asrin hosseini; mohammad reza golabi; safar marofi; nasim khalediyan; mohammad solatani
Abstract
Simulation of the rainfall-runoff process is the most important step in water engineering and water resource management studies. Exploitation of surface water and underground water resources, river management and flood warning requires prediction of river and runoff discharges of the watershed. In this ...
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Simulation of the rainfall-runoff process is the most important step in water engineering and water resource management studies. Exploitation of surface water and underground water resources, river management and flood warning requires prediction of river and runoff discharges of the watershed. In this study, Extended Kalman Filter-based Neural Network (EKFNN) method was used for rainfall-runoff modelling. Then, the results were compared with the Gene Expression Planning method, which showed good performance in rainfall-runoff modelling in most recent studies. The data used in this study is related to daily runoff and rainfall of the rain gauge and hydrometric stations of Malayer plain which includes Peyhan, Marvil and Namyleh stations, during the period of 2001 to 2013. The results indicated that the EKFNN model was superior to GEP model in daily river flow modelling in Malayer plain. In addition, the speed of implementation of the Gene Expression Planning model was greater and was able to present results in a short time. Finally, EKFNN model was selected as the superior model for Malayer plain.
Farzaneh Ghaemizadeh; Safar Marofi; Amin Toranjian; Alireza Ildoromi; Abbas Maleki
Abstract
In many regions especially dry areas such as Iran, groundwater resources are the main sources of drinking and agricultural water. In areas where natural supply and discharge of aquifer are not balanced, the water table will be dropped and the quality and quantity of aquifer water will be affected. The ...
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In many regions especially dry areas such as Iran, groundwater resources are the main sources of drinking and agricultural water. In areas where natural supply and discharge of aquifer are not balanced, the water table will be dropped and the quality and quantity of aquifer water will be affected. The aims of present study, was to use decision support tools to provide appropriate management method for artificial recharge of Hamedan-Bahar’s aquifer, using Boolean and Fuzzy pattern in GIS environment. Also, to provide a more economical solution, the possibility of using industrial wastewater treatment in the area, has been investigated. For this purpose, seven geographical information layers including slope, land use, surface infiltration, aquifer depth, aquifer quality, net feeding and transfer capability were interpolated. The resulted output maps showed that according to Boolean pattern 2.34 percent of the lands (equivalent to 10.95 km2 of the aquifer) are located in the central and eastern areas and according to fuzzy pattern 9.44 percent of the lands (equivalent to 44.22 km2 of the aquifer) which are scattered distributed, rated very good in terms of artificial recharge of Hamedan-Bahar aquifer. Also, the results showed that the Bu-Ali industrial estate water treatment plan outlet can be used to recharge the aquifer.
