Groundwater is a valuable resource for human life and economic development. Its quantity and quality are of vital importance in arid and semi-arid areas, where the climatic conditions are characterized by low rainfall and high evapotranspiration, impacting surficial water resources and the aquifer recharge. The concept of groundwater vulnerability was first introduced by J. Margat in 1968; today it is of importance for the protection of groundwater resources. Assessing the vulnerability of an aquifer permits the identification of areas that are more susceptible to being contaminated, allowing to carry out effective protection measures and management plans for pollutants or wastes. Vulnerability assessment is really relevant as remediation of aquifers would be difficult and expensive (Aydi, 2018; Yin et al., 2013).
The intrinsic vulnerability defines the vulnerability of an aquifer to a variety of pollutants, independently of their nature, and it is related to the aquifer’s features (hydrological, geological, and hydrogeological) (Oke, 2020). In that sense the vulnerability depends on the resistance of the aquifer itself when receiving pollutants from outside, the lower the resistance, the greater the vulnerability. Influencing factors are: depth to groundwater; net recharge rate; aquifer media; topography; vadose zone; hydraulic conductivity; aquifer thickness; and, pumping density rate in case of over-pumping (Abu-Bakr, 2020).
Aquifers will have different reactions to different pollutants due to their physicochemical characteristics. In those cases, it is more appropriate to talk about the specific vulnerability which defines the vulnerability to a specific contaminant or group of contaminants considering the contaminants’ properties and its interaction with the aquifer (Gogu and Dassargues, 2000; Voutchkova et al., 2021).
Many methods have been developed to assess the groundwater vulnerability; they can be classified into three types: simulation methods, statistical methods, and index methods. The index-based techniques have the advantage that they do not depend on data availability or similarities (Barbulescu, 2020), being widely used. One of the most widely used index-based methods is the DRASTIC index, developed by the United States Environmental Protection Agency (EPA) to assess the potential for groundwater contamination (Aller, 1987). DRASTIC considers seven parameters: Depth to water table (D), net Recharge (R), Aquifer media (A), Soil media (S), Topography (T), Impact of the vadose zone (I), and hydraulic Conductivity (C) which, together, form the acronym.
Frequently, new parameters are added to the seven main hydrogeological parameters of the DRASTIC index. Additional parameters used by authors include: land-use (Kozłowski and Sojka, 2019), lineament (Abdullah et al., 2015), proximity to rivers, residential areas and roads (Aydi, 2018), hydraulic parameters (Lappas, I and Matiatos, I, 2014), redox state of the aquifer (Voutchkova et al., 2021), adsorption capacity of soils (Jr and Viero, 2006), contamination index (Cd) and heavy metal pollution index (HPI) (Haque et al., 2018). The DRASTIC index defines the aquifer intrinsic vulnerability; nevertheless, contaminant specific methods have been developed based on it. Thus, DRASTIC modifications have been undertaken to assess the groundwater vulnerability to nitrate (Jia et al., 2019; Voutchkova et al., 2021), pesticides (Al-Mallah and Al-Qurnawi, 2018; Thapa, 2018) and mining pollutants (Barbulescu, 2020; Haque et al., 2018; Tiwari et al., 2016).
Groundwater contamination related to the mining industry is an important global issue. Sulphide oxidation and the associated acid mine drainage (AMD) or acid rock drainage (ARD) is considered as one of the main water pollutants in many countries that have historic or current mining activities. AMD is prominent in both active and abandoned mining sites (Simate and Ndlovu, 2014). Mining areas are distinguished by the presence of waste dumps, mine tailings, water storage ponds, access roads and heap leach pads. These features are common indications of mining impacts to the surrounding areas and possible sources of metals. Some of these features are clearly detectable with remote sensing techniques (Werner et al., 2019). Indeed, many efforts have been undertaken to detect mining wastes, its impacts and site remediation by remote sensing (Balaniuk et al., 2020; Buczyńska, 2020; Connette et al., 2016; Firozjaei et al., 2021; Hao et al., 2019; Khosravi et al., 2021; McKenna et al., 2020). Normalized difference vegetation index (NDVI) is mostly used in vegetation growth research (Wang et al., 2021), it is calculated as the level of greenness using imagery. NDVI is also a useful tool for distinguishing the boundaries of vegetated terrain from tailings impoundments, which the NDVI primarily assigns negative pixel values (Firozjaei et al., 2021; Schimmer, 2008; Zeng et al., 2017).
To our knowledge, this is the first attempt to evaluate groundwater vulnerability to metallic pollution by the addition of a land use parameter in which possible sources of metals are considered to provide greater certainty to the vulnerability assessment at mining areas. We applied a supervised classification method to detect possible sources of metals on the area based on the NDVI values of known mining sites, mining wastes and mineralized areas of the study site.
The aims of the present work were: (i) propose a new method combining remote sensing and the DRASTIC procedure (modified DRASTIC method), (ii) identify possible sources of heavy metals (active and inactive mines, mining wastes and mineralized areas) by a remote sensing work using a supervised classification procedure based on NDVI, (iii) assessing the ground water vulnerability to metal pollution at the mining area of The Rio Sonora basin and, (iv) comparing and validating the results obtained by the DRASTIC method and the proposed modified DRASTIC method.