Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Author: search.filters.author.Tayfur, GökmenSubject: search.filters.subject.Drought

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  • Article
    Citation - WoS: 16
    Citation - Scopus: 19
    Meteorological Drought Assessment and Trend Analysis in Puntland Region of Somalia
    (MDPI, 2023) Muse, Nur Mohamed; Tayfur, Gökmen; Safari, Mir Jafar Sadegh
    Drought assessment and trend analysis of precipitation and temperature time series are essential in the planning and management of water resources. Long-term precipitation and temperature historical records (monthly for 41 years, from 1980 to 2020) are used to investigate annual drought characteristics and trend analysis in Somalia's northern region. Six drought indices of the normal Standardized Precipitation Index (normal-SPI), the log normal Standardized Precipitation Index (log-SPI), the Standardized Precipitation Index using the gamma distribution (Gamma-SPI), the Percent of Normal Index (PNI), the Discrepancy Precipitation Index (DPI), and the Deciles Index (DI) are used in this study for the annual drought assessment. The log-SPI, the gamma-SPI, the PNI, and the DPI could capture historical extreme and severe droughts that occurred in the early 1980s and over the last two decades. The results indicate that Somalia has gone through extended drought periods over the past quarter century, exacerbating the existing humanitarian situation. The normal-SPI, gamma-SPI, and PNI indicate less and moderate drought conditions, whereas log-SPI, DPI, and DI accurately capture historical extreme and severe drought periods; thus, these methods are recommended as annual drought assessment tools in the studied region. Not only are the PNI and DPI less correlated to each other, but their correlation coefficient (CC) with SPI-based drought indices are not as high as SPI-based indices which are close to unity. For the purpose of the trend analysis, the Mann Kendall (MK) test, the Spearman's rho (SR) test, and the Sen test are used. Furthermore, the Pettitt test is implemented to detect the change points and the Thiel-Sen approach is used to estimate the magnitude of trend in the precipitation and temperature time series. The results indicate that there is overall warming in the region which has experienced a significant shift in trend direction since 2000. The trend analysis of annual precipitation data time series shows that Bossaso and Garowe stations have significant positive trends, while the Qardho station has no trend. In 1997 and 1998, respectively, abrupt changes in annual precipitation are detected at Qardho and Garowe stations. Due to the civil war of more than three decades in Somalia and the non-institutionalized governance to inform historical drought conditions in the country, determining the most appropriate meteorological drought index would help to develop a drought monitoring system for states and the entire country.
  • Article
    Citation - WoS: 27
    Citation - Scopus: 27
    Discrepancy Precipitation Index for Monitoring Meteorological Drought
    (Elsevier, 2021) Tayfur, Gökmen
    Widely employed precipitation drought indices, one way or another, impose probability distribution functions to the data when performing the drought analysis. This may be a plausible approach when the data do not have strong discrepancy which can impede the distribution. The precipitation data in semi-arid and especially in arid regions do have a strong discrepancy due to the sporadic rainfall occurring in such regions. Therefore, in the analysis of the drought for such regions, imposing any probability distribution function to the data could be futile. This study hence developed a new drought index called the Discrepancy Precipitation Index (DPI) for assessing and monitoring the meteorological drought. The method does not impose any probability distribution on the precipitation data. The method is based on the discrepancy of the data with respect to the mean value. The drought classifications are proposed based on the D-score values. Its drought classification ranges are straightforward as those of the Standard Precipitation Index (SPI). The method is applied to assess the meteorological drought at several stations located at different climatic regions such as the arid climate (Mauritania), semi-arid climate (Afghanistan) and the Mediterranean climate (Turkey). The results reveal that the DPI is more representative drought assessment tool for the arid climate regions. At semi-arid climate regions, the DPI can be an alternative drought index to the widely employed (the log-SPI and/or the gamma-SPI) indices. For the Mediterranean climate regions, the DPI can be used together with the other indices. The Discrepancy Measure (DM) is introduced to assess the strength of the discrepancy of the precipitation data series. As the DM of a precipitation series increases, the DPI captures more historical droughts.