Modeling of monthly rainfall and runoff of Urmia lake basin using “feed-forward neural network” and “time series analysis” model

Urmia lake basin located in northwestern Iran is the second largest saline lake in the world. Due to many reasons i.e. climate changes, several dam constructions, building a bridge across the Lake, extra agricultural consumption and improper management of water resources, the water level of the lake...

Full description

Saved in:

Bibliographic Details
Published in:	Water resources and industry Vol. 7-8; no. C; pp. 38 - 48
Main Authors:	Farajzadeh, Jamileh, Fakheri Fard, Ahmad, Lotfi, Saeed
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01-09-2014 Elsevier
Subjects:	ARIMA model Feed-forward neural network Flow coefficient regime Time series forecasting Urmia lake basin Time series forecasting Urmia lake basin Feed-forward neural network ARIMA model Flow coefficient regime
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	Urmia lake basin located in northwestern Iran is the second largest saline lake in the world. Due to many reasons i.e. climate changes, several dam constructions, building a bridge across the Lake, extra agricultural consumption and improper management of water resources, the water level of the lake has been decreased since 1997 and thousand hectares of emerged salty land has made numerous ecological and environmental problems. Therefore, an accurate forecast of the entrance runoff to the lake is important in managing the river flow and water transfer within basins. There are various methods for time-series based forecasting; in the presented study Feed-forward Neural Network and Autocorrelation Regressive Integrated Moving Average (ARIMA) models were applied to forecast the monthly rainfall in Urmia lake basin. The results showed that the estimated values of monthly rainfall through Feed-forward NN were close to ARIMA model with coefficient of correlation 0.62 and the root mean square error of 12.43mm over the 6 years test period; then rainfall amount were predicted for a 6-year period starting from 2012 (2012–2017). Using the runoff coefficient regime which was calculated from parallel data of rainfall over the basin and resulted runoff for the period of 39 years, the future runoff were obtained through predicted rainfall over that period.
ISSN:	2212-3717 2212-3717
DOI:	10.1016/j.wri.2014.10.003