Akademik Veri Yönetim Sistemi
Tezin Türü: Doktora
Tezin Yürütüldüğü Kurum: Yıldız Teknik Üniversitesi, Fen Bilimleri Enstitüsü, Türkiye
Tezin Onay Tarihi: 2025
Tezin Dili: İngilizce
Öğrenci: AHMAD SULAIMAN AHMAD ABU ARRA AHMAD SULAIMAN AHMAD ABU ARRA
Danışman: Eyüp Şişman
Özet:
Drought is one of the most dangerous natural disasters, negatively impacting natural resources and economic and social activities, especially in light of accelerating climate change and increasing pressure on water resources. The danger of drought lies in its being a "silent" disaster that develops gradually without direct effects, hindering early response and exacerbating its impacts. In regions such as Palestine, which suffer from scarce water resources, climate variability, and limited climatic and hydrological data, the need to develop accurate and flexible methodologies for monitoring and assessing drought becomes critical to enhancing water security and building proactive policies to adapt to climate change. This thesis aims to provide an integrated scientific and methodological framework for drought analysis by developing and applying new analytical tools based on the latest statistical and comparative methods. It focuses on improving the accuracy of drought assessments, expanding the ability to interpret drought trends, and classifying its various types, whether short-term or long-term, meteorological or hydrological. Several innovative analytical tools have been developed and used, most notably: the Frequency-Innovative Trend Analysis method (F-ITA), the Periodic Innovative Trend Analysis method (P-IPTA), the Innovative Drought Classification Matrix (IDCM), and the construction of intensity-duration-frequency (IDF) drought xxv curves. These methodologies have improved the ability of researchers and decisionmakers to analyze and understand the dynamic characteristics of drought across multiple timescales, at a level of detail unavailable with traditional methods. Results from applying the F-ITA method have shown that the methodology is capable of detecting nonlinear trends and changes in the temporal frequencies of different drought categories. The P-IPTA method, on the other hand, successfully addressed fluctuations in climate data, providing a more accurate view of the temporal patterns associated with drought. The comparison between the SPI and SPEI indices demonstrated their effectiveness, with classification agreement exceeding 60%. However, the use of different data (e.g., weather stations versus satellite data) revealed discrepancies that require validation and calibration. The thesis also demonstrated the significant impact of the selected time period on drought characteristics, recommending a minimum of 10 years for analysis on short timescales (meteorological drought) and 20 years for long timescales (hydrological drought), especially in countries with limited data, such as Palestine. The thesis also addressed the knowledge gap related to the use of theoretical distributions in calculating drought indices. It was found that many studies rely on the gamma distribution without verifying its suitability to the data, leading to significant errors. Conversely, empirical distributions demonstrated higher accuracy, particularly in assessing hydrological drought, highlighting the need to shift toward a non-parametric empirical approach to ensure more reliable results. IDF drought curves were also developed, which are a practical tool for drought assessment for planning and infrastructure design purposes. They provide an easyto-interpret and accurate method, especially when comparing different drought periods, drought event definitions, and their intensity and duration characteristics. In the context of practical application in Palestine, the impact of bias correction on reanalysis data (such as ERA5) was evaluated, and the results showed that the correction significantly improves the accuracy of assessments, especially in extreme conditions. Finally, the thesis compared two gridded global datasets: NASA's IMERG satellite data and the reanalysis ERA5-Land data, to assess their suitability for drought analysis. The results showed that the performance of the two datasets differed depending on the indicator used, geographic location, and climatic xxvi season. The results emphasized the importance of pre-validation and correction of global data before using them for drought monitoring and decision-making in arid and semi-arid regions. This thesis contributes scientifically by providing flexible and comprehensive analysis tools for drought studies. It serves as a foundation for developing water policies, sustainable planning, climate change adaptation strategies, and climate risk management.