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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Somayeh Emami and Hossein Dehghanisanij
The recent problems of Lake Urmia (LU) are caused by extensive and complex socio-ecological factors that require a comprehensive approach to consider the relationships between users and identify failure factors at the basin level. For this purpose, an ag...
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Mahdi Nakhaei, Fereydoun Ghazban, Pouria Nakhaei, Mohammad Gheibi, Stanislaw Waclawek and Mehdi Ahmadi
Precise forecasting of streamflow is crucial for the proper supervision of water resources. The purpose of the present investigation is to predict successive-station streamflow using the Gated Recurrent Unit (GRU) model and to quantify the impact of inpu...
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Jamal Ahmadaali, Gholam-Abbas Barani, Kourosh Qaderi and Behzad Hessari
In arid and semi-arid areas, unsustainable development of irrigated agriculture has reduced the water level of large lakes such as Aral, Urmia, Hamoon, and Bakhtegan. Urmia Lake, as a hyper saline and very shallow lake, located in the northwest of Iran, ...
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Farzad Emami and Manfred Koch
Modeling the hydrologic responses to future changes of climate is important for improving adaptive water management. In the present application to the Zarrine River Basin (ZRB), with the major reach being the main inflow source of Lake Urmia (LU), firstl...
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Alireza Taravat, Masih Rajaei, Iraj Emadodin, Hamidreza Hasheminejad, Rahman Mousavian, Ehsan Biniyaz
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Lake Urmia, the second largest saline Lake on earth and a highly endangered ecosystem, is on the brink of a serious environmental disaster similar to the catastrophic death of the Aral Sea. Progressive drying has been observed during the last decade, cau...
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