Feasibility study of using Climate Teleconnection Indices in prediction of spring precipitation in Iran Basins

Document Type : Research Paper


1 Department of Irrigation and Reclamation Engineering Department, Faculty of College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran.

2 Department of Natural Geography, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran

3 Department of Irrigation and Reclamation Engineering, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

4 Department of Water Sciences & Engineering, Faculty of Agriculture and Engineering, Arak University, Arak, Iran


Management and planning in the field of water resources in different seasons, especially in spring, is very vital for exploitation in the agricultural, industrial and drinking sectors in arid and semi-arid regions of the world, especially Iran. Climate Teleconnection Indices (CTI) as large-scale indices can be important in hydrological behavior at the basin scale. In this study, the relationship between these indices and spring rainfall in the basins of Iran was investigated and the possibility of using them as predictor variables was identified. For this purpose, the correlation of 40 CTI in time delays of 6 to 1 month with spring rainfall was investigated. The results showed that the percentage of stations that have a significant correlation with spring precipitation, varies depending on the location of the basin, but in general, the indicators related to ENSO and SSTs have the most frequent significant correlations with spring rainfall in the northern half, northwest, northeast and sometimes southwest springs. These indicators in the Caspian Sea basin with a delay of 3 to 6 months, Persian Gulf-Oman Sea with a delay of 1 to 3 months, Lake Urmia with a delay of 3 months, Central Plateau with a delay of 1 to 4 months, Eastern border with a delay of 1 and 6 months, and Qarahqom basin with a delay of 1 and 3 months have the highest amount. In general, it can be said that the spring rainfall in many stations located in the watersheds of the northern half of Iran have a significant correlation with the CTI, but in the southern, the central plateau and the eastern part have the lowest correlation, which is due to the low rainfall in this season in the southern regions. The results showed that the efficiency of predicting spring precipitation by MLP model is better than MLR model.


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