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Hüsamettin Tayşi
Gebze Technical University

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Preprint content
Published: 18 March 2021
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Heavy increase in urbanization, industrialization and population is causing an increase in emissions of greenhouse gases (GHG) and this causes variations in atmosphere. Climate change causes extreme rainfall events and these events are expected to be enhanced in the future. Since flooding is influencing urban areas, controlling and management of flooding is a major necessity. Intensity-Duration-Frequency (IDF) curves play a huge role in representing rainfall characteristics by linking intensity, duration, and frequency of rainfall. Analysing short-duration rainfall is crucial for urban areas due to fast responses of drainage systems against heavy rainfall events. IDF curves were generated via the Gumbel method for rainfalls from 5-min to 24-h in this study. However, providing short-duration rainfall data is challenging due to the low capacity, costs and geographic conditions. Therefore, the HYETOS disaggregation model was applied to obtain sub-hourly data. IDF curves are stationary since they only consider historical events. However, IDF curves must be non-stationary and time varying based on preparation for upcoming extreme events. This study aims to generate IDF curves under climate change scenarios. The Regional Climate Model (RCM) HadGEM2-ES generated under Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios and was used in the study to represent future rainfalls. Future daily rainfalls were disaggregated into sub-hourly using disaggregation parameters of corresponding station’s historical rainfall data since it is impossible to estimate parameters when hourly data is not available. With this new approach, future daily rainfall data is disaggregated into 5-min data by complying with historical rainfall patterns rather than complying with randomly selected rainfall characteristics. The study concluded that future rainfall intensities increases compared to historical IDF curves. RCP8.5 scenarios have higher rainfall intensities for all return periods compared to RCP4.5 scenarios for all stations except a station. In addition, the accuracy of the selected disaggregation model was verified.

ACS Style

Hüsamettin Tayşi; Mehmet Ozger. Disaggregation of Future Regional Climate Model Data to Generate Future Rainfall Intensity-Duration-Frequency Curves to Assess Climate Change Impacts. 2021, 1 .

AMA Style

Hüsamettin Tayşi, Mehmet Ozger. Disaggregation of Future Regional Climate Model Data to Generate Future Rainfall Intensity-Duration-Frequency Curves to Assess Climate Change Impacts. . 2021; ():1.

Chicago/Turabian Style

Hüsamettin Tayşi; Mehmet Ozger. 2021. "Disaggregation of Future Regional Climate Model Data to Generate Future Rainfall Intensity-Duration-Frequency Curves to Assess Climate Change Impacts." , no. : 1.

Article
Published: 06 October 2019 in Water
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Although the complexity of physically-based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e., Hydrologiska Bryåns Vattenbalansavdelning (HBV). This has rarely been done for conceptual models, as satellite data are often used in the spatial calibration of the distributed models. Three different soil moisture products from the European Space Agency Climate Change Initiative Soil Measure (ESA CCI SM v04.4), The Advanced Microwave Scanning Radiometer on the Earth Observing System (EOS) Aqua satellite (AMSR-E), soil moisture active passive (SMAP), and total water storage anomalies from Gravity Recovery and Climate Experiment (GRACE) are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms, all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture, are used to analyze the contribution of each individual source of information.

ACS Style

Mehmet Cüneyd Demirel; Alparslan Özen; Selen Orta; Emir Toker; Hatice Kübra Demir; Ömer Ekmekcioğlu; Hüsamettin Tayşi; Sinan Eruçar; Ahmet Bilal Sağ; Ömer Sarı; Ecem Tuncer; Hayrettin Hancı; Türkan Irem Özcan; Hilal Erdem; Mehmet Melih Koşucu; Eyyup Ensar Başakın; Kamal Ahmed; Awat Anwar; Muhammet Bahattin Avcuoğlu; Ömer Vanlı; Simon Stisen; Martijn J. Booij. Additional Value of Using Satellite-Based Soil Moisture and Two Sources of Groundwater Data for Hydrological Model Calibration. Water 2019, 11, 2083 .

AMA Style

Mehmet Cüneyd Demirel, Alparslan Özen, Selen Orta, Emir Toker, Hatice Kübra Demir, Ömer Ekmekcioğlu, Hüsamettin Tayşi, Sinan Eruçar, Ahmet Bilal Sağ, Ömer Sarı, Ecem Tuncer, Hayrettin Hancı, Türkan Irem Özcan, Hilal Erdem, Mehmet Melih Koşucu, Eyyup Ensar Başakın, Kamal Ahmed, Awat Anwar, Muhammet Bahattin Avcuoğlu, Ömer Vanlı, Simon Stisen, Martijn J. Booij. Additional Value of Using Satellite-Based Soil Moisture and Two Sources of Groundwater Data for Hydrological Model Calibration. Water. 2019; 11 (10):2083.

Chicago/Turabian Style

Mehmet Cüneyd Demirel; Alparslan Özen; Selen Orta; Emir Toker; Hatice Kübra Demir; Ömer Ekmekcioğlu; Hüsamettin Tayşi; Sinan Eruçar; Ahmet Bilal Sağ; Ömer Sarı; Ecem Tuncer; Hayrettin Hancı; Türkan Irem Özcan; Hilal Erdem; Mehmet Melih Koşucu; Eyyup Ensar Başakın; Kamal Ahmed; Awat Anwar; Muhammet Bahattin Avcuoğlu; Ömer Vanlı; Simon Stisen; Martijn J. Booij. 2019. "Additional Value of Using Satellite-Based Soil Moisture and Two Sources of Groundwater Data for Hydrological Model Calibration." Water 11, no. 10: 2083.