Intensity-duration-frequency curves exploiting neighbouring extreme precipitation data.

Records of precipitation extremes are essential for hydrological design. In urban hydrology, intensity-duration-frequency curves are typically estimated from observation records. However, conventional approaches seldom consider the areal extent of events. If they do, duration-dependent area reduction factors are used, but precipitation is measured at only a few locations. Due to the high spatial variability of precipitation, it is relatively unlikely that a gauged observation network will capture the extremes that occur during a precipitation event. Therefore, the area reduction approach cannot be regarded as the reduction of an observed maximum. To investigate precipitation extremes, spatial aspects need to be considered using different approaches. Here, we both address the conventional practice of area reduction and consider a within-area chance of increased precipitation, defined as the maximum precipitation intensity observed in a cluster within a selected domain. The results show that (1) the risk of urban flooding is routinely underestimated in current design practice, and (2) traditional calculations underestimate extremes by as much as 30-50%. We show how they can be revised sensibly. [ABSTRACT FROM AUTHOR]