Akademik Veri Yönetim Sistemi
10TH INTERNATIONAL INNOVATIVE STUDIES & CONTEMPORARY SCIENTIFIC RESEARCH CONGRESS, Tokyo, Japonya, 1 - 03 Eylül 2025, ss.1-2, (Özet Bildiri)
Hydrological drought is a climate phenomenon affecting water resources the most, especially in semi-arid regions such as the Konya Closed Basin in Türkiye, one of the largest inland basins and most vulnerable to recurrent drought. Hydrological drought assessment relies on several indices, such as the Streamflow Drought Index (SDI), which converts hydrological data into standard values using probability distribution functions. However, choosing the appropriate distribution function is a critical step, as it can significantly impact the index results and the accuracy of drought estimation. In this study, streamflow data from several monitoring stations within the basin were analyzed over a long period of time, and several common probability distribution functions were applied, including the Gamma distribution, the Log-Normal distribution, the Weibull distribution, and the Normal distribution. The suitability of each function was assessed using statistical measures such as the Kolmogorov-Smirnov (K-S) test, the Akaike Information Criterion (AIC), and the Bayesian Information Criterion (BIC). The SDI was then calculated for each function separately. The results showed clear differences between the SDI values generated by each function, with some functions increasing or decreasing the estimated drought severity, as well as different classifications of dry and wet periods. These results confirm that the selection of an appropriate probability distribution function should be based on the hydrological data characteristics of the basin, and that an inappropriate selection can lead to misleading estimates that impact water resource management decisions. Therefore, this study provides a practical framework for comparing distribution functions in drought assessment, supporting the development of more effective management strategies for closed basins prone to drought.