Assessment of groundwater vulnerability in the Daule

STOTEN-20830; No of Pages 10 Science of the Total Environment xxx (2016) xxx–xxx

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Assessment of groundwater vulnerability in the Daule aquifer, Ecuador, using the susceptibility index method Luís Ribeiro a,b,⁎, Juan Carlos Pindo a, Luis Dominguez-Granda a a b

Escuela Superior Politécnica del Litoral, ESPOL, Centro del Agua y Desarrollo Sustentable, Campus Gustavo Galindo Km 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1040-001 Lisboa, Portugal

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Groundwater vulnerability was assessed by using SI method. • Quaternary unit is classified as highly vulnerable due dominant paddy fields. • A monitoring network is proposed to acquire N03 data for SI map validation.

a r t i c l e

i n f o

Article history: Received 22 February 2016 Received in revised form 1 September 2016 Accepted 1 September 2016 Available online xxxx Editor: D. Barcelo Keywords: Vulnerability index Agriculture Contamination Net recharge Land use

a b s t r a c t The Guayas region in Ecuador is economically very important, producing 68% of the national crops. The main agricultural activities threaten the groundwater therein with nitrate contamination given the large fertiliser and water needs. The present work tests the applicability of the susceptibility index assessment method in evaluating the impact of agricultural activities on groundwater quality, using as a case study an aquifer of the Guayas river basin in Ecuador. The index adapts four parameters of the DRASTIC method and incorporated a new land use parameter. Results show that the areas highly vulnerable to contamination are located in irrigation perimeters of dominant paddy fields associated with the high recharge rates in the alluvial deposits. Respectively, moderately vulnerable and low-vulnerability areas correspond to aquatic environments and forests, semi-natural zones and water bodies. One of the main contributions of the Daule aquifer vulnerability is likely its wide, flat topography. A great part of the aquifer is at high risk of contamination by nitrates if a code of good agricultural practices is not applied. Therefore the implementation of a monitoring network to control the nitrates concentrations is the first step to assure groundwater quality for drinking purposes. © 2016 Elsevier B.V. All rights reserved.

1. Introduction ⁎ Corresponding author at: CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1040-001 Lisboa, Portugal.

Groundwater vulnerability can be defined as “an intrinsic property of a groundwater system that depends on the sensitivity of that system

http://dx.doi.org/10.1016/j.scitotenv.2016.09.004 0048-9697/© 2016 Elsevier B.V. All rights reserved.

Please cite this article as: Ribeiro, L., et al., Assessment of groundwater vulnerability in the Daule aquifer, Ecuador, using the susceptibility index method, Sci Total Environ (2016), http://dx.doi.org/10.1016/j.scitotenv.2016.09.004

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L. Ribeiro et al. / Science of the Total Environment xxx (2016) xxx–xxx

to human and/or natural impacts” (Vrba and Zoporozec, 1994). However, in addition to an intrinsic propierty that focuses singly on hydrogeological factors, there is also a specific vulnerability that involves factors related to human activities such as the type of contaminant and the land use. Accurately assessing the degree of vulnerability of bodies of water is highly important as it represents a very useful tool for the managing authorities to support Basin Water Plan The methods for assessing groundwater vulnerability can be divided in index methods, statistical methods and process methods (Focazio et al., 2002) Index methods assign numerical scores or ratings directly to various physical attributes to develop a range of vulnerability categories. Statistical methods range from simple summary or descriptive statistics of concentrations of targeted contaminants to more complex regression analyses that incorporate the effects of several predictor variables. Process-based methods refer to approaches that either simulate or otherwise take into account physical processes of water movement and the associated fate and transport of contaminants in the environment. These approaches usually include the use of process simulating models that calculate the distribution of vulnerable or intrinsically susceptible areas based on the movement of water and solutes. Simple and quick methods using only lithological information are currently applied for large scales These methods are considerably open to criticism as permeability classes are attributed subjectively to lithological types (Robbins, 1998). Other evaluation methods, called parametric, are based on the selection of a set of parameters considered representative for assessing the degree of vulnerability. The parametric methods include: i.) DRASTIC, an acronymic of seven variables from which the model name is derived: depth to water, recharge, aquifer media, soil media, topography, impact of the vadose zone, and hydraulic conductivity (Aller et al., 1987); ii.) the AVI method derived from the aquifer vulnerability index (van Stempvoort et al., 1993); and iii.) GOD, an acronym of three variables—groundwater occurrence, overall lithology of the unsaturated zone and depth to groundwater (Foster, 1987). These methods are generally developed with discrete intervals whereby each interval is assigned a value or class of values that reflect the degree of sensitivity to contamination, and with a weighting system option. In addition to the intrinsic vulnerability methods several other methods are available to evaluate specific vulnerability. These can be classified as: i.) lithological oriented, such as EPIK, an acronym of the parameters epikarst (E), protective cover (P), infiltration conditions (I) and karstic network (K) (Doerfliger & Zwahlen, 1997), or ii.) pollutant oriented such as SI (susceptibility index) for nitrate (Ribeiro, 2000). The determining factor for choosing the most appropriate methods for assessing groundwater vulnerability is the availability of sufficient quantitative and qualitative data on aquifer hydrological, hydrogeological and geomorphological features. The selected method is required to have a more expeditious nature without the need for generating estimates with high levels of uncertainty or the use of a large number of parameters. DRASTIC is one of the most widely used groundwater vulnerability assessment index methods, with applications in countries such as the United States (Rupert, 2001), Sweden (Rosen, 1994), South Korea (Kim and Hamm, 1999), South Africa (Lynch et al., 1997) and Portugal (Lobo-Ferreira and Oliveira, 1993), among many others. Although the authors of DRASTIC (cf. Aller et al., 1987) recognised that there is a clear interaction between some parameters, they also understood that the elimination of some parameters entails a loss of valuable information on the outcome of the index. The reaction was the development of methods that integrate a reduced number of parameters, such as AVI or GOD, yet without losing the representation of the main processes or the integration of the parameter land use and of a new weighting system, such as the SI. However, synthesising the

vulnerability characteristics in a minimum number of parameters is not without detrimental aspects. For example, the use of AVI is highly dependent on whether there is a significant number of lithological logs with spatial representation in the area under review, so as to be able to estimate the thickness and hydraulic conductivity of the hydro-stratigraphic units above the water table. Finally, the great majority of the methods ignore parameters that may have an important role in groundwater vulnerability assessment in certain areas such as the hydraulic gradient, the porosity, the content of soil moisture and various reactive and absorption/adsorption properties. A discussion about these issues can be found in Stigter et al. (2006). Field studies show that specific methods incorporating information about the land cover type and/or the type of associated human activities (e.g., the type and nature of agricultural practices) perform better than the purely intrinsic methods (Stigter et al., 2006). A negative aspect of the intrinsic methods is the arbitrariness of the weighting system for the parameters used. This is because the incorporated consensus of a Delphi has been obtained in a specific hydro-climatic environment, and thus, unable to be applied to assess vulnerability in differing climatic realities (for example, DRASTIC). Another frequent criticism of the DRASTIC method is the redundancy in the parameters used for calculating the index—such is the case of S and I parameters whose influence overrides that of the already part vadose subset. For instance and according to Francés et al. (2002), the soil type is indirectly represented by land use, hereby referring to Foster (1987). However, many authors, including Foster (1987) and Vrba and Zaporozec (1994), recognize that the soil can have a large attenuation potential, especially when rich in clay minerals and organic matter. In other words, leaving the soil properties out of the vulnerability assessment is not necessarily an obvious choice. On the other hand, an additional justification can be given by the fact that, due to ploughing, tillage and many other techniques applied to improve the soil structure and fertility, the natural soils are frequently disturbed during cultivation of land so that they lose much of their original characteristics. The same type of redundancy exists for the aquifer type parameters and hydraulic conductivity. Since its creation by Ribeiro (2000), Susceptibility Index (SI) has been applied in various case studies, mainly in Portugal: aquifer de Gabros de Beja (Francés et al., 2002; Serra et al., 2003; Ribeiro et al., 2003; Nascimento et al., 2004); Tejo and Sado aquifer (Paralta et al., 2001; Batista, 2004); Albufeira golf course (Stigter et al., 2002); Campina de Faro and Tavira aquifers (Stigter et al., 2003; Stigter et al., 2006; Stigter, 2005); Escusa aquifer (Amaro, 2004); Moura-Ficalho aquifer (Oliveira, 2004); and Évora-Montemor-Cuba aquifer (Mendes, 2004). The work of Stigter et al. (2006) was a fundamental step in SI validation because it proved that the incorporation of land use in the index calculations clearly benefits the vulnerability assessment of diffuse agricultural pollution. Therein, results obtained using validation with NO3 concentration measured in situ show the advantage of SI over DRASTIC, with the latter revealing an underestimation of the vulnerability for almost the entire aquifer area. Since then, SI has been successfully applied in different case studies to assess vulnerability: Oualidia-Sidi Moussa wetland, Morocco (El Himmer et al., 2013); Sidi Bouzid Aquifer, Tunisia (Aydi et al., 2012); aquifer of Nalgonda district, Telangana, India (Brindha and Elango, 2015); Nabeul-Hammamet aquifer, Tunisia (Anane et al., 2013); aquifer in Melaka State of Malaysia (Shirazi et al., 2013); Metline–Ras Jebel–Raf Raf aquifer, Tunisia (Hamza et al., 2007); Oued Guéniche, Tunisia (Hamza and Added, 2009); Bajo Cauca, Antioquia, Colombia (Ribeiro et al., 2011); and Caldas de Cavaca, Portugal (Teixeira et al., 2014). The main objective of this work is to evaluate the vulnerability of the Daule aquifer in the Guayas river basin, Ecuador, applying SI. This aquifer is threatened by diffuse nitrate contamination induced by agricultural practices, especially rice cultivation.



Implementing state qualitative and quantitative monitoring programmes helps to improve the planning, development, protection and management of groundwater, anticipating or controlling pollution sources and problems of overexploitation or degradation. In this case we argue that the implementation of a network to control the nitrates concentrations is vital to promote the sustainability of groundwater sources suitable for drinking purposes as well to fulfill the gap in data towards the creation of a more reliable SI map for the Daule aquifer. For the great majority of cases, groundwater monitoring networks are randomly designed, including the Daule aquifer, and consequently, need to be revised and optimised to reduce operation time and cost, remove redundant data, and strengthen the sparseness data zone with a supplementary observation well. Among the various methods for designing groundwater monitoring networks are the geostatistical ranking methods to augment or design monitoring networks for site-characterisation purposes.

2. SI method The above-mentioned DRASTIC shortcomings triggered the development of the new index, SI. Within this index, the addition of a new parameter, land use (LU) allows for incorporating the influence of the anthropogenic factors in its calculation, transforming the index from intrinsic to specific. The additional inclusion of a new weighting system inferred from a Delphi panel of Portuguese experts (Hsu and Sandford, 2007) guarantees that the results are more precise in the hydro-environmental characterisation of case studies. The principal types of land use and their assigned ratings identified by Portuguese experts (Ribeiro, 2000) are shown in Table 1. SI index method is fully described and discussed in Stigter et al. (2006).

3. Hydrogeology and aquifer systems in Guayas river basin The Guayas River Basin is located in the central-western part of Ecuador (00° 14 ‘S, 02° 27′ S; 78° 36 ‘W, 80° 36′ W) and drains through the Guayas River into the Pacific Ocean, just south of the city of Guayaquil. Most of the basin is in the coast region, while its eastern part drains to the Andean western slope of Ecuador. There are 14 aquifer systems in the Guayas river basin. In a recent study (SENAGUA, 2014), these aquifer systems were classified as verified and potential systems, depending on the level of relevant information available and using a valuation methodology in accordance with the values of flow, static level, well depth and permeability. An alternative but integrative categorisation based on detailed hydrogeological investigation of the aquifer properties, and taking into consideration its economic importance and capacity to provide the human consumption needs during water shortages, would be most useful as it would allow the identification of priority aquifers. Table 1 Land use classes and respective rates using in SI method. Land use

Rating

Agricultural areas Irrigation perimeters (annual crops), paddy fields Permanent crops (orchards, vine yards) Heterogeneous agricultural areas Pastures and agro-forested areas Artificial areas Industrial waste discharges, landfills Quarries, shipyards, open-air mines Continuous urban areas, airports, harbours, (rail)roads, areas with industrial or commercial activity, laid out green spaces Discontinuous urban areas Natural areas Aquatic environments (salt marshes, salinas, intertidal zones) Forests and semi-natural zones Water bodies

90 70 50 50 100 80 75 70 50 0 0

3

The systems Quevedo, Daule, Babahoyo – Ventanas, Milagro - Naranjito and Naranjal - Ponce Enriquez are considered priority aquifers for further research. Daule aquifer was selected for this study because of the enormous importance in terms of water supply for the agriculture. Their location in the basin can be seen in Fig. 1. Geologically, in the Daule aquifer there are three formation types (SENAGUA, 2014) that are represented in Fig. 2. Geologically the Daule aquifer is composed by the following formations: Balzar, Pichilingue, Angostura, Piñón and alluvial deposits. The Balzar formation from the Pliocene age consists of tuff, sandstone, laminated clays, sandstones with calcareous levels and conglomerates with medium to high permeability and intergranular porosity. In this region there are wells for drinking and domestic use, with depths ranging from 5 to 140 m, flow rates between 1 and 8 L/s, electrical conductivity (EC) values below 284 μS/cm and average pH of about 6.2. The Pichilingue formation from the Pleistocene age consists of river sediments with depths of wells varying from 3 to 36 m, flow b3 L/s and, EC below 264 μS/cm. Water is supplied for drinking and domestic purposes. The Angostura formation from the Miocene age, is composed of sandstones, basal conglomerate, green shale, and limestone banks with low to medium permeability. Wells are for drinking and domestic use, with a range of depths from 5 to 15 m, flow rates below 0.5 L/s and EC between 922 and 1431 μS/cm. The Piñón formation is composed of extrusive basaltic rocks with pyroclastic, not stratified, breccias and agglomerate, and is considered to be an aquiclude. The alluvial deposits consist of sediments carried by rivers, and coalluvial deposits are composed by poorly consolidated silt-clay materials. Both deposits have high permeability and porosity. Fig. 3 displays the hydrographical network. The river Daule is the main stream and the rivers Pula and Pedro Carbo are tributaries. The main water consumer from the rivers is agriculture, especially rice, corn and mango. Groundwater is mainly used for cultivation of banana trees. The main recharge sources are rain and river infiltration. 4. Application of SI to Daule aquifer In order to develop vulnerability maps, first, the different layers of topographical, land use and hydrogeological information are required. 4.1. Depth of water (D) Although there is a lack of information regarding the flow conceptual model of the Daule aquifer, we conclude from various studies that the aquifer is unconfined (SENAGUA, 2014). In order to consider a more pessimistic scenario for groundwater vulnerability, the water level values used were those registered in 2005, which were representative of a rainy season. This piezometric surface was then subtracted from the topographic surface to obtain the map of water table depths. The smallest depths to groundwater are found in the topographically flat parts near the Daule and its tributaries. In other areas, depths increase, and at some regions such as the north and west parts can even reach 30 m. The ranged values were transformed with Table 2 data. 4.2. Net recharge (R) The Guayas basin is characterised by a rainy season from December to May. Mean annual precipitation is 1462 mm and ranges from 1060 to 2316 mm, with variations related to west–east orographic factors. In dry years, precipitation can drop to 400 mm and it can increase to 4000 in wet years, such as during El Nino events. March is the wettest month, with a mean precipitation of 365 mm; August is the driest


4


Fig. 1. Location of the five more important aquifers in Guayas River basin (adapted from SENAGUA (2014).

month with a mean of 9.8 mm. Seventy-eight percent of total precipitation occurs between January and April (Borbor-Cordova et al., 2006). An average value of 20% of the precipitation was used for net recharge (SENAGUA, 2014, Nimmo et al., 2005). We also considered the part of recharge induced by irrigation from surface water and return flow that depends mainly on crop water requirements and irrigation efficiencies. In the case of the Daule region, rice cultivation requires a huge amount of water, and thereby, we have to assign the highest ranking to these areas. The ranged values were transformed with Table 2 data. In most irrigated areas corresponding to rice crops, the assigned rating is 80, indicating a recharge between 178 and 254 mm. In other areas where the geological formations are less permeable, the rating corresponded to 60. The non-agricultural areas, corresponding to urban areas were thus assigned a rating of 10, equal to recharge lower than 51 mm.

With very few exceptions, all the areas received the maximum rating (10), as topography here is very flat (slopes b 2%). 4.5. Land use (LU)

The aquifer media map was constructed based on the geological map, taking into account the relative intrinsic permeability of the lithologies of the geological formations described in Section 3. The different lithologies were transformed with Table 3 data. . The highest rating of 100 is assigned to the Quaternary alluvial and colluvial deposits. The rating of 70 is assigned to the areas of Pichilingue formation from the Pleistocene age, characterised by high permeable river sediments. Composed of medium to high permeability materials mainly sandstone, the Balzar formation received the rating 60.

The Guayas region is economically important in Ecuador because it produces 68% of the national crops, 73% of corn, 88% of bananas, 90% of export shrimp, 39% of cattle and 50% of industry and manufacturing. The main agricultural activities in the Daule region are rice, banana, palm, soy, sugar cane and maize. (Borbor-Cordova et al., 2006). Permanent crops consist of a combination of banana, sugar cane, fruit trees, plantain, African palm, cocoa, and coffee; annual crops include a combination of maize, rice, soybeans and vegetables. Table 4 is indicated fertiliser inputs to these various crops (BorborCordova et al., 2006). The input values were obtained from interviews with farmers and local agricultural agents, and multiplying this area by typical fertiliser application rates for each individual crop in this region of Ecuador. Large quantities of inorganic fertiliser such as urea, ammonium sulfate, super phosphate and ammonium phosphate are applied as routine agricultural practice in the Guayas basin (BorborCordova et al., 2006). A high rating (90) was assigned to banana and rice, which occupy N75% of the area of the Daule aquifer, while the lowest rating (0) was assigned to the areas occupied by forests, which assumes a null influence on the contamination potential. Non-agricultural land cover, urban areas and several areas with industrial or commercial activities received the rating 75. The resulting map is shown in Fig. 4.

4.4. Topography (T)

4.6. Implementation of a monitoring programme

Topographic maps (scale 1:25,000) were used to evaluate the percent slope of the land surface. SI ratings of Table 2 data were assigned to the correspondent ranges.

Based on a set of 67 monitoring wells and assuming an average range variogram of 6 km (the distance beyond which the variable is uncorrelated), we can evaluate the importance of each well in the spatial

4.3. Aquifer media (A)



A – A’

B – B*

Fig. 2. Geological formations in Daule aquifer, with two geological profiles.


5

6


Fig. 3. Hydrographical network in aquifer of Daule.

Table 2 Depth, recharge and topography classes and respective ratings using in SI method. Depth (m)

Rating

R (mm)

Rating

Topogaphy (%)

Rating

b1.5 1.5–4.6 4,6–9.1 9.1–15.2 15.2–22.9 22.9–30.5 N30.5

10 9 7 5 3 2 1

b51 51–102 102–178 178–254 N254

1 3 6 8 9

b2 2–6 6–12 12–18 N18

10 9 5 3 1

Note: The ratings are multiplied by 10.

Table 3 Aquifer media classes and respective ratings using in SI method. Massive shale Metamorphic/igneous Weathered metamorphic/igneous Glacial till Bedded sandstone, limestone and shale sequences Massive sandstone Massive limestone Sand and gravel Basalt Karst limestone

1–3 (2) 2–5 (3) 3–5 (4) 4–6 (5) 5–9 (6) 4–9 (6) 4–9 (8) 4–9 (8) 2–10 (9) 9–10 (10)

Note: The ratings are multiplied by 10; typical ratings between brackets.


L. Ribeiro et al. / Science of the Total Environment xxx (2016) xxx–xxx Table 4 Estimated values of N and P fertilisers using in land use activities in Guayas River basin (from Borbor-Cordova et al., 2006). Land use

N fertiliser kg/ha/year

P fertiliser Kg/ha/year

Permanent crops Annual crops Cocoa and coffee Banana Maize Sugar cane Rice Pastures Forests

99 58 90 250 46 140 68 0 0

13 6 8 20 5 20 0 0 0

7

Table 5 Weighting system using in SI method. Parameters

Depth

Recharge

Aquifer media

Topograhy

land use

Weight

0.186

0.212

0.259

0.121

0.222

representativeness of the Daule aquifer by calculating a representative index RK as follows: RK ¼

σ K1 2 −σ K 2 σK2

ð1Þ

whereσ 2 k is the kriging variance calculated with n points.σ 2 k1 is the kriging variance calculated with n-1 points.

Fig. 4. Land Use ranges and corresponding ratings according to SI, in Daule aquifer.


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Fig. 5. SI map of Daule aquifer.

4.7. Calculation of SI index and discussion Following parameter mapping, the vulnerability map was obtained by overlaying the individual maps in a GIS and calculating the indices on a fine mesh (grid spacing of 25 m). For each grid, SI was calculated through the weighted sum of the parameters, in turn based on the values listed in Table 5. The resulting map is displayed in Fig. 5. Six value-based categories were considered, and they reflect a qualitative vulnerability evaluation ranging from “extremely low” to “very high” (Fig. 6). A large part of the central quaternary alluvial deposits unit is classified as “highly” vulnerable (index 70–80) to contamination. This high vulnerability results from the presence of dominant paddy fields and

irrigation perimeters and due to high recharge rates. Where urban, industrial or commercial areas exist, the alluvial deposits classification decreases drastically to extremely low vulnerability (index 5–30). However, the area of forests and semi natural zones is classified as moderate to low vulnerability (index 50–60). The alluvial deposits in the south-eastern part coincide with areas of superficial aquatic habitats and forests, and are classified as moderate to high vulnerability (index 60–70). Large areas of the Pichilingue formation in the eastern part of the aquifer they are classified as moderate to highly vulnerable. This is mainly due to: i.) the lower net recharge rates (class 102–178) comparing with higher class occurring in the alluvial area; and ii.) although with less influence, to a deeper water table) in the north-eastern part



9

F Frequency SI 0 000 80 0 000 70 0 000 60 0 000 50 0 000 40 50 0,2% %

0 000 30 0 000 20 24 4,4% %

0 000 10 0

2,4% %

30 0

1 11,7% %

% 9 9,3%

40 0 5 50

50 0 6 60

2%

30 0 40

0

60 0 7 70

70 0 80 8

80 0 90

S SI(Class) Fig. 6. Classes of vulnerability in Daule aquifer using SI method.

of the aquifer. Similarly to the alluvial deposits, the influence of land use is also fundamental for the variability of the magnitude of the vulnerability index as seen in areas where forests, aquatic and semi natural environments exist. The majority of the Balzar formation situated in the western part of the aquifer is classified as low vulnerability (index 40–50) where the main land use is forests and semi-natural zones, and there are bodies of water. However, the presence of aquatic environments contributes to the increase of SI in some areas up to moderate to low (index 50– 60). The parameter net recharge has a contributing value for the SI calculation in the interval of 102–178 mm. Finally, the flat topography that is common throughout the aquifer (slopes b 2%) contributes considerably to the high vulnerability of the groundwater in the Daule aquifer. In short, a great majority of the aquifer is in high risk of contamination by nitrates on groundwater if good agriculture practices are not applied (FAO, 2004). Hence, we argue that the implementation of a network to control the nitrates concentrations is vital to promote the sustainability of groundwater sources suitable for drinking purposes. Notwithstanding, the level of uncertainty of the SI map is considered high because of the lack of information for characterising the different layers, especially recharge and depth to water maps, where the relative absence of spatially regular distributed data is a key issue. The consequence is generating errors and high levels of uncertainty in the estimation in areas where there is scarce information available, the implementation of a representative monitoring network is an urgent step to fulfill the gap in data towards the creation of a more reliable SI map. Therefore a monitoring network is proposed by calculating the representative index RK by using Eq. 1 and the 67 wells represented in Fig. 7. Considering a RK threshold of 4, the most representative wells for NO3 measurements for SI map validation are the red points represented in Fig. 7. These results will help decision-makers to improve sampling campaigns by identifying undersampled areas as well as for the declustering of the data in order to obtain representative data to validate SI map.

Fig. 7. Monitoring network of aquifer of Daule (Red points are the selected points to be used for NO3 measurements for SI map validation). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)


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5. Conclusions The application of the susceptibility index for diffuse agricultural pollution as a specific vulnerability method, clearly benefits from the incorporation of land use in the index calculations. High recharge and flat topography contribute to high vulnerability. The results of applying SI in the Daule aquifer show that a great majority of the aquifer is at high risk of contamination by nitrates if good agricultural practices are not applied. This is due to the large amounts of fertiliser used in the cultivation of rice and banana as well the excess of water in irrigation. Therefore, the implementation of a network to control the concentrations of nitrates is vital to protect the groundwater sources for drinking purposes. In spite of the lack of NO3 concentrations measurements to validate the SI map, this map allowed the proposition of a groundwater monitoring network. Moreover, this map can represent a useful tool for the authorities, supporting decision-making in terms of water resources planning and for implementing monitoring programmes and networks to control groundwater quality in the Daule aquifer. Acknowledgments This work was sponsored by Project PROMETEO from the Secretary of Education, Science, Technology and Innovation of Republic of Ecuador (SENESCYT) in the context of the project strengthening the national capabilities in quantitative hydrogeology: concepts, techniques and methods, which takes place in CADS-ESPOL, Guayaquil, Ecuador. The assistance of Ana Silva, Ana Buxo and Teresa Melo was deeply appreciated. References Aller, L., Bennet, T., Lehr, J.H., Petty, R.J., 1987. DRASTIC: a standardized system for evaluating groundwater pollution potential using hydrogeologic settings U.S. EPA Report 600/2–85/018, 1987. Amaro, S., 2004. Fácies Hidroquímica e Qualidade da Água do Sistema Aquífero Carbonatado de Castelo de Vide, Tese de Mestrado em Georrecursos. Instituto Superior Técnico, Lisboa. Anane, M., Abidi, B., Lachaal, F., Limam, A., Jellali, S., 2013. GIS-based DRASTIC Pesticide DRASTIC and the Susceptibility Index (SI): comparative study for evaluation of pollution. Hydrogeol. J. 21 (3), 715–731. http://dx.doi.org/10.1007/s10040-013-0952-9. Aydi, W., Saidi, S., Chalbaoui, M., Chaib, S., Ben Dhia, H., 2012. Evaluation of the Groundwater Vulnerability to Pollution Using an Intrinsic and a Specific Method in a GIS Environment. Arabian. Journal for Science and Engineering 38 (7). http://dx.doi.org/10. 1007/s13369-012-0417-9 07/2012. Batista, S., 2004. Exposição da Água Subterrânea a Pesticidas e Nitratos em Ecossistemas Agrícolas do Ribatejo e Oeste e da Beira Litoral. Tese de Doutoramento em Engenharia Agronómica. Instituto Superior de Agronomia, Lisboa. Borbor-Cordova, M.J., Boyer, E.W., Mcdowell, W.H., Hal, C.A., 2006. Nitrogen and phosphorus budgets for a tropical watershed impacted by agricultural land use: Guayas Ecuador. Biogeochemistry 79, 135–161. http://dx.doi.org/10.1007/s10533-006-9009-7. Brindha, K., L., E., 2015. Cross comparison of five popular groundwater pollution vulnerability index approaches. J. Hydrol. 524, 597–613. http://dx.doi.org/10.1016/j.jhydrol. 2015.03.003 05/2015. Doerfliger, N., Zwhalen, F., 1997. EPIK- A new method for outlining of protection areas in karstic environment. In: Gunnay, G., AI, J. (Eds.), International Symposium and Field seminar on karst waters and environmental impacts. Balkema, Rotterdam, Antalya, Turkey, pp. 117–123. El Himer, H., Fakir, Y., Stigter, T.Y., Lepage, M., El Mandour, A., Ribeiro, L., 2013. Assessment of the vulnerability to pollution of a wetland watershed. The case study of OualidiaSidi Moussa wetland. Morocco. Aquatic Ecosystem Health & Management. 16 (2), 205–215. FAO, 2004. Good Agricultural Practices – a working concept, background paper for the FAO Internal Workshop on Good Agricultural Practices. Working group paper series n. 5, Rome, Italy. Focazio, M.J., Reilly, T.E., Rupert, M.G., Helsel, D.R., 2002. Assessing ground-water vulnerability to contamination: providing scientifically defensible information for decision makers, USGS report c. 1224 p. 33. Foster, S., 1987. Fundamental concepts in aquifer vulnerability, pollution risk and protection strategy. In: Van Duijvanbooden, W., Van Waegeningh, H.G. (Eds.), Vulnerability of Soil and Groundwater to Pollution, Proceedings and Information No 38 of the International Conference Held in the Netherlands, in 1987, TNO Committee on Hydrological Research 38. Proc., Delft, The Netherlands, pp. 69–86. Francés, A., Paralta, E., Fernandes, J., Ribeiro, L., 2002. Development and Application in the Alentejo Region of a Method to Assess the Vulnerability of Groundwater to Diffuse Agricultural Pollution: the Susceptibility Index. In: L., R. (Ed.), FGR’01 - 3rd

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