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A computationally inexpensive inundation model has been developed from freely available data sources for the northern Bay of Bengal region to estimate flood risk from storm surges. This is the first time Shuttle Radar Topography Mission (SRTM) terrain data have been used in a dynamic coastal inundation model. To reduce SRTM noise, and the impact of vegetation artefacts on the ground elevation, the SRTM data were up-scaled from their native 90 m resolution to 900 m. A sub-grid routine allowed estuary channels with widths less than this resolution to be simulated efficiently, and allowed six major river flows to be represented. The inundation model was forced with an IIT-D model hindcast of the 2007 cyclone Sidr flood event, using parameters from two cyclone databases (IBTrACs and UNISYS). Validation showed inundation prediction accuracy with a root mean squared error (RMSE) on predicted water level of ∼ 2 m, which was of the same order of magnitude as the forcing water-level uncertainties. Therefore, SRTM and other publicly available data can be useful for coastal flood risk management in data-poor regions, although the associated uncertainty needs to be expressed to end users. Better SRTM processing techniques may improve inundation model performance, and future work should also seek to improve storm tide uncertainties in this region.

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Many software model checkers only detect counterexamples with deep loops after exploring numerous spurious and increasingly longer counterexamples. We propose a technique that aims at eliminating this weakness by constructing auxiliary paths that represent the effect of a range of loop iterations. Unlike acceleration, which captures the exact effect of arbitrarily many loop iterations, these auxiliary paths may under-approximate the behaviour of the loops. In return, the approximation is sound with respect to the bit-vector semantics of programs. Our approach supports arbitrary conditions and assignments to arrays in the loop body, but may as a result introduce quantified conditionals. To reduce the resulting performance penalty, we present two quantifier elimination techniques specially geared towards our application. Loop under-approximation can be combined with a broad range of verification techniques. We paired our techniques with lazy abstraction and bounded model checking, and evaluated the resulting tool on a number of buffer overflow benchmarks, demonstrating its ability to efficiently detect deep counterexamples in C programs that manipulate arrays.

LEWIS, M.; HORSBURGH, K.; BATES, P., and SMITH, R., 2011. Quantifying the uncertainty in future coastal flood risk estimates for the U.K. Journal of Coastal Research, 27(5), 870-881. West Palm Beach (Florida), ISSN 0749-0208.Future sea-level rise will increase coastal flood risk in the U.K., yet the hazard uncertainties associated with such future risk estimates have not been fully explored. The sensitivity of coastal flood-risk mapping to future uncertainties was investigated by propagating ranges of plausible parameters through a LISFLOOD inundation model of a significant historic flood event to the North Somerset (U.K.) coast. Mean sea-level rise (including land movement) was found to have the greatest effect on the extent of flood inundation. Analysis of the latest research into the future storm-surge climate of the U.K. indicates no change above natural variability, thus, future, extreme water-level estimates (for the U.K.) should be based on observations and not Regional Circulation Models until research indicates otherwise. Evidence suggests that the current approach of forcing the inundation model with an extreme water level of a constant return period is incorrect. This uncertainty of the peak storm tide height along the coastline had a significant effect on our results. We present a new boundary-forcing technique to force the inundation model with (method C), based on the spatial characteristics of real events, which can account for the natural storm-surge variability. Indeed, if sea-level rise is included with method C, a great deal of the uncertainty surrounding such a future flood-hazard estimate can be quantified and communicated clearly and effectively.www.JCRonline.org ADDITIONAL INDEX WORDS: Flood risk, coastal inundation, sea level rise, storm tide, extreme water level, uncertainty.

a b s t r a c tIn addition to technical and economic constraints, tidal energy leasing is generally governed by demand for sites which contain the highest tidal streams, and does not take into account the phase relationship (i.e. the time lag) between sites. Here, the outputs of a three-dimensional tidal model are analysed to demonstrate that there is minimal phase diversity among the high tidal stream regions of the NW European shelf seas. It is therefore possible, under the current leasing system, that the electricity produced by the first generation of tidal stream arrays will similarly be in phase. Extending the analysis to lower tidal stream regions, we demonstrate that these lower energy sites offer more potential for phase diversity, with a mean phase difference of 1.25 h, compared to the phase of high energy sites, and hence more scope for supplying firm power to the electricity grid. We therefore suggest that a state-led leasing strategy, favouring the development of sites which are complementary in phase, and not simply sites which experience the highest current speeds, would encourage a sustainable tidal energy industry.

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