Akademik Veri Yönetim Sistemi
The 8th International Conference on Natural and Engineering Sciences, İstanbul, Türkiye, 21 Kasım 2023, ss.12, (Özet Bildiri)
Drought is one of the most detrimental natural disasters that affects a wide range of areas including social
and ecological aspects of life. Accurate and reliable drought monitoring is becoming more crucial to drought
mitigation as the effects of climate change intensify. Within the last few decades, drought indices such as
The Standardized Precipitation Index (SPI) and The Standardized Streamflow Index (SSFI) have been widely
used for drought monitoring based on different variables. Even though these single variable indices are
frequently used in academic studies, they may be insufficient for drought monitoring due to the complexity
of drought phenomena. In this study, The Gringorten plotting position formula was modified to develop a
Multivariate Standardized Drought Index (MSDI) that probabilistically combines The Standardized
Precipitation Index and The Standardized Streamflow Index. This index can be used to characterize droughts
based on the integrated state of precipitation and runoff. Çoruh River Basin, located in the northeastern
region of Turkey, was selected as the study area of this paper. Throughout the Çoruh River Basin, 8
hydrological and 8 meteorological stations were chosen for this study. Monthly streamflow and monthly
precipitation data were taken from the selected stations for the years 1989-2011. Regression analyses were
performed for the missing data in both hydrological and meteorological stations. Inverse Distance Weighting
method was used to estimate the precipitation data at the location of the hydrological stations. The MSDI for
various time scales were calculated. The MSDI values for different time scales are then evaluated against
commonly used single variable indices for the same time scale. The correlation coefficients between SPI,
SSFI and MSDI are then calculated to evaluate the reliability of the developed MSDI. Drought severity levels
for various time scales were classified and the severe and extreme droughts identified were subsequently
analyzed.