Differences in consequences between peak arrivals and movement directions of an extreme rainfall in flood modeling

To avoid damages and costs for the society due to flooding is it important to be able to model accurate rain scenarios. Due to climate change is it thought that there will be more heavy rainfalls in the future which will increase the risk for flooding. This master thesis will therefore look at the parameters that affect the risk for flooding with focus on raincloud movement and peak arrivals. Earlier research has shown that different directions of the rain will affect the flooding risk differently. Generally will a rain that has the same direction as the downstream flow lead to a higher risk for flooding. The peak arrival time has also shown to lead to different results were a late peak arrival seems to lead to a higher risk for flooding. There is usually too little time and costly to test different movement and peak arrival scenarios, so this report will focus on which of these parameters that have the greatest flooding impact and largest internal variation.  MIKE 21 (created by DHI) is the software used to model the different rain scenarios. The rain types used to test the different scenarios will be a uniform rain, a traditional CDS-rain and five rain shapes that are based on empirical rain types created by SMHI.  The shape of the empirical rains is based on several studies from measured rain events with weather radar. Weather radar have become a fundamental tool in weather forecasting because it can collect data in near real time and also measure the spatial variation inside the rainfall.  These seven mentioned rain types will not be moving, and the rain will have the same spatial intensity over the study area. They will be compared both to each other but also to a CDS-rain that will move over the study area in 4 different directions (north-south, east-west, south - north and west - east).  The different directions gave all very similar results while there was a larger difference between the rain types with different peak arrivals. The peak-value seems to be an important factor when it comes to flooding risk based on the results in this report. The constant uniform rain had the lowest amount of flooded areas while the CDS-rain (which had the highest peak) affected the area the most.