000012544 001__ 12544
000012544 005__ 20160816160225.0
000012544 04107 $$aeng
000012544 046__ $$k2015-12-28
000012544 100__ $$aAcar, Resat
000012544 24500 $$aMODELLING SNOWMELT RUNOFF USING AN ARTIFICIAL NEURAL NETWORK (ANN) APPROACH

000012544 24630 $$n3.$$pProceedings of the 3rd International Conference on Advances in Civil, Structural and Mechanical Engineering
000012544 260__ $$bInstitute of Research Engineers and Doctors
000012544 506__ $$arestricted
000012544 520__ $$2eng$$aThe use of artificial neural networks (ANNs) is becoming increasingly common in the analysis of hydrology and water resources problems. In this research, an ANN was developed and used to model the snowmelt runoff, in a catchment located in a semiarid climate in Turkey. The multilayer perceptron (MLP) neural network was chosen for use in the current study. The one year data (2009) obtained from the stations, located in Erzurum Kırkgoze (Cipak) basin, are integrated into daily average time series of temperature (T), solar radiation (R), snow-covered area (S), snow water equivalent (SWE), runoff coefficient for snow (Cs). The results indicate that the artificial neural network method is suitable to predict the river discharges by using some variables and parameters of snowmelt for the Kırkgoze Basin.  

000012544 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000012544 653__ $$a Artificial Neural Network, Modelling, Snowmelt Runoff Model, Turkey.

000012544 7112_ $$a 3rd International Conference on Advances in Civil, Structural and Mechanical Engineering$$cBangkok, Thailand$$d2015-12-28 / 2015-12-29$$gACSM3
000012544 720__ $$aAcar, Resat$$iSenocak, Serkan$$iCelik, Semet
000012544 8560_ $$ffischerc@itam.cas.cz
000012544 8564_ $$s832703$$uhttps://invenio.itam.cas.cz/record/12544/files/ACSM-15-508.pdf$$yOriginal version of the author's contribution as presented on CD, id ACSM-15-508, doi: 10.15224/978-1-63248-083-5-63.
000012544 962__ $$r12525
000012544 980__ $$aPAPER