Performance of two stochastic approaches for forecasting water quality and streamflow data from Yesilιrmak River, Turkey

被引:68
作者
Kurunç, A
Yürekli, K
Çevik, O
机构
[1] Gaziosmanpasa Univ, Fac Agr, Tashciftlik, Tokat, Turkey
[2] Gaziosmanpasa Univ, Fac Econ & Adm Sci, Tashciftlik, Tokat, Turkey
关键词
water quality; streamflow; ARIMA model; Thomas-Fiering model; forecast accuracy;
D O I
10.1016/j.envsoft.2004.11.001
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This study evaluates the forecasting performance of two modeling approaches, ARIMA and Thomas-Fiering, for selected water quality constituents and streamflow of the Yesilurmak River at Durucasu monitoring station. For this purpose, 13-year (1984-1996) monthly time series records were used to obtain the best model of each water quality constituent and streamflow from both modeling approaches. The comparison of the mean and variance of 5-year (1997-2001) observed data vs. forecasted data from the selected best models showed that the pH model from Thomas-Fiering, and EC and Cl- models from ARIMA modeling approaches should be used with caution since the forecasting values from these models does not preserve the basic statistics of observed data in terms of mean. Also the results of forecast accuracy measures including root mean square error and mean absolute error calculated for two approaches indicated that between two approaches, for Yesilumak River Thomas-Fiering model presents more reliable forecasting of water quality constituents and streamflow than ARIMA model. (c) 2005 Published by Elsevier Ltd.
引用
收藏
页码:1195 / 1200
页数:6
相关论文
共 17 条
[1]  
[Anonymous], 1997, Nonparametric methods for quantitative analysis
[2]  
Bails D.G., 1982, Business Fluctuations: Forecasting and Applications
[3]  
Box G. E. P., 1970, Time series analysis, forecasting and control
[4]  
Clarke R.T., 1984, MATH MODELS HYDROLOG
[5]  
Devore J., 1993, STAT EXPLORATION ANA
[6]   Evaluation of streamflow predictions by the IHACRES rainfall-runoff model in two South African catchments [J].
Dye, PJ ;
Croke, BFW .
ENVIRONMENTAL MODELLING & SOFTWARE, 2003, 18 (8-9) :705-712
[7]  
Greene W.H., 2000, ECONOMETRIC ANAL
[8]  
Hipel K. W., 1994, DEV WATER SCI, V45, DOI DOI 10.1016/S0167-5648(08)70651-8
[9]   Neural network modeling of salinity variation in Apalachicola River [J].
Huang, WR ;
Foo, S .
WATER RESEARCH, 2002, 36 (01) :356-362
[10]   MEASURE OF LACK OF FIT IN TIME-SERIES MODELS [J].
LJUNG, GM ;
BOX, GEP .
BIOMETRIKA, 1978, 65 (02) :297-303