Snow hydrology studies in the mountainous eastern part of Turkey

Acar, Reşat; Şenocak, Serkan; Şengül, Selim

doi:10.1109/ieem.2009.5373102

Cited by 6 publications

(7 citation statements)

References 2 publications

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Section: Area Of Studymentioning

confidence: 99%

“…Although the basin can be considered small in terms of scale, it has a large elevation difference that makes it possible to conduct snow modeling of major basins such as the Euphrates Basin. Previous snow studies in the area have shown how important snow dynamics and snow modeling are for this region [2,10,27,[32][33][34][35][36][37][38][39][40][41]. The study area is located within the city center limits of Erzurum in Turkey, which is located at the intersection of Turkey's three major basins: the Çoruh, Aras, and Euphrates basins, and the snowmelt of the mountains in this region is the main source of water for these basins [3,42].…”

Section: Area Of Studymentioning

confidence: 99%

“…Station information is provided in Table 1 for each of the locations that are shown in Figure 1. This allowed climate data from stations in a mountainous basin with high snow potential to be collected in real time and of sufficient quality [35,36]. The upper levels of the study area are surrounded by basalts.…”

Section: Area Of Studymentioning

confidence: 99%

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Predicting Snowmelt Runoff at the Source of the Mountainous Euphrates River Basin in Turkey for Water Supply and Flood Control Issues Using HEC-HMS Modeling

Şengül

İspirli

2022

Water

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Predicting the runoff from snowpack accumulated in mountainous basins during the melting periods is very important in terms of assessing issues such as water supply and flood control. In this study, the Hydrological Engineering Center–Hydrological Modeling System (HEC-HMS) was used to simulate snowmelt runoff in the Kırkgöze–Çipak Basin that has a complex topography where altitude differences range from 1823 m to 3140 m above the sea level. The Kırkgöze–Çipak Basin, located in eastern Turkey, is a basin where snowfall is highly effective during the cold season. There are three automatic meteorology and snow observation stations and three stream gauge stations in the basin, which are operated especially for the calibration and validation of hydrological parameters at different altitudes and exposures. In this study, the parameters affecting snow accumulation–melting and runoff were investigated using the simulations on an hourly basis carried out over a three-year period for temporal and spatial distribution at the basin scale. Different from previous studies focusing on the rate of snowmelt, the temperature index method, which is calculated with physically-based parameters (R2 = 0.77~0.99), was integrated into the runoff simulations (R2 = 0.84) in the basin. The snowmelt-dominated basin is considered to be the source of the headwaters of the Euphrates River.

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Section: Area Of Studymentioning

confidence: 99%

Section: Area Of Studymentioning

confidence: 99%

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Predicting Snowmelt Runoff at the Source of the Mountainous Euphrates River Basin in Turkey for Water Supply and Flood Control Issues Using HEC-HMS Modeling

Şengül

İspirli

2022

Water

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“…It is shown that the sufficient and qualified climate data can be collected in a real time from three stations, having different aspects and altitudes, in a mountainous basin with high snow potential in Kırkgöze (Çipak) basin [2]. Variables and parameters that is used to predict the discharge by ANN is calculated from the three automatic meteorological stations in conjunction with remote sensing and geographic information systems.…”

Section: B Datamentioning

confidence: 99%

Modelling Snowmelt Runoff Using an Artificial Neural Network ANN Approach

Acar¹,

Çelik²,

Şenocak³

2015

Third International Conference on Advances in Civil, Structural and Mechanical Engineering - ACSM 2015

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“…Xu, et al, have used BPN and Compared between BPN models and four process-based models, namely a lumped model(Xinanjiang), a semi-distributed model (XXT), and ESSI and SWAT (two distributed models). It is found that all the four process-based models perform poorer compared with BPN models for I-day lead time to 20-day lead time [196]. Xui, et al, have applied TOPMODEL, Digital Elevation Model (DEM) and TOPMODEL can be used as a stream flow prediction tool and hence as an agricultural drought forecasting tool [197].…”

Section: Rainfall-runoff Modelingmentioning

confidence: 99%

Appropriateness of Neural Networks in Climate Prediction and Interpolations: A Comprehensive Literature Review

Karmakar¹,

Choubey²,

Mishra³

2016

IJAIS

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To be familiar with appropriateness of Neural Network in climate prediction and spatial interpolation, e comprehensive literature review of past 50 years is done and offered in this paper. And it is established that Neural Network such as BPN, RBF is best appropriate to be predicted chaotic behavior of climate variables like rainfall, rainfall runoff, and have efficient enough for prediction in long period. It is also found that Neural Network is significant for spatial interpolation of mean climate variables.

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Snow hydrology studies in the mountainous eastern part of Turkey

Cited by 6 publications

References 2 publications

Predicting Snowmelt Runoff at the Source of the Mountainous Euphrates River Basin in Turkey for Water Supply and Flood Control Issues Using HEC-HMS Modeling

Predicting Snowmelt Runoff at the Source of the Mountainous Euphrates River Basin in Turkey for Water Supply and Flood Control Issues Using HEC-HMS Modeling

Modelling Snowmelt Runoff Using an Artificial Neural Network ANN Approach

Appropriateness of Neural Networks in Climate Prediction and Interpolations: A Comprehensive Literature Review

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