Özet
A methodology using the standardised precipitation index is proposed to develop critical drought intensity-duration-frequency (IDF) curves. We define dry periods within which we recognise droughts of different durations. The most severe drought for each drought duration in each year is called the critical drought. The total probability theorem-coupled frequency analysis is used to determine the best-fit probability distribution function of drought severity, which is then converted to intensity. The generalised extreme value probability distribution function is found to best fit the critical drought severity. The methodology is implemented using monthly precipitation data for a meteorological station in Turkey. The critical drought intensity decreases linearly with increasing drought duration, whereas the return period increases exponentially when the drought becomes more severe. The site-specific IDF curves furnished with an empirical relationship between the intensity and return period allow one to characterise the drought not by an index-based intensity but by its return period. This kind of presentation is physically easier to understand, in particular for stakeholders and decision makers in practice.
| Orijinal dil | İngilizce |
|---|---|
| Sayfa (başlangıç-bitiş) | 1337-1358 |
| Sayfa sayısı | 22 |
| Dergi | Hydrological Sciences Journal |
| Hacim | 66 |
| Basın numarası | 8 |
| DOI'lar | |
| Yayın durumu | Yayınlandı - 2021 |
Bibliyografik not
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Finansman
This work was supported by the Istanbul Technical University [MUA-2019-42094]; Fulbright [Academic Research Scholarship]; and Scientific and Technological Research Council of Turkey [2219 Post-doctoral Research Program]. With the contribution of the co-authors, this study was formulated during the research study of H. Aksoy as a Fulbright Visiting Scholar at the University of Illinois, Urbana-Champaign (UIUC), USA. The research study of H. Aksoy has been supported by (1) Fulbright through the Academic Research Scholarship; (2) Istanbul Technical University (ITU) through the International Research and Cooperation Program, UAIP, Project: MUA-2019-42094; and (3) the Scientific and Technological Research Council of Turkey (TUBITAK) through the 2219 Post-doctoral Research Program. All these supports are greatly appreciated. H. Aksoy thanks the Department of Geography and Geographic Information Science for the hospitality and support provided during his stay at UIUC. With the contribution of the co-authors, this study was formulated during the research study of H. Aksoy as a Fulbright Visiting Scholar at the University of Illinois, Urbana-Champaign (UIUC), USA. The research study of H. Aksoy has been supported by (1) Fulbright through the Academic Research Scholarship; (2) Istanbul Technical University (ITU) through the International Research and Cooperation Program, UAIP, Project: MUA-2019-42094; and (3) the Scientific and Technological Research Council of Turkey (TUBITAK) through the 2219 Post-doctoral Research Program. All these supports are greatly appreciated. H. Aksoy thanks the Department of Geography and Geographic Information Science for the hospitality and support provided during his stay at UIUC.
| Finansörler | Finansör numarası |
|---|---|
| International Research and Cooperation Program | |
| TUBITAK | |
| UAIP | |
| University of Illinois at Urbana-Champaign | |
| Türkiye Bilimsel ve Teknolojik Araştirma Kurumu | |
| Istanbul Teknik Üniversitesi | MUA-2019-42094 |
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