[1] Increasing availability of ensemble outputs from general circulation models (GCMs) and regional climate models (RCMs) permits fuller examination of the implications of climate uncertainties in hydrological systems. A Bayesian statistical framework is used to combine projections by weighting and to generate probability distributions of local climate change from an ensemble of RCM outputs. A stochastic weather generator produces corresponding daily series of rainfall and potential evapotranspiration, which are input into a catchment rainfall-runoff model to estimate future water abstraction availability. The method is applied to the Thames catchment in the United Kingdom, where comparison with previous studies shows that different downscaling methods produce significantly different flow predictions and that this is partly attributable to potential evapotranspiration predictions. An extended sensitivity test exploring the effect of the weights and assumptions associated with combining climate model projections illustrates that under all plausible assumptions the ensemble implies a significant reduction in catchment water resource availability.

[1] Bayesian theory of model calibration provides a coherent framework for distinguishing and encoding multiple sources of uncertainty in probabilistic predictions of flooding. This paper demonstrates the use of a Bayesian approach to computer model calibration, where the calibration data are in the form of spatial observations of flood extent. The Bayesian procedure involves generating posterior distributions of the flood model calibration parameters and observation error, as well as a Gaussian model inadequacy function, which represents the discrepancy between the best model predictions and reality. The approach is first illustrated with a simple didactic example and is then applied to a flood model of a reach of the river Thames in the UK. A predictive spatial distribution of flooding is generated for a flood of given severity.

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Many of the earthworks that support UK transport networks are suffering because of their age and historical lack of investment in maintenance and repair. Current asset owners have to satisfy users' expectations of minimal delay in the context of ageing assets, imperfect knowledge of their condition, limited resources, increasing traffic, higher speeds, increasing environmental standards and an increasing threat from climate change. This paper summarises current asset-management practice for infrastructure embankments and illustrates how current research is providing information to assist asset owners in improving asset-management practice in the light of climate change. Additionally, it re-examines asset-management practice using a simple sustainability-based framework.

Abstract:A methodology is developed to examine the susceptibility of a transport system to rainfall-induced landslides and is demonstrated for part of the UK rail network with regard to the potential changes that might occur with climate change. A mathematical model is given for the system failure and a statistical model is formulated for the joint distribution of rainfall at different points along the railway line. These are used to investigate the response of earth embankments along the railway line to current and future climate scenarios, including the effects of rainfall and evapotranspiration on slope hydrology and stability. It is shown that, for the system of clay embankments in question, the moisture profile through the embankment at the end of the summer months has a critical effect on system stability, both in terms of expected failure timing and probability of failure. Further, it is seen that, with changing climate, the system stability is likely to increase unless the degradation of embankment material properties, another potential effect of changed climate, is taken into account. The spatial distribution of failures is also likely to change.