Accumulation soils like “Ockererde”—forgotten soil units in soil-classification systems

2005 ◽  
Vol 168 (6) ◽  
pp. 741-748 ◽  
Author(s):  
Sabine Fiedler ◽  
Reinhold Jahn
Soil Research ◽  
2020 ◽  
Vol 58 (6) ◽  
pp. 519
Author(s):  
H. F. Teng ◽  
R. A. Viscarra Rossel ◽  
R. Webster

Differences between local systems of soil classification hinder the communication between pedologists from different countries. The FAO–UNESCO Soil Map of the World, as a fruit of world-wide collaboration between innumerable soil scientists, is recognised internationally. Ideally, pedologists should be able to match whole classes in their local systems to those in an international soil classification system. The Australian Soil Classification (ASC) system, created specifically for Australian soil, is widely used in Australia, and Australian pedologists wish to translate the orders they recognise into the FAO soil units when writing for readers elsewhere. We explored the feasibility of matching soil orders in the ASC to units in the FAO legend using a multivariate analysis. Twenty soil properties, variates, of 4927 profiles were estimated from their visible–near infrared reflectance (vis–NIR) spectra. We arranged the profiles in a Euclidean 20-dimensional orthogonal vector space defined by standardised variates. Class centroids were computed in that space, and the Euclidean distances between the centroids of the ASC orders and units in the FAO scheme were also computed. The shortest distance between a centroid of any ASC order and one of units in the FAO classification was treated as a best match. With only one exception the best matches were those that an experienced pedologist might expect. Second and third nearest neighbours in the vector space provided additional insight. We conclude that vis–NIR spectra represent sufficiently well the essential characters of the soil and so spectra could form the basis for the development of a universal soil classification system. In our case, we could assign with confidence the orders of the ASC to the units of the FAO scheme. A similar approach could be applied to link other national classification systems to one or other international systems of soil classification.


Author(s):  
Murad Y. Abu-Farsakh ◽  
Zhongjie Zhang ◽  
Mehmet Tumay ◽  
Mark Morvant

Computerized MS-Windows Visual Basic software of a cone penetration test (CPT) for soil classification was developed as part of an extensive effort to facilitate the implementation of CPT technology in many geotechnical engineering applications. Five CPT soil engineering classification systems were implemented as a handy, user-friendly, software tool for geotechnical engineers. In the probabilistic region estimation and fuzzy classification methods, a conformal transformation is first applied to determine the profile of soil classification index (U) with depth from cone tip resistance (qc) and friction ratio (Rf). A statistical correlation was established in the probabilistic region estimation method between the U index and the compositional soil type given by the Unified Soil Classification System. Conversely, the CPT fuzzy classification emphasizes the certainty of soil behavior. The Schmertmann and Douglas and Olsen methods provide soil classification charts based on cone tip resistance and friction ratio. However, Robertson et al. proposed a three-dimensional classification system that is presented in two charts: one chart uses corrected tip resistance (qt) and friction ratio (Rf); the other chart uses qt and pore pressure parameter (Bq) as input data. Five sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the five different CPT soil classification methods were compared.


Author(s):  
Tibor Tóth

Soil salinity has been causing problems for agriculturists for millennia, primarily in irrigated lands. The importance of salinity issues is increasing, since large areas are affected by irrigation-induced salt accumulation. A wide knowledge base has been collected to better understand the major processes of salt accumulation and choose the right method of mitigation. There are two major types of soil salinity that are distinguished because of different properties and mitigation requirements. The first is caused mostly by the large salt concentration and is called saline soil, typically corresponding to Solonchak soils. The second is caused mainly by the dominance of sodium in the soil solution or on the soil exchange complex. This latter type is called “sodic” soil, corresponding to Solonetz soils. Saline soils have homogeneous soil profiles with relatively good soil structure, and their appropriate mitigation measure is leaching. Naturally sodic soils have markedly different horizons and unfavorable physical properties, such as low permeability, swelling, plasticity when wet, and hardness when dry, and their limitation for agriculture is mitigated typically by applying gypsum. Salinity and sodicity need to be chemically quantified before deciding on the proper management strategy. The most complex management and mitigation of salinized irrigated lands involves modern engineering including calculations of irrigation water rates and reclamation materials, provisions for drainage, and drainage disposal. Mapping-oriented soil classification was developed for naturally saline and sodic soils and inherited the first soil categories introduced more than a century ago, such as Solonchak and Solonetz in most of the total of 24 soil classification systems used currently. USDA Soil Taxonomy is one exception, which uses names composed of formative elements.


Land ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 154 ◽  
Author(s):  
Orestis Kairis ◽  
Vassiliki Dimitriou ◽  
Chrysoula Aratzioglou ◽  
Dionisios Gasparatos ◽  
Nicholas Yassoglou ◽  
...  

Two soil mapping methodologies at different scales applied in the same area were compared in order to investigate the potential of their combined use to achieve an integrated and more accurate soil description for sustainable land use management. The two methodologies represent the main types of soil mapping systems used and still applied in soil surveys in Greece. Diomedes Botanical Garden (DBG) (Athens, Greece) was used as a study area because past cartographic data of soil survey were available. The older soil survey data were obtained via the conventional methodology extensively used over time since the beginnings of soil mapping in Greece (1977). The second mapping methodology constitutes the current soil mapping system in Greece recently used for compilation of the national soil map. The obtained cartographic and soil data resulting from the application of the two methodologies were analyzed and compared using appropriate geospatial techniques. Even though the two mapping methodologies have been performed at different mapping scales, using partially different mapping symbols and different soil classification systems, the description of the soils based on the cartographic symbols of the two methodologies presented an agreement of 63.7% while the soil classification by the two taxonomic systems namely Soil Taxonomy and World Reference Base for Soil Resources had an average coincidence of 69.5%.


2020 ◽  
Vol 15 (No. 2) ◽  
pp. 101-115 ◽  
Author(s):  
Tereza Zádorová ◽  
Daniel Žížala ◽  
Vít Penížek ◽  
Aleš Vaněk

The possibility of the adequate use of data and maps from historical soil surveys depends, to a large measure, on their harmonisation. Legacy data originating from a large-scale national mapping campaign, “Systematic soil survey of agricultural soils in Czechoslovakia (SSS, 1961–1971)”, were harmonised and converted according to the actual system of soil classification and descriptions used in Czechia – the Czech taxonomic soil classification system (CTSCS). Applying the methods of taxonomic distance and quantitative analysis and reclassification of the selected soil properties, the conversion of two types of mapping soil units with different detailed soil information (General soil representative (GSR), and Basic soil representative (BSR)) to their counterparts in the CTSCS has been effectuated. The results proved the good potential of the used methods for the soil data harmonisation. The closeness of the concepts of the two classifications was shown when a number of soil classes had only one counterpart with a very low taxonomic distance. On the contrary, soils with variable soil properties were approximating several related units. The additional information on the soil skeleton content, texture, depth and parent material, available for the BSR units, showed the potential in the specification of some units, though the harmonisation of the soil texture turned out to problematic due to the different categorisation of soil particles. The validation of the results in the study region showed a good overall accuracy (75% for GSR, 76.1% for BSR) for both spatial soil units, when better performance has been observed in BSR. The conversion accuracy differed significantly in the individual soil units, and ranged from almost 100% in Fluvizems to 0% in Anthropozems. The extreme cases of a complete mis-classification can be attributed to inconsistencies originating in the historical database and maps. The study showed the potential of modern quantitative methods in the legacy data harmonisation and also the necessity of a critical approach to historical databases and maps.


2018 ◽  
Vol 69 (4) ◽  
pp. 206-214 ◽  
Author(s):  
Cezary Kabała ◽  
Beata Łabaz

Abstract Taking into account the fact that (a) measurement of the cation exchange capacity and base saturation is practically unavailable in the field, that formally makes impossible the reliable field classification of many soils, (b) base saturation is measured or calculated by various methods those results significantly differ, (c) base saturation and soil pH are highly positively correlated, it is suggested to replace the base saturation with pHw (measured in distilled/deionized water suspension) in the classification criteria for diagnostic horizons and soil units/subunits, both in the Polish Soil Classification and FAO-WRB. Based on statistical analysis of 4500 soil samples, the following pHw values are recommended instead of 50% base saturation: pHw <5.5 for umbric and pHw ≥5.5 for the mollic horizon, and for Chernozems, Kastanozems, Phaeozems (directly) and Umbrisols (indirectly). Furthermore, the pHw <4.7 may feature the Dystric qualifier in mineral soils and respective Reference Soil Groups of WRB; while the pHw ≥4.7 may feature the Eutric qualifier. The distinction between subtypes of the brown soils in the Polish Soil Classification may base on the pHw 4.7 or 5.0, but using different requirements of pH distribution in the depth control section. The replacement of the base saturation with pH refers to the formal soil classification only, and does not exclude the use of base saturation for professional soil characteristics.


Author(s):  
Mohsen Makki ◽  
Kolja Thestorf ◽  
Sabine Hilbert ◽  
Michael Thelemann ◽  
Lutz Makowsky

Abstract Purpose In urban areas, humans shape the surface, (re-)deposit natural or technogenic material, and thus become the dominant soil formation factor. The 2015 edition of the World Reference Base for Soil Resources (WRB) describes anthropogenic urban soils as Anthrosols or Technosols, but the methodological approaches and classification criteria of national soil classification systems are rather inconsistent. Stringent criteria for describing and mapping anthropogenic soils in urban areas and their application are still lacking, although more than half (53%) of the urban soils in Berlin are built-up by or contain anthropogenic material. Materials and methods On behalf of the Berlin Senate Department for the Environment, Transport and Climate Protection and in close cooperation with the German Working Group for Urban Soils, a comprehensive guideline for soil description in the Berlin metropolitan area (BMA), with special regard to anthropogenic/technogenic parent material and anthropogenic soils, has been developed. Our approach includes all previous standard works for soil description and mapping and is based on studies that have been conducted in the BMA over the last five decades. Special emphasis was placed on the integration of our manual into the classification system of the German soil mapping guideline (KA5). Results and discussion The extension of existing data fields (e.g., the further subdivision of land use types) as well as the creation of new data fields (e.g., pH value) adapted to the requirements of urban soil mapping has been carried out. Additional technogenic materials that occur in urban environments have been added to the list of anthropogenic parent materials. Furthermore, we designed appendices that clearly characterize typical soil profiles of the BMA and depict technogenic materials, their physical and chemical characteristics, as well as their origin and distribution. Our approach will set new benchmarks for soil description and mapping in urban environments, which will improve the quality of urban soil research in the BMA. It is expected that our approach will provide baselines for urban soil mapping in other metropolitan areas. Conclusions Our guideline is a comprehensive manual for the description of urban soils within a national soil classification system. This mapping guideline will be the future standard work for soil surveys and soil mapping in the federal state of Berlin. Currently, representatives from federal and state authorities are reviewing our guideline, with a view to potentially integrating key components into the classification system of the forthcoming 6th edition of the German soil mapping guideline (KA6).


Author(s):  
Anthony S. R. Juo ◽  
Kathrin Franzluebbers

Several pedological soil classification schemes have been developed to classify soils worldwide based on morphological features, stage of weathering, and to some extent their chemical and physical properties. Three soil classification systems are commonly used as research and teaching tools in the tropics, namely, the USDA Soil Taxonomy classification, the FAO/UNESCO World Soil Legends, and the French soil classification system. Brazil, the country with the largest land area in the tropics, has its own national soil classification system. However, soil survey, classification, and interpretation are costly and time-consuming, and few countries in the tropics have completed soil maps that are at a scale detailed enough to be useful to farmers and land users. In the absence of soil information at state, county or farm level, the authors propose a simple descriptive grouping of major soils in the tropics based on clay mineralogy to facilitate discussion on soil management and plant production in the subsequent chapters of this book. Reference to the Soil Taxonomy classification will be made when such information is available. It should be pointed out that the main purpose of this technical grouping is to provide field workers, especially those who are less familiar with the various soil classification systems, with a simple framework for planning soil management strategies. It by no means replaces the national and international soil taxonomy and classification systems that are designed for communication among soil scientists and for more detailed interpretation of soil survey data and land-use planning. This technical scheme classifies major arable soils in the tropics into four groupings according to their dominant clay mineralogy. They are • kaolinitic soils • oxidic soils • allophanic soils • smectitic soils Kaolinitic soils are deeply weathered soils with a sand, loamy sand, or sandy loam texture in the surface horizon and a clayey B horizon (20-60%). Silt content is low (< 20%) throughout the profile. Kaolinite (> 90%) is the dominant mineral in the clay fraction. These soils have an effective CEC of less than 12 cmol/kg of clay in the lower B horizon. Kaolinitic soils have a relatively high bulk density, especially in the clayey subsoil horizons (> 1.40 Mg/m3). The structure of the subsoil horizons is usually massive or blocky.


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