Modeling Monthly Rainfall in Southern Baluchestan Basin

Autor: Safar Marofi, Reza Norooz Valashedi, Foroogh Golkar
Jazyk: perština
Rok vydání: 2017
Předmět:
Zdroj: تحقيقات جغرافيايی, Vol 32, Iss 1, Pp 149-162 (2017)
Druh dokumentu: article
ISSN: 1019-7052
2538-4384
Popis: Flood and drought have caused several damages in natural and unnatural ecosystems in recent decade. Rainfall prediction can be useful in water resource management. The goal of this study is modeling the monthly precipitation of south east of Iran in South-Baluchistan basin, using artificial neural network (ANN) and stochastic models. This area has an unpredictable and complicated monthly rainfall pattern due to impact of several different precipitation systems of other surrounding regions. SARIMA time series models and Time Delay Neural Network (TDNN) are used in monthly precipitation forecasting. Monthly time series of rainfall during 1351-52 to 1387-88 in selected station were used in this study. Stations selection was based on Geographical distribution and data quality. Comparing the results of models of forecasting showed that TDNN model is superior to SARIMA time series model due to different rainfall systems and very sporadic precipitation in this area.
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