Thesis Type: Postgraduate

Institution Of The Thesis: Middle East Technical University, Graduate School of Natural and Applied Sciences, Turkey

Approval Date: 2020

Thesis Language: English


Supervisor: İsmail Yücel


Flash floods are among the most destructive natural disasters in both Turkey and world that cause loss of life and property. In this study, monthly distribution of heavy rainfall events in the period of 2015-2019 is examined to show the frequency and distribution of flash floods associated with these heavy rainfall events in Turkey. The monthly distribution of lightning observations for the period of 2015 and 2019 is also studied to release the relationship between heavy rainfall events and lightning flashes during warm season. Black Sea and Middle East Flash Flood Guidance System (BSMEFFGS) is used for flash floods warnings in Turkey. The system compares rainfall threshold values (Flash Flood Guidance, FFG) with basin-based rainfall estimates and predictions. ALARO, ECMWF and WRF numerical weather prediction (NWP) models provide rainfall predictions within the system. In this study, ten flash flood events resulted from different precipitation characteristics occurred between 2017 and 2019 in Turkey are determined to evaluate the NWP models. The success of the NWP models is measured with whether FFG threshold values were exceeded by rainfall predictions through these flash flood cases. vi In this study, it is determined that heavy rainfall events often occur over interior parts of Turkey during warm season due to convective instability conditions especially in May and June. It is proven in this study that lightning observations have the potential to be used for nowcasting flash flood warnings because of similar distribution of heavy rainfall events and lightning flashes during warm season. It is derived from the flash flood case studies that the NWP models within the BSMEFFGS are successful in capturing the flash floods caused by nonconvective heavy rainfalls, while the models up to some extent are capable for convective-induced events.