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    Comparison of four precipitation based meteorological drought indices in the Yesilirmak Basin, Turkey
    (Hungarian Meteorological Service, 2023) Zeybekoglu, Utku; Hezarani, Alyar Boustani; Keskin, Asl Ulke
    Drought, which is often defined as not enough precipitation, does not a mean simple lack of precipitation. This condition, which occurs when humidity is less than the average value for many years, is caused by a disrupted balance between precipitation and evaporation in a region. It is very difficult to predict the start and the end time of drought. In the present study, the drought conditions of the stations selected from Yesilirmak Basin between 1970 and 2014 were determined by using Z-Score Index (ZSI), China-Z Index (CZI), Modified China-Z Index (MCZI), and Standard Precipitation Index (SPI), and the compliance of these indices to the SPI was investigated. It was determined that these indices gave parallel results to each other, and SPI detected drought earlier than other indices.
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    Öğe
    Hydrological and Meteorological Drought Forecasting for the Yesilirmak River Basin, Turkey
    (Hakan ÇAGLAR, 2021) Hezarani, Alyar Boustani; Zeybekoglu, Utku; Keskin, Asli Ülke
    Drought is the most dangerous natural disaster. It differs from the other disasters in that it occurs insidiously, its effects are revealed gradually, and it persists for a long period. Drought has huge, negative effects on both society and natural ecosystems. In this study, values from the Standardized Precipitation Index (SPI) were used to generate drought estimation models by using Artificial Neural Networks (ANN). In addition, the probability of hydrological drought was determined by using SPI values to predict Streamflow Drought Index (SDI) values with ANN. Also, the SPI and SDI were used as the meteorological and hydrological drought indices, respectively, in conjunction with Feed Forward Neural Networks (FFNN), in ANN models. For this purpose, three rainfall and three flow gauging stations located in the Yesilirmak River Basin of Turkey were selected as the study units. The SPI and SDI values for the stations were calculated in order to create ANN estimation models. Different ANN forecasting models for SPI and SDI were trained and tested. In addition, the effects of the spatial distribution of precipitation on flows were determined by using the Thiessen Method to develop the SDI prediction model. The results generated by the ANN prediction models and resulting values were compared and the performances of the models were analyzed. The combination of ANN and SPI predicted meteorological drought with high accuracy but the combination of ANN and SDI was not as good in predicting hydrological drought.