223 resultados para Agriculture Forecasting
Resumo:
This study addresses three issues: spatial downscaling, calibration, and combination of seasonal predictions produced by different coupled ocean-atmosphere climate models. It examines the feasibility Of using a Bayesian procedure for producing combined, well-calibrated downscaled seasonal rainfall forecasts for two regions in South America and river flow forecasts for the Parana river in the south of Brazil and the Tocantins river in the north of Brazil. These forecasts are important for national electricity generation management and planning. A Bayesian procedure, referred to here as forecast assimilation, is used to combine and calibrate the rainfall predictions produced by three climate models. Forecast assimilation is able to improve the skill of 3-month lead November-December-January multi-model rainfall predictions over the two South American regions. Improvements are noted in forecast seasonal mean values and uncertainty estimates. River flow forecasts are less skilful than rainfall forecasts. This is partially because natural river flow is a derived quantity that is sensitive to hydrological as well as meteorological processes, and to human intervention in the form of reservoir management.
Resumo:
Despite the success of studies attempting to integrate remotely sensed data and flood modelling and the need to provide near-real time data routinely on a global scale as well as setting up online data archives, there is to date a lack of spatially and temporally distributed hydraulic parameters to support ongoing efforts in modelling. Therefore, the objective of this project is to provide a global evaluation and benchmark data set of floodplain water stages with uncertainties and assimilation in a large scale flood model using space-borne radar imagery. An algorithm is developed for automated retrieval of water stages with uncertainties from a sequence of radar imagery and data are assimilated in a flood model using the Tewkesbury 2007 flood event as a feasibility study. The retrieval method that we employ is based on possibility theory which is an extension of fuzzy sets and that encompasses probability theory. In our case we first attempt to identify main sources of uncertainty in the retrieval of water stages from radar imagery for which we define physically meaningful ranges of parameter values. Possibilities of values are then computed for each parameter using a triangular ‘membership’ function. This procedure allows the computation of possible values of water stages at maximum flood extents along a river at many different locations. At a later stage in the project these data are then used in assimilation, calibration or validation of a flood model. The application is subsequently extended to a global scale using wide swath radar imagery and a simple global flood forecasting model thereby providing improved river discharge estimates to update the latter.
Resumo:
The ECMWF ensemble weather forecasts are generated by perturbing the initial conditions of the forecast using a subset of the singular vectors of the linearised propagator. Previous results show that when creating probabilistic forecasts from this ensemble better forecasts are obtained if the mean of the spread and the variability of the spread are calibrated separately. We show results from a simple linear model that suggest that this may be a generic property for all singular vector based ensemble forecasting systems based on only a subset of the full set of singular vectors.
Resumo:
Reclaimed water provides an important contribution to the water balance in water-scarce Jordan, but the quality of this water presents both benefits and challenges. Careful management of reclaimed water is required to maximize the nutrient benefits while minimizing the salinity risks. This work uses a multi-disciplinary research approach to show that soil response to irrigation with reclaimed water is a function of the management strategies adopted on the farm by the water user. The adoption of management methods to maintain soil productivity can be seen to be a result of farmers’ awareness to potentially plant-toxic ions in the irrigation water (70% of Jordan Valley farmers identified salinization as a hazard from irrigation with reclaimed water). However, the work also suggests that farmers’ management capacity is affected by the institutional management of water. About a third (35%) of farmers in the Jordan Valley claimed that their ability to manage salinization was limited by water shortages. Organizational interviews revealed that institutional awareness of soil management challenges was quite high (34% of interviewees described salinization as a risk from water reuse), but strategies to address this challenge at the institutional level require greater development.
Resumo:
Productivity growth is conventionally measured by indices representing discreet approximations of the Divisia TFP index under the assumption that technological change is Hicks-neutral. When this assumption is violated, these indices are no longer meaningful because they conflate the effects of factor accumulation and technological change. We propose a way of adjusting the conventional TFP index that solves this problem. The method adopts a latent variable approach to the measurement of technical change biases that provides a simple means of correcting product and factor shares in the standard Tornqvist-Theil TFP index. An application to UK agriculture over the period 1953-2000 demonstrates that technical progress is strongly biased. The implications of that bias for productivity measurement are shown to be very large, with the conventional TFP index severely underestimating productivity growth. The result is explained primarily by the fact that technological change has favoured the rapidly accumulating factors against labour, the factor leaving the sector. (C) 2004 Elsevier B.V. All rights reserved.
Resumo:
Sustainable development requires the reconciliation of demands for biodiversity conservation and increased agricultural production. Assessing the impact of novel farming practices on biodiversity and ecosystem services is fundamental to this process. Using farmland birds as a model system, we present a generic risk assessment framework that accurately predicts each species' current conservation status and population growth rate associated with past changes in agriculture. We demonstrate its value by assessing the potential impact on biodiversity of two controversial land uses, genetically modified herbicide-tolerant crops and agri-environment schemes. This framework can be used to guide policy and land management decisions and to assess progress toward sustainability targets.
Biosecurity in agriculture: an economic analysis of coexistence of professional and hobby production
Resumo:
One component of biosecurity is protection against invasive alien species, which are one of the most important threats worldwide to native biodiversity and economic profitability in various sectors, including agriculture. However, agricultural producers are not homogeneous. They may have different objectives and priorities, use different technologies, and occupy heterogeneous parcels of land. If the producers differ in terms of their attitude towards invasive pests and the damages they cause, there are probably external effects in the form of pest spread impacts and subsequent damages caused. We study such impacts in the case of two producer types: profit-seeking professional producers and utility-seeking hobby producers. We show that the hobby producer, having first set a breeding ground for the pest, under-invests in pest control. We also discuss potential policy instruments to correct this market failure and highlight the importance of considering different stakeholders and their heterogeneous incentives when designing policies to control invasive alien species.