Comparing the Effects of Different Daily and Sub-Daily Downscaling Approaches on the Response of Urban Stormwater Collection Systems

Change in the spatiotemporal pattern of precipitation is one the most important effects of climate change. This may result in considerable changes in urban flooding and yield a variation in the rate and volume of stormwater, resulting in the failure of stormwater collection systems. In the current paper, the effects of different downscaling methods on a built urban network have been assessed and compared. The case study is a 320-ha urban watershed with a built stormwater collection system located in the City of Tehran, Iran. Two single (SDSM and DMDM) and two multisite downscaling techniques with a daily temporal resolution have been employed and two sub daily (based of GEV distribution and MOF) methods have been used to further disaggregate the downscaled data. To evaluate the climate change impacts, three climate change scenarios, i.e. RCP 2.6, RCP 4.5 and RCP 8.5, have been used. Based on our findings, DMDM appears to outperform the other techniques in terms of our statistical similarity and dissimilarity metrics for daily downscaling. In addition, the sub-daily disaggregation method via GEV distribution delivers better results in comparison to the MOF. After simulating the stormwater collection system based on the downscaling results, we found that the number of flooded channels and junctions using RCP 8.5 results is significantly higher than RCP 4.5 and RCP 2.6 scenarios, indicating the relatively high risk of urban flooding under RCP 8.5 scenario.