Existing Soil Data Research Articles

Soil carbon stocks as affected by land-use changes across the Pampa of southern Brazil

ABSTRACT The “campos” of the Pampa are unique Brazilian ecosystems, which provide key environmental services, including C storage. These grassy ecosystems have been rapidly converted to intensive land-uses, mainly intensive grain crops (soybeans) and Eucalyptus silviculture. These new land-uses could decrease soil C stocks, depending on soil management. This study aimed to assess soil organic carbon (SOC) changes after the conversion of native grasslands to cropland (soybeans/cover crops under no-tillage) and forestry (Eucalyptus). Eight representative sites in this biome were selected for soil sampling (Alegrete-ALE, Aceguá-ACE, Jari-JAR, Jaguarão-JAG, Pinheiro Machado-PIM, Lavras-LAV, Santo Antônio das Missões-SAM, São Gabriel-SAG). Soil sampling was conducted in dug pits (0.30 m wide × 0.30 m long × 0.40 m depth) spaced by 50 m at each site, to 0.30 m depth. Soil bulk density and SOC were obtained by samples obtained with volumetric rings. Soil organic C was analyzed by dry combustion. Soil C stocks were calculated per layer and cumulatively (0.00-0.20 and 0.00-0.30 m). Soil C content was higher under grasslands in soils from sites with finer, clayey texture (ACE, JAG), and lower in soils at sites with sandier topsoil. Land-use conversion to silviculture and cropland minimally affected SOC stocks. The same pattern was observed with soil N, because of the tight connection between C and N cycles. Soil bulk density was similar across sites and layers, but higher values were measured in sites with coarser texture. Mean SOC stock of the grassland sites was 62 ± 24.6 Mg ha -1 , similar to 66 Mg ha -1 reported for grasslands soils of Rio Grande do Sul State, and higher than that reported by IPCC for this region (55 ± 4.4 Mg ha -1 ). Adopting these default values would lead to underestimation of baseline SOC stocks in the region. Land-use conversion to cropland did not affect SOC stocks significantly, probably because of the adoption of no-tillage system with winter cover crops. Soil C stocks were lower in Eucalyptus stands in the 0.00-0.30 m soil layer, which could be attributed to intensive soil management at planting and lower soil fertility in some sites. This lack of effect of conversion on soil C was attributed to the short time since conversion and adoption of soil conservation practices (no-tillage) in cropland. The study contributed to reduce existing soil data gaps in the region and supports Brazilian public initiatives like the ABC Program and National Greenhouse Gas Inventories.

National soil data in EU countries, where do we stand?

AbstractAt the European scale, soil characteristics are needed to evaluate soil quality, soil health and soil‐based ecosystem services in the context of the European Green Deal. While some soil databases exist at the European scale, a much larger wealth of data is present in individual European countries, allowing a more detailed soil assessment. There is thus an urgent and crucial need to combine these data at the European scale. In the frame of a large European Joint Programme on agricultural soils launched by the European Commission, a survey was conducted in the spring of 2020, in the 24 European participating countries to assess the existing soil data sources, focusing on agricultural soils. The survey will become a contribution to the European Soil Observatory, launched in December 2020, which aims to collect metadata of soil databases related to all kind of land uses, including forest and urban soils. Based upon a comprehensive questionnaire, 170 soil databases were identified at local, regional and national scales. Soil parameters were divided into five groups: (1) main soil parameters according to the Global Soil Map specifications; (2) other soil chemical parameters; (3) other physical parameters; (4) other pedological parameters; and (5) soil biological features. A classification based on the environmental zones of Europe was used to distinguish the climatic zones. This survey shows that while most of the main pedological and chemical parameters are included in more than 70% of the country soil databases, water content, contamination with organic pollutants, and biological parameters are the least frequently reported parameters. Such differences will have consequences when developing an EU policy on soil health as proposed under the EU soil strategy for 2023 and using the data to derive soil health indicators. Many differences in the methods used in collecting, preparing, and analysing the soils were found, thus requiring harmonization procedures and more cooperation among countries and with the EU to use the data at the European scale. In addition, choosing harmonized and useful interpretation and threshold values for EU soil indicators may be challenging due to the different methods used and the wide variety of soil land‐use and climate combinations influencing possible thresholds. The temporal scale of the soil databases reported is also extremely wide, starting from the '20s of the 20th century.

Solid-solution partitioning of micronutrients Zn, Cu and B in tropical soils: Mechanistic and empirical models

Trace elements such as zinc (Zn), copper (Cu) and boron (B) are important micronutrients for crop production. Their bioavailability is essential to crops yield quantity and quality in many tropical soils. Nutrient bioavailability depends partly on the soil nutrient status, and in particular on the reactive and soluble fractions. Adsorption/desorption and precipitation/dissolution processes control the partitioning of the reactive pool over the solid and solution phase. However, so far the solid-solution partitioning of trace elements has mostly been studied in temperate and often contaminated soils. We studied, therefore, the solid-solution partitioning of Zn, Cu and B for 172 soils from Burundi, Rwanda and Kenya, using extensive soil characterization in combination with multi-surface modelling and two types of empirical Freundlich type partition relations. Our aim was to enhance the understanding of the soil chemical processes that control the solid-solution partitioning of the three micronutrients in these soils from the tropics with a multi-surface model, and to use this knowledge as benchmark to develop partition relations that require less input data and are more convenient tools for predicting the concentration in solution based on existing soil data. We show that the generic multi-surface model applied to these tropical soils performs similarly for Zn and Cu as in previous studies on temperate and contaminated soils. The Zn and Cu speciation was dominated by adsorption to soil organic matter, with an increased importance of metal (hydr)oxides with increasing pH. Given its generally low concentrations in these soils, dissolved organic matter was found to be important only for the solution speciation of Cu. The adsorption of B was mainly to metal (hydr)oxides at low pH, and with increasing pH soil organic matter became more important. The multi-surface model overestimated the dissolved B concentration for most soil samples, which we attributed to an inaccurate estimation of reactive B. Interestingly, the variation in observed and modeled solid-solution partitioning expressed as Kd of Cu and B among the soils was relatively small (∼1 log L kg−1), and the concentration in solution was consistently mainly controlled by the reactive concentration. Generally, the optimized partition relations resulted in a smaller prediction error compared to the multi-surface models. The partition relations in which the concentration in solution was optimized, resulted generally in an overestimation for the lowest observed concentrations, and an underestimation for highest concentrations of all three elements. Partition relations with optimized Freundlich parameters Kf and n resulted in more robust predictions since the prediction error was not related to the actual measured concentration. The partition relations from this study are easy-to-use tools for predicting the dissolved concentrations of Zn, Cu and B in soils from the tropics with low contents of these micronutrients and can therefore enhance the use of current existing soil information data for Sub-Saharan Africa.

Design of a Spun Pile Vertical Wall Breakwater for the Improvement of Damaged Cellular-Cofferdam

A new breakwater is on demand to replace the function of an existing steel sheet pile cellular-cofferdam at TPPI Tuban Port of East Java. The existing breakwater has been partially damaged due to severe corrosion and hard attack by monsoon waves. An open frame structure of spun pile vertical-wall breakwater is proposed as an alternative design. The spun pile is a pre-stressed concrete hollow cylinder pile with outer diameter 1800mm and thickness of 200mm. The spun pile lengths vary between minimum 28m to maximum 33m according to the position of hard soil against seabed. The new breakwater is designed to stand against 100yrs RP wave with Hs = 4.7m. Wave height variations around the structure are simulated using Boussinesq Wave module of MIKE21 software, while SAP2000 is used to calculate the strength of superstructure to withstand existing loads and certain load combinations. Plaxis software is used mainly to analyze substructure using existing soil data. This article describes the design process of spun pile vertical wall breakwater, started from loads calculation, then define load combinations, analyze structure in SAP2000, analyze structure in Plaxis, determination of specification and dimension, to design drawings creation.

Modification of Ground Motions for Use in Central North America

ABSTRACTExisting procedures are used to modify available recorded ground motions to conform to realistic seismic hazard and regional soil conditions for Central North America. Site-specific bedrock ground motions were defined by spectrally-matching select recorded ground motions to conditional mean spectra (CMS) corresponding to a 1000-year return period. Soil profiles developed using existing soil data from the region are used to propagate the bedrock ground motions to the ground surface, for use in dynamic structural analysis. A suite of surface ground motions was developed for locations in southern Illinois; these ground motions are available in an online repository.

Mapping key soil properties to support agricultural production in Eastern China

The spatial prediction of soil attributes plays important roles in establishing areas for agricultural development and sustainable land management. This paper aimed to model and map various soil properties (i.e. texture, pH, and soil organic matter content) at a spatial resolution of 90m across a 21million-ha. area in Eastern China using 2895 legacy topsoil observations coupled with freely available covariates (i.e. DEM, Landsat, Climate and Radar data). A decision tree model (Cubist) and a Regression Kriging (RK) approach were used in the modelling process. The prediction results showed that the RK approach achieved high accuracy in predicting the spatial distributions of soil properties that were affected by human activities (i.e. soil pH and organic matter content). Moreover, DEM data decomposed to different spatial scales and climate factors were found to be the most important predictors in this study area. It was concluded that the current methodology can be readily expanded to the whole China using existing soil data as a contribution to the GlobalSoilMap project.

A GIS based method for soil mapping in Sardinia, Italy: A geomatic approach

A new project was recently initiated for the realization of the “Land Unit and Soil Capability Map of Sardinia” at a scale of 1:50,000 to support land use planning. In this study, we outline the general structure of the project and the methods used in the activities that have been thus far conducted. A GIS approach was used. We used the soil-landscape paradigm for the prediction of soil classes and their spatial distribution or the prediction of soil properties based on landscape features. The work is divided into two main phases. In the first phase, the available digital data on land cover, geology and topography were processed and classified according to their influence on weathering processes and soil properties. The methods used in the interpretation are based on consolidated and generalized knowledge about the influence of geology, topography and land cover on soil properties. The existing soil data (areal and point data) were collected, reviewed, validated and standardized according to international and national guidelines. Point data considered to be usable were input into a specific database created for the project. Using expert interpretation, all digital data were merged to produce a first draft of the Land Unit Map. During the second phase, this map will be implemented with the existing soil data and verified in the field if also needed with new soil data collection, and the final Land Unit Map will be produced. The Land Unit and Soil Capability Map will be produced by classifying the land units using a reference matching table of land capability classes created for this project.

Sustainability, certification, and regulation of biochar

Biochar has a relatively long half-life in soil and can fundamentally alter soil properties, processes, and ecosystem services. The prospect of global-scale biochar application to soils highlights the importance of a sophisticated and rigorous certification procedure. The objective of this work was to discuss the concept of integrating biochar properties with environmental and socioeconomic factors, in a sustainable biochar certification procedure that optimizes complementarity and compatibility between these factors over relevant time periods. Biochar effects and behavior should also be modelled at temporal scales similar to its expected functional lifetime in soils. Finally, when existing soil data are insufficient, soil sampling and analysis procedures need to be described as part of a biochar certification procedure.

Geographical Information System of Soil Investigation Data for Construction Purposes

Field soil investigation prior to the foundation design of any structure is a must for the design engineer. Since the cost of such operation is rather high, then it is sometimes impractical. The design and the preliminary cost estimation of the construction are then impossible to be prepared. This paper applies Geographical Information System – GIS via Google earth to all over Bangkok area thus enables engineer to retrieve the physical characteristics of soil layers from the existing soil data. In addition, utilizing the feature of Google earth can be illustrated more visibility in the required position of boring log and position of retrieved soil boring log data. Moreover, it can be applied to everywhere around the world.

Comparison of Linear and Nonlinear Kriging Methods for Characterization and Interpolation of Soil Data

Characterization and analysis of large quantities of existing soil data represent highly complicated tasks because of the spatial correlation, uncertainty, and complexity of the processes underlyin...

Soil parameter variability affecting simulated fieldscale water balance, erosion and phosphorus losses

Field-scale modelling is widely used as a means to look into interdependencies of processes and to assess potential effects of agricultural management practices as well as of climate and socio-economic scenarios. Generalisation from field-scale results to cover all agricultural land in a catchment by using typical soilcrop- slope combinations has been restricted by a lack of information for the systematic parameterisation of soils. Data from single experimental fields are seldom representative for the whole respective catchment. In this study typical soil profiles for mineral agricultural soils in Finland are defined. Key parameters describing e.g. the texture and water holding capacity of soils, were generated from existing soil data using expert knowledge and are aimed to be used for field-scale modelling when the target is not to model a particular field but soils of certain type in general. Estimates for water balance and phosphorus losses, obtained with the ICECREAM model by applying these data sets, were realistic and compatible with experimental results measured in Finland.;

Soils and their relationship to aspect and vegetation history in the eastern Southern Alps, Canterbury High Country, South Island, New Zealand

Abstract This study focuses on soils in a mountainous catchment area located in the eastern part of the Southern Alps, South Island, New Zealand. The objective was to check the soils for non- or poorly crystalline constituents (metal organic complexes, short-range-order minerals) and if there is a relationship between pedogenesis and aspect and more recent landscape history. The morphology of the soils indicates brown soils (dystric cambisols, dystrudepts) with only few signs of podsolisation. In contrast, selected chemical properties of the soils reveal very strong weathering and leaching. Feo/Fed ratios are high and exceeding 0.6 in almost every soil horizon. Oxalate-extractable aluminium and silicon show prominent peaks in the lower subsoil horizons with 1.76–2.52% Alo and up to 0.68% for Sio on southern aspects. This is considerably higher than the values measured for soils on northern aspects (0.59% to 1.07% Alo, max. 0.26% Sio). This aspect relationship is also applying to phosphate retention reaching values of more than 90% on southern aspects and not more than 70% for northern aspects. Additionally, significant movement of organic matter in soils on southern aspects is evident by measurements of organic carbon and pyrophosphate-extractable Al and Fe. Thus soil formation can be regarded as more advanced on southern aspects. Allophane in association with organic matter can be considered as an important constituent in southern aspect subsoils being responsible for the typical andic properties. Metal-humus complexes and ferrihydrite are of subordinate significance. Considering the actual soil forming conditions under scrub-grassland (esp. soil acidity), it is unlikely that weathering and leaching is still strong enough today to allow significant podsolisation and the formation of short-range-order minerals. Under consideration of existing soil data from other studies it is proposed that these components and the podsolisation features are relicts caused by more acidic conditions under former forest cover which supported a stronger weathering and leaching.

Factors controlling soil development in sand dunes: evidence from a coastal dune soil chronosequence

Aerial photographs, maps and optically stimulated luminescence dates were combined with existing soil data to construct high resolution chronosequences of soil development over 140 years at a temperate Atlantic UK dune system. Since soil formation had progressed for varying duration under different climate and nitrogen deposition regimes, it was possible to infer their relative influence on soil development compared with location-specific variables such as soil pH, slope and distance to the sea. Results suggest that soil development followed a sigmoid curve. Soil development was faster in wet than in dry dune habitats. In dry dunes, rates were greater than in the literature: they increased with increasing temperature and nitrogen deposition and decreased with increasing summer gales. The combination explained 62% of the variation. Co-correlation meant that effects of nitrogen deposition could not be differentiated from temperature. In wet dune habitats rates increased with temperature and decreased with gales. The combination explained only 23% of the variation; surprisingly, rainfall was not significant. Effects of location-specific variables were not significant in either habitat type. Nitrogen accumulation was faster in wet than dry dune habitats, averaging 43 kg N ha−1 per year overall. Nitrogen accumulation greatly exceeded inputs from atmospheric deposition, suggesting rates of input for biological N fixation are 10–60 kg N ha−1 per year. Recent climate and/or nitrogen deposition regimes may have accelerated soil development compared with past rates. These data suggest the importance of changing climate on soil development rates and highlight the contribution of biological N fixation in early successional systems.

Carbon stock assessment and soil carbon management in agricultural land‐uses in Thailand

AbstractThe organic carbon pool in agricultural land‐uses is capable of enhancing agricultural sustainability and serving as a potential sink of atmospheric carbon dioxide. A study was carried out to estimate and map carbon stock of different agricultural land‐uses in a sub‐watershed of Thailand and to assess the land‐use sustainability with respect to carbon management. A quadrat sampling methodology was adopted to estimate the biomass and its carbon content of 11 different land‐uses in the study area. Existing soil data were used to calculate the soil carbon. GIS was used for integrating biomass carbon, soil carbon and carbon stock mapping. Roth carbon model was used to project the soil carbon of present land‐uses in the coming 10 years and based on which the sustainability of land‐uses was predicted. The total carbon stock of agricultural land‐uses was estimated to be 20·5 Tg, of which 41·49 per cent was biomass carbon and 58·51 per cent was soil carbon. Among the land‐uses, para rubber had the highest average biomass C (136·34 Mg C ha−1) while paddy had the lowest (7·08 Mg C ha−1). About four‐fifths of agricultural land‐uses in the watershed are sustainable in maintaining the desired level of soil carbon in coming 10 years while one‐fifths are unstable. Such information on carbon stock could be valuable to develop viable land‐use options for agricultural sustainability and carbon sequestration. Copyright © 2007 John Wiley & Sons, Ltd.

Estimation and potential improvement of the quality of legacy soil samples for digital soil mapping

Legacy soil data form an important resource for digital soil mapping and are essential for calibration of models for predicting soil properties from environmental variables. Such data arise from traditional soil survey. Methods of soil survey are generally empirical and based on the mental development of the surveyor, correlating soil with underlying geology, landforms, vegetation and air-photo interpretation. There are no statistical criteria for traditional soil sampling, and this may lead to biases in the areas being sampled. The challenge is to test the use of legacy data for large-area mapping (e.g. national or continental extents) in order to limit the funds of field survey for large-area mapping. The problem is then to assess the reliability and quality of the legacy soil databases that have been mainly populated by traditional soil survey, and if there is a possibility of additional funding for sampling, to determine where new sampling units should be located. This additional sampling can be used to improve and validate the prediction model. Latin hypercube sampling (LHS) has been proposed as a sampling design for digital soil mapping when there is no prior sample. We use the principle of hypercube sampling to assess the quality of existing soil data and guide us to locations that need to be sampled. First an area is defined and the empirical environmental data layers or covariates are identified on a regular grid. The existing soil data are matched with the environmental variables. The HELS algorithm is used to check the occupancy of the legacy sampling units in the hypercube of the quantiles of the covarying environmental data. This is to determine whether legacy soil survey data occupy the hypercube uniformly or if there is over- or under-observation in the partitions of the hypercube. It also allows posterior estimation of the apparent probability of sample units being surveyed. From this information we can design further sampling. The methods are illustrated using legacy soil samples from Edgeroi, New South Wales, Australia, and from a large part of the Danube Basin. One third of the total number of sampling units are added to the original dataset. These new sampling units improve the representation of the feature space of the covariate. The standard deviation of the overall density is consequently smaller.

SOIL SPATIAL DISTRIBUTION IN THE ARMORICAN MASSIF, WESTERN FRANCE: EFFECT OF SOIL-FORMING FACTORS

Soil spatial distribution, i.e. the spatial distribution of soils within landscapes, is difficult to predict because numerous processes operate simultaneously, but variably, over time. Quantifications of large areas with an acceptable degree of precision and low in cost require the development of specific methods making the best possible use of existing soil data and auxiliary information such as soil-forming factors. The quantification of the influence of soil-forming factors on soil spatial distribution is seldom performed over large areas such as regions. This study aimed to quantify the relationship between soil spatial distribution and the soil-forming factors of geology, topography, climate, and tectonic regime in order to predict soil spatial distribution over a wide region (30,000 km 2 ). The Armorican Massif (western France), a complex basement of Proterozoic and Paleozoic rocks affected by recent tectonic activity and characterized by variations in topography and climate, was chosen as the study site. Detailed soil maps (1:25,000) were used to describe soil spatial distribution along transects. An ANOVA performed on 314 transects showed a high correlation between the occurrence of soils with particular features (namely redoximorphic, leached, glossic, and albic) and geological substrate, uplift ratio, mean slope gradient, and net rainfall. No such correlation was found with fluvic soils. These soil-forming factors seem to act through saprolite quality and erosion processes, which in turn control the development of soil features. A quantification of the relationship between soil features and soil-forming factors was performed by regression analysis in order to allow further prediction of the soil spatial distribution over the entire Armorican Massif. These results revealed and quantified the hitherto unrecognized role of tectonism on soil distribution and its relative importance in respect to other soil-forming factors. Finally, such an analysis, which is based on existing maps, can help to describe, quantify, and predict detailed soil spatial distribution at smaller scales.

Quantitative mapping of soil types based on regression kriging of taxonomic distances with landform and land cover attributes

Nowadays, French soil scientists tend to gather new and existing soil data into a common database. The use of this database potentially allows for resolving environmental issues, largely through soil mapping. The purpose of this study is to present a methodology for mapping soil types illustrated by typical observations in the soil database, in this case from the La Rochelle area on the French Mid-Atlantic Coast. The main hypothesis underlying the method is that soil types result from environmental factors such as landform, parent material, and land cover. The method can be divided into four stages. The first step is to construct a local soil type classification from the database by a two-stage continuous classification procedure. The result of this procedure is that at each observation point, the soil is described by a vector of taxonomic distances to each of k centroidal soil types. In the example given, k=18. The second step involves fitting soil–environment equations, one for each centroidal soil type, by regressing taxonomic distances on layers of multivariate environmental data observed on a fine 20-m grid, by multiple linear regression. In this case, the layers are terrain attributes derived from a digital elevation model and land cover attributes derived from three bands of a SPOT image. The third step is to predict k maps or raster GIS layers representing taxonomic distances to soil types on the 20-m grid, using the soil–environment equations and the kriging of the residuals from the regressions. This results in many potential maps: a summary map depicting the nearest centroidal soil type (the soil type for which the taxonomic distance is least) at each location is possibly the most useful, and another one representing the minimum taxonomic distance which, if considered too large, might suggest locations for further field survey to refine the soil types. A map of standard errors of the kriged taxonomic distance residuals to the nearest centroidal soil type can be made to indicate spatial uncertainty. Continuous fuzzy membership maps can also be constructed from the distances. The fourth step involves validation with an independent soil data set allowing discovery of the nature of the actual prediction errors. Thirty-eight percent of sites in a validation sample of 1234 sites was unequivocally validated, 23% was equivocally validated, and the remainder was predicted wrongly by the method.

Distributed agro-hydrological modeling of an irrigation system in western Turkey

A clear understanding of all the components of the water balance is essential to analyze possible measures of water savings in irrigated agriculture. However, most components of the water balance are not easily measurable either in terms of the required time interval or the complexity of the processes. For an irrigated area in the Western part of Turkey, the physically based one-dimensional agro-hydrological model SWAP for water transport and crop growth was applied in a distributed manner to reveal all the terms of the water balance. A combination of point data and distributed areal data was used as input for the model. The emphasis was put on the conversion from available data to required data. Simulations were carried out for the period 1985–1996 and detailed analyses were performed for two successive years, a pre-drought year, 1988, and a dry year, 1989. Irrigation deliveries were reduced substantially in 1989, resulting in a modified water balance. Lateral fluxes to drains were reduced, bottom fluxes were changed from groundwater recharge to capillary rise, evapotranspiration was lower, and, most importantly, relative yield was reduced. All these changes were obtained for specific sites by combining existing soil data with cropping patterns. It was concluded that the use of the SWAP model in a distributed way is a useful tool to analyze all the components of the water balance for a whole irrigation system.