Modeling soil organic carbon dynamics in Oxisols of Ibiruba (Brazil) with the Century Model

introduction of conservation practices in degraded agricultural land will generally recuperate soil quality, especially by increasing soil organic matter. This aspect of soil organic C (SOC) dynamics under distinct cropping and management systems can be conveniently analyzed with ecosystem models such as the Century Model. In this study, Century was used to simulate SOC stocks in farm fields of the Ibiruba region of north central Rio Grande do Sul state in Southern Brazil. The region, where soils are predominantly Oxisols, was originally covered with subtropical woodlands and grasslands. SOC dynamics was simulated with a general scenario developed with historical data on soil management and cropping systems beginning with the onset of agriculture in 1900. From 1993 to 2050, two contrasting scenarios based on no-tillage soil management were established: the status quo scenario, with crops and agricultural inputs as currently practiced in the region and the high biomass scenario with increased frequency of corn in the cropping system, resulting in about 80% higher biomass addition to soils. Century simulations were in close agreement with SOC stocks measured in 2005 in the Oxisols with finer texture surface horizon originally under woodlands. However, simulations in the Oxisols with loamy surface horizon under woodlands and in the grassland soils were not as accurate. SOC stock decreased from 44% to 50% in fields originally under woodland and from 20% to 27% in fields under grasslands with the introduction of intensive annual grain crops with intensive tillage and harrowing operations. The adoption of conservation practices in the 1980s led to a stabilization of SOC stocks followed by a partial recovery of native stocks. Simulations to 2050 indicate that maintaining status quo would allow SOC stocks to recover from 81% to 86% of the native stocks under woodland and from 80% to 91 % of the native stocks under grasslands. Adoption of a high biomass scenario would result in stocks from 75% to 95% of the original stocks under woodlands and from 89% to 102% in the grasslands by 2050. These simulations outcomes underline the importance of cropping system yielding higher biomass to further increase SOC content in these Oxisols. This application of the Century Model could reproduce general trends of SOC loss and recovery in the Oxisols of the Ibiruba region. Additional calibration and validation should be conducted before extensive usage of Century as a support tool for soil carbon sequestration projects in this and other regions can be recommended. (C) 2009 Elsevier B.V. All rights reserved.

Soil CO(2) emission estimated by different interpolation techniques

Soil CO(2) emissions are highly variable, both spatially and across time, with significant changes even during a one-day period. The objective of this study was to compare predictions of the diurnal soil CO(2) emissions in an agricultural field when estimated by ordinary kriging and sequential Gaussian simulation. The dataset consisted of 64 measurements taken in the morning and in the afternoon on bare soil in southern Brazil. The mean soil CO(2) emissions were significantly different between the morning (4.54 mu mol m(-2) s(-1)) and afternoon (6.24 mu mol m(-2) s(-1)) measurements. However, the spatial variability structures were similar, as the models were spherical and had close range values of 40.1 and 40.0 m for the morning and afternoon semivariograms. In both periods, the sequential Gaussian simulation maps were more efficient for the estimations of emission than ordinary kriging. We believe that sequential Gaussian simulation can improve estimations of soil CO(2) emissions in the field, as this property is usually highly non-Gaussian distributed.

Spatial patterns of soil attributes and components in a mangrove system in Southeast Brazil (Sao Paulo)

Purpose Among environmental factors governing innumerous processes that are active in estuarine environments, those of edaphic character have received special attention in recent studies. With the objectives of determining the spatial patterns of soil attributes and components across different mangrove forest landscapes and obtaining additional information on the cause-effect relationships between these variables and position within the estuary, we analyzed several soil attributes in 31 mangrove soil profiles from the state of So Paulo (Guaruja, Brazil). Materials and methods Soil samples were collected at low tide along two transects within the CrumahA(0) mangrove forest. Samples were analyzed to determine pH, Eh, salinity, and the percentages of sand, silt, clay, total organic carbon (TOC), and total S. Mineralogy of the clay fraction (< 2 mm) was also studied by X-ray diffraction analysis, and partitioning of solid-phase Fe was performed by sequential extraction. Results and discussion The results obtained indicate important differences in soil composition at different depths and landscape positions, causing variations in physicochemical parameters, clay mineralogy, TOC contents, and iron geochemistry. The results also indicate that physicochemical conditions may vary in terms of different local microtopographies. Soil salinity was determined by relative position in relation to flood tide and transition areas with highlands. The proportions of TOC and total S are conditioned by the sedimentation of organic matter derived from vegetation and by the prevailing redox conditions, which clearly favored intense sulfate reduction in the soils (similar to 80% of the total Fe is Fe-pyrite). Particle-size distribution is conditioned by erosive/deposition processes (present and past) and probably by the positioning of ancient and reworked sandy ridges. The existing physicochemical conditions appear to contribute to the synthesis (smectite) and transformation (kaolinite) of clay minerals. Conclusions The results demonstrate that the position of soils in the estuary greatly affects soil attributes. Differences occur even at small scales (meters), indicating that both edaphic (soil classification, soil mineralogy, and soil genesis) and environmental (contamination and carbon stock) studies should take such variability into account.

Geochronology of weathering and landscape evolution, Dugald River valley, NW Queensland, Australia

40Ar/39Ar laser incremental heating analyses of individual grains of supergene jarosite, alunite, and cryptomelane from weathering profiles in the Dugald River area, Queensland, Australia, show a strong positive correlation between a sample’s age and its elevation. We analyzed 125 grains extracted from 35 hand specimens collected from weathering profiles at 11 sites located at 3 distinct elevations. The highest elevation profile hosts the oldest supergene minerals, whereas progressively younger samples occur at lower positions in the landscape. The highest elevation sampling sites (three sites), located on top of an elongated mesa (255 to 275 m elevation), yield ages in the 16 to 12 Ma range. Samples from an intermediate elevation site (225 to 230 m elevation) yield ages in the 6 to 4 Ma range. Samples collected at the lowest elevation sites (200 to 220 m elevation) yield ages in the 2.2 to 0.8 Ma interval. Grains of supergene alunite, jarosite, and cryptomelane analyzed from individual single hand specimens yield reproducible results, confirming the suitability of these minerals to 40Ar/39Ar geochronology. Multiple samples collected from the same site also yield reproducible results, indicating that the ages measured are true precipitation ages for the samples analyzed. Different sites, up to 3 km apart, sampled from weathering profiles at the same elevation again yield reproducible results. The consistency of results confirms that 40Ar/39Ar geochronology of supergene jarosite, alunite, and cryptomelane yields ages of formation of weathering profiles, providing a reliable numerical basis for differentiating and correlating these profiles. The age versus elevation relationship obtained suggest that the stepped landscapes in the Dugald River area record a progressive downward migration of a relatively flat weathering front. The steps in the landscape result from differential erosion of previously weathered bedrock displaying different susceptibility to weathering and contrasting resistance to erosion. Combined, the age versus elevation relationships measured yield a weathering rate of 3.8 m. Myr−1 (for the past 15 Ma) if a descending subhorizontal weathering front is assumed. The results also permit the calculation of the erosion rate of the more easily weathered and eroded lithologies, assuming an initially flat landscape as proposed in models of episodic landscape development. The average erosion rate for the past 15 Ma is 3.3 m. Myr−1, consistent with erosion rates obtained by cosmogenic isotope studies in the region.

Empirical catchment-wide rainfall erosivity models for two rivers in the humid tropics of Australia

The concept of rainfall erosivity is extended to the estimation of catchment sediment yield and its variation over time. Five different formulations of rainfall erosivity indices, using annual, monthly and daily rainfall data, are proposed and tested on two catchments in the humid tropics of Australia. Rainfall erosivity indices, using simple power functions of annual and daily rainfall amounts, were found to be adequate in describing the interannual and seasonal variation of catchment sediment yield. The parameter values of these rainfall erosivity indices for catchment sediment yield are broadly similar to those for rainfall erosivity models in relation to the R-factor in the Universal Soil Loss Equation.

A landscape-scale test of the predictive ability of a spatially explicit model for population viability analysis

1. Although population viability analysis (PVA) is widely employed, forecasts from PVA models are rarely tested. This study in a fragmented forest in southern Australia contrasted field data on patch occupancy and abundance for the arboreal marsupial greater glider Petauroides volans with predictions from a generic spatially explicit PVA model. This work represents one of the first landscape-scale tests of its type. 2. Initially we contrasted field data from a set of eucalypt forest patches totalling 437 ha with a naive null model in which forecasts of patch occupancy were made, assuming no fragmentation effects and based simply on remnant area and measured densities derived from nearby unfragmented forest. The naive null model predicted an average total of approximately 170 greater gliders, considerably greater than the true count (n = 81). 3. Congruence was examined between field data and predictions from PVA under several metapopulation modelling scenarios. The metapopulation models performed better than the naive null model. Logistic regression showed highly significant positive relationships between predicted and actual patch occupancy for the four scenarios (P = 0.001-0.006). When the model-derived probability of patch occupancy was high (0.50-0.75, 0.75-1.00), there was greater congruence between actual patch occupancy and the predicted probability of occupancy. 4. For many patches, probability distribution functions indicated that model predictions for animal abundance in a given patch were not outside those expected by chance. However, for some patches the model either substantially over-predicted or under-predicted actual abundance. Some important processes, such as inter-patch dispersal, that influence the distribution and abundance of the greater glider may not have been adequately modelled. 5. Additional landscape-scale tests of PVA models, on a wider range of species, are required to assess further predictions made using these tools. This will help determine those taxa for which predictions are and are not accurate and give insights for improving models for applied conservation management.

Modelling solute transport in structured soils: Performance evaluation of the ADR and TRM models

The movement of chemicals through the soil to the groundwater or discharged to surface waters represents a degradation of these resources. In many cases, serious human and stock health implications are associated with this form of pollution. The chemicals of interest include nutrients, pesticides, salts, and industrial wastes. Recent studies have shown that current models and methods do not adequately describe the leaching of nutrients through soil, often underestimating the risk of groundwater contamination by surface-applied chemicals, and overestimating the concentration of resident solutes. This inaccuracy results primarily from ignoring soil structure and nonequilibrium between soil constituents, water, and solutes. A multiple sample percolation system (MSPS), consisting of 25 individual collection wells, was constructed to study the effects of localized soil heterogeneities on the transport of nutrients (NO3-, Cl-, PO43-) in the vadose zone of an agricultural soil predominantly dominated by clay. Very significant variations in drainage patterns across a small spatial scale were observed tone-way ANOVA, p < 0.001) indicating considerable heterogeneity in water flow patterns and nutrient leaching. Using data collected from the multiple sample percolation experiments, this paper compares the performance of two mathematical models for predicting solute transport, the advective-dispersion model with a reaction term (ADR), and a two-region preferential flow model (TRM) suitable for modelling nonequilibrium transport. These results have implications for modelling solute transport and predicting nutrient loading on a larger scale. (C) 2001 Elsevier Science Ltd. All rights reserved.

Use of bulk density profiles from X-radiography to examine structural crust models

Exponential and sigmoidal functions have been suggested to describe the bulk density profiles of crusts. The present work aims to evaluate these conceptual models using high resolution X-radiography. Repacked seedbeds from two soil materials, air-dried or prewetted by capillary rise, were subjected to simulated rain, which resulted in three types of structural crusts, namely, slaking, infilling, and coalescing. Bulk density distributions with depth were generated using high-resolution (70 mum), calibrated X-ray images of slices from the resin-impregnated crusted seedbeds. The bulk density decreased progressively with depth, which supports the suggestion that a crust should be considered as a nonuniform layer. For the slaking and the coalescing crusts, the exponential function underestimated the strong change in bulk density across the morphologically defined transition between the crust and the underlying material; the sigmoidal function provided a better description. Neither of these crust models effectively described the shape of the bulk density profiles through the whole seedbed. Below the infilling and slaking crusts, bulk density increased linearly with depth as a result of slumping. In the coalescing crusted seedbed, the whole seedbed uniformly collapsed and most of the bulk density change within the crust could be ascribed to slumping (0.33 g cm(-3)) rather than to crusting (0.12 g cm(-3)). Finally, (i) X-radiography appears as a unique tool to generate high resolution bulk density profiles and (ii) in structural crusts, bulk density profiles could be modeled using the existing exponential and sigmoidal crusting models, provided a slumping model would be coupled.

Australia-wide predictions of soil properties using decision trees

This paper describes the construction of Australia-wide soil property predictions from a compiled national soils point database. Those properties considered include pH, organic carbon, total phosphorus, total nitrogen, thickness. texture, and clay content. Many of these soil properties are used directly in environmental process modelling including global climate change models. Models are constructed at the 250-m resolution using decision trees. These relate the soil property to the environment through a suite of environmental predictors at the locations where measurements are observed. These models are then used to extend predictions to the continental extent by applying the rules derived to the exhaustively available environmental predictors. The methodology and performance is described in detail for pH and summarized for other properties. Environmental variables are found to be important predictors, even at the 250-m resolution at which they are available here as they can describe the broad changes in soil property.

Critical comparison of Julius Kruttschnitt Mineral Research Centre (JKMRC) blast fragmentation models

Blast fragmentation can have a significant impact on the profitability of a mine. An optimum run of mine (ROM) size distribution is required to maximise the performance of downstream processes. If this fragmentation size distribution can be modelled and controlled, the operation will have made a significant advancement towards improving its performance. Blast fragmentation modelling is an important step in Mine to Mill™ optimisation. It allows the estimation of blast fragmentation distributions for a number of different rock mass, blast geometry, and explosive parameters. These distributions can then be modelled in downstream mining and milling processes to determine the optimum blast design. When a blast hole is detonated rock breakage occurs in two different stress regions - compressive and tensile. In the-first region, compressive stress waves form a 'crushed zone' directly adjacent to the blast hole. The second region, termed the 'cracked zone', occurs outside the crush one. The widely used Kuz-Ram model does not recognise these two blast regions. In the Kuz-Ram model the mean fragment size from the blast is approximated and is then used to estimate the remaining size distribution. Experience has shown that this model predicts the coarse end reasonably accurately, but it can significantly underestimate the amount of fines generated. As part of the Australian Mineral Industries Research Association (AMIRA) P483A Mine to Mill™ project, the Two-Component Model (TCM) and Crush Zone Model (CZM), developed by the Julius Kruttschnitt Mineral Research Centre (JKMRC), were compared and evaluated to measured ROM fragmentation distributions. An important criteria for this comparison was the variation of model results from measured ROM in the-fine to intermediate section (1-100 mm) of the fragmentation curve. This region of the distribution is important for Mine to Mill™ optimisation. The comparison of modelled and Split ROM fragmentation distributions has been conducted in harder ores (UCS greater than 80 MPa). Further work involves modelling softer ores. The comparisons will be continued with future site surveys to increase confidence in the comparison of the CZM and TCM to Split results. Stochastic fragmentation modelling will then be conducted to take into account variation of input parameters. A window of possible fragmentation distributions can be compared to those obtained by Split . Following this work, an improved fragmentation model will be developed in response to these findings.

Soil remediation time to achieve clean-up goals I: influence of soil water content

The current models are not simple enough to allow a quick estimation of the remediation time. This work reports the development of an easy and relatively rapid procedure for the forecasting of the remediation time using vapour extraction. Sandy soils contaminated with cyclohexane and prepared with different water contents were studied. The remediation times estimated through the mathematical fitting of experimental results were compared with those of real soils. The main objectives were: (i) to predict, through a simple mathematical fitting, the remediation time of soils with water contents different from those used in the experiments; (ii) to analyse the influence of soil water content on the: (ii1) remediation time; (ii2) remediation efficiency; and (ii3) distribution of contaminants in the different phases present into the soil matrix after the remediation process. For sandy soils with negligible contents of clay and natural organic matter, artificially contaminated with cyclohexane before vapour extraction, it was concluded that (i) if the soil water content belonged to the range considered in the experiments with the prepared soils, then the remediation time of real soils of similar characteristics could be successfully predicted, with relative differences not higher than 10%, through a simple mathematical fitting of experimental results; (ii) increasing soil water content from 0% to 6% had the following consequences: (ii1) increased remediation time (1.8–4.9 h, respectively); (ii2) decreased remediation efficiency (99–97%, respectively); and (ii3) decreased the amount of contaminant adsorbed onto the soil and in the non-aqueous liquid phase, thus increasing the amount of contaminant in the aqueous and gaseous phases.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Fire effects on soil after an experimental burnt

5th International Conference of Fire Effects on Soil Properties