Groundwater Quality Prediction and Investigating the Effect of its Changes on Land Prices

Document Type : Research Paper

Authors

• Reza Moghaddasi ¹
• Danial Valadkhan ²
• Amir Mohammadinejad ¹

¹ Faculty Member of Agricultural Economics, Islamic Azad University of Science and Research

² Ph. D student of Agricultural Economic - Natural Resources and Environmental

10.30495/jae.2024.31888.2383

Abstract

The main goal of this study is to predict the groundwater quality index in the short term. This process is made with the historical data of four variables that affect groundwater quality as input data. The effective parameters on the groundwater quality index ‎include rainfall rate, temperature and groundwater ‎abstraction was collected from 2009 to 2021. The results showed that the decrease in rainfall, and increase in temperature and the increase in groundwater abstraction in the warm seasons of the year cause a decrease in the groundwater quality index with a short-term break. Also the results showed that the Long-Short Term Memory model is efficient in groundwater quality prediction by using the historical data of the mentioned variables. Finally, by comparing the changes in the water quality index and the agricultural farms price, it was found that changes in the ground water quality first causes a decline in agricultural activity levels and agriculture land prices, and then by changing lands owner behavior, land price changes become ineffective.

Keywords

• Groundwater
• Water Quality
• Prediction
• Neural Network
• LSTM

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