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Summary: Projections of climate for the 2080s from an ensemble of global climate models (GCMs) run under a medium–high (A2) emissions scenario are used to simulate changes in groundwater resources of a Chalk aquifer in central-southern England. Few studies that have investigated the impacts of climate change on groundwater resources have addressed uncertainty. In this paper the uncertainty associated with use of a suite of GCM outputs in catchment scale impact studies is quantified. A range of predictions is obtained by applying precipitation and temperature change factors, derived from thirteen GCMs, to a distributed recharge model and a groundwater flow model of the Chalk aquifer of the Marlborough and Berkshire Downs and south-west Chilterns in the UK. The ensemble average suggests there will be a 4.9% reduction in annual potential groundwater recharge across the study area, although this is not statistically significant at the 95% confidence level. The spread of results for simulated changes in annual potential groundwater recharge range from a 26% decrease to a 31% increase by the 2080s, with ten predicting a decrease and three an increase. Whilst annual recharge is not found to change significantly, the multi-model results suggest that the seasonal variation in the groundwater resource will be greater, with higher recharge rates during a reduced period of time in winter. The spread of predictions for changes in river baseflow, at the bottom of the largest river sub-catchment, is from −16 to +33% in March and from −68 to −56% in October. The effects of climate change are shown to depend significantly on the type of land-use. It is concluded that further research is required to quantify the effect of different vegetation types on Chalk covered by different thicknesses of soil and their response to a changing climate. [Copyright &y& Elsevier]

Summary: This paper develops tools to assess regional drought events based on limited periods of record and applies them to regional climate model output to examine potential future changes in drought due to increased greenhouse gases. The drought metric was defined as a monthly time series of standardized 12-month precipitation accumulations. Regional drought events were characterised by determining the severity, area, duration and frequency of dry periods. In order to improve statistical inference of drought events, a drought generator was adopted to synthesis a large number of events trained on the available data. In nearly all cases, the drought generator produces synthetic events with drought characteristics statistically indistinguishable from the training data. Severity–Area–Frequency (SAF) curves and Area–Probability (Area–P) curves could then be constructed from the synthetic data to determine the return period of a drought event of a given severity covering a given area. These techniques were applied to observations and to output from the Hadley Centre regional climate model (HadRM3). HadRM3, when driven by climate reanalysis data, has good correlation with the observed drought metric. HadRM3 also captures the timing of observed dry periods but not the relative seriousness of any particular period. Natural variability is large with regional drought characteristics highly dependent on the time period covered by the training data. Although the synthetic drought characteristics of HadRM3 generally overlap with the observed natural variability; the model slightly overestimates the area of observed drought; underestimate its frequency; and underestimate the severity at any given area. HadRM3 projections of changes in drought characteristics over the second half of the 21st century under increased atmospheric greenhouse gases hint at an increase in the severity of drought. However, any changes are not readily distinguishable from natural variability or projection uncertainty. Therefore it is not yet possible to robustly predict changes in UK meteorological droughts arising from increased greenhouse gasses. [Copyright &y& Elsevier]