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Yayın Investigating the thermally transferred optically stimulated luminescence source trap in fired geological quartz(Pergamon-Elsevier Science Ltd, 2014-03) Koul, Dileep K.; Patil, Pravinkumar G.; Oniya, Ebenezer O.; Polymeris, George S.The pre-dosed thermoluminescence (TL) emission of quartz has been found to be useful in retrospective dosimetry and archaeometry. Though the pre-dosed optically stimulated luminescence (OSL) and emissions have been reported to be similar, the former has been found to be un-reliable for the equivalent dose estimation. As this measurement protocol involves thermal heating at around 400 degrees C, the work reported in this paper investigated the influence of this heating on the OSL using fired specimens from various regions. The results suggested that the discrepancy in the behaviour of two emissions is caused by the presence of the thermally transferred optically stimulated luminescence (TT-OSL) induced by thermal-activation involved in the pre-dose treatment. This transferred signal was observed to be very significant in the case of samples containing a prominent higher-temperature TL peak at similar to 375 degrees C. The characterization of this signal based on (i) the nature of the glow curves, (ii) thermal-annealing of the OSL trap, (iii) observation of the TT-OSL, (iv) bleaching of the source trap and (v) the correlation between TL and OSL seems to suggest that the trap corresponding to this TL peak is the source trap in the TT-OSL emission mechanism.Yayın Drought analysis in the Seyhan River Basin based on standardized drought indices using a new approach considering seasonality(Springer Science and Business Media Deutschland GmbH, 2025-01) Terzi, Tolga Barış; Önöz, BihratDrought is a significant natural disaster with adverse effects on both social and ecological systems. Unlike other natural disasters, drought develops slowly and gradually, complicating its early detection and often resulting in severe impacts on affected regions. Consequently, accurate and dependable drought monitoring is essential for devising effective mitigation strategies. Standardized drought indices are vital tools in drought monitoring, providing a means to quantify and characterize drought events. Most standardized drought indices utilize the Standardized Precipitation Index (SPI) method, which is valued for its simplicity and flexibility. However, this study contends that the SPI method lacks several critical elements, particularly in practice, such as determining the most suitable probability distribution for hydrometeorological variables. Therefore, this study proposes a novel methodology for calculating standardized drought indices and assesses its performance against conventional and nonparametric standardized indices, employing various methods capable of capturing complex dependencies. The novel methodology involves identifying the best-fit probability distributions for each data group through various goodness-of-fit tests. This approach ensures that each group is modeled optimally, considering the seasonal variations inherent to each group. The Seyhan River Basin has been chosen as a case study for the proposed methodology. The drought characteristics of the basin are analyzed using indices derived from the new methodology, the conventional SPI method, and the nonparametric method. Additionally, trend analyses were performed on the calculated indices to identify any directional changes in drought patterns within the Seyhan River Basin. The performance of the proposed methodology was evaluated by analyzing its relationship with nonparametric standardized indices and comparing it to the relationship between conventional standardized indices and nonparametric standardized indices. The results show that the newly proposed methodology outperforms the conventional SPI method across various dependence measures, suggesting it captures the underlying data structure more effectively than the SPI method.
