Comparing Soil Taxonomy (2014) and updated WRB (2015) for describing calcareous and gypsiferous soils, Central Iran

Sarmast, Masoomeh; Farpoor, Mohammad Hady; Esfandiarpour-Boroujeni, I.

doi:10.1016/j.catena.2016.05.026

Cited by 8 publications

(4 citation statements)

References 6 publications

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“…Soil clay minerals have two main sources: (1) neoformation and transformation by pedogenic processes, and (2) inheritance from parent rocks, or addition by eolian or fluvial processes to soil surface (Schaetzl and Anderson, 2005). Palygorskite, smectite, chlorite, illite, kaolinite, and vermiculite have been reported as dominant clay minerals in arid and semi-arid areas of Iran (Salehi et al, 2002;Khormali and Abtahi, 2003;Owliaie et al, 2006;Nadimi and Farpoor, 2013;Sarmast et al, 2016;Sarmast et al, 2017). Neoformation of palygorskite as a result of calcite and gypsum precipitation seems to be a major pathway for the occurrence of this mineral in the studied soils of southwestern Iran.…”

Section: Introductionmentioning

confidence: 89%

Soil-landscape relationship as indicated by pedogenesis data on selected soils from Southwestern, Iran

Owliaie¹,

Najafi‐Ghiri²,

Shakeri³

2018

Eurasian Journal of Soil Science (Ejss)

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Article Info Received : 02.10.2017 Accepted : 02.01.2018 Soils of semiarid regions of Dehdasht and Choram in Southwestern Iran have formed on alluvium derived from mixed calcareous-gypsiferous materials from Lower Miocene to Upper Pliocene. In order to characterize and classify the soils and to determine the soillandscape relationship in the area, nine pedons located on different physiographic positions including plateau, river alluvial plain, piedmont plain, alluvial plain and alluvial fan have been described, sampled and analyzed. Physicochemical analyses, clay mineralogy and micromorphological studies were performed. The results showed that topography and parent material were two important soil forming factors affecting soil formation in the area. The soils were dominated by carbonate, gypsum, and clay illuviation and accumulation. More developed soils were found on the stable plateau and piedmont plain. Clay illuviation and argillic horizon development in soils of the more stable alluvial plain were assumed to be relict features from presumably more humid climates. Palygorskite, illite, chlorite, smectite, kaolinite, and quartz clay minerals were identified in almost all physiographic surfaces, but more palygorskite and less smectite were found in the soils with gypsiferous parent materials. Observations by SEM revealed the occurrence of neoformed palygorskite as thread-like faces and coating of gypsum crystals and marly matrix. Coating and infilling of gypsum and calcite crystals in voids and channels were common pedofeatures observed in the soils studied. Two different distribution patterns of Fe-Mn oxides were identified in aquic and non-aquic soils.

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Section: Introductionmentioning

confidence: 89%

Soil-landscape relationship as indicated by pedogenesis data on selected soils from Southwestern, Iran

Owliaie¹,

Najafi‐Ghiri²,

Shakeri³

2018

Eurasian Journal of Soil Science (Ejss)

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“…Perhaps, this was due to the effect of climate and the different solubility rates of gypsum and calcium carbonates, where the lower solubility rate of calcium carbonates resulted in its presence on the soil surface, thus making it more The prediction of gypsum was controlled mainly by rainfall, temperature, and elevation, while CCE predictions were controlled by salinity index as well as Bands 5 and 7 from the Landsat 8 data (Figure 3). Perhaps, this was due to the effect of climate and the different solubility rates of gypsum and calcium carbonates, where the lower solubility rate of calcium carbonates resulted in its presence on the soil surface, thus making it more visible in satellite imagery [66]. When predicting EC, the most influential predictors were temperature, Band 2, and salinity index (Figure 3), which was in contrast to Mosleh et al [62], where they reported that elevation, curvature, planform curvature, and profile curvature were the key predictors of EC.…”

Section: Variable Importance Analysismentioning

confidence: 99%

A Comparison of Model Averaging Techniques to Predict the Spatial Distribution of Soil Properties

et al. 2022

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This study tested and evaluated a suite of nine individual base learners and seven model averaging techniques for predicting the spatial distribution of soil properties in central Iran. Based on the nested-cross validation approach, the results showed that the artificial neural network and Random Forest base learners were the most effective in predicting soil organic matter and electrical conductivity, respectively. However, all seven model averaging techniques performed better than the base learners. For example, the Granger–Ramanathan averaging approach resulted in the highest prediction accuracy for soil organic matter, while the Bayesian model averaging approach was most effective in predicting sand content. These results indicate that the model averaging approaches could improve the predictive accuracy for soil properties. The resulting maps, produced at a 30 m spatial resolution, can be used as valuable baseline information for managing environmental resources more effectively.

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“…The two aforementioned soil classification systems are essential for promoting global communication regarding soil between soil scientists and all those involved in land management and soil resource conservation processes. A large number of researchers have compared the characteristics of soil types belonging to the two classification systems under different conditions, such as anthropogenic soil [22], urban and industrial soil [23], and calcareous soil [24,25]. The aforementioned studies showed that the WRB system had made special efforts to simplify the requirements of soil classification.…”

Section: Introductionmentioning

confidence: 99%

Appraisal of Soil Taxonomy and the World Reference Base for Soil Resources Applied to Classify Purple Soils from the Eastern Sichuan Basin, China

et al. 2023

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Purple soil is a type of global soil that is referred to by various names in different countries, which makes it difficult to understand, utilize, and ameliorate purple soil internationally. Soil Taxonomy (ST) and the World Reference Base for Soil Resources (WRB) are the most widely used soil classification systems in the world. The aim of this study was to clarify the classification of purple soil in ST and the WRB and to establish a reference between different classification systems of purple soil. Therefore, based on the current principles and methods of the ST and WRB systems, 18 typical purple soil profiles in the eastern Sichuan Basin were identified, retrieved, and classified. Then, the soil units of the WRB were compared with those of ST and the Chinese Soil Taxonomy (CST). The results revealed that the 18 typical purple soil profiles could be classified into three soil orders, four soil group orders, and seven soil subgroups in ST and four reference soil groups (RSGs) in the WRB; each profile had its own unique principal and supplementary qualifier combinations within the soil units. It was found that when compared with the ST system, the WRB and CST systems had stronger abilities to distinguish purple soil. In addition, the WRB system was able to more comprehensively consider soil characteristics such as soil layer thickness, ferric horizon, soil color, texture mutations, and carbonate through qualifiers. However, the CST system added diagnostic characteristics, such as the lithologic characteristics of purplish sandstones and shales and the ferric properties and alic properties at the soil group and subgroup levels, which enhanced the differentiation ability of the purple soil at the subgroup level.

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Comparing Soil Taxonomy (2014) and updated WRB (2015) for describing calcareous and gypsiferous soils, Central Iran

Cited by 8 publications

References 6 publications

Soil-landscape relationship as indicated by pedogenesis data on selected soils from Southwestern, Iran

Soil-landscape relationship as indicated by pedogenesis data on selected soils from Southwestern, Iran

A Comparison of Model Averaging Techniques to Predict the Spatial Distribution of Soil Properties

Appraisal of Soil Taxonomy and the World Reference Base for Soil Resources Applied to Classify Purple Soils from the Eastern Sichuan Basin, China

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