Soil Mapping Units Research Articles

The influence of input data quality in determining areas suitable for crop growth at the global scale – a comparative analysis of two soil and climate datasets

AbstractThe assessment of biophysical crop suitability requires datasets on soil and climate. In this study, we investigated the differences in topsoil properties for the dominant soil mapping units between two global soil datasets. We compared the ISRIC World Soil Information Center’s World Inventory of Soil Emissions Potential 5 by 5 arc min Soil Map of the World (ISRIC‐WISE 5by5 SMW ) with the Harmonized World Soil Database (HWSD) in 0.5 arc min. We also incorporated annual mean temperature and mean precipitation from two global climate datasets that were the WorldClim measurement‐based climate dataset and the Kiel Climate Model (KCM) modelled results of global climate from 1960 to 1990. We then applied a fuzzy logic approach using different combinations and resolutions of the datasets to determine the effects on the extent and distribution of suitable areas for 15 crops. We only used the spatially dominant soil class in the mapping units in the soil databases (resampled to the same resolution of 5 arc min), and we found that the estimates of topsoil properties (0–20 cm in ISRIC‐WISE and 0–30 cm in HWSD) of the seven analysed parameters were up to 40% lower in most of the HWSD than in the ISRIC‐WISE 5by5 SMW. Results from the KCM are 0.1 °C (1%) lower in mean global annual temperature and 20% higher in average global annual precipitation compared with the WorldClim data. The HWSD‐based runs resulted in 10% less crop‐suitable land than the ISRIC‐WISE 5by5 SMW‐based results. The KCM simulations predicted 1% less crop‐suitable land than the WorldClim model. Despite generalizations, our results demonstrate that discrepancies in crop suitable areas are largely due to the differences in the soil databases rather than to climate.

The impact of erosion on the classification of Mollisols in Iowa

Fenton, T. E. 2012. The impact of erosion on the classification of Mollisols in Iowa. Can. J. Soil Sci. 92: 413–418. The fertile black soils in the Great Plains and Western States of the United States are dark brown Chernozems in the Canadian system of soil taxonomy and Mollisols, when a mollic epipedon is present, according to the United States soil taxonomy. Other primary criteria are organic carbon content, color, structure, and thickness of the mollic epipedon. Accelerated erosion can affect all of these properties and is especially critical for soils that have slope gradients of more than 2%. Accelerated erosion and erosion phases are recognized in field mapping based on the amount of A horizon remaining but criteria provided in the Soil Taxonomy guidelines conflict with procedures outlined in the Soil Survey Field Manual and result in a dichotomy between the classification system and field mapping practices. Soil map unit data for the five most extensive Mollisol soil series in Iowa that have multiple phases of slope and erosion were summarized and variations between the taxonomic and survey principles were identified. Eroded units comprise 26 to 77% of the total mapped area of the series studied and do not qualify as Mollisols under the taxonomic system. However, under the principle of following the genetic thread to classify soils, the taxonomic system should be modified to accommodate the eroded units that have the same genetic pathway as their uneroded counterparts. This could be accomplished by placing primary emphasis on the organic carbon content and waiving the color requirement for eroded soil map units.

The impact of erosion on the classification of Mollisols in Iowa

Fenton, T. E. 2012. The impact of erosion on the classification of Mollisols in Iowa. Can. J. Soil Sci. 92: 413-418. The fertile black soils in the Great Plains and Western States of the United States are dark brown Chernozems in the Canadian system of soil taxonomy and Mollisols, when a mollic epipedon is present, according to the United States soil taxonomy. Other primary criteria are organic carbon content, color, structure, and thickness of the mollic epipedon. Accelerated erosion can affect all of these properties and is especially critical for soils that have slope gradients of more than 2%. Accelerated erosion and erosion phases are recognized in field mapping based on the amount of A horizon remaining but criteria provided in the Soil Taxonomy guidelines conflict with procedures outlined in the Soil Survey Field Manual and result in a dichotomy between the classification system and field mapping practices. Soil map unit data for the five most extensive Mollisol soil series in Iowa that have multip...

Analysis of the Representation of Soil Map Units using a Common Apparent Electrical Conductivity Sampling Design for the Mapping of Soil Properties

The introduction of new technologies such as GIS and GPS has led to demands for more detailed and accurate soils information than is available in traditional soil surveys. One of the common methods for acquiring more detailed soils information is through apparent electrical conductivity (ECa) surveys conducted by slowly pulling ECa equipment through fi elds along transects and collecting georeferenced ECa data. This study investigated how well the data collected from these transect surveys represent soil map units (SMUs) established by Order 1 soil surveys. On the whole, the transect surveys did a good job of representing the fi eld SMUs. However, SMUs that were only present in a small percentage (<5% by area) of the fi elds studied tended to be represented fairly poorly. The SMUs that were present in more than 5% of the fi eld area tended to be represented well by the transect surveys. Peer Reviewed Papers

Soil Taxonomy in Romania

The Romanian System of Soil Taxonomy (RSST) is a consistent soil classification based on the concept of soil as a natural self-standing entity introduced by V.V. Dokuchaev (and in Romania by G. Murgoci) and modernized taking into account the objective criteria for soil characterization and identification introduced by Guy Smith and American Soil Survey Staff. The RSST is a hierarchical system having the soil (genetic) type as basic reference taxon. The soil types are grouped at the highest level into soil (genetic) classes, equivalent to soil order in U.S. Soil Taxonomy. The soil type and their subdivisions correspond to suborders, great groups and subgroups of soils in U.S. Soil Taxonomy. At lower levels, the genetic and lithological variety of RSST corresponds, to a certain extent, to the family and series of soils in U.S. Soil Taxonomy. The soil nomenclature of RSST, in a great extent traditional and very similar to those of the World Reference Base for Soil Resources, differs considerably from the U.S. Soil Taxonomy terminology, in that it is rationally and logically constructed, and self-significant. In the large scale soil survey of Romania, each soil map unit delineated on the map is also characterized as an environmental soil unit by registering soil and land data in the form of a “fraction,” whereby the soil properties are given as the numerator and the land attributes as the denominator.

Evaluating Salinity and Sodium Levels on Soils before Drain Tile Installation: A Case Study

Soil salinity has emerged as one of the most serious and widespread consequences of the climatic wet period affecting the northern region of the American Midwest since 1993. Groundwater levels have increased, causing not only millions of hectares of prevented planting in the Dakotas, but also much higher levels of soil salinity on otherwise productive soils. A persistent comment from producers throughout eastern North Dakota during the wet cycle was that salinity had emerged in areas where it was never a problem before. Management techniques to reduce salinity effects include crop selection, use of cover crops after harvest, calcium chemical amendments for sodic soils, tillage changes to reduce upland recharge, and tile drainage to lower water tables. Soil data collected to establish background salinity and sodicity levels on a Nahon soil map unit (fine, smectitic, frigid Calcic Natrudolls) east of Wheatland, ND are presented with a broader interpretation regarding the need to perform soil chemical sampling for certain soils before installing tile drainage.

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

Saturated hydraulic conductivity (Ks) of the soil is a key variable in the water cycle. For the humid tropics, information about spatial scales of Ks 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 Ks along a transect in a tropical rainforest using undisturbed soil cores at 06 and 612 cm depth. The Ks means were estimated with a linear mixed model fitted by residual maximum likelihood (REML), and the spatial variation in Ks was investigated with the maximum overlap discrete wavelet packet transform (MODWPT). The mean values of Ks did not differ between soil map units. The best wavelet packet basis for Ks at 06 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 Ks 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.

Soil profile sulfate in irrigated southern high plains cotton fields and Ogallala groundwater

Sulfate (SO4) is one of the most important anions in soils and groundwater in semiarid regions, including west Texas. Crops9 sulfur (S) requirement is about 10% to 20% of the nitrogen requirements. However, there is far less information on soil test SO4-S (S in the SO4 form [sulfate-S]) for the western United States, compared to the humid eastern United States. The deposition of S from the atmosphere has declined nationwide, as coal-fired power plants have been scrubbing their emissions of S. This, combined with greater cotton yields and the lack of S fertilization on the Texas Southern High Plains (SHP) point to the need for a soil profile SO4-S assessment. The first objective of this study was to assess residual soil profile SO4-S content in irrigated cotton (Gossypium hirsutum) fields across a range of soil types and counties of the Texas SHP. The second objective was to compile regional SO4-S concentration data from the Texas Water Development Board irrigation well water quality database and analyze Ogallala groundwater SO4-S levels by county, soil map unit, and well depth. Soil profile (0 to 0.9 m [0 to 36 in]) SO4-S content ranged from 120 to 475 kg ha−1 (107 to 424 lb ac−1) among seven center-pivot fields sampled. About half of this S was in the 0.6 to 0.9 m (24 to 36 in) soil layer, which typically was sandy clay loam or clay loam in texture. Well water SO4-S concentration ranged from 9 to 220 mg L−1 (ppm) in clayey soils with deep groundwater to sandy soils with shallow groundwater, respectively. Groundwater SO4-S concentration was greater than the USEPA drinking water standard of 83 mg L−1 in 32% of the wells, especially in the southeastern corner of the study area. There was no consistent relationship between soil map unit and SO4-S content in the soil profile (0 to 0.9 m). A significant negative relationship between well depth and well water SO4-S concentration was observed in all the eleven-county study area of the SHP of West Texas. In conclusion, soil profile SO4 content to 0.9 m is high in SHP irrigated cotton fields and in most cases should be adequate for crop S nutritional requirements.

Delineating Salinity and Sodicity Distribution in Major Soil Map Units of El Paso, Texas, Using Electromagnetic Induction Technique

A majority of the irrigated area in the Trans-Pecos basin in the United States is affected by both salinity and sodicity that affect the long-term viability of irrigated agriculture in the region. Accurate information on spatial distribution of salinity and sodicity in the irrigated areas at a field scale is necessary for developing effective management practices. Currently, information on the amount and the distribution of salts within the irrigated areas of the Trans-Pecos basin is not available. Conventional method of soil salinity (saturated paste electrical conductivity) and sodicity (sodium adsorption ratio) assessment at a high spatial resolution is expensive, time consuming, and labor intensive. Electromagnetic induction technique can offer a low-cost, noninvasive, and rapid alternative for determining the spatial distribution of both salinity and sodicity. In this study, we evaluated the accuracy of EMI technique to delineate salt and sodicity distribution within a 12-ha study site that had all four dominant soil map units (Saneli-clayey over sandy or sandy-skeletal, montmorillonitic [calcareous], thermic Vertic Torrifluvents; Tigua-very fine, montmorillonitic (calcareous), thermic Vertic Torrifluvents; Harkey-coarse-silty, mixed [calcareous], thermic Typic Torrifluvents; Glendale-fine-silty, mixed [calcareous], thermic Typic Torrifluvents) of the Trans-Pecos basin. Salinity and sodicity values estimated by EMI technique ranged from 0.73 to 10.55 dS m−1 and sodium adsorption ratio ranged from 1.2 to 21.6 mmol1/2 L−1/2. Results of this project indicated that the EMI technique can produce accurate information on salinity distribution. Soil clay and moisture content at the time of the survey strongly influenced the accuracy of the EMI technique.

Sediment source identification in a semiarid watershed at soil mapping unit scales

Selective erosion and transport of silt and clay particles from watershed soil surfaces leads to enrichment of suspended sediments by size fractions that are the most effective scavengers of chemical pollutants. Thus, preferential transport of highly reactive size fractions represents a major problem relative to sediment/chemical transport in watersheds, and offsite water quality. The objective of this research was to develop an approach to identify sediment sources at a soil mapping unit scale for the purpose of designing site specific best management practices which affect greater reductions in runoff and erosion losses. Surface soil samples were collected along transects from each of the major 25 mapping units in six subwatersheds of the Walnut Gulch Experimental Watershed. Suspended sediments were collected from supercritical flumes at the mouth of each subwatershed. Laboratory analyses included basic soil/sediment physical and chemical properties, radioisotopes, and stable carbon isotopes, all by standard methods. Aggregation index (AI) values [100 · (1 − water dispersible clay / total clay)] were taken as an indicator of relative soil erodibility. Potential sediment yield index (PSYI) values were calculated by multiplying percent relative area for individual soil mapping units times (100 − AI). Particle size results indicated that suspended sediments were enriched in clay, relative to the watershed soils, by an average of 1.28. Clay enrichment ratios (ER) were significantly (P ≤ 0.01) and positively correlated with AI, an indication that these two parameters can be equated with erodibility and sediment yield. The PSYI values for the six subwatersheds ranged from 68.0 to 81.7. The stable carbon isotope data for the suspended sediments gave a C3 (shrubs) to C4 plant (grasses) ratio that ranged from 1.06 to 2.25, indicating greater erosion from the more highly erodible, shrub-dominated subwatersheds which also coincided with the highest PSYI values. Correlation coefficients determined individually for PSYI versus clay ER, C3/C4 plant ratios, and multivariate mixing model results were: 0.962 (P ≤ 0.01), 0.905 (P ≤ 0.01), and 0.816 (P ≤ 0.05), respectively. These statistically significant relationships support the accuracy of a potential sediment yield index approach for identifying suspended sediment sources at soil mapping unit scales.

Soil Resource Database at Village Level for Developmental Planning

A study was carried out in village Mohammadabad, Nalgonda district, Andhra Pradesh to demonstrate the potential of high-resolution remote sensing data in generating soil resource database at village level that would facilitate natural resource developmental planning. For this study, detail soil resource database was generated by interpreting IRS Resourcesat-1 LISS-IV + Cartosat-1 merged data and by undertaking soil survey and soil analysis. This database was integrated with cadastral map and was analysed for preparation of an action plan for the village that included recommendation on suitable crops, soil and water conservation measures and distribution of soil health card to farmers. The study indicates that the LISS-IV + Cartosat-1 merged satellite data helps in mapping soils at phase level and in delineation of more number of pure soil mapping units i.e. consociations at 1:10.000 scale. The plot-wise resource potential and constraints reveals that significant inter and intra-field soil variability exists. Soil fertility assessment indicates that the soils of the village are low to medium in fertility (available NPK Content) and micronutrients like copper, manganese and iron content is above the critical level for optimum growth of crops while zinc content is less than the critical level.

Scale Effects of Geographical Soil Datasets on Soil Carbon Estimation in Louisiana, USA: A Comparison of STATSGO and SSURGO

Estimation of soil organic carbon (SOC) pools and fluxes bears large uncertainties because SOC stocks vary greatly over geographical space and through time. Although development of the U.S. Soil Survey Geographic Database (SSURGO), currently the most detailed level with a map scale ranging from 1:12 000 to 1:63 360, has involved substantial government funds and coordinated network efforts, very few studies have utilized it for soil carbon assessment at the large landscape scale. The objectives of this study were to 1) compare estimates in soil organic matter among SSURGO, the State Soil Geographic Database (STATSGO), and referenced field measurements at the soil map unit; 2) examine the influence of missing data on SOC estimation by SSURGO and STATSGO; 3) quantify spatial differences in SOC estimation between SSURGO and STATSGO, specifically for the state of Louisiana; and 4) assess scale effects on soil organic carbon density (SOCD) estimates from a soil map unit to a watershed and a river basin scale. SOC was estimated using soil attributes of SSURGO and STATSGO including soil organic matter (SOM) content, soil layer depth, and bulk density. Paired t-test, correlation, and regression analyses were performed to investigate various relations of SOC and SOM among the datasets. There were positive relations of SOC estimates between SSURGO and STATSGO at the soil map unit ( R 2 = 0.56, n = 86, t = 1.65, P = 0.102; depth: 30 cm). However, the SOC estimated by STATSGO were 9%, 33% and 36% lower for the upper 30-cm, the upper 1-m, and the maximal depth (up to 2.75 m) soils, respectively, than those from SSURGO. The difference tended to increase as the spatial scale changes from the soil map unit to the watershed and river basin scales. Compared with the referenced field measurements, the estimates in SOM by SSURGO showed a closer match than those of STATSGO, indicating that the former was more accurate than the latter in SOC estimation, both in spatial and temporal resolutions. Further applications of SSURGO in SOC estimation for the entire United States could improve the accuracy of soil carbon accounting in regional and national carbon balances.

Strategies to evaluate goodness of reference strips for in-season, field scale, irrigated corn nitrogen sufficiency

The nitrogen (N) sufficiency approach to assess plant N status for in-season N management requires a non-N-limiting reference to make N recommendations. Use of reference strips in fields with spatially variable soils and the impact this variability has within N enriched reference strips are not well understood. Consequently three strategies were investigated to evaluate the impact of spatially variable sandy soils within reference strips in two commercial center pivot-irrigated corn fields. Evaluation strategies were: (i) ignore soil spatial variability throughout the reference strips, (ii) account for soil variability in the reference strips based on second-order NRCS soil map units, and (iii) account for soil variability based on apparent electrical conductivity (ECa) data as a surrogate for soil texture differences in the reference strips. A sufficiency index (SI) calculated from radiometer measured canopy reflectance data (SIsensor) and from SPAD chlorophyll meter data (SImeter) at two growth stages during corn vegetative growth were used to assess N sufficiency within the N enriched reference strips. By ignoring soil spatial variability in the reference strips, corn in the sandier soils was designated N deficient. Accounting for soil spatial variability using NRCS soil mapping units improved N sufficiency designations of corn in the reference strip for the different soil types contained within the reference strip but tended to designate corn in lighter texture areas within a mapping unit as N deficient. Use of ECa as a surrogate for soil texture typically performed best for classifying corn N sufficiency throughout the reference strip and is recommended as a method to obtain reference strip normalizing values in fields with spatially variable sandy soils.

Integração de dados do quickbird e atributos do terreno no mapeamento digital de solos por redes neurais artificiais

No presente estudo, foi realizada uma avaliação de diferentes variáveis ambientais no mapeamento digital de solos em uma região no norte do Estado de Minas Gerais, utilizando redes neurais artificiais (RNA). Os atributos do terreno declividade e índice topográfico combinado (CTI), derivados de um modelo digital de elevação, três bandas do sensor Quickbird e um mapa de litologia foram combinados, e a importância de cada variável para discriminação das unidades de mapeamento foi avaliada. O simulador de redes neurais utilizado foi o "Java Neural Network Simulator", e o algoritmo de aprendizado, o "backpropagation". Para cada conjunto testado, foi selecionada uma RNA para a predição das unidades de mapeamento; os mapas gerados por esses conjuntos foram comparados com um mapa de solos produzido com o método convencional, para determinação da concordância entre as classificações. Essa comparação mostrou que o mapa produzido com o uso de todas as variáveis ambientais (declividade, índice CTI, bandas 1, 2 e 3 do Quickbird e litologia) obteve desempenho superior (67,4 % de concordância) ao dos mapas produzidos pelos demais conjuntos de variáveis. Das variáveis utilizadas, a declividade foi a que contribuiu com maior peso, pois, quando suprimida da análise, os resultados da concordância foram os mais baixos (33,7 %). Os resultados demonstraram que a abordagem utilizada pode contribuir para superar alguns dos problemas do mapeamento de solos no Brasil, especialmente em escalas maiores que 1:25.000, tornando sua execução mais rápida e mais barata, sobretudo se houver disponibilidade de dados de sensores remotos de alta resolução espacial a custos mais baixos e facilidade de obtenção dos atributos do terreno nos sistemas de informação geográfica (SIG).

Digital soil mapping at pilot sites in the northwest coast of Egypt: A multinomial logistic regression approach

The study examines a digital soil mapping approach for the production of soil maps by using multinomial logistic regression on soil and terrain information at pilot sites in the Northwestern Coastal region of Egypt. The aim is to reproduce the original map and predict soil distribution in the adherent landscape. Reference soil maps produced by conventional methods at Omayed and Nagamish areas were used. Spectral and terrain parameters were calculated and logit models of the soil classes were developed. Predicted soil classes’ maps were produced. Software’s IDRISI/SAGA/SATISTCA/SPSS were used. The terrain and spectral parameters were found to be significantly influential and the selection of the land surfaces predictors was satisfactory. The McFadden pseudo R-squares ranged from 0.473 to 0.496. The most significant terrain parameters influencing the spatial distribution of the soil classes were elevation, valley depth, multiresolution ridgetop flatness index, multiresolution valley-bottom flatness index, and SAGA wetness index. However, the most influential spectral parameters are the first two principal components of the six Landsat Enhanced Thematic Mapper bands. The overall accuracy of the predicted soil maps ranged from 72% to 74% with a Kappa Index ranging from 0.62 to 0.64. The developed probability models were successfully used to predict the spatial distribution of the soil mapping units at pixel resolutions of 28.5 m × 28.5 m and 90 m × 90 m at adjacent unvisited areas at Matrouh and Alamin. The developed methodology could contribute to the allocation and to the soil digital mapping and management of new expansion sites in remote desert areas of Egypt.

Categorical Analysis of Spatial Variability in Economic Yield Response of Corn to Nitrogen Fertilization

Despite growing interests in variable‐rate nitrogen (VRN) fertilizer applications, we still lack basic knowledge and practical methodology for identifying major factors that can be used to guide VRN application to corn (Zea mays L.). The objective was to develop a methodology for identifying a predictable relationship between economic yield response (YR) to N and commonly measured soil and terrain attributes in the presence of spatial dependence. Six 30‐ha no‐till fields in central Iowa were studied during 6 yr. Urea‐ammonium nitrate solution was sidedressed at 112 and 140 kg N ha−1 in alternating strips replicated from 10 to 22 times. Yield responses to the high rate were calculated in a 20 by 25 m grid pattern and classified into profitable and nonprofitable categories within each field. Autologistic models were used to identify which (if any) of the following factors economically affected YR: elevation, apparent soil electrical conductivity (ECa), slope, topographic wetness index (TWI), or digital soil map units. Significant effects of some of the factors were found within 8 of 15 site‐years. Within five of these site‐years, well‐drained areas with lower ECa and TWI, and higher elevation and slope had the higher probability of profitable YR, but these effects were not stable over time. Within the proposed methodology, a high spatial resolution of YR is used that increases the ability to identify areas profitable to N, and farmers can explore VRN possibilities by applying a small fertilizer increment below or above a uniform optimal rate in many alternating strips across fields.

Decision trees for digital soil mapping on subtropical basaltic steeplands

When soil surveys are not available for land use planning activities, digital soil mapping techniques can be of assistance. Soil surveyors can process spatial information faster, to assist in the execution of traditional soil survey or predict the occurrence of soil classes across landscapes. Decision tree techniques were evaluated as tools for predicting the ocurrence of soil classes in basaltic steeplands in South Brazil. Several combinations of types of decicion tree algorithms and number of elements on terminal nodes of trees were compared using soil maps with both original and simplified legends. In general, decision tree analysis was useful for predicting occurrence of soil mapping units. Decision trees with fewer elements on terminal nodes yield higher accuracies, and legend simplification (aggregation) reduced the precision of predictions. Algorithm J48 had better performance than BF Tree, RepTree, Random Tree, and Simple Chart.

MONITORING LAND COVER CHANGES OF THE NORTHWESTERN AREA AT EL FAYOUM DEPRESSION AND ITS SOIL SUITABILITY FOR AGRICULTURAL PURPOSES

This study is a trail for monitoring land cover changes by using LandsatImagery technique as well as determining soil suitability for irrigated agricultureat the north-western outskirt of El-Fayoum depression during a period of 1984-2005. The studied area lies between latitudes of 29o 19 and 29o 26 N andlongitudes of 30o 24 and 30o 34E. To achieve this target, Landsat Imagerytechnique was carried out using two Landsat Thematic Mapper and EnhanceThematic Mapper scenes acquired on 1984 and 2005 covering the north-westernpart of El-Fayoum depression have been processed. A supervised Spectral AnglerMapper approach was also applied to classify the images into four land use/coverclasses, i.e., urban, agriculture, water and desert areas. It was observed that somedesert areas had been transformed into agriculture and settlement during theinvestigated period of twenty one year (1984-2005).This study clarified that the reclaimed area for agriculture purposes duringthe studied period reached 1726.91 ha, which constitute about 8.15 % of the totalarea under study and nation settlement (arbanization) increased with about 310.06ha, which couple nearly 1.46% of the total area. Whereas, the water area waspromoted with 31.48 ha, which equal about 0.22 %. All the land cover units wereincreased account on the expanse of desert unit, which decreased with 2097.20 ha(9.78% of the total studied area). These increases are more attributed to thegeophysical and anthropogenic processes such as salinity, alkalinity, waterlogging, wind erosion, reclamation of new agricultural land and urbanization.The satellite image interpretation map of the year 2005 was identified intotwo main landscapes and thirteen landform units, based on the visualinterpretation of Landsat data ETM7 (Enhanced Thematic Mapper 7) andapplying the Landscape feature approaches. The validity of physiographic map bounders were field checked to represent the different soil mapping units withmodel soil profiles. Thirty-two mini pits were located and studied for setting up the physiographic boundaries and characteristic of soil map legend. Also, thevariations of soil characteristics between the main identified physiographic unitswere represented by eighteen soil profiles, which chosen to be fullmorphologically described according to USDA (2003).Soil taxa were surveyed according to the USDA (1975 and 2010), and thestudied soils could be categorized into three orders and six sub-groups, asfollows: Aridisols (Typic Calcigypsids, Lithic Calcigypsids, and TypicHaplocalcids), Entisols (Typic Torriorthents and Typic Torrifluvents) andVertisols (Typic Haplotorrierts). According to the parametric system undertakenby Sys and Verheye (1978), soil suitability classes of the studied area could becategorized into four classes, i.e., highly (S1), moderately (S2), marginally (S3)and not suitable (N1 & N2).

HOW SOIL FORMING PROCESSES DETERMINE SOIL-BASED VITICULTURAL ZONING

The aim of this study was to elucidate the soil forming processes of representative vineyard soils, and to discuss the implications on a soil-based viticultural zoning at very detailed scale. The study area is located in Priorat, Penedes and Conca de Barbera viticultural areas (Catalonia, North-eastern Spain). The studied soils belong to representative soil map units determined at 1:5,000 scale, according to Soil Taxonomy classification. The soil forming processes, identified through morphological and micromorphological analyses, have significant effects on some soil properties. For example, the different processes of clay accumulation in soils developed from granodiorites in Priorat or gravel deposits in Conca de Barbera, are primarily responsible for significant differences in clay content, available water capacity and cation exchange capacity. These soils properties, especially those related to soil moisture regime, have a direct influence on vineyard management and grape quality. However, soil forming processes are not always reflected on soil classification, especially in soils modified by man. We show that climate or geology alone cannot be used in viticultural zoning at very detailed scale, unless soil forming processes are taken into account.

Assessing geopedological soil mapping approach by statistical and geostatistical methods: A case study in the Borujen region, Central Iran

Geopedology, using geomorphologic and supervised classification bases, has been proposed as a soil surveying method. It undertakes a systematic approach to map soilscapes. This approach tries to reduce the budget of accomplishing soil surveys as well as increasing the purity of mapping units. But to what extent it has been succeeded is the question. The main objective of this research was to validate the geopedological mapping methodology by statistical and geostatistical methods in the Borujen region, Central Iran. After a primary interpretation of the study area on air photos (1:20 000 scale), 94 pedons were excavated on a 125 m square sampling grid in the sample area for geostatistical studies. To achieve the statistical aims, a geomorphic unit which encompassed the maximum surface of the sample area (and also the study area) was selected and the biggest delineation of this unit with 19 pedons was considered. The credibility of generalizing the results of the geopedological approach for the studied unit was tested by comparison with 15 pedons in a similar unit outside the sample area, named the validation area. Properties of the soils, including percentage of clay, rock fragments (2–75 mm) and total carbonates in the soil family control section, percentage of organic matter in the A horizon and its thickness, were selected for statistical and geostatistical analyses. Univariate and multivariate statistical analyses obtained from the units in the sample and the validation areas, showed that the means of soil variables were similar. A high difference between A horizon thickness variances in the sample area and the validation area affected the significance of the variation test in the univariate and multivariate results. Our study demonstrated that, when comparing the same factors from sample and validation areas, the spatial distribution and spatial dependency level of soil attributes were different. Therefore, although the geopedological approach tries to distinguish more homogeneous soil mapping units, it is still not able to fully define and represent the real variability of soil properties and show the chaotic behavior or nature of the soils. We recommend further investigations on different techniques of stratifying the landscape in order to better analyze and understand the soil-forming processes and the nature of soil variability and to improve sampling and mapping approaches. We suggest that the additional determination of the phases of landforms and phases of soil series will improve mapping in the future.