30 resultados para Methane emissions modeling


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Currently in Brazil, as in other parts of the world, the concern is great with the increase of degraded agricultural soil, which is mostly related to the occurrence of soil compaction. Although soil texture is recognized as a very important component in the soil compressive behaviors, there are few studies that quantify its influence on the structural changes of Latosols in the Brazilian Cerrado region. This study aimed to evaluate structural changes and the compressive behavior of Latosols in Rio Verde, Goiás, through the modeling of additional soil compaction. The study was carried out using five Latosols with very different textures, under different soil compaction levels. Water retention and soil compression curves, and bearing capacity models were determined from undisturbed samples collected on the B horizons. Results indicated that clayey and very clayey Latosols were more susceptible to compression than medium-textured soils. Soil compression curves at density values associate with edaphic functions were used to determine the beneficial pressure (σ b) , i.e., pressure with optimal water retention, and critical pressure (σcrMAC), i.e., pressure with macroporosity below critical levels. These pressure values were higher than the preconsolidation pressure (σp), and therefore characterized as additional compaction. Based on the compressive behavior of these Latosols, it can be concluded that the combined preconsolidation pressure, beneficial pressure and critical pressure allow a better understanding of compression processes of Latosols.

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Soil C-CO2 emissions are sensitive indicators of management system impacts on soil organic matter (SOM). The main soil C-CO2 sources at the soil-plant interface are the decomposition of crop residues, SOM turnover, and respiration of roots and soil biota. The objectives of this study were to evaluate the impacts of tillage and cropping systems on long-term soil C-CO2 emissions and their relationship with carbon (C) mineralization of crop residues. A long-term experiment was conducted in a Red Oxisol in Cruz Alta, RS, Brazil, with subtropical climate Cfa (Köppen classification), mean annual precipitation of 1,774 mm and mean annual temperature of 19.2 ºC. Treatments consisted of two tillage systems: (a) conventional tillage (CT) and (b) no tillage (NT) in combination with three cropping systems: (a) R0- monoculture system (soybean/wheat), (b) R1- winter crop rotation (soybean/wheat/soybean/black oat), and (c) R2- intensive crop rotation (soybean/ black oat/soybean/black oat + common vetch/maize/oilseed radish/wheat). The soil C-CO2 efflux was measured every 14 days for two years (48 measurements), by trapping the CO2 in an alkaline solution. The soil gravimetric moisture in the 0-0.05 m layer was determined concomitantly with the C-CO2 efflux measurements. The crop residue C mineralization was evaluated with the mesh-bag method, with sampling 14, 28, 56, 84, 112, and 140 days after the beginning of the evaluation period for C measurements. Four C conservation indexes were used to assess the relation between C-CO2 efflux and soil C stock and its compartments. The crop residue C mineralization fit an exponential model in time. For black oat, wheat and maize residues, C mineralization was higher in CT than NT, while for soybean it was similar. Soil moisture was higher in NT than CT, mainly in the second year of evaluation. There was no difference in tillage systems for annual average C-CO2 emissions, but in some individual evaluations, differences between tillage systems were noticed for C-CO2 evolution. Soil C-CO2 effluxes followed a bi-modal pattern, with peaks in October/November and February/March. The highest emission was recorded in the summer and the lowest in the winter. The C-CO2 effluxes were weakly correlated to air temperature and not correlated to soil moisture. Based on the soil C conservation indexes investigated, NT associated to intensive crop rotation was more C conserving than CT with monoculture.

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Soil organic matter (SOM) plays an important role in carbon (C) cycle and soil quality. Considering the complexity of factors that control SOM cycling and the long time it usually takes to observe changes in SOM stocks, modeling constitutes a very important tool to understand SOM cycling in forest soils. The following hypotheses were tested: (i) soil organic carbon (SOC) stocks would be higher after several rotations of eucalyptus than in low-productivity pastures; (ii) SOC values simulated by the Century model would describe the data better than the mean of observations. So, the aims of the current study were: (i) to evaluate the SOM dynamics using the Century model to simulate the changes of C stocks for two eucalyptus chronosequences in the Rio Doce Valley, Minas Gerais State, Brazil; and (ii) to compare the C stocks simulated by Century with the C stocks measured in soils of different Orders and regions of the Rio Doce Valley growing eucalyptus. In Belo Oriente (BO), short-rotation eucalyptus plantations had been cultivated for 4.0; 13.0, 22.0, 32.0 and 34.0 years, at a lower elevation and in a warmer climate, while in Virginópolis (VG), these time periods were 8.0, 19.0 and 33.0 years, at a higher elevation and in a milder climate. Soil samples were collected from the 0-20 cm layer to estimate C stocks. Results indicate that the C stocks simulated by the Century model decreased after 37 years of poorly managed pastures in areas previously covered by native forest in the regions of BO and VG. The substitution of poorly managed pastures by eucalyptus in the early 1970´s led to an average increase of C of 0.28 and 0.42 t ha-1 year-1 in BO and VG, respectively. The measured C stocks under eucalyptus in distinct soil Orders and independent regions with variable edapho-climate conditions were not far from the values estimated by the Century model (root mean square error - RMSE = 20.9; model efficiency - EF = 0.29) despite the opposite result obtained with the statistical procedure to test the identity of analytical methods. Only for lower soil C stocks, the model over-estimated the C stock in the 0-20 cm layer. Thus, the Century model is highly promising to detect changes in C stocks in distinct soil orders under eucalyptus, as well as to indicate the impact of harvest residue management on SOM in future rotations.

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A method for determining soil hydraulic properties of a weathered tropical soil (Oxisol) using a medium-sized column with undisturbed soil is presented. The method was used to determine fitting parameters of the water retention curve and hydraulic conductivity functions of a soil column in support of a pesticide leaching study. The soil column was extracted from a continuously-used research plot in Central Oahu (Hawaii, USA) and its internal structure was examined by computed tomography. The experiment was based on tension infiltration into the soil column with free outflow at the lower end. Water flow through the soil core was mathematically modeled using a computer code that numerically solves the one-dimensional Richards equation. Measured soil hydraulic parameters were used for direct simulation, and the retention and soil hydraulic parameters were estimated by inverse modeling. The inverse modeling produced very good agreement between model outputs and measured flux and pressure head data for the relatively homogeneous column. The moisture content at a given pressure from the retention curve measured directly in small soil samples was lower than that obtained through parameter optimization based on experiments using a medium-sized undisturbed soil column.

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The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

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The correct use of closed field chambers to determine N2O emissions requires defining the time of day that best represents the daily mean N2O flux. A short-term field experiment was carried out on a Mollisol soil, on which annual crops were grown under no-till management in the Pampa Ondulada of Argentina. The N2O emission rates were measured every 3 h for three consecutive days. Fluxes ranged from 62.58 to 145.99 ∝g N-N2O m-2 h-1 (average of five field chambers) and were negatively related (R² = 0.34, p < 0.01) to topsoil temperature (14 - 20 ºC). N2O emission rates measured between 9:00 and 12:00 am presented a high relationship to daily mean N2O flux (R² = 0.87, p < 0.01), showing that, in the study region, sampling in the mornings is preferable for GHG.

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Paddy rice fields may contribute to methane (CH4) emission from soil due to anaerobic conditions after flooding. Alternatives to continuous flooding irrigation in rice have been developed to mitigate CH4 efflux into the atmosphere. This study aims to investigate the effects of irrigation managements in the CH4 efflux during the rice growing season. An experiment was carried out at in Santa Maria, Rio Grande do Sul State, Brazil, during 2007/08 and 2009/10 growing seasons. The treatments were continuous flooding and intermittent irrigation in 2007/08 and continuous flooding, intermittent irrigation and flush irrigation in 2009/10. Intermittent irrigation is effective in mitigating CH4 efflux from rice fields when climatic conditions enable water absence during cultivation, but its efficiency depends on the electrochemical soil conditions during the flooding cycles.

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Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.

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Soil can be either source or sink of methane (CH4), depending on the balance between methanogenesis and methanotrophy, which are determined by pedological, climatic and management factors. The objective of this study was to assess the impact of drainage of a highland Haplic Histosol on CH4 fluxes. Field research was carried out in Ponta Grossa (Paraná, Brazil) based on the measurement of CH4 fluxes by the static chamber method in natural and drained Histosol, over one year (17 sampling events). The natural Histosol showed net CH4 eflux, with rates varying from 238 µg m-2 h-1 CH4, in cool/cold periods, to 2,850 µg m-2 h-1 CH4, in warm/hot periods, resulting a cumulative emission of 116 kg ha-1 yr-1 CH4. In the opposite, the drained Histosol showed net influx of CH4 (-39 to -146 µg m-2 h-1), which resulted in a net consumption of 9 kg ha-1 yr-1 CH4. The main driving factors of CH4 consumption in the drained soil were the lowering of the water-table (on average -57 cm, vs -7 cm in natural soil) and the lower water content in the 0-10 cm layer (average of 5.5 kg kg-1, vs 9.9 kg kg-1 in natural soil). Although waterlogged Histosols of highland areas are regarded as CH4 sources, they fulfill fundamental functions in the ecosystem, such as the accumulation of organic carbon (581 Mg ha-1 C to a depth of 1 m) and water (8.6 million L ha-1 = 860 mm to a depth of 1 m). For this reason, these soils must not be drained as an alternative to mitigate CH4 emission, but effectively preserved.

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Estimation of soil load-bearing capacity from mathematical models that relate preconsolidation pressure (σp) to mechanical resistance to penetration (PR) and gravimetric soil water content (U) is important for defining strategies to prevent compaction of agricultural soils. Our objective was therefore to model the σp and compression index (CI) according to the PR (with an impact penetrometer in the field and a static penetrometer inserted at a constant rate in the laboratory) and U in a Rhodic Eutrudox. The experiment consisted of six treatments: no-tillage system (NT); NT with chiseling; and NT with additional compaction by combine traffic (passing 4, 8, 10, and 20 times). Soil bulk density, total porosity, PR (in field and laboratory measurements), U, σp, and CI values were determined in the 5.5-10.5 cm and 13.5-18.5 cm layers. Preconsolidation pressure (σp) and CI were modeled according to PR in different U. The σp increased and the CI decreased linearly with increases in the PR values. The correlations between σp and PR and PR and CI are influenced by U. From these correlations, the soil load-bearing capacity and compaction susceptibility can be estimated by PR readings evaluated in different U.

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ABSTRACT Intrinsic equilibrium constants of 17 representative Brazilian Oxisols were estimated from potentiometric titration measuring the adsorption of H+ and OH− on amphoteric surfaces in suspensions of varying ionic strength. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. The former was fitted by calculating total site concentration from curve fitting estimates and pH-extrapolation of the intrinsic equilibrium constants to the PZNPC (hand calculation), considering one and two reactive sites, and by the FITEQL software. The latter was fitted only by FITEQL, with one reactive site. Soil chemical and physical properties were correlated to the intrinsic equilibrium constants. Both surface complexation models satisfactorily fit our experimental data, but for results at low ionic strength, optimization did not converge in FITEQL. Data were incorporated in Visual MINTEQ and they provide a modeling system that can predict protonation-dissociation reactions in the soil surface under changing environmental conditions.

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ABSTRACT Intrinsic equilibrium constants for 22 representative Brazilian Oxisols were estimated from a cadmium adsorption experiment. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. Intrinsic equilibrium constants were optimized by FITEQL and by hand calculation using Visual MINTEQ in sweep mode, and Excel spreadsheets. Data from both models were incorporated into Visual MINTEQ. Constants estimated by FITEQL and incorporated in Visual MINTEQ software failed to predict observed data accurately. However, FITEQL raw output data rendered good results when predicted values were directly compared with observed values, instead of incorporating the estimated constants into Visual MINTEQ. Intrinsic equilibrium constants optimized by hand calculation and incorporated in Visual MINTEQ reliably predicted Cd adsorption reactions on soil surfaces under changing environmental conditions.

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The objective of this work was to evaluate the effect of biochar application on soil nitrous oxide emissions. The experiment was carried out in pots under greenhouse conditions. Four levels of ground commercial charcoal of 2 mm (biochar) were evaluated in a sandy Albaqualf (90% of sand): 0, 3, 6, and 9 Mg ha-1. All treatments received 100 kg ha-1 of N as urea. A cubic effect of biochar levels was observed on the N2O emissions. Biochar doses above 5 Mg ha-1 started to mitigate the emissions in the evaluated soil. However, lower doses promote the emissions.

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The objective of this work was to evaluate a generalized response function to the atmospheric CO2 concentration [f(CO2)] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (R²), and the root mean square error (RMSE). The f(CO2) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO2 emissions for the next generation of climate scenarios for the 21st century.

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Abstract:The objective of this work was to develop and validate a prognosis system for volume yield and basal area of intensively managed loblolly pine (Pinus taeda) stands, using stand and diameter class models compatible in basal area estimates. The data used in the study were obtained from plantations located in northern Uruguay. For model validation without data loss, a three-phase validation scheme was applied: first, the equations were fitted without the validation database; then, model validation was carried out; and, finally, the database was regrouped to recalibrate the parameter values. After the validation and final parameterization of the models, a simulation of the first commercial thinning was carried out. The developed prognosis system was precise and accurate in estimating basal area production per hectare or per diameter classes. There was compatibility in basal area estimates between diameter class and whole stand models, with a mean difference of -0.01 m2ha-1. The validation scheme applied is logic and consistent, since information on the accuracy and precision of the models is obtained without the loss of any information in the estimation of the models' parameters.