Kuraklık Riskinin Bulanık Mantık Yardımıyla Türkiye Genelinde Değerlendirilmesi

İsmail Dabanlı

doi:10.24012/dumf.499660

Kuraklık Riskinin Bulanık Mantık Yardımıyla Türkiye Genelinde Değerlendirilmesi

Öz

Bu çalışmada meteorolojik ve sosyo-ekonomik veriler kullanılarak elde edilen kuraklık afet ve hassasiyetlik göstergeleri yardımıyla Türkiye genelinde kuraklık riski bulanık mantık çıkarımı (BMÇ) yaklaşımıyla bütüncül olarak değerlendirilmiştir. Kuraklık afetinin tam olarak anlaşılmasında kuraklık risk ve hassasiyetinin önemi bilinse de Türkiye için bütüncül ve yeterli miktarda bilimsel çalışmanın varlığından bahsetmek zordur. Kuraklık Afet Göstergesi (KAG) kuraklığın görülme ihtimaline dayanan standart yağış göstergesi (SYG) (Standardized Precipitation Index-SPI) kullanılarak kuraklık kavramının daha iyi anlaşılmasını kolaylaştırmak için hesaplanmıştır. Bunun yanında, Kuraklık Hassasiyet Göstergesi (KHG) kuraklığın sonuçlarının bağlı olduğu güncel dört adet sosyo-ekonomik veri kullanılarak hesaplanmıştır. BMÇ yardımıyla kuraklık afet ve hassasiyet göstergelerinin, kuraklık riskinin belirlenmesindeki öneminin vurgulanması bu çalışmanın temel hedefidir. Çalışma sonucunda elde edilen bulgulara göre Türkiye genelinde 81 il arasında 5 ilin düşük kuraklık riski taşıdığı, 61 ilin orta kuraklık riskine sahip olduğu, 14 ilde yüksek kuraklık riskinin bulunduğu ve son olarak sadece Konya’da çok yüksek kuraklık riski ortaya çıktığı tespit edilmiştir.

Anahtar Kelimeler

Kuraklık,SYG,afet,risk,hassasiyet,bulanık mantık,Türkiye

Kaynakça

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Ayrıntılar

Birincil Dil

Türkçe

Konular

-

Bölüm

Araştırma Makalesi

Yazarlar

İsmail Dabanlı ^*
0000-0003-3108-8167
Türkiye

Yayımlanma Tarihi

15 Mart 2019

Gönderilme Tarihi

19 Aralık 2018

Kabul Tarihi

27 Şubat 2019

Yayımlandığı Sayı

Yıl 2019 Cilt: 10 Sayı: 1

DOI

https://doi.org/10.24012/dumf.499660

IZ

https://izlik.org/JA65NP85EK

Kaynak Göster

RIS / Bibtex

IEEE

[1]İ. Dabanlı, “Kuraklık Riskinin Bulanık Mantık Yardımıyla Türkiye Genelinde Değerlendirilmesi”, DÜMF MD, c. 10, sy 1, ss. 359–372, Mar. 2019, doi: 10.24012/dumf.499660.

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