The abbreviated 'wiki' is used to describe a tool allowing the collaborative development of densely linked set of web pages. Recently, 1 See http://www.iscmem.org/WorkGroup 02.htm 2 See http://cee.uiuc.edu/research/pub/htmlStorage/WorkingGroups/ Uncertainty PUB WG7.pdf References Cameron D. 2006. An application of the UKCIP02 climate change scenarios to flood estimation by continuous simulation for a gauged catchment in the northeast of Scotland, UK (with uncertainty). Journal of Hydrology 328(1-2): 212-226. Defra/Environment Agency. 2003. Risk, performance and uncertainty in Flood and Coastal Defence-A Review. R&D technical Report FD2392/TR1, May 2003, www2.defra.gov.uk/science/ project data/DocumentLibrary/FD2302/FD2302 3434 TSM.pdf. Pappenberger F, Beven KJ. 2006. Ignorance is bliss-or 7 reasons not to use uncertainty analysis. Water Resources Research 42(5): W05302. Doi: 10·1029/2005WR004820. Pappenberger F, Harvey H, Beven KJ, Hall J, Romanovicz R, Smith P. 2005. Risk and Uncertainty-Tools and Implementation -Flood Risk Management Research Consortium (download from www.floodrisk.org.uk and www.floodrisk.net). Lancaster University: Lancaster.
Open Source, in which the source code to software is freely shared and improved upon, has recently risen to prominence as an alternative to the more usual closed approach to software development. A number of high profile projects, such as the Linux operating system kernel and the Apache web server, have demonstrated that Open Source can be technically effective, and companies such as Cygnus Solutions (now owned by Red Hat) and Zope Corporation have demonstrated that it is possible to build successful companies around open source software. Open Source could have significant benefits for hydroinformatics, encouraging widespread interoperability and rapid development. In this paper we present a brief history of Open Source, a summary of some reasons for its effectiveness, and we explore how and why Open Source is of particular interest in the field of hydroinformatics. We argue that for technical, scientific and business reasons, Open Source has a lot to offer.
Flood risk management is in many countries a major expense, and while the returns on this investment, in terms of risk reduction, are also high, the process of developing and choosing between management options is of critical importance. New sources of data and the falling cost of computation have made possible new approaches to options appraisal. The state of the art has a number of limitations, however. We present a comprehensive but parsimonious framework for computational decision analysis in flood risk management that addresses these issues. At its core is a simple but flexible model of change on the decadal time scale of typical option appraisals, including the management interventions that are the subject of decision along with influences, such as climate change, that are independent of the processes of flood risk management. A fully integrated performance model is developed, estimating both costs and benefits. Uncertainty analysis can thereby be applied to performance metrics of direct interest to stakeholders. We illustrate the framework with an implementation for a hypothetical flood risk management decision. We discuss possible variants of the framework that could be extended to fields other than flood risk management.
Risk analysis of areas protected by flood defence systems involves probabilistic analysis of a large number of scenarios in which one or more of the defence sections that make up the system has failed. In systems with large numbers of defence sections, the computational expense of this calculation can be prohibitive. When the probability of failure of each defence section is not negligibly small, sampling approaches that are now in widespread use may not converge on a stable risk estimate in reasonable computational time. To overcome this worrying limitation, this paper reformulates the flood risk calculation in terms of the cumulative distribution function of the volume of floodwater entering a floodplain. An algorithm is presented whose computational expense scales linearly with the number of sections in the flood defence system. The approach is applied to flood risk analysis in areas protected by extensive systems of flood defences in the Thames estuary, revealing how flood risk varies depending on the characteristics of the flood defence system and floodplain topography. It opens up the possibility of more exhaustive risk-based appraisal and uncertainty analysis of flood risk management options than have hitherto been feasible.
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