BackgroundExtensive human activities and unplanned land uses have put groundwater resources of Shiraz plain at a high risk of nitrate pollution, causing several environmental and human health issues. To address these issues, water resources managers utilize groundwater vulnerability assessment and determination of protection. This study aimed to prepare the vulnerability maps of Shiraz aquifer by using Composite DRASTIC index, Nitrate Vulnerability index, and artificial neural network and also to compare their efficiency.MethodsThe parameters of the indexes that were employed in this study are: depth to water table, net recharge, aquifer media, soil media, topography, impact of the vadose zone, hydraulic conductivity, and land use. These parameters were rated, weighted, and integrated using GIS, and then, used to develop the risk maps of Shiraz aquifer.ResultsThe results indicated that the southeastern part of the aquifer was at the highest potential risk. Given the distribution of groundwater nitrate concentrations from the wells in the underlying aquifer, the artificial neural network model offered greater accuracy compared to the other two indexes. The study concluded that the artificial neural network model is an effective model to improve the DRASTIC index and provides a confident estimate of the pollution risk.ConclusionsAs intensive agricultural activities are the dominant land use and water table is shallow in the vulnerable zones, optimized irrigation techniques and a lower rate of fertilizers are suggested. The findings of our study could be used as a scientific basis in future for sustainable groundwater management in Shiraz plain.

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Access to safe and reliable drinking water is amongst the important indicators of development in each society, and water scarcity is one of the challenges and limitations affecting development at national and regional levels and social life and economic activity areas. Generally, there are two types of drinking water sources: the first type is surface waters, including lakes, rivers, and streams and the second type is groundwaters existing in aquifers. Amongst aquifers, karst aquifers play an important role in supplying water sources of the world. Therefore, protecting these aquifers from pollution sources is of paramount importance. COP method is amongst the methods to investigate the intrinsic vulnerability of this type of aquifers, so that areas susceptible to contamination can be determined before being contaminated and these sources can be protected. In the present study, COP method was employed in order to spot the regions that are prone to contamination in the region. This method uses the properties of overlying geological layers above the water table (O factor), the concentration of flow (C factor), and precipitation (P factor) over the aquifer, as the parameters to assess the intrinsic vulnerability of groundwater resources. In this regard, geographical information system (GIS) and remote sensing (RS) were utilized to prepare the mentioned factors and the intrinsic vulnerability map was obtained. The results of COP method indicated that the northwest and the west of the region are highly and very vulnerable. This study indicated that regions with low vulnerability were observed in eastern areas, which accounted for 15.6% of the area. Moderate vulnerability was 40% and related to the northeast and southeast of the area. High vulnerability was 38.2% and related to western and southwestern regions. Very high vulnerability was 6.2% and related to the northwest of the area. By means of the analysis of sensitivity of the model, it was determined that the focus factor of the flow has the greatest impact on the creation of vulnerability in the region. Also, these results were validated through electrical conductivity and discharge time series of the regional springs that are located in the vulnerable zones.

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