farrokh asadzadeh; Kamal Khosraviaqdam; Nafiseh Yaghmaeian Mahabadi; Hassan Ramezanpour
Abstract
Introduction: Soil texture is the average size of soil particles which depends on the relative proportion of sand, silt and clay contents. Soil texture is one of the most important features used by soil and environmental scientists to describe soils. Soil texture directly affects the soil porosity, which ...
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Introduction: Soil texture is the average size of soil particles which depends on the relative proportion of sand, silt and clay contents. Soil texture is one of the most important features used by soil and environmental scientists to describe soils. Soil texture directly affects the soil porosity, which in turn, determines water-retention and flow characteristics, nutrient-holding capacity, internal drainage, sorption characteristics and long-term soil fertility. High-resolution soil maps are essential for land-use planning and other activities related to forestry, agriculture and environment protection. Given the soil texture roles in controlling the soil functions, it is necessary to understand the spatial distribution of this feature in regional scale. As soil texture is a staticproperty, regional scale soil texture maps can thus help environmental scientists to predict different soil-related processes. The objective of this study was to develop a soil textural class map using Terra satellite MODIS sensor images.
Material and Methods: To achieve this goal, the digital elevation model SRTM radar of the studied area for soil samples from different altitudes and slopes was prepared in foursen consecutive 30 meters time frame. The nearest neighbor method with an error of less than 0.5 pixels was used and the elevation layers were mosaicked and transmitted to the UTM ZON-38 coordinate system and GIS Ready Became. The normalized difference vegetation index of bands 1 and 2 of the matrix was obtained to isolate the reflection of the electromagnetic spectrum of vegetation and soil. This final mosaicked digital elevation model was then divided into different altitudes to accurately evaluate the surface texture. The 60 spatial points were selected to estimate the texture of surface soil in thestudied area with systematic randomized sampling. In the current study, soil texture was determined forthe air-dried samplesusing hydrometer. The SWIR bands of MODIS with resolution of 500 meters were selected for sampling dates. After corrections, DN values of the bands for sampling points were extracted. The Pearson correlation coefficient and step wise regression techniques were used to establish proper relationships between the DN values of the SWIR bands and the soil particles. Kriging and cokriging methods were also employed to create a spatially distributed map of the soil textural classes.
Results and Discussion: The results showed that there is a close correlation between the SWIR bands of the terra satellite and the MODIS sensor with band 3, and using this auxiliary variable significantly reduces the estimation error. The best model for fitting semivariogram for clay, silt and sand contents were spherical, spherical and exponential models and the best fitting Cross-semivariogram for clay, silt and sand contents were spherical, exponential and exponential models, respectively. The highest and lowest error estimation was, respectively, related to sand and clay content. The maximum and minimum decrease of estimation error by the auxiliary variables was found for sand and clay content, respectively. The nugget/sill ratio of the kriging semivariograms was greater than 25%for sand and claycontentand lower than 25%for sand and silt content. This indicates that sand and silt contents had a strong spatial dependency, and clay content hada moderate spatial dependency. These ratios for cokriging cross-semivariograms of sand, silt and clay contentsware less than 25%. The interpolation of estimated soil texture was also determined using the cokriging method with 70% of the soil texture measured in the laboratory.
Conclusions: Our results indicated thatcokriging method estimated the soil particles more accurately as compared with linear multi-variable stepwise regression and kriging methods. Application of cokriging method also reduces the number of sampling points and the estimation error of soil texture zoning. Therefore, cokriging method seems to be better suited in impact assessments for data-scarceregions such as Iran.
M. J. Pajand; H. Emami; Alireza Astaraei
Abstract
Introduction: Topography is an important and effective property affecting the soil quality. Some researchers demonstrated that degree and aspect of land slope may influence the particle size distribution and gravel. Slope degree affects the surface and subsurface run-off, drainage, soil temperature, ...
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Introduction: Topography is an important and effective property affecting the soil quality. Some researchers demonstrated that degree and aspect of land slope may influence the particle size distribution and gravel. Slope degree affects the surface and subsurface run-off, drainage, soil temperature, stability of soil aggregates and soil erosion. This research was carried out to determine the spatial variation of soil properties in different slope degrees of northern and southern slopes in Khorasan Razavei province, Iran.
Material and Methods: This study was performed in Sanganeh research station (longitude 60o 15ʹ60ʺ and latitude 36o 41ʹ 36ʺ), of north-eastern, Khorasan Razavi province of Iran. In order to study the effects of topography on some soil physical and chemical properties, a topo-sequence with the same slope length, parent materials and cover crops was selected. 30 soil samples (0-30 cm depth) were collected from different slopes of less than 5, 5-15, 15-30, 30-50 and more than 50 percent of both southern and northern aspects. In this study, the soil particle size distribution (texture) was measured by hydrometer method, organic carbon and calcium carbonate were determined by wet oxidation and titration with HCl 6 M, respectively and soil structural stability index, aggregates mean weight diameter and particles fractal dimension were calculated by related equations. Finally, the studied soil properties of 5 slopes (less than 5, 5-15, 15-30, 30-50, and more than 50%) and 2 aspects (north and south) with 3 replicates were compared by nested experimental design and Tuky test in JMP statistical software.
Results and Discussion: The maximum and minimum clay contents as well as fractal dimension and organic carbon contents were found in less than 5% and more than 50% of south slopes, respectively. Clay content and fractal dimension in north aspect were also significantly (P
Ali reza Karimi
Abstract
Loess deposits of Kopeh Dagh area usually occur patchy, with low thickness and should be identified and differentiated from other deposits for environmental planning and landscape evolution studies. The objective of this study was to identify distribution and determine the characteristics of loess deposits ...
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Loess deposits of Kopeh Dagh area usually occur patchy, with low thickness and should be identified and differentiated from other deposits for environmental planning and landscape evolution studies. The objective of this study was to identify distribution and determine the characteristics of loess deposits and investigate their formation in the Sarakhs area. Thirty surface samples were collected from the study area and analyzed for particle size distribution. Coarse silt and very fine sand are the dominant fraction of the sediments and overally exceed 70%. Dominance of coarse silt and very fine sand, lack of coarse fragments and abrupt boundary of these sediments with underlying materials are evidences of eolian origin. With decreasing very fine sand and increasing coarse silt, sand dunes in the east and center of the area gradually change to loess deposits from Sarakhs city towards Dousti dam (along Hariroud River) and Kopeh Dag heights in the south and west. The maximum thickness of loess sediment occurred around the Dousti dam. Dominance of coarse silt and very fine sand in the sediments and gradual boundary between sand dunes and loess deposits shows the local source of the particles. Kopeh Dagh heights in southern and western parts of the area, like a barrier have trapped eolian sediments and caused their formation.
H. Beigi Harchegani; Y. Ostovari
Abstract
Particle size distribution (PSD) is one of the most important soil physical properties. The Grey Model GM(1,1) is a new method and different from empirical and parametrical models for description and estimation of soil particle size distribution. In this study, the models of Grey GM(1,1) and Skaggs ...
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Particle size distribution (PSD) is one of the most important soil physical properties. The Grey Model GM(1,1) is a new method and different from empirical and parametrical models for description and estimation of soil particle size distribution. In this study, the models of Grey GM(1,1) and Skaggs have been used to estimate PSD in five soil textural classes including 138 soil samples taken from Shahrekord Plain. For evaluating and comparison of two models, four statistical indices (MSE, MAPE, AAE, R2) and 1:1 lines were used. The results showed that the performance of both models was relatively good in all five textures. However, Skaggs and Grey GM(1,1) had the best performance in loam and clay textures, respectively. It seems that the performance of Skaggs and Grey GM(1,1) models improved when soil textures changed to coarser and finer textures, respectively. Absolute cumulative error (AAE) of the Skaggs model in some textures tended to decrease while that of the Grey GM(1,1) tended to slightly increase with increasing uniformity and curvature indices of soil.
