Long Lead Flood Simulation Using Downscaled GCM Data in Arid and Semi-arid Regions: A Case Study

Flood is one of the most calamitous natural disasters that causes extensive property and life damages across the world. It however, could be a blessing due to its special natural water resources recharging value. By simulating the magnitude of probable floods considering the anthropogenic and natural effects and implementing contingency plans, their damages could be reduced. In this paper, the General Circulation Model (GCM) climate change scenarios are employed to simulate future floods. The GCM scenarios include simulation of climatic signals of the future considering green house gas emission forces. In this study a statistical downscaling model (SDSM) has been applied for rainfall downscaling to provide regional results from GCM outputs. Then, a rainfall-runoff model called HECHMS has been employed to estimate runoff in the region. The maximum simulated rainfall for each year that is of high enough potential to cause flood, is introduced into the rainfall-runoff model to simulate the plausible hydrograph of the flood. The proposed procedure is applied to the Kajoo River basin in South Baloochestan region, south-east of Iran.