For urban watersheds, the storm sewer network provides indispensable data for flood modeling but often needs to be simplified to balance the conflict between the large amount of data and current computing power. The sensitivity of a flood simulation to the data precision of a storm sewer network needs to be explored to develop reasonable generalization strategies. In this study, the impact of using the stroke scaling method to generalize a storm sewer network on a flood simulation was analyzed in terms of the total inflow of the outfalls and flood results. The results of the three study basins showed that different complexities of a sewer network did not have a significant effect on the outfall's total inflow for an area with a single drainage system but did for an area with multiple drainage systems. In addition, serious flooding was mainly distributed at the backbone pipes, which can be identified with the simplified sewer network. Several effective generalization strategies were developed for sewer networks that consider the distribution characteristics of the drainage system and application requirements. This study is theoretically important for better understanding the data sensitivity of flood modeling and simulation and practically important for improving the modeling efficiency and the accuracy of urban flood simulation.
Herein, the raindrop size distribution (DSD) and rainfall microphysics characteristics are investigated at multiple stations within the Yangtze River Delta (YRD) under two air pollution conditions. Raindrop data from 14 Thies Clima Laser Precipitation Monitor disdrometers spanning approximately 2 years were employed together with corresponding air pollution data. Rain gauge data and several types of meteorological data were also used. The DSD characteristics were found to vary across the YRD; thus, we compiled DSD‐based demarcations between convective rain and stratiform rain at each site. During summer, the average mass‐weighted mean drop diameter parameter value was higher by a mean 20%, and the average normalized intercept parameter value was lower by a mean 12% in polluted atmosphere conditions for both convective rain and stratiform rain, as well as for different rainfall intensity classes. The differences in atmospheric conditions between clear and polluted air conditions partially account for the uncertainties in the DSD characteristics. Air pollution resulted in uncertainty in the shape parameter‐slope parameter relationship and in the rainfall kinetic energy‐rainfall intensity (KE‐R) relationship. The air pollution index can be integrated into the KE‐R relationship to improve the KE simulation accuracy. In addition, air pollution causes some uncertainty in the radar reflectivity‐rainfall intensity (Z‐R) relationship, while the acceptable deviation of the Z‐R relationship did not significantly impact the accuracy of rainfall simulations. This study improves our understanding of DSD and provides a comprehensive overview of the relationship between air pollution and rainfall microphysics for a typical urban agglomeration area.
Designed for rainstorms and flooding, hydrosystems are largely based on local rainfall Intensity-Duration-Frequency (IDF) curves which include nonstationary components accounting for climate variability. IDF curves are commonly calculated using downscaling outputs from General Circulation Models (GCMs) or Regional Circulation Models (RCMs). However, the downscaling procedures used in most studies are based on one specific time scale (e.g., 1 h) and generally ignore scale-driven uncertainty. This study analyzes the uncertainties in IDF curves stemming from RCM downscaling ratios for four representative weather stations in the United Kingdom. We constructed a series of IDF curves using distribution-based scaling bias-correction technology and a statistical downscaling method to explore the scale-driven uncertainty of IDF curves. The results revealed considerable scale-induced uncertainty of IDF curves for short durations and long return periods; however, there was no clear correlation with the mean storm intensity of the IDF curves of different RCM ensemble members for each duration and return period. The scale-driven uncertainty of IDF curves, which may be propagated or enhanced through hydrometeorological applications, is critical and cannot be ignored in the hydrosystem design process; therefore, a multi-scale method to derive IDF curves must be developed.
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