Knowledge of the response of extreme precipitation to urbanization is essential to ensure societal preparedness for the extreme events caused by climate change. To quantify this response, this study scales extreme precipitation according to temperature using the statistical quantile regression and binning methods for 231 rain gauges during the period of 1985-2014. The positive 3%-7% scaling rates were found at most stations. The nonstationary return levels of extreme precipitation are investigated using monthly blocks of the maximum daily precipitation, considering the dependency of precipitation on the dewpoint, atmospheric air temperatures, and the North Atlantic Oscillation (NAO) index. Consideration of Coordination of Information on the Environment (CORINE) land-cover types upwind of the stations in different directions classifies stations as urban and nonurban. The return levels for the maximum daily precipitation are greater over urban stations than those over nonurban stations especially after the spring months. This discrepancy was found by 5%-7% larger values in August for all of the classified station types. Analysis of the intensity-duration-frequency curves for urban and nonurban precipitation in August reveals that the assumption of stationarity leads to the underestimation of precipitation extremes due to the sensitivity of extreme precipitation to the nonstationary condition. The study concludes that nonstationary models should be used to estimate the return levels of extreme precipitation by considering the probable covariates such as the dewpoint and atmospheric air temperatures. In addition to the external forces, such as large-scale weather modes, circulation types, and temperature changes that drive extreme precipitation, urbanization could impact extreme precipitation in the Netherlands, particularly for short-duration events.
- Extreme events
- Statistical techniques