Iranian Journal of Irrigation & Drainage

Iranian Journal of Irrigation & Drainage

Application of artificial intelligence modeling and energy economic analyses to evaluate and optimize drinking water pumping systems

Document Type : Original Article

Authors
Abdolrazagh Ghooli 1
Abdolreza Zahiri 2
Jamshid Piri 3
1 Water Engineering Dep., Faculty of Water and Soil Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Iran
2 Department of Water Science and Engineering, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.
3 Water Engineering Dep., University of Zabol, Iran
Abstract
Given the increasing population growth, as well as the intensification of the effects of climate change, and the increase in droughts in arid regions of the world, finding efficiency enhancement initiatives for water systems are considered to be the key solution in reducing the water and energy utilization. In this study, first, with the help of artificial neural networks, the behavior (pump spped) of the drinking water pumping system of Bandar Turkman located in Golestan Province was modeled over a 4-year period (1401-1398) and based on simple characteristics of this system (including the water level in the well, monthly pumping flow rate, and pump installation depth). The results showed that the calculated values of the pump speed have appropriate accuracy over the entire range of changes of this variable, although with increasing pump speed, the efficiency and accuracy of modeling decreases somewhat. Economic analysis of the pumping systems under consideration showed that the mean overall efficiency of the pumps was about 10 percent, which is much lower than industry standards (70 percent) and indicates the existence of serious challenges in the performance of the pumping systems studied in this research. It was also found that the energy consumption of these systems can be reduced to a large extent. The average monthly potential energy consumption savings in this system is equivalent to 44% of the annual consumption cost.
Keywords
Economic analysis
Optimization
Pumping systems
Machine learning models
Energy consumption
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Iranian Journal of Irrigation & Drainage
Volume 19, Issue 4 - Serial Number 113
September and October 2025
Pages 521-535