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

Year 2017, Volume: 18 Issue: 3, 212 - 218, 30.11.2017

Semih Ediş , Efehan Ulaş

https://doi.org/10.18182/tjf.315398

Cited By: 1

Abstract

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.

Keywords

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

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

Abstract

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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