Spatial variability of Southeastern U.S. Coastal Plain soil physical properties: Implications for site-specific management

Our objectives were to describe the field-scale horizontal and vertical spatial variability of soil physical properties and their relations to soil map units in typical southeastern USA coastal plain soils, and to identify the soil properties, or clusters of properties, that defined most of the variability within the field. The study was conducted on a 12-ha field in Kinston, NC. A 1:2400 scale soil survey had delineated three soil map units in the field: Norfolk loamy sand, Goldsboro loamy sand, and Lynchburg sandy loam. These are representative of millions of hectares of farmland in the Coastal Plain of the southeastern USA. Sixty soil cores were taken to ∼ 1-m depth, sectioned into five depth increments, and analyzed for: soil texture as percentage sand, silt, and clay; soil water content (SWC) at − 33 and − 1500 kPa; plant available water (PAW); saturated hydraulic conductivity (Ksat); bulk density (BD); and total porosity. A penetrometer was used to measure cone index (CI) at each sample location. Variography, two mixed-model analyses, and principal components analysis were conducted. Results indicated that soil physical properties could be divided into two categories. The first category described the majority of the within-field variability and included particle size distribution (soil texture), SWC, PAW, and CI. These characteristics showed horizontal spatial structure that was captured by soil map units and especially by the division between sandy loams and finer loam soils. The second class of variables included BD, total porosity, and Ksat. These properties were not spatially correlated in the field and were unrelated to soil map unit. These findings support the hypothesis that coastal plain soil map units that delineate boundaries between sandy loams versus finer loam soils may be useful for developing management zones for site-specific crop management.     

农田土壤质地空间分布的三维随机模拟及其不确定性评价

定量描述土体三维构型对于土地利用及农田水肥管理研究极其重要.本研究根据华北山前冲积平原区一块农田内的109个土壤剖面观测数据,运用马尔科夫地质统计学方法构建了土壤质地种类的三维空间分布模型,在100次随机模拟的基础上,分别得到了土壤质地种类的优化分布图及其概率分布图.结果表明,一维嵌入转移概率模型能很好地描述农田水平和垂直方向上各土壤质地种类的空间连续性及毗邻转移趋势.优化分布图虽能直观反映土壤质地种类的空间分布特征,但存在明显的平滑效应,不能刻画土壤质地种类空间分布的不确定性.而采用概率分布的方式来描述土壤质地种类空间分布的不确定性,能够有效地克服该缺点.     

Laboratory evaluation of a model for soil crumbling for prediction of the optimum soil water content for tillage

A model for soil crumbling, called the capillary crumbling model (CCM) was introduced by Aluko and Koolen [Aluko, O.B., Koolen, A.J., 2000. The essential mechanics of capillary crumbling of structured agricultural soils. Soil Till. Res. 55, 117–126]. According to the CCM, the optimum soil water content for tillage (θ_OPT) may be defined as the water content at which the capillary bonding strength between aggregates is minimum. The objective of this study was to evaluate the CCM for the arable layer of 10 agricultural soils (sandy loam to clay textures) from semi-arid regions in western Iran. The results were compared with conventional soil workability limits such as 0.85 of the soil plastic limit (0.85θ_PL), Proctor critical water content (θ_Proctor), 0.6 or 0.7 of water content at matric suction of 50 hPa (0.6–0.7θ_50 hPa), and the Kretschmer optimum water content (θ_Kretschmer = θ_PL − 0.15(θ_LL − θ_PL)) where θ_LL is the soil liquid limit. Repacked soil cores were prepared from intact soil aggregates (0.50–4.75 mm) to 0.9 of the critical bulk density (to represent the soil conditions before tillage). Tensile strength and matric suction of the cores were determined at different soil water contents obtained by slow drying. The CCM provided evidence for the physics and mechanics of crumbling in the studied soils. It revealed that effective stresses are the dominant inter-aggregates forces, at least for the wet range of soil water content. A fall in strength of inter-aggregate bonds (i.e. tensile strength) was recorded due to water emptying from structural pores in a narrow range of matric suction (h_OPT) which was consistent with the model. With increasing soil organic matter and clay contents the fall became more distinct, indicating increased structural stability. The θ_OPT values determined by the CCM were found in the h_OPT range 551–612 hPa corresponding to 0.91–0.79θ_PL, which was in agreement with published values for the soil workability limit. Negative correlations between h_OPT and clay and organic matter contents clearly confirmed the increasing effect of soil structure on the enlargement of inter-aggregate pores. High correlations were observed between θ_OPT and 0.85θ_PL, θ_Proctor or 0.7θ_50 hPa. The results showed that the CCM might be recommended as a physically based method for the determination of θ_OPT. Considering the 1:1 relationships between θ_OPT and 0.85θ_PL or θ_Proctor, and easy determination of θ_PL and θ_Proctor, use of these indices is recommended in situations where the CCM is not applicable.     

Cadmium speciation as influenced by soil water content and zinc and the studies of kinetic modeling in two soils textural classes

Background and aimsSince few studies have existed in the literature about the effect of zinc (Zn) on cadmium (Cd) chemical forms in soils. Therefore, this study has been performed to determine the impact of Zn on cadmium Cd chemical forms in two soil textural classes in Fars province-Iran at two soil water content (SWC) (flooded soil water content (FSWC) and field capacity soil water content (FCSWC)) and study the kinetic modeling of Cd.Methods and materialsVariables were three levels of Cd (0, 30 and 60 mg kg^-1 of soil as CdSO₄·8H₂O), three levels of Zn (0, 5 and 10 mg kg^-1 of soil as Zn-EDTA) three level Incubation times (2, 4 and eight weeks), two soil textural classes (clay and sandy clay loam) and two SWC. The randomized completed block design (RCBD) was used for this experiment. The Tessier sequential extraction method was used to determine the Cd concentration in (WsEx), (Fe-MnOx), (Car), (Om) and (Res) chemical forms.ResultsIn the FSWC, Zn reduced the Cd concentration in Fe-MnOx, Car and Om forms and increased the WsEx but had no significant effect on the Res form. Changes in the Cd chemical forms under the influence of Zn in both soils followed a similar trend. In the FCSWC, Zn reduced the Cd concentration Car and Om forms and increased the Cd concentration in the Fe-MnOx and WsEx forms while had no significant effect on Res form in the sandy clay loam soil. In the clay soil adding Zn reduced the Cd concentration in Car and Om fractions and increased the Fe-MnOx and Res forms while has no significant effect on WsEx form. The competitive transport and adsorption Interactions between these two ions caused the changing in the Cd concentration in its chemical forms. Zn reduces the Cd concentration in the forms which are easily released into the soil solution from where they can be absorbed by plants. The power function kinetic mode is the best fitted model which can describe the Cd adsorption in our soil samples. The clay and organic compounds control the Cd adsorption in soils. The higher rate of Cd adsorption in almost all shaking times shows that Cd has more ability to occupy the adsorption sites in soils.     

Determination of Soil Type Boundaries using Electromagnetic Induction Scanning Techniques

Information on the spatial distribution of soil texture and soil water is vital in understanding crop yield variation. Such information allows improved management of all agricultural inputs. One of the limiting factors in the mapping of soil texture information, however, is cost.Confusion matrix analysis was used to determine whether bulk apparent electrical conductivity (ECa) data derived from electro-magnetic induction (EMI) scanning at field capacity, and clustered using a k-means algorithm, accurately delineates soil textural boundaries in a field containing clay loam and sandy loam soils.The ECa map was compared to two soil surveys, the first conducted at one sample per hectare and the second at four to eight samples per hectare. Using confusion matrix analysis a significantly stronger relationship was measured between the ECa map and soil units of the more intensive soil map, than with the lower sampling density soil survey. This relationship was between two classes of soil with a difference in clay content of 12% and two clusters with a difference in mean ECa of 16·9 mS m⁻¹.     

Driving forces of soil organic matter change in Jiangsu Province of China

Soil organic matter (SOM) is a key property determining soil functions and a major form of carbon stored in soil. Understanding the spatial and temporal variability of SOM and the driving forces responsible for spatial and temporal changes is important to assess regional soil quality and carbon sequestration potential and, particularly, to establish better practices for land use and management. We evaluated the spatio‐temporal change in SOM content from 1979–1982 to 2006 and its driving forces in Jiangsu Province, East China, using geostatistics. The results showed that mean SOM content increased from 16.60 ± 8.50 to 18.31 ± 8.32 g/kg over a 26‐yr period. The maps of SOM generated by ordinary kriging represented the increasing trend from north to south across the province in the two periods. The level of SOM in 1979–1982 affected the pattern of change: the SOM increasing in areas initially with a small content while decreasing in areas having a large content. The map of SOM change showed that the rate of increase decreased from north to south within the province. Increased fertilizer application promoted crop production with more residual biomass being retained in the soil, which resulted in increased SOM content. Land use changes to paddy, upland or forest improved SOM content, whereas abandoning land reduced SOM content.     

Comparing SSURGO Data with Geospatial Field Measurements to Estimate Soil Texture and Infiltration Rate Classes in Glaciated Soils

The infiltration rate (IR) of water is a key soil property related to hydrological processes, soil health, and ecosystem services. However, detailed measurements of IR in the field and/or laboratory are labor-intensive and expensive to perform. Soil judging in the field provides a rapid and inexpensive method to estimate IR classes based on soil texture, soil organic carbon/matter, and soil structure. The objectives of this study were to classify and compare soil texture and IR for the A horizon across the 147 ha Cornell University Willsboro Research Farm using the Soil Survey Geographic (SSURGO) database and field-based measurements. Soil texture was the dominating factor to explain the general trend of Entisols > Inceptisols > Alfisols with regard to IR in the A horizon. In general, the variability in soil texture observed in field measurements was consistent with the variability reported in the SSURGO database, although the SSURGO representative values for soil texture did not completely match measured mean values for all soil map units. With the exception of one soil map unit, estimates of IR classes utilizing soil judging in the field criteria also were consistent when using either SSURGO or field-based data. Estimating infiltration rate classes for ecosystem services frameworks using geospatial analysis of field and/or SSURGO data can be enhanced with emerging technologies (e.g., sensors) and/or easily measured conventional soil properties.     

Temporal stability in soil water content patterns across agricultural fields

When a field or a small watershed is repeatedly surveyed for soil water content, locations can often be identified where soil water contents are either consistently larger or consistently less than the study area average. This phenomenon has been called temporal stability, time stability, temporal persistence, or rank stability in spatial patterns of soil water contents. Temporal stability is of considerable interest in terms of facilitating upscaling of observed soil water contents to obtain average values across the observation area, improving soil water monitoring strategies, and correcting the monitoring results for missing data. The objective of this work was to contribute to the existing knowledge base on temporal stability in soil water patterns using frequent multi-depth measurements with Multisensor Capacitance Probes (MCPs) installed in a coarse-texture soil under multi-year corn production. Water contents at 10, 30, 50, and 80 cm depths were measured every 10 min for 20 months of continuous observation from May 2001 to December 2002. The MCPs revealed temporal stability in soil water content patterns. Temporal stability was found to increase with depth. The statistical hypothesis could not be rejected (P < 0.0001) that data collected each 10 min, each 2 h, each day, and each week had the same temporal stability. The locations that were best for estimating the average water contents were different for different depths. The best three locations for the whole observation period were the same as the best locations for a month of observations in about 60% of the cases. Temporal stability for a specific location and depth could serve as a good predictor of the utility of this location for estimating the area-average soil water content for that depth. Temporal stability could be efficiently used to correct area-average water contents for missing data. Soil water contents can be upscaled and efficiently monitored using the temporal stability of soil water content patterns.     

Spatial variability of 2,4-dichlorophenoxyacetic acid (2,4-D) mineralisation potential at a millimetre scale in soil

We analysed the ability of soil units of millimetre size to mineralise a herbicide, 2,4-D, using incubations of individual aggregates (2-7 mm diameter) and 6×6×6 mm³ cubes dissected from soil cores, under standard conditions. Mineralisation of ¹⁴C-ring labelled 2,4-D was measured using a barite paper trap and a Phosphorimager to record the evolved ¹⁴C-CO₂ from these very small soil samples. We found a large variability of 2,4-D mineralisation potential between aggregate size classes, between individual aggregates of the same size and between the different dissected cubes from a given core. We explained this variability by an uneven distribution of the degrading microorganisms at this scale, and to a lesser extent, an uneven distribution of C, necessary for co-metabolism. Furthermore, we found that in a soil core, the dissected cubes with a large mineralisation potential were not randomly distributed, but rather organised into centimetre sized hot spots.     

Impacts of land-use pattern on soil water-content variability on the Loess Plateau of China

Abstract

Long-term vegetation restoration carried out on the slopes of the Loess Plateau of China employed different spatial and temporal land-use patterns but very little is known about the effects of these patterns on soil water-content variability. For this study the small Donggou catchment was selected to investigate soil water-content distributions for three spatial scales, including the entire catchment area, sampling transects, and land-use systems. Gravimetric soil water contents were determined incrementally to a soil depth of 1.20 m, on 10 occasions from April to October, 2007, at approximately 20-day intervals. Results indicated that soil water contents were affected by the six land-use types, resulting in four distinct patterns of vertical distribution of soil moisture (uniform, increasing, decreasing, and fluctuating with soil depth). The soil water content and its variation were also influenced in a complex manner by five land-use patterns distributed along transects following the gradients of five similar slopes. These patterns with contrasting hydrological responses in different components, such as forage land (alfalfa)–cropland–shrubland or shrubland–grassland (bunge needlegrass)–cropland–grassland, showed the highest soil water-content variability. Soil water at the catchment scale exhibited a moderate variability for each measurement date, and the variability of soil water content decreased exponentially with increasing soil water content. The minimum sample size for accurate data for use in a hydrological model for the catchment, for example, required many more samples for drier (69) than for wet (10) conditions. To enhance erosion and runoff control, this study suggested two strategies for land management: (i) to create a mosaic pattern by land-use arrangement that located units with higher infiltration capacities downslope from those with lower soil infiltrabilities; and (ii) raising the soil-infiltration capacity of units within the spatial mosaic pattern where possible.     

Occurrence and hydrological effects of water repellency in different soil and land use types in Mexican volcanic highlands

Little is known on the hydrological behavior of the volcanic ash soils, which are characterized by extremely high porosities and hydraulic conductivities. In this study the occurrence and hydrological effects of water repellency were investigated at a plot scale for different types of land use and volcanic soils in Mexican volcanic highlands from Michoacan, Mexico: [1] fir, pine and oak mixed forest soils developed from lavas, [2] soils developed from volcanic ashes and pyroclastic sediments under sparse fir, pine and oak forest and shrubland, [3] pine and oak forested soils developed from lavas and pyroclastic sediments, and [4] bare soils on recent ash sediments in plain surfaces. Soil water repellency was assessed using the water drop penetration time test and rainfall simulations were performed on circular plots (50 cm in diameter) during 30 min and at an intensity of 90 mm h^− 1 in order to study the hydrological response of each area. The return period for storms with a similar intensity in the area is 10 years. The shape and depth of the wetting front after simulated rainfall was also analyzed. Soil water repellency showed a high variability among the different studied zones. Organic matter content, soil texture and acidity were the most important factors for developing hydrophobicity. A wide range of soil water repellency classes (hydrophilic to severely water-repellent soils) has been found in soils under dense fir, pine and oak mixed forests or shrubland, while inexistent or slight water repellency has been observed in soils under sparse forest or at bare ash-covered areas. At a plot scale, marked differences in the hydrological behavior of the studied land use and soil zones were observed after the rainfall simulations. Soil water repellency contributes to fast ponding and runoff generation during the first stages of rainstorms. Runoff was enhanced in water-repellent forested soils (average runoff coefficients between 15.7 and 19.9%), in contrast to hydrophilic or slightly water-repellent soils, where runoff rates were lower (between 1.0 and 11.7%). Shallow and irregular wetting fronts were observed at water-repellent zones, reducing the soil water storage capacity. The implications of soil water repellency in soil hydrology and erosion risk in the area shed light on the soil hydrology of the studied ecosystems, and can contribute to develop better management policies.     

Modeling and correction of soil penetration resistance for varying soil water content

For this study penetration resistance (PR) was measured within the profiles of four Oxisols for a wide range of water contents (θ) and bulk densities. Obtained data were utilized to parameterize 23 previously applied regression models. The most promising models were selected to illustrate effects of soil texture on PR. Finally, a new correction method based on normalization of PR with θ corresponding to a matric potential of − 10 kPa was introduced. Evaluation of texture effects revealed that for very wet soils PR was lowest, but increased with clay content. PR at − 1500 kPa exhibited a maximum at clay content of 35% and at − 10 kPa PR was least affected by texture. From all regression models three- and two-parametric exponential and power functions yielded closest matches to measured data. The proposed correction significantly dampened the influence of θ on PR, which allows better comparison for a specific soil or among different soils.     

沂蒙山区桃园棕壤斥水性对理化性质的空间响应

以沂蒙山区典型土地利用桃园棕壤为例,在分析降雨前后桃园棕壤斥水性与理化性质空间变异的基础上,探讨了棕壤斥水性对土壤含水量、有机质含量和土壤质地的空间响应特征。按照1 m×1 m网格等间距测定降雨前后土壤实际斥水性与含水量,同时采集表层0~3 cm土壤样品,分析其有机质含量与砂粒、粉粒、黏粒含量,并借助经典统计学、地统计学与空间自相关理论对土壤斥水性及理化性质进行空间格局与空间相关性分析。结果表明:沂蒙山区桃园棕壤的斥水程度强烈,雨后斥水性显著降低;降雨前后棕壤斥水性均具有中等变异水平和较强的空间自相关性,且呈指数模型分布,各向异性显著。受结构变异和随机变异作用,斥水性空间格局沿耕作方向呈条带状分布,在其垂直方向上最小变程为1.4 m。土壤质地是影响棕壤斥水性空间变异的主要因素,斥水性与粉粒含量呈空间正相关,与砂粒和黏粒含量呈空间负相关,相关程度粉粒砂粒黏粒;棕壤斥水性与含水量呈空间负相关,相关度雨前较弱,雨后显著。     

A general approach to estimate soil water content from thermal inertia

Remote sensing is a promising technique for obtaining information of the earth's surface. Remotely sensed thermal inertia has been suggested for mapping soil water content. However, a general relationship between soil thermal inertia and water content is required to estimate soil water content from remotely sensed thermal inertia. In this study, we propose a new model that relates soil thermal inertia as a function of water content. The model requires readily available soil characteristics such as soil texture and bulk density. Heat pulse measurements of thermal inertia as a function of water content on nine soils of different textures were made to generate a universal Kerstan function. Model validation was performed independently in both laboratory and field, and the retrieved soil water contents from the new model were compared with previous models. Laboratory evaluation on an Iowa silt loam showed that the RMSE of the new model was 0.029 m³ m⁻³, significantly less than [Murray, T., Verhoef, A., 2007. Moving towards a more mechanistic approach in the determination of soil heat flux from remote measurements. I. A universal approach to calculate thermal inertia. Agric. For. Meteorol. 147, 80–87] model (0.109 m³ m⁻³) and [Ma, A.N., Xue, Y., 1990. A study of remote sensing information model of soil moisture. In: Proceedings of the 11th Asian Conference on Remote Sensing. I. November 15-21. International Academic Publishers, Beijing, pp. P-11-1P-11-5.] model (0.105 m³ m⁻³). Similar results were obtained in a field test on a Chinese silt loam: the RMSE of the new model, [Murray, T., Verhoef, A., 2007. Moving towards a more mechanistic approach in the determination of soil heat flux from remote measurements. I. A universal approach to calculate thermal inertia. Agric. For. Meteorol. 147, 80–87] model, and [Ma, A.N., Xue, Y., 1990. A study of remote sensing information model of soil moisture. In: Proceedings of the 11th Asian Conference on Remote Sensing. I. November 15-21. International Academic Publishers, Beijing, pp. P-11-1P-11-5.] model were 0.018, 0.071, and 0.159 m³ m⁻³, respectively. Additionally the model was validated using literature data in which soil thermal properties were estimated from in situ temperature measurements. The mean errors of estimated water content were generally less than 0.02 m³ m⁻³. We concluded that the new model was able to provide accurate water content predictions from soil thermal inertia.     

Predicting soil workability and fragmentation in tillage: a review

Soil workability and friability are required parameters to consider when creating suitable seedbeds for crop establishment and growth. Knowledge of soil workability is important for scheduling tillage operations and for reducing the risk of tillage‐induced structural degradation of soils. A reliable evaluation of soil workability implies a distinctive definition of the critical water content (wet and dry limits) for tillage. In this review, we provide a comprehensive assessment of the methods for determining soil workability, and the effects of soil properties and tillage systems on soil workability and fragmentation. The strengths and limitations of the different methods for evaluating the water content for soil workability, such as the plastic limit, soil water retention curve (SWRC), standard Proctor compaction test, field assessment, moisture‐pressure‐volume diagram, air permeability and drop‐shatter tests are discussed. Our review reveals that there is limited information on the dry limit and the range of water content for soil workability for different textured soils. We identify the need for further research to evaluate soil workability on undisturbed soils using a combination of SWRC and the drop‐shatter tests or tensile strength; (i) to quantify the effects of soil texture, organic matter and compaction on soil workability; and (ii) to compare soil water content for workability in the field with theoretical soil workability, thereby improving the prediction of soil workability as part of a decision support system for tillage operations.     

Applicability of site-specific pedotransfer functions and rosetta model for the estimation of dynamic soil hydraulic properties under different vegetation covers

Background, Aims, and Scope  During the last decades, different methods have been developed to determine soil hydraulic properties in the field and laboratory. These methodologies are frequently time-consuming and/or expensive. An indirect method, named Pedotransfer Functions (PTFs), was developed to predict soil hydraulic properties using other easily measurable soil (physical and chemical) parameters. This work evaluates the use of the PTFs included in the Rosetta model (Schaap et al. 2001) and compares them with PTFs obtained specifically for soils under two different vegetation covers. Methods  Rosetta software includes two basic types of pedotransfer functions (Class PTF and Continuous PTF), allowing the estimation of van Genuchten water retention parameters using limited (textural classes only) or more extensive (texture, bulk density and one or two water retention measurements) input data. We obtained water retention curves from undisturbed samples using the ‘sand box’ method for potentials between saturation and 20 kPa, and the pressure membrane method for potentials between 100 and 1500 kPa. Physical properties of sampled soils were used as input variables for the Rosetta model and to determine site-specific PTFs. Results  The Rosetta model accurately predicts water content at field capacity, but clearly underestimates it at saturation. Poor agreement between observed and estimated values in terms of root mean square error were obtained for the Rosetta model in comparison with specific PTFs. Discrepancies between both methods are comparable to results obtained by other authors. Conclusions  Site-specific PTFs predicted the van Genuchten parameters better than Rosetta model. Pedotransfers functions have been a useful tool to solve the water retention capacity for soils located in the southern Pyrenees, where the fine particle size and organic matter content are higher. The Rosetta model showed good predictions for the curve parameters, even though the uncertainty of the data predicted was higher than for the site-specific PTFs. Recommendations and Perspectives  The Rosetta model accurately predicts the retention curve parameters when the use is related with wide soil types; nevertheless, if we want to obtain good predictors using a homogenous soil database, specific PTFs are required. ESS-Submission Editor: Prof. Zhihong Xu, PhD (zhihong.xu@griffith.edu.au)     

Digital soil mapping of available water content using proximal and remotely sensed data

Two‐thirds of all irrigated agriculture in Australia is undertaken within the Murray–Darling Basin. However, climate change predictions for this region suggest rainfall will decrease. To maintain profitability, more will need to be done by irrigators with less water. In this regard, irrigators need to be aware of the spatial distribution of the available water content (AWC) in the root‐zone (i.e. 0.0–0.90 m). To reduce the cost, digital soil mapping (DSM) techniques are being used to map soil properties related to AWC (e.g. soil texture). The purpose of this study was to create a DSM of the AWC at the district scale. This is achieved by determining AWC by the difference between laboratory measured permanent wilting point (PWP) and field capacity (FC) and using pressure plate apparatus. The PWP and FC data are coupled to remote (i.e. gamma‐ray spectrometry) and proximal (i.e. EM38 and EM34) sensed data and two trend surface parameters. Using a hierarchical spatial regression (HSR), we predict PWP and FC across the areas of Warren and Trangie in the lower Macquarie valley, Australia. The reliability of the DSM of PWP and FC were compared using prediction precision (RMSE – root mean square error) and bias (ME – mean error). The best results were achieved using EM38‐v, EM34‐20, eU and eTh. The DSM map of AWC is consistent with known Pedoderms and provides a basis for agricultural water management.     

Geospatial modeling of surface soil texture of agricultural land using fuzzy logic,geostatistics and GIS techniques

ABSTRACT

Soil texture is a key controlling factor of soil properties and its functions include water and nutrient holding capacity, retention of pollutants, root development, soil biodiversity, and biogeochemical cycling. From the geotechnical standpoint, it is interesting to analyze the soil texture in regions due to its relation with the infiltration and runoff processes and, consequently, the effect on erosion processes. The purpose of this study is to present a methodology that provides the soil texture spatial variation by using Fuzzy logic theory and geostatistical technique in Geographic Information System (GIS) platform. A total of 140 soil samples were taken from topsoil (0–30 cm) in the study area located in the north of Guilan Province, the southern coast of Caspian Sea, Northern Iran. The soil textural classes were converted to numerical values (fuzzy values) using the fuzzy logic concept. The fuzzy values were spatially interpolated by ordinary kriging method such that the fitted model on experimental semi-variogram was exponential with moderate structure. The results showed the accuracy of soil texture predictive map was acceptable according to the values of normalized root-mean-square error for train data set (0.182) and test data set (0.179). The knowledge of the spatial variability of soil properties such as the soil texture can be an important tool for land-use planning in order to reduce the potential soil losses during rainy seasons. The results indicated that the integration of fuzzy logic, geostatistics, and GIS can improve the interpolation process.