Çankırı Acıçay-Tatlıçay Havzalarında arazi kullanım türlerinin Bayes Ağları yöntemiyle tahmin edilmesi

Son yıllarda küresel ısınma ve iklim değişikliğinin dereler üzerindeki rejim bozukluğunu ortaya çıkardığı uzmanlar tarafından tespit edilmiştir. Bu rejim bozuklukları dere, ırmak ve nehirlerin hidromorfolojilerinde de değişimlere sebep olarak zaman zaman sel ve taşkınların oluşmasına sebep olmaktadır. Özellikle yarı-kurak havzalarda bölge yapısının ve özelliklerinin bilinmesi muhtemel felaketleri engellemede önemli bir faktördür. Bu çalışmanın amacı, Çankırı ilinde bulunan Tatlıçay ve Acıçay havzalarında belirlenmiş 513 noktadaki ölçümler ile derelerdeki hidromorfolojik yapının belirlenmesi, arazi kullanma türünün (AKT) hangi parametrelere göre değiştiğinin incelenmesi ve arazi yapısının tahmin edilmesidir. Bu amaçla dört farklı Bayes Ağ senaryosu belirlenmiştir. Bu senaryolarda, farklı parametreler belirlendiğinde AKT’nin yüzde kaç olasılıkla tahmin edildiği saptanmıştır. Bu sonuçlara göre en yüksek olasılıkla belirlenen AKT tipi iğne yapraklı orman olup, bu oran %97 olarak bulunmuştur.

Anahtar Kelimeler:

Bayes Ağları, Arazi Kullanma Türü, Rosgen Dere Sınıfı, Çankırı

Using Bayesian Network to predict the watershed land use type of Çankırı Acıçay-Tatlıçay

In recent years, experts have identified that climate change and global warming affects stream flow regime. These changes cause floods and erosion in creeks, streams, rivers etc. Especially in semi-arid watersheds, the structure of the land usage type is an important factor in preventing possible disasters. The aim of this study is to determine watershed land usage type by using hydro-morphological structure of stream and some physical water quality parameters. To do so, hydro-morphological observations and some physical water quality parameters were collected from 513 different points in Acıçay and Tatlıçay watershed. For this purpose, four different Bayesian network scenarios were considered to see the changes in the type of the land use. In this scenario, the prediction probability of the watershed land usage type was determined with different parameters. In conclusion, coniferous forest was predicted with the highest probability rate of %97.

Keywords:

Çankırı Bayesian network, Land use type, Rosgen stream classification, Çankırı,

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