پیش بینی بارندگی ماهانه ایستگاه بارانسنجی پونل با استفاده از رگرسیون خطی و آنالیز طیف تکین
عنوان مقاله English
Monthly Precipitation Forecasting in Ponel Raingauge Station Using Linear Regression and Singular Spectrum Analysis
نویسنده English
Rainfall/ precipitation, as one of the most important inputs to hydrological systems, is one of the most
significant parameters in many hydrological models. In the recent decades, different types of forecasting
methods are employed for forecasting and analyzing monthly precipitation rates. Linear regression is one
of the methods are being used for this purpose. Recently, the use of singular spectrum analysis in water
resources studies for removing random components of hydrological series has extensively increased. The
main objective of this study is to investigate the use of linear regression coupled with singular spectrum
analysis for monthly precipitation forecasting. The monthly data of Ponel raingauge station which span the
period from 1991 to 2010 (i.e. 20 years) were used to develop the proposed model. The proposed model
was compared with regular linear regression and the results indicated the superiority of combined linear
regression and singular spectrum analysis models.
کلیدواژهها English
