Document Type : Article
Authors
1
Dept. of Civil Engineering Isfahan University of Technology
2
Dept. of Irrigation and Reclamation Engineering College of Agriculture and Natural Resources University of Tehran
Abstract
Nowadays, due to population growth, climate change impacts, hydrological
uncertainty, and increasing water requirements, society, more than ever, needs
to have an accurate integrated management to supply its demands in different
parts such as agriculture, hygienists, and industry. One of the fundamental
steps in performing an integrated water resources management in a wide basin,
and supplying its demands is the optimum conjunctive use of surface water and
groundwater. In this regard, in this study, the optimum utilization of surface
water and groundwater resources is applied in Najafabad plain in Gavkhooni
basin, which is one of the most important sub-basins due to the following
reasons: (1) its contribution to supplying the agricultural needs of the basin,
(2) having negative balanced problems and loss of quality and quantity of
groundwater resources, (3) having certain complexity in terms of nutritional
conditions and interaction between water surfaces such as Zayandehrud River. To
solve the problem, the simulation-optimization method using Artificial Neural
Network model for simulating and Honey-Bee Mating algorithm as the optimization
model was applied. After training Artificial Neural Network model with 276 rows
of data from the last 23 years, the optimization model was developed due to
different constraints such as water resources capacity, drawdown of water table
in aquifer, maximum amount of surface water, and ground water. To create an
optimal utilization model, after linking simulation model and optimization models, an operating policy including 3 scenarios with different climatic conditions was developed. The results showed that selected simulation model with R2 above 95 percent and less than 8 percent error in the validation of the model for forecasting has a good performance in simulating the aquifer behavior. In addition, results show that the model can improve the mean groundwater level in three different climatic conditions: wet, normal, and dry years in the left region to the 2.3, 0.75, 1.36 meters and in the right region to the 2.14, 1.14, 0.8 meters, respectively.
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