Hydrological and Meteorological Drought Forecasting for the Yesilirmak River Basin, Turkey

Öz

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.

Anahtar Kelimeler

• ANN
• Drought Indices
• Hydrological Drought
• Meteorological Drought
• Yesilirmak Basin
• Turkey.

Yeşilırmak Havzası için Hidrolojik ve Meteorolojik Kuraklık Tahmini, Türkiye

Öz

Kuraklık en tehlikeli doğal afettir. Diğer afetlerden farkı, sinsi bir şekilde gerçekleşmesi, etkilerinin yavaş yavaş ortaya çıkması ve uzun süre devam etmesidir. Kuraklığın hem toplum hem de doğal ekosistemler üzerinde çok büyük, olumsuz etkileri vardır. Bu çalışmada, Yapay Sinir Ağları (YSA) kullanılarak kuraklık tahmin modelleri oluşturmak için Standardize Yağış İndeksi (SPI) değerleri kullanılmıştır. Ek olarak, YSA ile Akarsu Kuraklık İndeksi (SDI) değerlerini tahmin etmek için SPI değerleri kullanılarak hidrolojik kuraklık olasılığı belirlenmiştir. Ayrıca YSA modellerinde İleri Beslemeli Sinir Ağları (FFNN) ile birlikte sırasıyla meteorolojik ve hidrolojik kuraklık indeksleri olarak SPI ve SDI kullanılmıştır. Bu amaçla, Türkiye Yeşilırmak Havzasında bulunan üç yağış ve üç akış ölçme istasyonu çalışma birimi olarak seçilmiştir. YSA tahmin modellerini oluşturmak için istasyonlara ait SPI ve SDI değerleri hesaplanmıştır. SPI ve SDI için farklı YSA tahmin modelleri eğitilmiş ve test edilmiştir. Ayrıca, SDI tahmin modelini geliştirmek için Thiessen Metodu kullanılarak yağışların mekansal dağılımının akışlar üzerindeki etkileri belirlenmiştir. YSA tahmin modellerinin ürettiği sonuçlar ve elde edilen değerler karşılaştırılarak modellerin performansları analiz edilmiştir. ANN ve SPI kombinasyonu meteorolojik kuraklığı yüksek doğrulukla öngördü, ancak ANN ve SDI kombinasyonu hidrolojik kuraklığı tahmin etmede o kadar iyi değildir.

Anahtar Kelimeler

• ANN
• Kuraklık Endeksleri
• Hidrolojik Kuraklık
• Meteorolojik Kuraklık
• Yeşilırmak Havzası
• Türkiye.

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