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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/userguides/explore-bristol-research/ebr-terms/ Sensitivity of peak flow to the change of rainfall temporal pattern1 due to warmer climate 2 Abstract 8The widely used design storms in urban drainage networks has different drawbacks. One of 9 them is that the shape of the rainfall temporal pattern is fixed regardless of climate change. 10However, previous studies have shown that the temporal pattern may scale with temperature 11 due to climate change, which consequently affects peak flow. Thus, in addition to the scaling 12 of the rainfall volume, the scaling relationship for the rainfall temporal pattern with 13 temperature needs to be investigated by deriving the scaling values for each fraction within 14 storm events, which is lacking in many parts of the world including the UK. Therefore, this 15 study analysed rainfall data from 28 gauges close to the study area with a 15-min resolution 16 as well as the daily temperature data. It was found that, at warmer temperatures, the rainfall 17 temporal pattern becomes less uniform, with more intensive peak rainfall during higher 18 intensive times and weaker rainfall during less intensive times. This is the case for storms 19 with and without seasonal separations. In addition, the scaling values for both the rainfall 20 volume and the rainfall fractions (i.e. each segment of rainfall temporal pattern) for the 21 summer season were found to be higher than the corresponding results for the winter season. 22Applying the derived scaling values for the temporal pattern of the summer season in a 23 hydrodynamic sewer network model produced high percentage change of peak flow between 24 the current and future climate. This study on the scaling of rainfall fractions is the first in the 25 *Revised Manuscript with no changes marked Click here to view linked References UK, and its findings are of importance to modellers and designers of sewer systems because 26 it can provide more robust scenarios for flooding mitigation in urban areas. 27Keywords: rainfall temporal pattern; scaling for rainfall volume and fraction; climate 28 change; peak flow 29 30

Most areas around the world lack fine rainfall records which are needed to derive Intensity-Duration-Frequency (IDF) curves, and those that are available are in the form of daily data. Thus, the disaggregation of rainfall data from coarse to fine temporal resolution may offer a solution to that problem. Most of the previous studies have adopted only historical rainfall data as the predictor to disaggregate daily rainfall data to hourly resolution, while only a few studies have adopted other historical climate variables besides rainfall for such a purpose. Therefore, this study adopts and assesses the performance of two methods of rainfall disaggregation one uses for historical temperature and rainfall variables while the other uses only historical rainfall data for disaggregation. The two methods are applied to disaggregate the current observed and projected modeled daily rainfall data to an hourly scale for a small urban area in the United Kingdom. Then, the IDF curves for the current and future climates are derived for each case of disaggregation and compared. After which, the uncertainties associated with the difference between the two cases are assessed. The constructed IDF curves (for the two cases of disaggregation) agree in the sense that they both show that there is a big difference between the current and future climates for all durations and frequencies. However, the uncertainty related to the difference between the results of the constructed IDF curves (for the two cases of disaggregation) for each climate is considerable, especially for short durations and long return periods. In addition, the projected and current rainfall values based on disaggregation case which adopts historical temperature and rainfall variables were higher than the corresponding projections and current values based on only rainfall data for the disaggregation.