险评估提供了参考。     

基于线性源法与图像处理的土壤饱和导水率快速测量方法

土壤饱和导水率是计算土壤剖面水通量以及设计灌溉和排水系统的重要参数,其测量准确与否直接影响各类水文和水动力学模型的预测精度。然而,现有土壤饱和导水率测定方法费时费力,给土壤水动力学研究工作带来了诸多不便。为此,该研究提出了一种基于线性源入流法与手机图像处理相结合的土壤饱和导水率快速测量方法。该方法首先利用手机拍照获取图像记录充分供水条件下线性水流在土壤表面扩散的过程,图像经处理后计算出土壤表面湿润面积及其随时间的变化关系,然后根据线性源入流法估算的土壤稳态入渗率来测得土壤饱和导水率,并与传统的定水头标准法测得的饱和导水率进行对比。结果表明：图像经畸变校正与二值化处理之后计算出栓皮栎林区土壤、油松林区土壤和砂壤土表面湿润面积与时间具有较好的幂指数关系,决定系数R2分别为0.994、0.995和0.998;在此基础上,采用线性源入流法测量栓皮栎林区土壤、油松林区土壤和砂壤土的稳态入渗率（即土壤饱和导水率）分别为23.40±1.21、23.86±1.83和22.99±2.26 mm/h,同时使用定水头标准法测量三种土样得到的饱和导水率分别为24.41±1.53、24.26±0.37和23.81±0.10 mm/h,与定水头标准法相比,该研究提出的土壤饱和导水率测量方法的相对误差分别为4.14%、1.64%和3.42%。可见,该研究提出的测定方法较为合理、简便、准确,可为获取土壤饱和导水率提供一种新的测量手段,后续研究会将该方法用于野外环境下土壤饱和导水率的原位测定,并验证该方法的准确性。     

Estimation and analysis of soil hydraulic properties through infiltration experiments: comparison of BEST and DL fitting methods

The BEST method (Beerkan estimation of soil transfer parameters through infiltration experiments) appears promising and easy to estimate not only saturated hydraulic conductivity but also water retention and hydraulic characteristics. However, few tests have been conducted to test the methodology. This study involved field BEST infiltration experiments for three layers (surface, 15 and 30 cm) for each of three soils with different soil textures under grassland. By comparing BEST with DL (differentiated linearization method), we found that the DL method did not produce a good estimate of the soil hydraulic properties and neither did it identify the transient flow state. The BEST method resulted in reasonable results and is therefore promising. However, with BEST we encountered some anomalies when calculating hydraulic properties in some cases with too few data points under the transient flow state. We show that the application of BEST field experiments requires a wide range of soil water content from initial to saturated states so as to include sufficient transient flow. The soil hydraulic properties determined using the BEST method showed contrasting characteristics between different soil textures with higher saturated hydraulic conductivity under coarse texture and lower values under loam textures, especially with highly compacted soils. Vertical variation in soil hydraulic properties was significant, and the surface layer had a lower saturated hydraulic conductivity partly caused by compaction (high bulk density) or by remnants of grass plants. Further research on the effects of compaction and grass plants on soil hydraulic properties is needed.