Climate Change Effects on Rainfall and Management of Urban Flooding

Sammanfattning: Flooding in urban basins is intensifying due to increasing urbanization and climate change and variability. This thesis presents how the effects of climate change and high-intensive rainfall on the urban drainage system and management of flooding in urban areas of were studied in Mumbai, India and Southern Sweden, including Skåne and Gothenburg. Various statistical and analytical tools were applied to study trends and extreme events in two study areas. The impact of climate change on Mumbai was studied using nine GCM simulations with bias correction using DBS methodology. For Gothenburg, RCM output and observations were used to predict the characteristics of rainfall. Through use of transient DBS processed projection data, an impact analysis (climate and extreme value statistics) was performed for the future period of the years 2010 to 2099. Trend analysis using the student t-test and the Mann-Kendall test was also performed. Further, Random Cascade modelling was applied on daily rainfall data to reproduce high temporal resolution data for Mumbai. The method can be used for development of IDF curves. The generated data were used for flood modelling in the area and the generation of flood maps. Trends for monthly, seasonal, and annual precipitation were studied for Mumbai (1951-2004). For Southern Sweden, daily and multi-day precipitation trends were studied. Long-term precipitation trends were determined using the Mann-Kendall test, the student t-test, and linear regression. The trends for rainfall in Mumbai were corroborated with climatic indices using multivariate statistical tools, namely PCA and SVD. PCA was also used for explaining variability in RCM-generated precipitation in Gothenburg. Analytical analyses were made of the drainage systems in Mumbai and Gothenburg. Finally, an integrated two dimensional (2D) hydrodynamic runoff model was used to simulate storm-water flooding and related processes in the metropolitan areas of Mumbai, India. The analysis revealed a high degree of variability in rainfall over Mumbai. A significant decreasing trend for long-term southwest monsoon rainfall was found. Also, a decrease in average maximum daily rainfall was indicated. The southwest monsoon rainfall over Mumbai was found to be inversely related to the Indian Ocean dipole, the El Ninõ-Southern Oscillation, and the East Atlantic Pattern. In Southern Sweden, however, annual precipitation has increased significantly due to increasing winter precipitation. There is an increasing trend for maximum annual daily precipitation at one location where the annual maximum often occurs in winter. The number of events with short return periods is increasing, but the number of other extreme events has not increased. Evaluation of the baseline period using the DBS bias correction method showed that observed and scaled rainfall data are strongly correlated and that these can represent various key statistics including mean, variance, and extreme values. The analysis of future long-term climate projections revealed a positive significant trend for 4 out of 9 model simulations for daily extreme rainfall during the period 2010-2099. In the case of Gothenburg, the results obtained pointed towards the usefulness of high resolution RCMs for impact studies. In random cascade modelling, very good agreement between modelled and observed disaggregation rainfall series was found for time scales larger than 1/2 h when short-term data were available. Established IDF-curves showed that the current design standard for Mumbai City has a return period of less than one year. Thus, annual recurring flooding problems in Mumbai appear evident. This was further emphasized in results from flood modelling and analytical studies.