108 resultados para Soil and Water Assessment Tool (SWAT)
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An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.
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Proceedings of the 9th International Conference of the International Soil conservation Organisation (ISCO-9), from 26-30 August 1996 in Bonn, Germany
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Off-site effects of soil erosion are becoming increasingly important, particularly the pollution of surface waters. In order to develop environmentally efficient and cost effective mitigation options it is essential to identify areas that bear both a high erosion risk and high connectivity to surface waters. This paper introduces a simple risk assessment tool that allows the delineation of potential critical source areas (CSA) of sediment input into surface waters concerning the agricultural areas of Switzerland. The basis are the erosion risk map with a 2 m resolution (ERM2) and the drainage network, which is extended by drained roads, farm tracks, and slope depressions. The probability of hydrological and sedimentological connectivity is assessed by combining soil erosion risk and extended drainage network with flow distance calculation. A GIS-environment with multiple-flow accumulation algorithms is used for routing runoff generation and flow pathways. The result is a high resolution connectivity map of the agricultural area of Switzerland (888,050 ha). Fifty-five percent of the computed agricultural area is potentially connected with surface waters, 45% is not connected. Surprisingly, the larger part of 34% (62% of the connected area) is indirectly connected with surface waters through drained roads, and only 21% are directly connected. The reason is the topographic complexity and patchiness of the landscape due to a dense road and drainage network. A total of 24% of the connected area and 13% of the computed agricultural area, respectively, are rated with a high connectivity probability. On these CSA an adapted land use is recommended, supported by vegetated buffer strips preventing sediment load. Even areas that are far away from open water bodies can be indirectly connected and need to be included in planning of mitigation measures. Thus, the connectivity map presented is an important decision-making tool for policy-makers and extension services. The map is published on the web and thus available for application.
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With the publication of the quality guideline ICH Q9 "Quality Risk Management" by the International Conference on Harmonization, risk management has already become a standard requirement during the life cycle of a pharmaceutical product. Failure mode and effect analysis (FMEA) is a powerful risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to biopharmaceutical processes brings about some difficulties. The proposal presented here is intended to serve as a brief but nevertheless comprehensive and detailed guideline on how to conduct a biopharmaceutical process FMEA. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. The application for such a biopharmaceutical process FMEA is widespread. It can be useful whenever a biopharmaceutical manufacturing process is developed or scaled-up, or when it is transferred to a different manufacturing site. It may also be conducted during substantial optimization of an existing process or the development of a second-generation process. According to their resulting risk ratings, process parameters can be ranked for importance and important variables for process development, characterization, or validation can be identified. LAY ABSTRACT: Health authorities around the world ask pharmaceutical companies to manage risk during development and manufacturing of pharmaceuticals. The so-called failure mode and effect analysis (FMEA) is an established risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to pharmaceutical processes that use modern biotechnology (biopharmaceutical processes) brings about some difficulties, because those biopharmaceutical processes differ from processes in mechanical and electrical industries. The proposal presented here explains how a biopharmaceutical process FMEA can be conducted. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. With the help of this guideline, different details of the manufacturing process can be ranked according to their potential risks, and this can help pharmaceutical companies to identify aspects with high potential risks and to react accordingly to improve the safety of medicines.
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It has been proposed that gonadotropins and/or gonadotropin releasing hormone (GnRH) could be involved in the pathophysiology of the side effects after spaying in bitches, such as urinary incontinence and an increased production of a woolly undercoat. In order to provide tools to investigate the role of these hormones in dogs we developed immunohistochemical techniques and real-time RT-PCR to study whether GnRH-, LH-, and FSH-receptors exist in canine skin and urinary bladder. Tissue samples from the skin of the flank region and the ventral midline of the urinary bladder from euthanised dogs were examined. We were able to quantify mRNA expression of GnRH-, FSH-, and LH-receptors in canine skin and bladder biopsies with a high primer efficacy. Immunohistochemical studies showed that GnRH-, FSH-, and LH-receptors are expressed in vessel walls, the epidermis, the hair follicle and in sebaceous and sweat glands in canine skin and in transitional epithelium, and smooth muscle tissue in the urinary bladder. Our data provide the fundamentals to examine the distribution of FSH-, LH-, and GnRH-receptors in canine skin and urinary bladder and to assess gene activity at the transcriptional level by real-time RT-PCR.
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Traditionally, desertification research has focused on degradation assessments, whereas prevention and mitigation strategies have not sufficiently been emphasised, although the concept of sustainable land management (SLM) is increasingly being acknowledged. SLM strategies are interventions at the local to regional scale aiming at increasing productivity, protecting the natural resource base, and improving livelihoods. The global WOCAT initiative and its partners have developed harmonized frameworks to compile, evaluate and analyse the impact of SLM practices around the globe. Recent studies within the EU research project DESIRE developed a methodological framework that combines a collective learning and decision-making approach with use of best practices from the WOCAT database. In-depth assessment of 30 technologies and 8 approaches from 17 desertification sites enabled an evaluation of how SLM addresses prevalent dryland threats such as water scarcity, soil and vegetation degradation, low production, climate change, resource use conflicts and migration. Among the impacts attributed to the documented technologies, those mentioned most were diversified and enhanced production and better management of water and soil degradation, whether through water harvesting, improving soil moisture, or reducing runoff. Water harvesting offers under-exploited opportunities for the drylands and the predominantly rainfed farming systems of the developing world. Recently compiled guidelines introduce the concepts behind water harvesting and propose a harmonised classification system, followed by an assessment of suitability, adoption and up-scaling of practices. Case studies go from large-scale floodwater spreading that make alluvial plains cultivable, to systems that boost cereal production in small farms, as well as practices that collect and store water from household compounds. Once contextualized and set in appropriate institutional frameworks, they can form part of an overall adaptation strategy for land users. More field research is needed to reinforce expert assessments of SLM impacts and provide the necessary evidence-based rationale for investing in SLM. This includes developing methods to quantify and value ecosystem services, both on-site and off-site, and assess the resilience of SLM practices, as currently aimed at within the new EU CASCADE project.
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Exposure to combination antiretroviral therapy (cART) can lead to important metabolic changes and increased risk of coronary heart disease (CHD). Computerized clinical decision support systems have been advocated to improve the management of patients at risk for CHD but it is unclear whether such systems reduce patients' risk for CHD.
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Soil erosion on sloping agricultural land poses a serious problem for the environment, as well as for production. In areas with highly erodible soils, such as those in loess zones, application of soil and water conservation measures is crucial to sustain agricultural yields and to prevent or reduce land degradation. The present study, carried out in Faizabad, Tajikistan, was designed to evaluate the potential of local conservation measures on cropland using a spatial modelling approach to provide decision-making support for the planning of spatially explicit sustainable land use. A sampling design to support comparative analysis between well-conserved units and other field units was established in order to estimate factors that determine water erosion, according to the Revised Universal Soil Loss Equation (RUSLE). Such factor-based approaches allow ready application using a geographic information system (GIS) and facilitate straightforward scenario modelling in areas with limited data resources. The study showed first that assessment of erosion and conservation in an area with inhomogeneous vegetation cover requires the integration of plot-based cover. Plot-based vegetation cover can be effectively derived from high-resolution satellite imagery, providing a useful basis for plot-wise conservation planning. Furthermore, thorough field assessments showed that 25.7% of current total cropland is covered by conservation measures (terracing, agroforestry and perennial herbaceous fodder). Assessment of the effectiveness of these local measures, combined with the RUSLE calculations, revealed that current average soil loss could be reduced through low-cost measures such as contouring (by 11%), fodder plants (by 16%), and drainage ditches (by 53%). More expensive measures such as terracing and agroforestry can reduce erosion by as much as 63% (for agroforestry) and 93% (for agroforestry combined with terracing). Indeed, scenario runs for different levels of tolerable erosion rates showed that more cost-intensive and technologically advanced measures would lead to greater reduction of soil loss. However, given economic conditions in Tajikistan, it seems advisable to support the spread of low-cost and labourextensive measures.