Volume 12, Issue 24 (9-2021)                   J Watershed Manage Res 2021, 12(24): 228-235 | Back to browse issues page


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Norooz Valashedi R, Helali J. (2021). Caspian Sea Basin Autumnal Precipitation Forecasting Based on Teleconnection Patterns. J Watershed Manage Res. 12(24), 228-235. doi:10.52547/jwmr.12.24.228
URL: http://jwmr.sanru.ac.ir/article-1-1103-en.html
Sari Agricultural Sciences and Natural Resources University
Abstract:   (2383 Views)
Extended Abstract
Introduction and Objective: Teleconnection patterns are one of the effective hydro-climatological factors in predicting precipitation, temperature and discharge on a large scale. Oppositely, comprehensive and integrated management of water resources requires that rainfall variables and consequently runoff flow can be predicted. From a dynamic and synoptic approach, teleconnection patterns can affect the precipitation pattern of different regions. The purpose of this study is to inspect the relationship between these indicators and autumn rainfall in the Caspian Sea basin and forecast it using various statistical models.
Material and Methods: Therefore, in this study, Caspian Sea sub-basins were selected and autumn rainfall in the 28-year period from 1987 to 2015 was calculated. Then the correlation of MEI, SOI, NCP, NAO, AO, CSST, P-SST and MSST indices with autumn rainfall in July, Aug, Sep, Oct, Nov, summer, Aug-Sep-Oct and Sep-Oct-Nov was calculated. And the most important ones that had the highest correlation were considered as inputs to different models. Finally, autumn rainfall forecasting was done using a statistical model and three artificial intelligence models with different structures.
Results: The study showed that various teleconnection patterns were effective depending on the type of sub-basin and time step. Prediction results showed that the difference between observational and modeled data in the training period was small and increased somewhat in the test period and reached about -25.7 to 47.6 mm in the whole sub-basins. Thoughtfulness of the type of analytical model showed that both SVR and MLP models had higher accuracy than GRNN and MLR models, so that the Root Mean Square Error by SVR model in Aras, Atrak, Haraz-Sefidrood, Qarahsu-Gorgan, Serazod-Haraz, and Haraz-Qarahsu sub-basins. 6.18, 7.34, 35.44, 18.25, 19.58, 17.68 and 47.22 mm, respectively, and the coefficient of determination will be 0.94, 0.91, 0.92, 0.84, 0.88, 0.88 and 0.87, respectively.
Conclusion: Therefore, the results show a strong relationship between teleconnection indices with autumn rainfall in the study basin. These include NAO, SOI, AO and Caspian and Mediterranean Sea surface temperatures at different time delays. With these results, steps can be taken to more accurately predict and manage the water resources of the Caspian Sea basin.
 
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Type of Study: Research | Subject: هواشناسی
Received: 2020/08/12 | Revised: 2022/02/23 | Accepted: 2020/09/28 | Published: 2021/09/1

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