Analysis of Post-processing Method for Dynamic Models Output by using Network Data for Drought of North West of Iran

Since long time ago, prediction of precipitation status and investigation of drought hazards in catchment areas of North West of Iran, due to the critical importance of discharge rate of related catchments for Lake Uromia, has been one of the most important challenging issues in efficient management of water resources; management of vast capital of water resources and energy production of the country is highly affected by the aforesaid factors. Therefore, application of dynamic methods may play significant role in adjustment of such conditions concerning the frequencies of climate parameters and occurrence of imbalance behaviors in precipitation pattern of the country. In this regard, application of Aphrodite data can greatly reduce calculation errors and considers proper distribution of time and place in the category of post-processing framework. A wide range of methods has been used in the post-processing analysis of the output of dynamic methods; Therefore, application of post-processing technique may develop outputs of dynamic models to be used in subscales and the outputs of these models may be implemented in macro-environment management with a more comprehensive approach. Main objective of the present research consisted of developing the accuracy of seasonal predictions of precipitation of North-west of the country using dynamic model output post-processing method used toward managing the drought hazard.