Please use this identifier to cite or link to this item:
Title:  Study on prediction of snowmelt using energy balance equations and comparing with regression method in the Eastern part of Turkey
Authors: Yerdelen, Cahit
Acar, Resat
Keywords: Energy balance;Mass balance;Snow;Snowmelt model;Regression;Hydrology
Issue Date: Jul-2005
Publisher: CSIR
Abstract:  This paper presents two snowmelt models: i) Energy balance model (EBM); and ii) Linear regression model (LRM). To decide suitable model for the basin, daily mean flow data of Kırkgöze discharge gauging station of State Hydraulic Works (DSİ) was applied to Karasu-Kırkgöze mountainous basin that has 233.2 km2 watershed drainage basin and elevation range of 1830-2854 m in the eastern part of Turkey. EBM was applied during snow melting period, in March-May for 1987-1995. Hourly temperature (T), wind velocity (V), shortwave radiation (Rd), relative humidity (RH) and intensity of rainfall (Y) were used as input parameters. Intervals of constants in EBM that are snow surface conductance (KS), snow surface saturated conductance (KSat), liquid holding capacity of snow (Lk), fresh snow visible band reflectance (αvo) and fresh snow near infrared band reflectance (αiro) were determined for each period. The coefficients of correlation (R) between snow melting data calculated by EBM and gauging data were in the range of 0.88-0.98 for each year (R2=0.77-0.96). Moreover, LRM is established for the only period of 1987 using observed discharges of basin and meteorological variables. The computed coefficient of correlation (R) between regression model including five predictor variables (T, Rd, RH, V & Y) and gauging data was obtained as 0.87 (R2=0.757). Two models are then compared in terms of coefficient of correlations. EBM was found more representative than LRM to predict snowmelt in eastern part of Turkey due to high coefficient of correlation.
Page(s): 520-528
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.64(07) [July 2005]

Files in This Item:
File Description SizeFormat 
JSIR 64(7) 520-528.pdf516.1 kBAdobe PDFView/Open

Items in NOPR are protected by copyright, with all rights reserved, unless otherwise indicated.