Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

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.

USE OF SCALED SEMIVARIOGRAMS IN THE PLANNING SAMPLE OF SOIL PHYSICAL PROPERTIES IN SOUTHERN AMAZONAS, BRAZIL

There is a great lack of information from soil surveys in the southern part of the State of Amazonas, Brazil. The use of tools such as geostatistics may improve environmental planning, use and management. In this study, we aimed to use scaled semivariograms in sample design of soil physical properties of some environments in Amazonas. We selected five areas located in the south of the state of Amazonas, Brazil, with varied soil uses, such as forest, archaeological dark earth (ADE), pasture, sugarcane cropping, and agroforestry. Regular mesh grids were set up in these areas with 64 sample points spaced at 10 m from each other. At these points, we determined the particle size composition, soil resistance to penetration, moisture, soil bulk density and particle density, macroporosity, microporosity, total porosity, and aggregate stability in water at a depth of 0.00-0.20 m. Descriptive and geostatistical analyses were performed. The sample density requirements were lower in the pasture area but higher in the forest. We concluded that managed-environments had differences in their soil physical properties compared to the natural forest; notably, the soil in the ADE environment is physically improved in relation to the others. The physical properties evaluated showed a structure of spatial dependence with a slight variability of the forest compared to the others. The use of the range parameter of the semivariogram analysis proved to be effective in determining an ideal sample density.

USE OF SCALED SEMIVARIOGRAMS IN THE PLANNING SAMPLE OF SOIL CHEMICAL PROPERTIES IN SOUTHERN AMAZONAS, BRAZIL

The lack of information concerning the variability of soil properties has been a major concern of researchers in the Amazon region. Thus, the aim of this study was to evaluate the spatial variability of soil chemical properties and determine minimal sampling density to characterize the variability of these properties in five environments located in the south of the State of Amazonas, Brazil. The five environments were archaeological dark earth (ADE), forest, pasture land, agroforestry operation, and sugarcane crop. Regular 70 × 70 m mesh grids were set up in these areas, with 64 sample points spaced at 10 m distance. Soil samples were collected at the 0.0-0.1 m depth. The chemical properties of pH in water, OM, P, K, Ca, Mg, H+Al, SB, CEC, and V were determined at these points. Data were analyzed by descriptive and geostatistical analyses. A large part of the data analyzed showed spatial dependence. Chemical properties were best fitted to the spherical model in almost all the environments evaluated, except for the sugarcane field with a better fit to the exponential model. ADE and sugarcane areas had greater heterogeneity of soil chemical properties, showing a greater range and higher sampling density; however, forest and agroforestry areas had less variability of chemical properties.

SPATIAL UNCERTAINTY OF NUTRIENT LOSS BY EROSION IN SUGARCANE HARVESTING SCENARIOS

The assessment of spatial uncertainty in the prediction of nutrient losses by erosion associated with landscape models is an important tool for soil conservation planning. The purpose of this study was to evaluate the spatial and local uncertainty in predicting depletion rates of soil nutrients (P, K, Ca, and Mg) by soil erosion from green and burnt sugarcane harvesting scenarios, using sequential Gaussian simulation (SGS). A regular grid with equidistant intervals of 50 m (626 points) was established in the 200-ha study area, in Tabapuã, São Paulo, Brazil. The rate of soil depletion (SD) was calculated from the relation between the nutrient concentration in the sediments and the chemical properties in the original soil for all grid points. The data were subjected to descriptive statistical and geostatistical analysis. The mean SD rate for all nutrients was higher in the slash-and-burn than the green cane harvest scenario (Student’s t-test, p<0.05). In both scenarios, nutrient loss followed the order: Ca>Mg>K>P. The SD rate was highest in areas with greater slope. Lower uncertainties were associated to the areas with higher SD and steeper slopes. Spatial uncertainties were highest for areas of transition between concave and convex landforms.

SPATIAL VARIABILITY OF SOIL PROPERTIES IN AN AGRARIAN REFORM SETTLEMENT

ABSTRACT The study of soil chemical and physical properties variability is important for suitable management practices. The aim of this study was to evaluate the spatial variability of soil properties in the Malhada do Meio settlement to subsidize soil use planning. The settlement is located in Chapadinha, MA, Brazil, and has an area of 630.86 ha. The vegetation is seasonal submontane deciduous forest and steppe savanna. The geology is formed of sandstones and siltstones of theItapecuru Formation and by colluvial and alluvial deposits. The relief consists of hills with rounded and flat tops with an average altitude of 67 m, and frequently covered over by ferruginous duricrusts. A total of 183 georeferenced soil samples were collected at the depth of 0.00-0.20 m inPlintossolos, Neossolo andGleissolo. The following chemical variables were analyzed: pH(CaCl2), H+Al, Al, SB, V, CEC, P, K, OM, Ca, Mg, SiO2, Al2O3, and Fe2O3; along with particle size variables: clay, silt, and sand. Descriptive statistical and geostatistical analyses were carried out. The coefficient of variation (CV) was high for most of the variables, with the exception of pH with a low CV, and of sand with a medium CV. The models fitted to the experimental semivariograms of these variables were the exponential and the spherical. The range values were from 999 m to 3,690 m. For the variables pH(CaCl2), SB, and clay, there are three specific areas for land use planning. The central part of the area (zone III), where thePlintossolos Pétricos and Neossolos Flúvicos occur, is the most suitable for crops due to higher macronutrient content, organic matter and pH. Zones I and II are indicated for environmental preservation.

Terrain forms and spatial variability of soil properties in an area cultivatedwith citrus

The technique of precision agriculture and soil-landscape allows delimiting areas for localized management, allowing a localized application of agricultural inputs and thereby may contribute to preservation of natural resources. Therefore, the objective of this work was to characterize the spatial variability of chemical properties and clay content in the context of soil-landscape relationship in a Latosol (Oxisol) under cultivation of citrus. Soil samples were collected at a depth of 0.0-0.2 m in an area of 83.5 ha planted with citrus, as a 50-m intervals grid, with 129 points in concave terrain and 206 points in flat terrain, totaling 335 points. Values for the variables that express the chemical characteristics and clay content of soil properties were analyzed with descriptive statistics and geostatistical modeling of semivariograms for making maps of kriging. The values of range and kriging maps indicated higher variability in the shape of concave topography (top segment) compared with the shape of flat topography (slope and hillside segments below). The identification of different forms of terrain proved to be efficient in understanding the spatial variability of chemical properties and clay content of soil under cultivation of citrus.

Spatial variability of the rainfall erosive potential in the State of Mato Grosso do Sul, Brazil

Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map.Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.

Spatial autocorrelation of ndvi and gvi indices derived from landsat/tm images for soybean crops in the western of the state of Paraná in 2004/2005 crop season

This research aims at studying spatial autocorrelation of Landsat/TM based on normalized difference vegetation index (NDVI) and green vegetation index (GVI) of soybean of the western region of the State of Paraná. The images were collected during the 2004/2005 crop season. The data were grouped into five vegetation index classes of equal amplitude, to create a temporal map of soybean within the crop cycle. Moran I and Local Indicators of Spatial Autocorrelation (LISA) indices were applied to study the spatial correlation at the global and local levels, respectively. According to these indices, it was possible to understand the municipality-based profiles of tillage as well as to identify different sowing periods, providing important information to producers who use soybean yield data in their planning.

Spatial influence of physical and chemical parameters on management zone definition in apple orchards

ABSTRACT Precision agriculture adoption in Brazilian apple orchards is still incipient. This study aimed at evaluating the spatial variability of certain soil properties as soil density, soil penetration resistance, electrical conductivity, yield, and fruit quality in an apple orchard through digital mapping, as well as assessing the correlation between these factors by means of geostatistics, establishing management zones. Forty representative points were set within 2.5 hectares of apple orchard, wherein soil samples were collected and analyzed, besides measurements of fruit quality (Brix degree, size or diameter, pulp firmness and color) to generate an overall index quality. We concluded that the fruit quality indexes, when isolated, did not show strong spatial dependence, unlike the index of fruit quality (FQI), derived from a combination of these parameters, allowing orchard planning according to management zones based on quality.

Modeling, optimizing and simulating robot calibration with accuracy improvement

This work describes techniques for modeling, optimizing and simulating calibration processes of robots using off-line programming. The identification of geometric parameters of the nominal kinematic model is optimized using techniques of numerical optimization of the mathematical model. The simulation of the actual robot and the measurement system is achieved by introducing random errors representing their physical behavior and its statistical repeatability. An evaluation of the corrected nominal kinematic model brings about a clear perception of the influence of distinct variables involved in the process for a suitable planning, and indicates a considerable accuracy improvement when the optimized model is compared to the non-optimized one.

Infestation maps and spatial stability of main weed species in maize culture

A study on the spatial distribution of the major weeds in maize was carried out in 2007 and 2008 in a field located in Golegã (Ribatejo region, Portugal). The geo-referenced sampling focused on 150 points of a 10 x 10 m mesh covering an area of 1.5 ha, before herbicide application and before harvest. In the first year, 40 species (21 botanical families) were identified at seedling stage and only 22 during the last observation. The difference in species richness can be attributed to maize monoculture favouring reduction in species number. Three of the most representative species were selected for the spatial distribution analysis: Solanum nigrum, Chenopodium album and Echinochloa crus-galli. The three species showed an aggregated spatial pattern and spatial stability over both years, although the herbicide effect is evident in the distribution of some of them in the space. These results could be taken into account when planning site-specific treatments in maize.