Evaluation of Groundwater Quality using the GQI Index for Drinking Purposes

Extended Abstract Background: The use of groundwater for agricultural, industrial, and drinking purposes is significantly increasing worldwide. These resources are considered an important part of the renewable water ecosystem and have various advantages over surface waters, such as higher quality and less contamination. However, recent intermittent droughts and a noticeable decrease in surface water resources have led to the excessive use of groundwater sources and a decline in their quality. Therefore, understanding the quality of groundwater is crucial for proper planning and management of these resources and requires serious attention and detailed analysis. Additionally, one of the health problems in developing areas is the lack of access to safe drinking water, and human health is at the core of sustainable development in the region. Therefore, ensuring the welfare and health of the community at an acceptable level is not possible without access to clean and standardized drinking water. Water is important from both health and economic perspectives as it serves as a catalyst for industrial growth and the prosperity of the agricultural sector. In this regard, this research aims to evaluate and analyze the quality and spatial changes in groundwater quality based on the GQI assessment index. Methods: This research focuses on evaluating and analyzing spatial changes in groundwater quality within the study areas of Khanmirza, Lordegan, Boroujen, Ardal, and Kiar, located in  Chaharmahal and Bakhtiari province, for drinking purposes. Practical information is provided regarding the status of available water resources in the region for drinking purposes. To this aim, 28 groundwater samples were collected from legally operating wells in various locations within the mentioned counties during the  2020-2021 period and subjected to chemical analysis in the laboratory. The GQI (Groundwater Quality Index) was used to assess the quality of these samples for drinking purposes. In this study, the GQI was calculated based on the concentration values of 11 parameters, including electrical conductivity, acidity, total dissolved salts, calcium ion, sodium, magnesium, potassium, carbonate, bicarbonate, chloride, and sulfate. Subsequently, spatial zoning of the overall parameter values was performed using the chemical characteristics of the collected samples and employing the inverse distance weighting (IDW) interpolation method in the GIS software environment, and the desired information layers were obtained in raster format. Furthermore, overlays were performed by applying computational functions to the available information layers,, followed by estimating the GQI values and preparing raster maps of the index. The output maps can be utilized not only to determine the qualitative characteristics within the study area but also to analyze the trends of their variations, prepare zoning maps for  each parameter, and compare them with standard values. Results: The calculated GQI using measured samples categorizes a significant portion of the  study area within the excellent and good quality categories suitable for drinking. Additionally, the color spectrum of the zoning map indicates better water quality in the western and southern  parts of the study area than in the other sections. Generally, water quality decreases from the south toward the north and northeast. The sensitivity analysis of the model focuses on examining the impact of changing one input variable on a model's output variable. The sensitivity analysis revealed that parameters such as acidity, calcium, magnesium, total dissolved salts, and electrical conductivity had a negative effect (meaning an increase in index values and water quality improvement after removing these parameters and deterioration with their addition in the index calculation). Conversely, the concentrations of bicarbonate ions, sulfate, sodium, potassium, and chloride had a positive impact on water quality (meaning a decrease in index values and deterioration after removing these parameters and improvement with their addition in the index calculation). These parameters have allocated the highest to lowest changes in estimating the GQI index. Therefore, the GQI quality index shows greater sensitivity to the presence or absence of acidity and calcium bicarbonate than the other parameters used in determining the index, influencing decision-making regarding the classification of drinking water quality more than the other parameters. Despite having higher weights in calculating the index, some parameters show insignificant percentage changes in the index due to their presence or absence. For example, despite a lower weight of bicarbonate than magnesium ions, it shows a higher percentage change in the index after its removal than the percentage change caused by removing magnesium. Thus, higher weights for these components do not necessarily imply greater sensitivity of the model to them. Conclusion: The results of this study indicate that the groundwater quality in the studied areas is suitable for drinking purposes, and the groundwater in the study area has not been affected by changes resulting from the tested parameters in the drinking sector. Additionally, this study contributes to comprehensive and useful planning for the management and conservation of groundwater resources, enabling more informed decision-making based on groundwater quality maps in this regard.