994 resultados para Soil measurements


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We report on a distributed moisture detection scheme which uses a cable design based on waterswellable hydrogel polymers. The cable modulates the loss characteristic of light guided within a multi-mode optical fibre in response to relative water potentials in the surrounding environment. Interrogation of the cable using conventional optical time-domain reflectometry (OTDR) instruments allows water ingress points to be identified and located with a spatial resolution of 50 cm. The system has been tested in a simulated tendon duct grouting experiment as a means of mapping the extent of fill along the duct during the grouting process. Voided regions were detected and identified to within 50 cm. A series of salt solutions has been used to determine the sensor behaviour over a range of water potentials. These experiments predict that measurements of soil moisture content can be made over the range 0 to – 1500 kPa. Preliminary data on soil measurements have shown that the sensor can detect water pressure changes with a resolution of 45 kPa. Applications for the sensor include quality assurance of grouting procedures, verification of waterproofing barriers and soil moisture content determination (for load-bearing calculations).

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A controlled laboratory experiment is described, in principle and practice, which can be used for the of determination the rate of tissue decomposition in soil. By way of example, an experiment was conducted to determine the effect of temperature (12°C, 22°C) on the aerobic decomposition of skeletal muscle tissue (Organic Texel × Suffolk lamb (Ovis aries)) in a sandy loam soil. Measurements of decomposition processes included muscle tissue mass loss, microbial CO2 respiration, and muscle tissue carbon (C) and nitrogen (N). Muscle tissue mass loss at 22°C always was greater than at 12°C (p < 0.001). Microbial respiration was greater in samples incubated at 22°C for the initial 21 days of burial (p < 0.01). All buried muscle tissue samples demonstrated changes in C and N content at the end of the experiment. A significant correlation (p < 0.001) was demonstrated between the loss of muscle tissue-derived C (C1) and microbially-respired C (Cm) demonstrating CO2 respiration may be used to predict mass loss and hence biodegradation. In this experiment Q10 (12°C - 22°C) = 2.0. This method is recommended as a useful tool in determining the effect of environmental variables on the rate of decomposition of various tissues and associated materials.

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This paper describes a new approach to establish the probabilistic cable rating based on cable thermal environment studies. Knowledge of cable parameters has been well established. However the environment in which the cables are buried is not so well understood. Research in Queensland University of Technology has been aimed at obtaining and analysing actual daily field values of thermal resistivity and diffusivity of the soil around power cables. On-line monitoring systems have been developed and installed with a data logger system and buried spheres that use an improved technique to measure thermal resistivity and diffusivity over a short period. Based on the long-term continuous field data for more than 4 years, a probabilistic approach is developed to establish the correlation between the measured field thermal resistivity values and rainfall data from weather bureau records. Hence, a probabilistic cable rating can be established based on monthly probabilistic distribution of thermal resistivity

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In this paper, an automatic Smart Irrigation Decision Support System, SIDSS, is proposed to manage irrigation in agriculture. Our system estimates the weekly irrigations needs of a plantation, on the basis of both soil measurements and climatic variables gathered by several autonomous nodes deployed in field. This enables a closed loop control scheme to adapt the decision support system to local perturbations and estimation errors. Two machine learning techniques, PLSR and ANFIS, are proposed as reasoning engine of our SIDSS. Our approach is validated on three commercial plantations of citrus trees located in the South-East of Spain. Performance is tested against decisions taken by a human expert.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Ground-penetrating radar (GPR) is widely used for assessment of soil moisture variability in field soils. Because GPR does not measure soil water content directly, it is common practice to use calibration functions that describe its relationship with the soil dielectric properties and textural parameters. However, the large variety of models complicates the selection of the appropriate function. In this article an overview is presented of the different functions available, including volumetric models, empirical functions, effective medium theories, and frequency-specific functions. Using detailed information presented in summary tables, the choice for which calibration function to use can be guided by the soil variables available to the user, the frequency of the GPR equipment, and the desired level of detail of the output. This article can thus serve as a guide for GPR practitioners to obtain soil moisture values and to estimate soil dielectric properties.

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DGT (diffusive gradients in thin-films) has been proposed as a tool for predicting Cd concentrations in rice grain, but there is a lack of authenticating data. To further explore the relationship between DGT measured Cd and concentrations in rice cultivated in challenging, metal degraded, field locations with different heavy metal pollutant sources, 77 paired soil and grain samples were collected in Southern China from industrial zones, a "cancer village" impacted by mining waste and an organic farm. In situ deployments of DGT in flooded paddy rice rhizospheres were compared with a laboratory DGT assay on dried and rewetted soil. Total soil concentrations were a very poor predictor of plant uptake. Laboratory and field deployed DGT assays and porewater measurements were linearly related to grain concentrations in all but the most contaminated samples where plant toxicity occurred. The laboratory DGT assay was the best predictor of grain Cd concentrations, accommodating differences in soil Cd, pollutant source, and Cd:Zn ratios. Field DGT measurements showed that Zn availability in the flooded rice rhizospheres was greatly diminished compared to that of Cd, resulting in very high Cd:Zn ratios (0.1) compared to commonly observed values (0.005). These results demonstrate the potential of the DGT technique to predict Cd concentrations in field cultivated rice and demonstrate its robustness in a range of environments. Although, field deployments provided important details about in situ element stoichiometry, due to the inherent heterogeneity of the rice rhizosphere soils, deployment of DGT in dried and homogenized soils offers the best possibility of a soil screening tool.

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This paper presents a portable electrochemical instrument capable of detecting and identifying heavy metals in soil, in situ. The instrument has been developed for use in a variety of situations to facilitate contaminated land surveys, avoiding expensive and time-consuming procedures. The system uses differential pulse anodic stripping voltammetry which is a precise and sensitive analytical method with excellent limits of detection. The identification of metals is based on a statistical microprocessor-based method. The instrument is capable of detecting six different toxic metals (lead, cadmium, zinc, nickel, mercury and copper) with good sensitivity

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The major focus of this dissertation was to explain terroir effects that impact wine varietal character and to elucidate potential determinants of terroir by testing vine water status (VWS) as the major factor of the terroir effect. It was hypothesized that consistent water status zones could be identified within vineyard sites, and, that differences in vine performance, fruit composition and wine sensory attributes could be related to VWS. To test this hypothesis, ten commercial Riesling vineyards representative of each Vintners Quality Alliance sub-appellation were selected. Vineyards were delineated using global positioning systems and 75 to 80 sentinel vines per vineyard were geo-referenced for data collection. During the 2005 to 2007 growing seasons, VWS measurements [midday leaf water potential ('l')] were collected from a subset of these sentinel vines. Data were collected on soil texture and composition, soil moisture, vine performance (yield components, vine size) and fruit composition. These variables were mapped using global information system (GIS) software and relationships between them were elucidated. Vines were categorized into "low" and "high" water status regions within each vineyard block and replicate wines were made from each. Many geospatial patterns and relationships were spatially and temporally stable within vineyards. Leaf'l' was temporally stable within vineyards despite different weather conditions during each growing season. Generally, spatial relationships between 'l', soil moisture, vine size, berry weight and yield were stable from year to year. Leaf", impacted fruit composition in several vineyards. Through sorting tasks and multidimensional scaling, wines of similar VWS had similar sensory properties. Descriptive analysis further indicated that VWS impacted wine sensory profiles, with similar attributes being different for wines from different water status zones. Vineyard designation had an effect on wine profiles, with certain sensory and chemical attributes being associated from different subappellations. However, wines were generally grouped in terms of their regional designation ('Lakeshore', 'Bench', 'Plains') within the Niagara Peninsula. Through multivariate analyses, specific sensory attributes, viticulture and chemical variables were associated with wines of different VWS. Vine water status was a major contributor to the terroir effect, as it had a major impact on vine size, berry weight and wine sensory characteristics.

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Temporal and spatial patterns of soil water content affect many soil processes including evaporation, infiltration, ground water recharge, erosion and vegetation distribution. This paper describes the analysis of a soil moisture dataset comprising a combination of continuous time series of measurements at a few depths and locations, and occasional roving measurements at a large number of depths and locations. The objectives of the paper are: (i) to develop a technique for combining continuous measurements of soil water contents at a limited number of depths within a soil profile with occasional measurements at a large number of depths, to enable accurate estimation of the soil moisture vertical pattern and the integrated profile water content; and (ii) to estimate time series of soil moisture content at locations where there are just occasional soil water measurements available and some continuous records from nearby locations. The vertical interpolation technique presented here can strongly reduce errors in the estimation of profile soil water and its changes with time. On the other hand, the temporal interpolation technique is tested for different sampling strategies in space and time, and the errors generated in each case are compared.

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In this paper we pledge that physically based equations should be combined with remote sensing techniques to enable a more theoretically rigorous estimation of area-average soil heat flux, G. A standard physical equation (i.e. the analytical or exact method) for the estimation of G, in combination with a simple, but theoretically derived, equation for soil thermal inertia (F), provides the basis for a more transparent and readily interpretable method for the estimation of G; without the requirement for in situ instrumentation. Moreover, such an approach ensures a more universally applicable method than those derived from purely empirical studies (employing vegetation indices and albedo, for example). Hence, a new equation for the estimation of Gamma(for homogeneous soils) is discussed in this paper which only requires knowledge of soil type, which is readily obtainable from extant soil databases and surveys, in combination with a coarse estimate of moisture status. This approach can be used to obtain area-averaged estimates of Gamma(and thus G, as explained in paper II) which is important for large-scale energy balance studies that employ aircraft or satellite data. Furthermore, this method also relaxes the instrumental demand for studies at the plot and field scale (no requirement for in situ soil temperature sensors, soil heat flux plates and/or thermal conductivity sensors). In addition, this equation can be incorporated in soil-vegetation-atmosphere-transfer models that use the force restore method to update surface temperatures (such as the well-known ISBA model), to replace the thermal inertia coefficient.