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Groundwater quality is critical for sustaining human health, agriculture, and ecosystems, as it serves as a primary source of drinking water and irrigation worldwide. Poor groundwater quality can pose serious health risks, such as exposure to contaminants like nitrates, heavy metals, and pathogens, which can lead to waterborne diseases and long-term health issues. Assessing groundwater quality is essential for identifying potential contamination sources, ensuring safe water supply, and implementing effective water management strategies. Index-based methods, such as the GALDIT model, are widely used for assessing groundwater contamination vulnerability and providing a systematic approach to identify areas at risk. This study investigated the temporal variation of the GALDIT index in 2020 and predicted the GALDIT index for 2050, considering climate change scenarios and anthropogenic activities in the Miandoab aquifer in the north-west of Iran. Analysis of the GALDIT index in 2020 and 2050 revealed decrease in the GALDIT index near the coastline, because of the shrinkage of the Lake and more distance from the shoreline. Conversely, in the center of the aquifer, the GALDIT index was more due to anthropogenic activities, while the index remained relatively stable in the southern region.

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Groundwater Quality Assessment Via Using Shallow and Deep Learning Methods as FFNN, ANFIS and CNN

  • 章节

  • 发表日期：

    2026年

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  • Nardin Jabbarian Paknezhad,
  • Vahid Nourani

摘要

Groundwater quality is critical for sustaining human health, agriculture, and ecosystems, as it serves as a primary source of drinking water and irrigation worldwide. Poor groundwater quality can pose serious health risks, such as exposure to contaminants like nitrates, heavy metals, and pathogens, which can lead to waterborne diseases and long-term health issues. Assessing groundwater quality is essential for identifying potential contamination sources, ensuring safe water supply, and implementing effective water management strategies. Index-based methods, such as the GALDIT model, are widely used for assessing groundwater contamination vulnerability and providing a systematic approach to identify areas at risk. This study investigated the temporal variation of the GALDIT index in 2020 and predicted the GALDIT index for 2050, considering climate change scenarios and anthropogenic activities in the Miandoab aquifer in the north-west of Iran. Analysis of the GALDIT index in 2020 and 2050 revealed decrease in the GALDIT index near the coastline, because of the shrinkage of the Lake and more distance from the shoreline. Conversely, in the center of the aquifer, the GALDIT index was more due to anthropogenic activities, while the index remained relatively stable in the southern region.