6 resultados para Fate and transport ocean model

em eResearch Archive - Queensland Department of Agriculture


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In Australia communities are concerned about atrazine being detected in drinking water supplies. It is important to understand mechanisms by which atrazine is transported from paddocks to waterways if we are to reduce movement of agricultural chemicals from the site of application. Two paddocks cropped with grain sorghum on a Black Vertosol were monitored for atrazine, potassium chloride (KCl) extractable atrazine, desethylatrazine (DEA), and desisopropylatrazine (DIA) at 4 soil depths (0-0.05, 0.05-0.10, 0.10-0.20, and 0.20-0.30 m) and in runoff water and runoff sediment. Atrazine + DEA + DIA (total atrazine) had a half-life in soil of 16-20 days, more rapid dissipation than in many earlier reports. Atrazine extracted in dilute potassium chloride, considered available for weed control, was initially 34% of the total and had a half-life of 15-20 days until day 30, after which it dissipated rapidly with a half life of 6 days. We conclude that, in this region, atrazine may not pose a risk for groundwater contamination, as only 0.5% of applied atrazine moved deeper than 0.20 m into the soil, where it dissipated rapidly. In runoff (including suspended sediment) atrazine concentrations were greatest during the first runoff event (57 days after application) (85 μg/L) and declined with time. After 160 days, the total atrazine lost in runoff was 0.4% of the initial application. The total atrazine concentration in runoff was strongly related to the total concentration in soil, as expected. Even after 98% of the KCl-extractable atrazine had dissipated (and no longer provided weed control), runoff concentrations still exceeded the human health guideline value of 40 μg/L. For total atrazine in soil (0-0.05 m), the range for coefficient of soil sorption (Kd) was 1.9-28.4 mL/g and for soil organic carbon sorption (KOC) was 100-2184 mL/g, increasing with time of contact with the soil and rapid dissipation of the more soluble, available phase. Partition coefficients in runoff for total atrazine were initially 3, increasing to 32 and 51 with time, values for DEA being half these. To minimise atrazine losses, cultural practices that maximise rain infiltration, and thereby minimise runoff, and minimise concentrations in the soil surface should be adopted.

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Near infrared spectroscopy (NIRS) can be used for the on-line, non-invasive assessment of fruit for eating quality attributes such as total soluble solids (TSS). The robustness of multivariate calibration models, based on NIRS in a partial transmittance optical geometry, for the assessment of TSS of intact rockmelons (Cucumis melo) was assessed. The mesocarp TSS was highest around the fruit equator and increased towards the seed cavity. Inner mesocarp TSS levels decreased towards both the proximal and distal ends of the fruit, but more so towards the proximal end. The equatorial region of the fruit was chosen as representative of the fruit for near infrared assessment of TSS. The spectral window for model development was optimised at 695-1045 nm, and the data pre-treatment procedure was optimised to second-derivative absorbance without scatter correction. The 'global' modified partial least squares (MPLS) regression modelling procedure of WINISI (ver. 1.04) was found to be superior with respect to root mean squared error of prediction (RMSEP) and bias for model predictions of TSS across seasons, compared with the 'local' MPLS regression procedure. Updating of the model with samples selected randomly from the independent validation population demonstrated improvement in both RMSEP and bias with addition of approximately 15 samples.

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Cultivation and cropping of soils results in a decline in soil organic carbon and soil nitrogen, and can lead to reduced crop yields. The CENTURY model was used to simulate the effects of continuous cultivation and cereal cropping on total soil organic matter (C and N), carbon pools, nitrogen mineralisation, and crop yield from 6 locations in southern Queensland. The model was calibrated for each replicate from the original datasets, allowing comparisons for each replicate rather than site averages. The CENTURY model was able to satisfactorily predict the impact of long-term cultivation and cereal cropping on total organic carbon, but was less successful in simulating the different fractions and nitrogen mineralisation. The model firstly over-predicted the initial (pre-cropping) soil carbon and nitrogen concentration of the sites. To account for the unique shrinking and swelling characteristics of the Vertosol soils, the default annual decomposition rates of the slow and passive carbon pools were doubled, and then the model accurately predicted initial conditions. The ability of the model to predict carbon pool fractions varied, demonstrating the difficulty inherent in predicting the size of these conceptual pools. The strength of the model lies in the ability to closely predict the starting soil organic matter conditions, and the ability to predict the impact of clearing, cultivation, fertiliser application, and continuous cropping on total soil carbon and nitrogen.

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Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.

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This paper describes the employment of two experienced graziers as consultants to apply and evaluate a model for calculating 'safe' long-term grazing capacities of individual properties. The model was based on ecological principles and entailed estimates of average annual forage grown (kglha) on the different land systems on each property and the calculation of the number of livestock (dry sheep equivalents, DSE) required to 'safely' utilise this forage. The grazier consultants applied and evaluated the 'safe' grazing capacity model on 20 properties of their choosing. For evaluation, model results were compared with; (a) the Department of Lands rated carrying capacities for those properties and (b) the grazing capacity assessed independently by the owners of those properties. For the 20 properties, the average 'safe' grazing capacity calculated by the model (21.0 DSE/kmZ) was 8% lighter than the average of the owner assessed capacities (22.7 DSE/kmZ), which in tum was 37% lighter than the average of the pre-1989 Department of Lands rated carrying capacity (31.0 DSE/kmZ). The grazing land management and administrative implications of these results and the role graziers played as consultants are discussed.

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Wheat is at peak quality soon after harvest. Subsequently, diverse biota use wheat as a resource in storage, including insects and mycotoxin-producing fungi. Transportation networks for stored grain are crucial to food security and provide a model system for an analysis of the population structure, evolution, and dispersal of biota in networks. We evaluated the structure of rail networks for grain transport in the United States and Eastern Australia to identify the shortest paths for the anthropogenic dispersal of pests and mycotoxins, as well as the major sources, sinks, and bridges for movement. We found important differences in the risk profile in these two countries and identified priority control points for sampling, detection, and management. An understanding of these key locations and roles within the network is a new type of basic research result in postharvest science and will provide insights for the integrated pest management of high-risk subpopulations, such as pesticide-resistant insect pests.