Basin sediment yield estimation using basin morphological characteristics determined by Geographic Information Systems

Ercan Varol; Ahmet İrvem

Article Details

Basin sediment yield estimation using basin morphological characteristics determined by Geographic Information Systems

Authors:

Ercan Varol | Ahmet İrvem

Publisher:

Hatay Mustafa Kemal University

Main Topics:

Ziraat Mühendisliği

Journal:

Mustafa Kemal Üniversitesi Tarım Bilimleri Dergisi Vol.28 Issue 1, pp.1-10

Document Type:

Article

Publication Date:

7/2023

Document Language:

Turkish

Document ID (Org No.):

2001286051

pISSN:

2667-7733

Keywords:

Abstract:

 The morphological characteristics of 47 basins for different rainfall regions of Turkey were determined using Geographic Information Systems GIS. These features and data taken from flow and sediment monitoring stations were subjected to multiple regression analysis in order to develop basin sediment yield prediction equations for ungauged basins. Basins morphological characteristics were determined by using ILWIS-GIS software. Areas of the basins, the maximum relief, stream orders and elevations of the stations were determined using GIS. All data were analyzed using the best-subset within the multiple regression statistical method. As a result of analysis, individual sediment yield prediction equations for each region were generated. These regions were found to be appropriate in terms of providing the predetermined information of basin sediment yield for ungauged basins. In this study, sediment yield prediction equations for ungauged basins in the 5 regions 2, 3, 4, 5, and 7 were developed. These equations can be used, in terms of providing sediment data for ungauged basins. However, the prediction equation can not be generated for 1. Region because of insufficient data and equation for region 6 was not proper in terms of Nash-Sutcliffe coefficient. So that the number of observation stations has to be increased for 1. and 6. region.

 The morphological characteristics of 47 basins for different rainfall regions of Turkey were determined using Geographic Information Systems GIS. These features and data taken from flow and sediment monitoring stations were subjected to multiple regression analysis in order to develop basin sediment yield prediction equations for ungauged basins. Basins morphological characteristics were determined by using ILWIS-GIS software. Areas of the basins, the maximum relief, stream orders and elevations of the stations were determined using GIS. All data were analyzed using the best-subset within the multiple regression statistical method. As a result of analysis, individual sediment yield prediction equations for each region were generated. These regions were found to be appropriate in terms of providing the predetermined information of basin sediment yield for ungauged basins. In this study, sediment yield prediction equations for ungauged basins in the 5 regions 2, 3, 4, 5, and 7 were developed. These equations can be used, in terms of providing sediment data for ungauged basins. However, the prediction equation can not be generated for 1. Region because of insufficient data and equation for region 6 was not proper in terms of Nash-Sutcliffe coefficient. So that the number of observation stations has to be increased for 1. and 6. region.

 The morphological characteristics of 47 basins for different rainfall regions of Turkey were determined using Geographic Information Systems GIS. These features and data taken from flow and sediment monitoring stations were subjected to multiple regression analysis in order to develop basin sediment yield prediction equations for ungauged basins. Basins morphological characteristics were determined by using ILWIS-GIS software. Areas of the basins, the maximum relief, stream orders and elevations of the stations were determined using GIS. All data were analyzed using the best-subset within the multiple regression statistical method. As a result of analysis, individual sediment yield prediction equations for each region were generated. These regions were found to be appropriate in terms of providing the predetermined information of basin sediment yield for ungauged basins. In this study, sediment yield prediction equations for ungauged basins in the 5 regions 2, 3, 4, 5, and 7 were developed. These equations can be used, in terms of providing sediment data for ungauged basins. However, the prediction equation can not be generated for 1. Region because of insufficient data and equation for region 6 was not proper in terms of Nash-Sutcliffe coefficient. So that the number of observation stations has to be increased for 1. and 6. region.

 Akım ve sediment ölçümü yapılan 47 havzada, havzaların morfolojik özellikleri Coğrafi Bilgi sistemleri CBS ile belirlenerek, çoklu regresyon analizi ile Türkiyenin farklı yağış rejimi bölgeleri için sediment verimi tahmin modelleri geliştirilmiştir. ILWIS CBS yazılımı ile her havzanın maksimum rölyefi, akarsu derecesi, istasyon kotu ve havza alanı belirlenmiştir. Ölçülen değerler ve CBS ile belirlenen havza özellikleri, en iyi alt grup istatistik yöntemi kullanılarak, sediment verimi tahmininde en uygun havza parametreleri belirlenmiştir. Bu parametreler, çoklu regresyon analizinde kullanılarak yağış bölgeleri için ayrı ayrı sediment verimi tahmin modelleri geliştirilmiştir. Modellerin tahmin yeteneğini belirlemede ise Nash-Sutcliffe verimlilik katsayısı kullanılmıştır. Bu denklemlerin, çalışılan bölgelerdeki akım ve sediment gözlemi olmayan havzalarda, havza sediment verimi tahmini için ön fikir vermesi açısından uygun olduğu görülmüştür. Ayrıca, Türkiyenin yağış rejimi benzeyen 5 bölgesinde 2, 3, 4, 5 ve 7 sediment ölçümü olmayan havzalar için sediment verimi tahmin denklemleri geliştirilebilmiştir. Nash-Sutcliffe verimlilik katsayısına göre E0.90 en iyi tahmin denklemi 4. 5. ve 7. Bölgeler için geliştirilmiştir. 1. Bölge için yeterli havza ve akım gözlem istasyonu sayısı olmadığından tahmin denklemi geliştirilememiştir. 6. Bölge için geliştirilen tahmin denkleminin Nash-Sutcliffe verimlilik katsayısına göre uygun olmadığı görülmüştür. 1. ve 6. Bölgeler için akım ve sediment verimi ölçüm istasyonlarının sayısı artırılmalıdır.

Article Details

Basin sediment yield estimation using basin morphological characteristics determined by Geographic Information Systems

Authors:

Ercan Varol | Ahmet İrvem

Publisher:

Hatay Mustafa Kemal University

Main Topics:

Ziraat Mühendisliği

Journal:

Mustafa Kemal Üniversitesi Tarım Bilimleri Dergisi Vol.28 Issue 1, pp.1-10

Document Type:

Article

Publication Date:

7/2023

Document Language:

Turkish

Document ID (Org No.):

2001286051

pISSN:

2667-7733

Basin characteristics

Geographic Information Systems

Sediment yield

Multiple regression analysis

Subset analysis.

Havza özellikleri

Coğrafi Bilgi Sistemleri

sediment verimi

Coklu regresyon analizi

Alt grup analizi yöntemi.

Issues

Article Details

Authors: Ercan Varol | Ahmet İrvem

Publisher: Hatay Mustafa Kemal University

Main Topics: Ziraat Mühendisliği

Journal: Mustafa Kemal Üniversitesi Tarım Bilimleri Dergisi Vol.28 Issue 1, pp.1-10

Document Type: Article

Publication Date: 7/2023

Document Language: Turkish

Document ID (Org No.): 2001286051

pISSN: 2667-7733

Issues

Authors:

Ercan Varol | Ahmet İrvem

Publisher:

Hatay Mustafa Kemal University

Main Topics:

Ziraat Mühendisliği

Journal:

Mustafa Kemal Üniversitesi Tarım Bilimleri Dergisi Vol.28 Issue 1, pp.1-10

Document Type:

Article

Publication Date:

7/2023

Document Language:

Turkish

Document ID (Org No.):

2001286051

pISSN:

2667-7733