Global scale water stages from SAR imagery (GlosSARi) to support global flood forecasting

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.

Singular vector ensemble forecasting systems and the prediction of flow dependent uncertainty

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.

Toward a combined seasonal weather and crop productivity forecasting system: Determination of the working spatial scale

A methodology is presented for the development of a combined seasonal weather and crop productivity forecasting system. The first stage of the methodology is the determination of the spatial scale(s) on which the system could operate; this determination has been made for the case of groundnut production in India. Rainfall is a dominant climatic determinant of groundnut yield in India. The relationship between yield and rainfall has been explored using data from 1966 to 1995. On the all-India scale, seasonal rainfall explains 52% of the variance in yield. On the subdivisional scale, correlations vary between variance r(2) = 0.62 (significance level p < 10(-4)) and a negative correlation with r(2) = 0.1 (p = 0.13). The spatial structure of the relationship between rainfall and groundnut yield has been explored using empirical orthogonal function (EOF) analysis. A coherent, large-scale pattern emerges for both rainfall and yield. On the subdivisional scale (similar to 300 km), the first principal component (PC) of rainfall is correlated well with the first PC of yield (r(2) = 0.53, p < 10(-4)), demonstrating that the large-scale patterns picked out by the EOFs are related. The physical significance of this result is demonstrated. Use of larger averaging areas for the EOF analysis resulted in lower and (over time) less robust correlations. Because of this loss of detail when using larger spatial scales, the subdivisional scale is suggested as an upper limit on the spatial scale for the proposed forecasting system. Further, district-level EOFs of the yield data demonstrate the validity of upscaling these data to the subdivisional scale. Similar patterns have been produced using data on both of these scales, and the first PCs are very highly correlated (r(2) = 0.96). Hence, a working spatial scale has been identified, typical of that used in seasonal weather forecasting, that can form the basis of crop modeling work for the case of groundnut production in India. Last, the change in correlation between yield and seasonal rainfall during the study period has been examined using seasonal totals and monthly EOFs. A further link between yield and subseasonal variability is demonstrated via analysis of dynamical data.

The income requirements of marine protected areas

Given the growing impact of human activities on the sea, managers are increasingly turning to marine protected areas (MPAs) to protect marine habitats and species. Many MPAs have been unsuccessful, however, and lack of income has been identified as a primary reason for failure. In this study, data from a global survey of 79 MPAs in 36 countries were analysed and attempts made to construct predictive models to determine the income requirements of any given MPA. Statistical tests were used to uncover possible patterns and relationships in the data, with two basic approaches. In the first of these, an attempt was made to build an explanatory "bottom-up" model of the cost structures that might be required to pursue various management activities. This proved difficult in practice owing to the very broad range of applicable data, spanning many orders of magnitude. In the second approach, a "top-down" regression model was constructed using logarithms of the base data, in order to address the breadth of the data ranges. This approach suggested that MPA size and visitor numbers together explained 46% of the minimum income requirements (P < 0.001), with area being the slightly more influential factor. The significance of area to income requirements was of little surprise, given its profile in the literature. However, the relationship between visitors and income requirements might go some way to explaining why northern hemisphere MPAs with apparently high incomes still claim to be under-funded. The relationship between running costs and visitor numbers has important implications not only in determining a realistic level of funding for MPAs, but also in assessing from where funding might be obtained. Since a substantial proportion of the income of many MPAs appears to be utilized for amenity purposes, a case may be made for funds to be provided from the typically better resourced government social and educational budgets as well as environmental budgets. Similarly visitor fees, already an important source of funding for some MPAs, might have a broader role to play in how MPAs are financed in the future. (C) 2007 Elsevier Ltd. All rights reserved.

Innovative approach to building systems integration problems: Using systems theory, technological forecasting and scenario planning

Building services are worth about 2% GDP and are essential for the effective and efficient operations of the building. It is increasingly recognised that the value of a building is related to the way it supports the client organisation’s ongoing business operations. Building services are central to the functional performance of buildings and provide the necessary conditions for health, well-being, safety and security of the occupants. They frequently comprise several technologically distinct sub-systems and their design and construction requires the involvement of numerous disciplines and trades. Designers and contractors working on the same project are frequently employed by different companies. Materials and equipment is supplied by a diverse range of manufacturers. Facilities managers are responsible for operation of the building service in use. The coordination between these participants is crucially important to achieve optimum performance, but too often is neglected. This leaves room for serious faults. The need for effective integration is important. Modern technology offers increasing opportunities for integrated personal-control systems for lighting, ventilation and security as well as interoperability between systems. Opportunities for a new mode of systems integration are provided by the emergence of PFI/PPP procurements frameworks. This paper attempts to establish how systems integration can be achieved in the process of designing, constructing and operating building services. The essence of the paper therefore is to envisage the emergent organisational responses to the realisation of building services as an interactive systems network.

An information approach to the dynamics in farm income: implications for farmland markets

The valuation of farmland is a perennial issue for agricultural policy, given its importance in the farm investment portfolio. Despite the significance of farmland values to farmer wealth, prediction remains a difficult task. This study develops a dynamic information measure to examine the informational content of farmland values and farm income in explaining the distribution of farmland values over time.