Flood Prioritization Watersheds of the Aras River, Based on Geomorphometric Properties: Case Study Iğdır Province

Year 2021, Issue: 6, 21 - 40, 15.04.2021

Mustafa Utlu , Redvan Ghasemlounia

https://doi.org/10.46453/jader.781152

Cited By: 3

Abstract

Drainage watershed morphometry plays a major role in terms of understanding flood dynamics. Flood potentials are explained considering the linear, areal, and relief morphometry features of the watersheds. In general, there are number of geomorphometric indices in the description of these features. The formal geometries, geomorphology, geology, and general climate characteristics, etc., which play a decisive role in the flood potential in the watershed, can be determined relatively with morphometric indices. In this study, 35 different river watersheds draining their waters to the Aras, located in the center of Iğdır Province, were examined. Geographic information systems (GIS) and statistical software were chosen to analyze and calculate indices for this research. Flood events occur in these 35 different river watersheds and this study evaluates river watersheds in terms of their flood potential using 14 different indices. In the evaluation of the results obtained, the values that have a high impact on the floods are ranked according to their priorities. These results were evaluated in terms of flood priorities using morphometric analysis and principal component analysis methods. Flood priorities of watersheds, obtained through two different methods, are classified as high, medium, or low priorities. The number of common watersheds, determined based on two different methods, is 8 in river watersheds with "high" priority, 11 in river watersheds with "medium" priority, and 7 in river watersheds with "low" priority. According to these results, it is seen that river watersheds with high priority flood potential correspond to the areas where flood events occurred.

Keywords

Flood Prioritization, Morphometric Parameter, Geographic Information Systems (GIS), Principal Component Analysis (PCA)

Jeomorfometrik Özelliklere Göre Aras Nehri Havzalarının Taşkın Önceliklendirilmesi: Iğdır İli Örneği

Abstract

Drenaj havza morfometrisi, taşkın dinamiklerinin anlaşılması bakımından büyük rol oynamaktadır. Temel olarak havzaların çizgisel, alansal ve relief morfometri özellikleri dikkate alınarak taşkın olasılıkları açıklanmaktadır. Genel olarak bu özelliklerin açıklanmasında bir takım indisler bulunmaktadır. Havzalardaki taşkın potansiyelinde belirleyici rol oynayan şekilsel geometrileri, jeomorfoloji, jeolojisi ve genel iklim özellikleri vb., durumları morfometrik indisler ile göreceli olarak tespit edilebilmektedir. Bu çalışmada Iğdır ili merkezinde yer alan Aras Havzası’na sularını drene eden 35 farklı akarsu havzası incelendi. Çalışmanın gerçekleştirilmesinde coğrafi bilgi sistemleri (GIS) yazılımlarından ArcGIS 10.x, istatistik hesaplamaların yapılmasında ise SPSS ve excel programları kullanılmıştır. Bu 35 farklı akarsu havzasında taşkın olayları meydana gelmektedir. Bu akarsu havzaları 14 farklı indis kullanılarak taşkın potansiyeli bakımından değerlendirilmiştir. Kullanılan bu indisler, çizgisel, alansal ve relief morfometrisini içermektedir. Elde edilen sonuçların değerlendirilmesinde taşkınlar üzerinde yüksek etkiye sahip değerler önceliklerine göre sıralandırılmıştır. Bu sonuçlar, morfometrik analiz ve principal component analysis yöntemleri kullanılarak taşkın öncelikleri bakımından değerlendirilmiştir. İki farklı yönteme bağlı olarak elde edilen taşkın öncelikli havzalar yüksek-orta-düşük önceliğe sahip olarak sınıflandırılmıştır. İki farklı yönteme bağlı olarak tespit edilen ortak havza sayısı “Yüksek” önceliğe sahip havzalarda 8, orta önceliğe sahip havzalarda 11, düşük havza önceliğine sahip akarsu havzalarında ise 7’dir. Bu sonuçlara bağlı olarak yüksek önceliğe sahip taşkın potansiyeline sahip akarsu havzaları taşkın olaylarının meydana geldiği alanlara karşılık geldiği görülmektedir

Keywords

Taşkın önceliği,, Morfometrik parametre,, Coğrafi bilgi sistemleri,, Temel bileşenler analizi (PCA),

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