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Summary: This paper presents new rainfall and runoff data from a UK green roof test bed which has been collected almost-continuously over a 29-month period from 01/01/2007 to 31/05/2009. Overall, the monitoring period was fairly typical of the location’s long-term climatic averages, although the data set includes some extreme events in June 2007, which were associated with serious flooding locally. To focus on the system’s performance under rainfall events likely to be of interest from an urban drainage/stormwater management perspective, return period analysis has been applied to identify those storm events with a rainfall depth in excess of 5mm and a return period greater than one year. According to these criteria, 22 significant events have been identified, of which 21 have reliable runoff records. Overall the roof provided 50.2% cumulative annual rainfall retention, with a total volumetric retention equivalent to 30% during the significant events. The annual performance figures are towards the lower end of a range of international data, probably reflecting the fact that rainfall depths may be higher and evapotranspiration rates lower than in some more continental climatic settings. The roof’s finite retention depth means that the maximum possible retention percentage declines as storm depth increases, and retention varied from between 0 and 20mm, or 0% to 100%. Although some attenuation and delay of peak runoff is generally observed (mean peak flow reduction of 60% for the 21 significant events), the irregularity of natural rainfall patterns, combined with the variable influence of detention storage in specific events, makes the identification of peak-to-peak lag times difficult and arguably meaningless. Regression analyses have been undertaken to explore the potential to predict the roof’s hydrological performance as a function of storm characteristics. However, these are shown to have poor predictive capability, even for the system from which they were derived. Through a detailed examination of data from three contrasting events, it is argued that the inter-event processes are too complex to be captured by this type of modelling approach. Instead, an understanding of the hydrological processes affecting the flux of moisture into and out of the substrate is required to explain the observed runoff response. Locally-derived evapotranspiration rates and the roof’s observed maximum retention capacity are utilised to provide pragmatic guidance on the retention performance to be expected in response to selected design events. [ABSTRACT FROM AUTHOR]

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]