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Summary: Water companies in the United Kingdom have considered climate change in their water resources plans for more than a decade through studies funded by UK Water Industry Research (UKWIR). This paper presents an initial assessment of the impact of the UK Climate Projections 2009 (UKCP09) on river flows at a national scale for the 2020s under the A1B scenario and the implications for water resource planning. A daily hydrological modelling framework based on two conceptual model structures and the Generalized Likelihood Uncertainty Estimation (GLUE) methodology has been applied to 70 catchments across the UK. A Latin Hypercube Sampling approach was adopted to handle the probabilistic nature of UKCP09. Results show a decrease in mean annual flow over most of the UK, with negative median values of all monthly changes except in winter over the western and northern mountainous areas. Furthermore the results indicate a high likelihood of a significant decline in summer flows. An analysis of variance shows that the main uncertainty in river flow changes comes from the spread in climate projections. Finally results are found to be consistent with a previous UKWIR assessment based on individual projections from 6 Global Climate Models (GCMs) under the A2 scenario. The reduction in summer low-flows, critical for water resources, appears however more limited with UKCP09. Although most expected changes are within natural variability, the drier conditions overall and the greater spread of results with respect to previous assessments indicates a need for testing the robustness of water resource plans. [Copyright &y& Elsevier]

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]