Evaluation of the spatial pattern of surface soil water content of a karst hillslope in Southwest China using a state-space approach

This study aims to evaluate the effects of soil physicochemical properties and environmental factors on the spatial patterns of surface soil water content (SWC) based on the state-space approach and linear regression analysis. For this purpose, based on a grid sampling scheme (10 m × 10 m) applied to a 90 m × 120 m plot located on a karst hillslope of Southwest China, the SWC at 0–16 cm depth was measured 3 times across 130 sampling points, and soil texture, bulk density (BD), saturated hydraulic conductivity (K_s), organic carbon (SOC), and rock fragment content as well as site elevation (SE) were also measured at these locations. Results showed that the distribution pattern of SWC could be more successfully predicted by the first-order state-space models (R² = 67.5–99.9% and RMSE = 0.01–0.14) than the classic linear regression models (R² = 10.8–79.3% and RMSE = 0.11–0.24). The input combination containing silt content (Silt), K_s, and SOC produced the best state-space model, explaining 99.9% of the variation in SWC. And Silt was identified as the first-order controlling factor that explained 98.7% of the variation. In contrast, the best linear regression model using all of the variables only explained 79.3% of variation.     

渝东北紫色土饱和导水率传递函数研究

为研究渝东北紫色土理化性质在垂直空间上的分布情况以及对饱和导水率的影响,进而建立饱和导水率与各理化性质间的关系函数,推求饱和导水率的传递函数,选择渝东北开州区、云阳县等7个区县内45个紫色土典型田块为研究区域,运用Excel 2013和Matlab 2015b软件统计分析后,利用多元非线性回归法推求并验证了渝东北紫色土饱和导水率传递函数模型和模型参数。研究表明:①研究区土壤饱和导水率变化范围在0.16～195.68 cm/d,变化范围广,空间变异系数大,变异性较强;同一采样点深度越大,饱和导水率越小;②土壤饱和导水率与有机质含量有显著的指数函数关系,与饱和含水量有较强的二次函数关系,与土壤容重和土壤颗粒的相关性不大;③本次试验建立的土壤饱和导水率传递函数模型及模型系数检验合格,预测值与实际测算值误差较小,精度良好,可用于渝东北紫色土饱和导水率的预测工作。     

Spatial Variability of Soil Organic Matter and Cation Exchange Capacity in an Oxisol under Different Land Uses

ABSTRACT

Soil properties may exhibit large spatial variability. Frequently this variability is auto-correlated at a certain scale. In addition to soil-forming factors, soil management, land cover, and agricultural system may affect the spatial variability of agricultural soils. Soil organic matter (OM) is an important soil property contributing toward soil fertility and a key attribute in assessing soil quality. Increasing soil OM increases cation exchange capacity (CEC) and enhances soil fertility. We analyzed the impact of land use on the spatial variability of OM and CEC in a tropical soil, an Oxisol, within São Paulo state, Brazil. Land uses were prairie, maize, and mango. Soil samples were taken at 0–10 and 10–20 cm depths at 84 points within 1-ha plots, i.e., 100 m × 100 m. Statistical variability was higher for soil OM than for CEC. The mango plot contained the highest soil OM, whereas prairie the lowest. Also, soil OM and CEC were significantly related at all land use treatments and depths studied. All soil OM data sets and most of the CEC data sets (with two exceptions) exhibited spatial dependence. When spatial variability was present, the semivariograms showed a nugget effect plus a spherical or an exponential structure. Patterns of soil OM and CEC spatial variability (i.e., model type, ranges of spatial dependence, and nugget effects) were different between land uses and soil depths. In general, CEC exhibited a lower spatial autocorrelation and a weaker spatial structure than soil OM. Moreover, soil OM displayed a higher autocorrelation and was more strongly structured at the 0–10 cm depth than at the 10–20 cm depth. Interpolation by kriging or inverse distance weighting (IDW) allowed to illustrate how the spatial variability of soil OM and CEC differed due to land cover and sampling depth. Modeling and mapping the spatial distribution of soil OM and CEC provided a framework for spatially implicit comparisons of these soil properties, which may be useful for practical applications.     

Spatial variability of some nutrient constituents of an Alfisol from loess I. Classical statistical analysis

Classical statistical techniques were used to evaluate the lateral and vertical variability of some nutrient constituents, viz. NO₃, extractable K and Mg, and organic C, of a loess soil field. In all 50 sites at a 30m × 30m grid were selected within a 10 ha field situated about 25 km west of Hannover. Samples were taken at 0–30, 30–60 and 60–90 cm depths. Analysis based on cumulative probability density function showed that all properties except K in the 30–60 and 60–90 cm depths were normally distributed. K in these depths was lognormally distributed. Mean values of NO₃ increased with depth, that of K decreased and that of Mg remained nearly constant. Comparison of coeffizients of variation (CV – % variation) indicated that organic C was least variable laterally (CV = 8.7) and K the most (CV = 43.8 for 30–60 cm depth). The CV of NO₃ and Mg increased slightly with depth indicating less drastic vertical variation. The number of observations required to yield an estimate of the mean value within a prescribed accuracy and precision is shown to depend upon the nature and extent of the spatial variability of a parameter. Thus, estimated number of samples was smaller for lower CV values and vice versa. The optimum number of samples for a given property is determined by the depth in which the largest estimated number of samples is required to be taken.     

Soil macroporosity,hydraulic conductivity and air permeability of silty soils under long-term conservation tillage in Indiana

With the increasing use of conservation tillage, many questions about the long-term effects of tillage system on soil physical properties have been raised. Studies were conducted to evaluate saturated hydraulic conductivity (K_SAT), macropore characteristics and air permeability of two silty soils as affected by long-term conservation tillage systems in the state of Indiana. Measurements were taken during the tenth year of a tillage study on a Chalmers silty clay loam (Typic Haplaquoll) and the fifth year of a study on a Clermont silt loam (Typic Ochraqualf). Tillage systems were moldboard plow, chisel, ridge till-plant, and no-till in a rotation of corn (Zea mays L.) and soya beans (Glycine max L.). Saturated hydraulic conductivity was measured on large soil columns (25 × 25 × 40 cm) before spring tillage, and macropore size and continuity were assessed with staining techniques. Intact soil cores (8 cm diam × 10 cm) were collected in early July in the row and non-trafficked interrow at three depths (10–20, 20–30, and 30–40 cm) and were analyzed for air permeability (K_air), air-filled porosity and bulk density. Saturated hydraulic conductivity values were in the order plow > chisel > ridge till > no-till for the Chalmers soil and were significantly greater in the plow treatment than in the other 3 tillage systems on the Clermont soil. Differences in K_SAT between the 2 soils were generally greater than differences among tillage systems, and coefficients of variation were lower for treatments that did not include may fall tillage operations. At the 10-cm depth on the Chalmers soil, the chisel treatment had the greatest number of stained cylindrical channels, whereas for the Clermont soil the ridge till had the greatest number at this depth. Although the no-till treatment had similar or fewer total channels, it had the most continuous channels from the 10-cm depth to the 20- and 30-cm depths on both soils. Tillage system, row position and depth all affected K_air. On the Chalmers soil, plow, chisel and ridge systems had lower K_air between rows than in the row at the 10–20-cm depth, whereas no-till had constant K_air in the row and between the row. On the Clermont soil, ridge till had the highest K_air of all treatments at the 10–20-cm depth, and no-till had the highest K_air of all treatments at the 20–30-cm depth.     

Effects of compaction on soil hydraulic properties,penetration resistance and water flow patterns at the soil profile scale

The aim of this study was to quantify the effects of compaction on water flow patterns at the soil profile scale. Control and trafficked plots were established in field trials at two sites. The trafficked treatment was created by four passes track‐by‐track with a three‐axle dumper with a maximum wheel load of 5.8 Mg. One year later, dye‐tracing experiments were performed and several soil mechanical, physical and hydraulic properties were measured to help explain the dye patterns. Penetration resistance was measured to 50 cm depth, with saturated hydraulic conductivity (K_s), bulk density, and macroporosity and mesoporosity being measured on undisturbed soil cores sampled from three depths (10, 30 and 50 cm). Significant effects of the traffic treatment on the structural pore space were found at 30 cm depth for large mesopores (0.3–0.06 mm diameter), but not small mesopores (0.06–0.03 mm) or macroporosity (pores > 0.3 mm). At one of the sites, ponding was observed during the dye‐tracing experiments, especially in the trafficked plots, because of the presence of a compacted layer at plough depth characterized by a larger bulk density and smaller structural porosity and K_s values. Ponding did not induce any preferential transport of the dye solution into the subsoil at this site. In contrast, despite the presence of a compacted layer at 25–30 cm depth, a better developed structural porosity in the subsoil was noted at the other site which allowed preferential flow to reach to at least 1 m depth in both treatments.     

Exploring the variation in soil saturated hydraulic conductivity under a tropical rainforest using the wavelet transform

Saturated hydraulic conductivity (K_s) of the soil is a key variable in the water cycle. For the humid tropics, information about spatial scales of K_s and their relation to soil types deduced from soil map units is of interest, as soil maps are often the only available data source for modelling. We examined the influence of soil map units on the mean and variation in K_s along a transect in a tropical rainforest using undisturbed soil cores at 0–6 and 6–12 cm depth. The K_s means were estimated with a linear mixed model fitted by residual maximum likelihood (REML), and the spatial variation in K_s was investigated with the maximum overlap discrete wavelet packet transform (MODWPT). The mean values of K_s did not differ between soil map units. The best wavelet packet basis for K_s at 0–6 cm showed stationarity at high frequencies, suggesting uniform small‐scale influences such as bioturbation. There were substantial contributions to wavelet packet variance over the range of spatial frequencies and a pronounced low frequency peak corresponding approximately to the scale of soil map units. However, in the relevant frequency intervals no significant changes in wavelet packet variance were detected. We conclude that near‐surface K_s is not dominated by static, soil‐inherent properties for the examined range of soils. Several indicators from the wavelet packet analysis hint at the more dominant dynamic influence of biotic processes, which should be kept in mind when modelling soil hydraulic properties on the basis of soil maps.     

青海省东部不同土地利用方式下土壤饱和导水率分布及其影响因素

研究高寒地区土壤饱和导水率分布特征及其影响因素可为评估脆弱生态系统水源涵养能力和构建区域水文模型提供参数。通过测定青海省东部南北样线24个样点(0—30 cm)土壤基本理化性质和饱和导水率(K_s),分析了不同土地利用方式下K_s分布特征及其影响因素。结果表明:K_s均值表现为林地(1.89 cm/h)草地(1.62 cm/h)农地(1.41 10 cm/h),其中农地K_s(0.10～3.92 cm/h)随着土层深度增加逐渐减小,而林地(0.28～7.69 cm/h)和草地K_s(0.10～5.34 cm/h)随土层深度增加表现为先增加后减小。不同利用方式下K_s均与pH、容重、孔隙度、黏粒含量、有机质含量及饱和含水量显著相关(P0.05)。利用多元回归分析获得了农地以总孔隙度、非毛管孔隙度和饱和含水量为输入因子的K_s传递函数,林地以毛管孔隙度和非毛管孔隙度为输入因子的K_s传递函数和草地以容重、非毛管孔隙度和饱和含水量为输入因子的K_s传递函数。研究结果可为其他高寒地区不同土地利用方式下K_s的模拟和预测提供参考。     

SPATIAL VARIABILITY OF SOIL PHYSICAL PROPERTIES IN A REGION OF THE LOESS PLATEAU OF PR CHINA SUBJECT TO WIND AND WATER EROSION

The analysis of the spatial variability of soil properties is important for land management and construction of an ecological environment. The objectives of this study were to investigate the spatial variability of saturated hydraulic conductivity (K_S), total porosity (TP), capillary porosity (CP) and bulk density (BD) in relation to land use in a 0·54 km² watershed on the Loess Plateau. Topsoil samples (0–5 cm) from 154 sites within the watershed were collected and analyzed by classical and geostatistical statistics in the summer of 2009. The results from the classical statistical analyses indicated that TP, CP and BD had low variability whereas K_S had high variability with the watershed. Farmland had significantly lower BD and higher TP and CP than grassland, shrubland and woodland (p < 0·05). Geostatistical analyses revealed that the K_S semivariogram was best fit by a spherical model, the CP semivariogram was best fit by an exponential model and the TP and BD semivariograms were best fit by Gaussian models. The nugget to sill ratios and fractal dimension values indicated that all four soil properties had strong spatial dependence. Moran's I analysis showed that a 100‐m sampling interval would be adequate for detecting the spatial structure of the four soil physical properties within the watershed. Spatial interpolation maps could provide useful information for precision agriculture practices and ecological management. Copyright © 2011 John Wiley & Sons, Ltd.     

Effects of conocarpus biochar on hydraulic properties of calcareous sandy soil: influence of particle size and application depth

A laboratory column experiment was conducted to investigate the effects of 400°C biochar at application rate of 15 g kg^?1 (21.9 t ha^?1) with different particle sizes (<0.5 mm (S₁), 0.5–1 mm (S₂) and 1–2 mm (S₃)) and application depths (0–2 cm depth (D₀), 4–6 cm depth (D₅) and 8–10 cm depth (D₁₀)) on hydro-physical properties of sandy loam soil. The results indicated that applying biochar decreased the waterfront and saturated hydraulic conductivity of sandy loam soil. The cumulative evaporation was the highest and amounted to 40.9 mm in the non-treated soil, but it recorded the lowest amount of 32.2–35.5 mm in the biochar-treated soil. Applying biochar caused significant increases in the amount of conserved and retained water with the highest amount of water conserved in soil treated with S₂ biochar at D₅. Moreover, the cumulative water infiltration through the soil was significantly reduced by S₁ and S₂ biochars at D₀. The values of saturated hydraulic conductivity for biochar treatments were significantly lower than those for the control, with the lowest values for S₁ at D₀ and D₅. These results suggest positive improvement for the hydro-properties of coarse-textured soils following biochar addition, especially with finer particles of biochar.     

Leaching of Terbuthylazine and Bromacil Through Field Soils

A field experiment was designed to provide data on the effect of soil heterogeneity on the distribution of herbicides following leaching by irrigation and rain water. Terbuthylazine and bromacil, two nonconservative herbicides, together with CaBr₂, a conservative chemical, were used in the reported experiment. The experimental field consisted of a noncultivated 175-m² plot in which 20 observation points were randomly selected. A hundred and ten centimeters of irrigation and rainwater were applied and the field was periodically sampled for chemical distributions. The spatial variability of the field was determined by measuring the K_s (saturated conductivity) and α (Gardner parameter). Auxiliary laboratory experiments were performed to define the adsorption-desorption of the chemicals studied in these field soils. Results on the adsorption-desorption of terbuthylazine and bromacil and on the redistribution of these chemicals in the field to a depth of 120 cm during leaching are shown. Bromacil leached to a greater extent than terbuthylazine. The differences among the concentrations of herbicides in the various cores studied may be explained in terms of properties of the chemicals and soil spatial variability. The residual concentrations of terbuthylazine and bromacil were also determined to a depth of 400 cm after the leaching of 110 cm of water. In some of the cores, two zones showing a relatively high concentration of terbuthylazine and bromacil were observed at depths of 40–60 and 200–300 cm, respectively. This redistribution pattern of the herbicides could be explained by the preferential flow of the solute in the cores studied.     

反演含碎石碳酸盐岩红土水力特性

为探究喀斯特地区碎石夹层对碳酸盐岩红土水力特性的影响因素,通过室内模拟土柱入渗试验,采用垂直入渗水头法研究3种碎石体积含量(0,40％,80％)和3种碎石埋藏深度(0,5,15 cm)分别与累积入渗量、湿润锋、入渗特性和土壤水分特征曲线之间的关系,并采用3种模型分析了含碎石土壤对传统土壤入渗模型的适用性,将实测入渗数据...     

Using boosted regression trees to explore key factors controlling saturated and near‐saturated hydraulic conductivity

Hydraulic conductivity at and near saturation is difficult to predict. We investigated, for the first time, the potential of boosted regression trees to identify the key factors that determine saturated and near‐saturated hydraulic conductivities in undisturbed soils with a global meta‐database of tension infiltrometer measurements. Our results demonstrate that pedotransfer functions developed from meta‐databases may strongly over‐estimate prediction performance unless they are validated against each individual data source separately. For such a source‐wise cross‐validation, we estimated the hydraulic conductivity at a tension of 10 cm (K₁₀) and the saturated hydraulic conductivity (K_s) with coefficients of determination of 0.36 and 0.15, respectively. The most important predictors for K₁₀ were the average annual precipitation and temperature at the measurement location, which are key variables for pedogenesis and constrain soil management. More research is required for the in‐depth interpretation of their influence on hydraulic conductivity. The soil clay and organic carbon contents were also important predictors of K₁₀, with hydraulic conductivity decreasing as organic carbon contents increased up to 1.5% and as clay contents increased between about 10 and 40%. The direction of the tension‐sequence with which the infiltrometer data were collected was also a significant predictor. Land use and bulk density were the most important predictors for K_s. The direction of the tension‐sequence and the soil texture class were also important, with both coarse and fine‐textured soils generally having larger K_s values than medium‐textured soils.     

Effects of a bentonite–water mixture on soil-saturated hydraulic conductivity

To reduce water loss in light-textured soils, hydraulic conductivity should be reduced by mixing the soils with some soil conditioners, e.g. sodium-bentonite. The objectives of this study were to investigate the effects of irrigation water with different bentonite concentrations (0, 0.05, 0.1, 0.15 and 0.2%) on hydraulic gradient (i) and relative saturated hydraulic conductivity (K _rs) in a laboratory soil column with a loamy sand soil. Addition of sodium-bentonite to the soil increased i throughout each experiment. Furthermore, addition of bentonite reduced K _rs, and a 0.2% bentonite–water concentration after infiltration of 48 mm of bentonite–water mixture (BWM), reduced the K _rs value to 56% of K _s. K _rs was reduced as the concentrations of bentonite increased and its value reached ～0.5 to 0.6 as the infiltration of BWM increased. The lowest value of K _rs and the greatest reduction rate occurred at a bentonite concentration of 0.2%. It is concluded that BWM can be used as a channel liner. Using a 0.2% bentonite concentration resulted in a reduction in the seepage ratio from 1.0 to 0.08.     

Spatial Heterogeneity of Soil C:N Ratio in a Mollisol Watershed of Northeast China

The spatial variability of the soil C:N ratio (C:N) influences C and N leaching and basic fertility in the field. This paper aims to identify the spatial heterogeneity of C:N in a Mollisol watershed of Northeast China and determine the main mechanisms that drive these differences. A random sampling method was used, with both geostatistical and traditional analysis being used to describe the spatial distribution of the C:N at various depths. C:N was also compared between slope position, previous vegetation and tillage methods in the watershed. The horizontal distribution of the C:N was mainly influenced by structural factors (88·4–99·9%) and often gradually deceased along the hydrographic flow direction, becoming lowest at the watershed outlet. The C:N increased as soil depth increased at all slope positions, and was higher on the back slope than on summit slope, followed by bottom slope in all soil depths. C:N was negatively (significant at p < 0·01) correlated to TN, and positively (significant at p < 0·05) correlated to elevation at all soil depths. Compared to the reforested area, C:N was typically greater in the agricultural area in the 20–60 cm depth. The planting of soybean (Glycine max L) can significantly increase the C:N at the 40–50 cm depth. C:N was higher in cross‐slope tillage than in down‐slope tillage, especially at soil depths of 40–50 cm. Generally, topographical factors, land use, crop planting and tillage methods can effectively influence the spatial heterogeneity of C:N in this watershed. Copyright © 2015 John Wiley & Sons, Ltd.     

宁南山区草地植被恢复方式对土壤饱和导水率的影响

为评价宁南山区草地植被不同恢复方式对土壤入渗性能的影响,以不同植被群落的饱和导水率为研究对象,采用逐步回归研究退耕农地、禁牧荒地、封育草地导水率的变化及影响因子,并探讨了其作用机制。结果表明：3种植被恢复方式均有利于0-40 cm土壤饱和导水性能提高;各土层土壤饱和导水率均随植被恢复而不断提高,0-5 cm土层改善作用最为明显;农地退耕序列和荒地禁牧序列5-40 cm土层、封育草地序列0-40 cm土层土壤饱和导水率随土层深度下降而降低;影响土壤饱和导水率的因子为土壤有机质因子和土壤结构因子;3种植被恢复方式土壤有机质质量分数与Ks均呈显著的线性相关关系,在该区域有机质质量分数越高,Ks增加越快;土壤有机质积累是土壤饱和导水率提高的根本动力。因此,草地封育更利于提高使该地区土壤导水性能提高,促进生态恢复。     

Pedo-transfer functions for estimating the hydraulic properties of paddy soils in subtropical central China

Pedo-transfer functions (PTFs) have been widely used to estimate soil hydraulic properties in the simulation of catchment eco-hydrological processes. However, the accuracy of existing PTFs is usually inadequate for use. To develop PTFs for local use, soil columns were collected from a double rice-cropped agricultural catchment in subtropical central China. The PTFs for saturated soil hydraulic conductivity (K_s) and parameters (θ_s, α, and n) of the van Genuchten model for the soil water retention curve (SWRC) were obtained based on soil’s basic properties, and compared with models developed by Li et al. in 2007 and Wösten et al. in 1999, respectively. Our results indicated that K_s in the range of 0.04–1087 cm d^?1 and θ_s in the range of 0.34–0.51 cm³ cm^?3 were both well estimated with the R²_adj of 0.72 and 0.87, respectively, but α (0.04–0.65 cm^?1) and n (1.05–1.21) were relatively poorly predicted with the respective R²_adj of 0.38 and 0.55, despite the use of more input parameters. Our local derived PTFs outperformed the other two existing models. However, if the local PTFs for paddy soils are not available, the Wösten et al. 1999 model can be proposed as a useful alternative. Therefore, this study can improve our understanding of the development and application of PTFs for predicting paddy soil hydraulic properties in China.     

Effects of wastewater application on saturated hydraulic conductivity of different soil textures

As metropolitan areas expand, the municipal and industrial uses of freshwater increase. Therefore, water resources for irrigation become limited and wastewater reuse for irrigation becomes a good alternative. For this purpose, the effects of suspended solids in wastewater on the soil physical properties, i.e., saturated hydraulic conductivity, K_s, have to be considered. The objectives of this research were to study the effects of applying freshwater and differently treated wastewater on K_s in the surface and subsurface layers of sandy‐loam, loam, and clay‐loam soils. This effect was studied by investigating the ratio of K_s for wastewater to K_s for fresh water in soil surface as K_r1 and in soil subsurface as K_r2. The results showed that the application of freshwater did not reduce the K_r1 considerably. However, the reduction in K_r1 mainly occurred in soil depth of 0–50 mm due to the application of wastewater. This effect is more pronounced in clay‐loam soil than in loam and sandy‐loam soils. It is concluded that application of wastewater with TSS (total suspended solid) of ≥ 40 mg L^–1 resulted in K_r1 reduction of >50% in different soil textures. However, the K_r2 reduction at soil depth of 100–300 mm is not considerable by application of wastewater for different soil textures. Further, it is concluded that less purified wastewater can be used in light‐texture soils resulting in less reduction in K_r1. Empirical models were developed for predicting the value of K_r1 as a function of amounts of wastewater application and TSS for different soil textures that can be used in management of wastewater application for preventing deterioration of soil hydraulic conductivity.     

黄土丘陵区典型植被土壤物理性质差异及其对导水特性影响

选取黄土丘陵区12种典型植被样地,通过测定各样地不同土层植物残体生物量、土壤容重、毛管孔隙度、非毛管孔隙度及饱和导水率,研究各指标随土层深度和植被类型的变化规律及其对土壤饱和导水率的影响。结果表明:(1)除容重随土层深度增加外,植物残体、毛管孔隙度、非毛管孔隙度和饱和导水率均随土层深度减少,其中植物残体大多集中于表层土壤(0—10 cm),占总残体生物量的51.4%～85.7%。(2)不同植被类型其植物残体及土壤物理性质存在显著差异,乔木林地植物残体、农耕地土壤容重、灌木林地非毛管孔隙度及饱和导水率均最大,而毛管孔隙度与不同土地利用类型间无显著差异。(3)饱和导水率随植物残体生物量密度(0—10 cm)和土壤容重呈幂函数减小,随毛管孔隙度和非毛管孔隙度呈幂函数增大;土壤容重(BD)和非毛管孔隙度(NCP)是影响土壤饱和导水率(K_s)的主要因素,且土壤饱和导水率可表示为两者的综合非线性方程(K_s=0.6BD~(-4.717)NCP~(0.203),P0.01,R~2=0.63,NSE=0.50)。此外,沙棘灌木林地平均饱和导水率最大,有利于降雨过程中土壤水分入渗,具有较强的水土保持功能。本研究结果可为黄土高原植被恢复生态水文效益评价提供理论依据。     

Artificial neural networks for predicting unsaturated soil hydraulic characteristics at different applied tensions

Direct measurement of unsaturated hydraulic parameters that are crucial inputs in any modeling of water flow or solute transport through the vadose zone is costly and time-consuming. Therefore, indirect methods like artificial neural networks (ANNs) can be used to estimate these parameters. Different ANNs conditions [two training algorithms (Trainlm and Traingd), two transfer functions (Tansig and Logsig), and different combinations of the input variables sand, silt, clay, bulk density (BD), soil organic matter (SOM) and initial (?_i) and saturated (?_s) volumetric water content] were used to predict the unsaturated hydraulic conductivity, K _ψ [at six applied tensions (ψ) of 0–0.2 m] and sorptive number, α (at five ψ values of 0.03–0.2 m) that correspond to 138 soil samples from two neighboring study areas located in the Agricultural College, Shiraz University, Islamic Republic of Iran. A four-layer ANNs with three and four nodes in the hidden layers, performed the best in predicting K _ψ and α. Traingd produced the best predictions over all input variables when Tansig and Logsig transfer functions were used for K _ψ and α at different values of ψ, respectively. ‘Silt + clay + sand + BD + SOM’ was the most basic influential input variable for predictions of K _ψ and α at almost all values of ψ. The accuracy of ANNs-predicted K _ψ decreased with decreasing ψ from 0.2 to 0.1 m, followed by an increase to a ψ value of 0 m; a specific relationship was not observed for α. Therefore, ANNs can be used to predict K _ψ with greater confidence at moderate values of ψ than at lower or higher values. The normalized root mean square error, NRMSE, confirmed that ANNs predictions for K _ψ were more accurate than predictions for α. Because reliable predictions were obtained for K _ψ, and to a lesser extent for α, it is recommended that such intelligence models are used to predict these vital soil hydraulic attributes.