Estimation of Keban Dam Reservoir Level in Turkey Using Artificial Neural Network and Support Vector Machines.

Abstract

The correct estimation of the water level in a reservoir is crucial to optimizing the management of water resources. In this study, Artificial Neural Network (ANN) and Support Vector Machines (SVM) methods were used to estimate the level change of the dam reservoir. Keban Dam located in the Eastern Anatolia region of Turkey was selected as the application area and 731 daily observed data was used.

Artificial Neural Networks Method for Prediction of Rainfall-Runoff Relation: Regional Practice

“…Thus, the basin, which will be measured, is examined with some equations with these accumulation systems and other effective parameters. Recently, artificial intelligence method is a Black Box model that is frequently used in modeling the groundwater level (Demirci et al (2017(Demirci et al ( , 2018a, Üneş et al (2018a), Kaya et al (2018)), suspended sediment (Demirci and Baltaci (2013), , Tasar et al ( 2017)), rainfallrunoff relationship (Ünes et al (2018b), Tasar et al ( 2019)), dam reservoir and lake level (Ünes and Demirci (2015), Ünes et al (2015, 2019a), Demirci and Kaya (2019)), density flow plunging (Üneş (2010)), dam reservoir volume (Unes et al (2017), Demirci et al (2018b), Üneş et al (2019b)), sand bar crest ), evaporation (Üneş et al (2018c(Üneş et al ( ), Tasar et al (2018, Kaya and Tasar (2019)), many different disciplines-areas (Cansiz et al (2009(Cansiz et al ( , 2017a(Cansiz et al ( , 2017b(Cansiz et al ( , 2017c, Dogan et al (2017), Cansiz (2007Cansiz ( , 2011, Cansiz and Easa (2011), Cansız and Askar (2018), Dal et al (2019)).…”