Tezin Türü: Doktora
Tezin Yürütüldüğü Kurum: Dokuz Eylül Üniversitesi, Fen Bilimleri Enstitüsü, in, Türkiye
Tezin Onay Tarihi: 2021
Tezin Dili: İngilizce
Öğrenci: KHALED S.H. ALRAMLAWI
Danışman: Okan Fıstıkoğlu
Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
Özet:The frequency and intensity of extreme rainfall increased in the past century in several areas due to climate change. These increases threat stormwater infrastructure systems. Intensity-Duration-Frequency (IDF) Curves are commonly used for the design and management of urban infrastructure. The currently employed IDF curves are designed mainly based on the stationary assumption, which assumes the extreme rainfall characteristics (statistically) are invariant over time. Climate change is anticipated to alter the local climate conditions. Meaning that the statistical properties of rainfall cannot be considered as a stationary assumption. Consequently, it is crucial to update the IDF curves by considering possible changes in climate. IDF curves can be updated based on Global Climate Models (GCMs). Despite the progress in GCMs, the resolutions of GCMs outputs are too coarse to directly evaluate future changes at a local scale. Therefore, downscaling of GCMs outputs to the desired resolutions are required. This study aims to develop a new methodology that combined statistical downscaling, bias correction, and disaggregation of rainfall to update IDF curves based on GCMs under future projections.