Keywords

1 Introduction

Nowadays, groundwater vulnerability assessment has become a useful tool for groundwater contamination prevention. Groundwater vulnerability maps provide useful data to protect groundwater resources and to work as a tool for water management with changes in agricultural patterns and land use applications (Babiker et al. 2005; Albuquerque et al. 2013; Awawdeh et al. 2014; Singh et al. 2015). Several authors acknowledge two different types of groundwater vulnerability, the intrinsic vulnerability and extrinsic or specific vulnerability (Stiger et al. 2006): the first term as a function of hydrogeological factors and the second one defined through the potential anthropogenic influence. The most widely used method of vulnerability analysis is the DRASTIC index (Aller et al. 1987), as it is easy to compute with the minimum data requirement.

The main aim of this study was the evaluation of the groundwater vulnerability to contamination, in the Naturtejo Geopark (Fig. 1), using a modified DRASTIC method in a GIS environment. The modified DRASTIC index (DRASTICAI) was made by assigning a new attribute designated as anthropogenic influence.

Fig. 1
figure 1

Study area: Vila Velha de Rodão, Castelo Branco and Idanha-a-Nova municipalities integrating the Naturtejo Geopark

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2 Materials and Methods

The DRASTIC model is constructed using combined spatial datasets on depth to groundwater (D), aquifer recharge (R), aquifer media (A), soil media (S), topography (T), impact of the vadose zone (I) and hydraulic conductivity (C) of the aquifer (Aller et al. 1987). The purpose of the DRASTIC index implies multiplying each factor weight (Table 1) by its category rating (Table 2) as follows:

$$\begin{aligned} {\text{DRASTIC}} & = D_{{\text{r}}} *D_{{\text{w}}} + R_{{\text{r}}} *R_{{\text{w}}} + A_{{\text{r}}} *A_{{\text{w}}} + S_{{\text{r}}} *S_{{\text{w}}} \\ & \quad + T_{{\text{r}}} *T_{{\text{w}}} + I_{{\text{r}}} *I_{{\text{w}}} + C_{{\text{r}}} *C_{{\text{w}}} \\ \end{aligned}$$
(1)
Table 1 Assigned weights for DRASTIC parameters
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Table 2 DRASTIC
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In this study, one extra parameter was added to the DRASTIC model to map the groundwater vulnerability in the study area more accurately, including the anthropogenic influence. This new parameter, anthropogenic influence (AI), was assigned a weight value equal to 5, and the modified DRASTIC index, DRASTICAI, computed using the following equation:

$$\begin{aligned} {\text{DRASTICAI}} & = D_{{\text{r}}} *D_{{\text{w}}} + R_{{\text{r}}} *R_{{\text{w}}} + A_{{\text{r}}} *A_{{\text{w}}} + S_{{\text{r}}} *S_{{\text{w}}} \\ & \quad + T_{{\text{r}}} *T_{{\text{w}}} + I_{{\text{r}}} *I_{{\text{w}}} + C_{{\text{r}}} *C_{{\text{w}}} + AI_{{\text{r}}} *AI_{{\text{w}}} \\ \end{aligned}$$
(2)

where D is depth to groundwater, R is recharge rate (net), A is aquifer media, S is soil media, T is topography (slope), I is impact of the vadose zone, C is conductivity (hydraulic) of the aquifer, and AI is anthropogenic influence (Table 1):

ArcGIS 10 was used to process the datasets and to create the eight layers, corresponding to the eight considered attributes, and groundwater vulnerability maps by overlaying the available information (Fig. 2).

Fig. 2
figure 2

Maps corresponding to the topography and anthropogenic influence

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3 Results

For aquifer vulnerability assessment of the study area, seven and eight thematic maps were prepared for the DRASTIC and the DRASTICAI indices computation, respectively (Fig. 3).

Fig. 3
figure 3

DRASTIC and DRASTICAI layer attributes

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The DRASTIC risk map shows two different levels of vulnerability: low and moderate (Fig. 4a). The northern Idanha-a-Nova and Castelo Branco areas show low vulnerability (105–119) as the remaining territory is moderately vulnerable (120–138). However, when analysing the DRASTICAI map, it is possible to identify considerable changes in the spatial patterns of vulnerability (Fig. 4b). Indeed, five levels of growing vulnerability, from low to high, can be acknowledged. Idanha-a-Nova municipality is the most affected by the anthropogenic influence due to intensive farming activities.

Fig. 4
figure 4

DRASTIC (a) and DRASTICAI (b) maps

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4 Discussion

Land use parameters can significantly affect hydrogeological parameters. The properties of hydrogeological parameters can be changed by the use of pesticides, the addition of urban and industrial wastes, leakages from septic tanks and waste dumping sites. Land use classification of the study area showed that a major portion of the area is used for agriculture (Fig. 3). Groundwater is more vulnerable to nitrate concentration in agricultural fields. In groundwater systems, nitrate distribution principally depends upon the soil dynamics, recharge rate, groundwater movement and on-ground nitrogen loading (Shirazi et al. 2013). The study area is significantly influenced by agricultural activities.

The algebraic subtraction between the DRASTIC and DRASTICAI maps shows an important contribution of the anthropogenic influence (Fig. 5). It is possible to mention all over the surveyed area, but specifically in Idanha-a-Nova municipality, a rousing effect from low/moderate vulnerability up to highly vulnerable.

Fig. 5
figure 5

Map representing the algebraic subtraction of DRASTIC and DRASTICAI

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5 Concluding Remarks

This survey aimed at the evaluation of the groundwater vulnerability to contamination, in the Naturtejo Geopark area, using a modified DRASTIC index, DRASTICAI. This new index was constructed by adding a new attribute designated as anthropogenic influence.

The DRASTICAI spatial patterns indicate a clear influence of anthropogenic activities, mainly in the Idanha-a-Nova municipality.

Water is one of the most strategic resources in the world. Portugal has important resources of groundwater that may be strategic to face the expected dry years to come. Furthermore, regularly monitoring and evaluating groundwater quality is needed for integrated management and policymaking.