Comparison of optimal Artificial Neural Network models for groundwater nitrate simulation (Case Study: Behbahan Plain)

Subject Areas : Neural networks and deep learning

atefeh sayadi shahraki ¹ , Fahimeh Sayadi Shahraki ² , Bijan Haghighati ³

1 - سازمان تحقیقات، آموزش و ترویج کشاورزی شهرکرد
2 - Tehran, Islamic Azad University of Shahre qods
3 - Agricultural Research, Education and Extension Organization (AREEO), Shahrekord

Received: 2024-09-06 Accepted : 2024-11-05 Published : 2024-12-19

Keywords: Artificial Neural Network, Genetic Algorithm, Nitrate, Particle Swarm Optimization Algorithm, Simulation,

Abstract :

Groundwater is the most important water resource for drinking and agricultural usage especially in arid and semi-arid regions. So, it is important to note its quality. Nitrate is one of the groundwater pollutants which is mostly derived from agricultural and wastewater sources. Since nitrate determination using sampling was very expensive and limited, it is necessary to use new prediction methods like artificial neural network. The use of artificial neural networks in hydrological studies of the last decade shows that these models have a high ability to discover the relationship between data and recognize patterns. The success of neural network models in estimating different parameters of water sources has always been emphasized by different researchers.

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