Index-based groundwater vulnerability and water quality assessment in the arid region of Tata city (Morocco)

Journal Pre-proof Index-based groundwater vulnerability and water quality assessment in the arid region of Tata city (Morocco) Laura Heiß, Lhoussaine Bouchaou, Sokaina Tadoumant, Barbara Reichert PII:

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DOI:

https://doi.org/10.1016/j.gsd.2020.100344

Reference:

GSD 100344

To appear in:

Groundwater for Sustainable Development

Received Date: 8 August 2019 Revised Date:

21 January 2020

Accepted Date: 4 February 2020

Please cite this article as: Heiß, L., Bouchaou, L., Tadoumant, S., Reichert, B., Index-based groundwater vulnerability and water quality assessment in the arid region of Tata city (Morocco), Groundwater for Sustainable Development (2020), doi: https://doi.org/10.1016/j.gsd.2020.100344. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier B.V.

Index-based groundwater vulnerability and water quality assessment in the arid region of Tata city (Morocco) Graphical abstract

Groundwater vulnerability of the Tata city region based on (a) the DRASTIC Index (Di), (b) the DRASTIC-Land Cover Index (DLi), and (c) the rescaled DRASTIC-Land Cover Index (reDLi).

1

1

Index-based groundwater vulnerability and water quality assessment in the arid region of Tata

2

city (Morocco)

3

Laura Heiß*1), Lhoussaine Bouchaou2,3), Sokaina Tadoumant, Barbara Reichert1)

4

*

Corresponding author

5

1)

Institute for Geosciences, University of Bonn, Nussallee 8, 53115 Bonn, Germany. Phone:

6 7

+49228732491, Fax: +49228739037, [email protected]; [email protected]. 2)

Applied Geology and Geo-Environment Laboratory, Faculty of Science, Ibn Zohr University

8

of Agadir, Morocco. Phone: +212666769195, Fax: +212528220100, [email protected];

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[email protected].

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3)

International Water Research Institute (IWRI), Mohammed VI Polytechnic University, Mo-

11

rocco

12

Abstract

13

Within the Tata city region of the Moroccan Anti-Atlas Mountains groundwater is the only source for

14

drinking and irrigation water supply. Nevertheless, a moderate groundwater quality was already out-

15

lined. In order to understand the possible extent of groundwater pollution and to develop sustainable

16

groundwater management strategies, a groundwater vulnerably assessment was required. In this con-

17

text the overlay index model DRASTIC (depth of water, net recharge, aquifer media, soil media, to-

18

pography, impact of vadose zone, and hydraulic conductivity) was implemented using specific ratings

19

and weightings for each of the parameters. In the end, areas of greatest potential for groundwater con-

20

tamination were identified based on geological and hydrogeological parameters as well as on human

21

impact (land use).

22

The DRASTIC Index revealed that most of the study site is characterized by a low geological and

23

hydrogeological vulnerability. After implementing the land use parameter, a moderate vulnerability

24

was observed, indicating a greater groundwater pollution risk caused by human hazards. Areas of

25

greatest vulnerability occur along agricultural areas and villages. A single-parameter sensitivity anal-

26

yses resulted in a rescaling of the different DRASTIC parameters. Based on this rescaling process

27

most of the study site is of high vulnerability.

28

In a second step, hydrochemical groundwater data was used as an actual pollution indicator to verify

29

the vulnerability obtained from DRASTIC. To this end, a new Water Quality Index with respect to

30

drinking and irrigation purposes was developed, based on four key parameters (specific electrical con-

31

ductivity, chloride, nitrate, and ammonia). Thereby, nitrate revealed to be the most important chemical

32

parameter reducing the degree of usage. Elevated nitrate concentrations are restricted to urban areas

33

and derived from manure and septic waste.

34

Keywords: DRASTIC, Groundwater management, Morocco, Tata city, Vulnerability mapping, Water

35

Quality Index

36

1

37

Due to increasing climate variations, groundwater supply in drylands has gained research focus over

38

the last decades. The imbalance between groundwater recharge and extraction resulted in a continuous

39

decline in groundwater reservoirs. This is particularly true for Morocco, as some river basins experi-

40

ence a strong water deficit, because of the general decrease in precipitation (Abahous et al. 2017,

41

Filahi et al. 2016) and thus a lowering of groundwater levels (Bouchaou et al. 2011, Ouhamdouch and

42

Bahir 2017). In turn, climate variability affects groundwater quality both directly and indirectly (Hol-

43

man 2006, Earman and Dettinger 2011, Khatri and Tyagi 2015). For instance, an increase in ground-

44

water temperature, caused by global warming, might affect temperature-dependent biogeochemical

45

processes within aquifer systems (Figura et al. 2011). Furthermore, Morocco is stressed by groundwa-

46

ter deterioration induced by land use changes as well as demographic and urban pressures (Karmaoui

47

et al 2014). Given that access to clean water is the most basic human need the Moroccan Water Law

48

No 10-95 (1995) (Salman and Bradlow 2006) has prioritized the protection of the aquatic ecosystems.

49

Groundwater resources within the arid region of Tata city (Moroccan Anti-Atlas Mountains) are of

50

major concern, since it is the only regional source for drinking and irrigation water supplies. Nonethe-

Introduction

2

51

less, over the last decade, water quality reports of the Moroccan Ministry for Territory, Water, and

52

Environment (French: Ministère chargé de l’Aménagement du Territoire, de l’Eau et de

53

l’Environnement (MATEE)) (2003, 2009, and 2014) already outlined a moderate groundwater quality

54

within the Tata city region. In this context, specific electrical conductivity was of major importance in

55

terms of usage purposes. Thus, an assessment of groundwater vulnerability is very important in order

56

to understand the possible extent of groundwater pollution and to develop sustainable groundwater

57

management strategies. In fact, groundwater monitoring and mathematical modelling are not applica-

58

ble on a regional scale in data-scarce environments. Hence, a study to evaluate the potential of

59

groundwater contamination over a large geographical area involving a variety of geological, hydro-

60

geological, and anthropogenic parameters is needed. To this end, several methods have been devel-

61

oped to evaluate groundwater vulnerability and these can be subdivided into three groups: process

62

based, statistical, and overlay index (Kumar et al. 2015). The selection of an appropriate method de-

63

pends on each particular study site with its characteristics and data availability. One of the most wide-

64

spread used standard groundwater vulnerability mapping approaches is the overlay index model of

65

DRASTIC introduced by Aller et al. (1987). This approach combines maps of different geological and

66

hydrogeological parameters that control the movement of contaminants from the surface to the satu-

67

rated zone. The DRASTIC model was applied to arid and semi-arid regions (Hamza et al. 2007, Al

68

Kuisi et al. 2014, Adjim and Bensaoula 2013) as well as to Morocco in particular (Sadiki et al. 2018,

69

Knouz et al. 2018, Sinan and Razack 2009, Ettazarini 2006, Jilali et al. 2015). Furthermore, McLay et

70

al. (2001), Stigter et al. (2006), and Neshat et al. (2014) evaluated the linkage between the DRASTIC

71

model and groundwater chemistry. Once DRASTIC was applied, areas that are more prone to

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groundwater contamination than others can be identified. Thus, areas that require groundwater moni-

73

toring or protective management strategies can be defined and such measures can aid the local com-

74

munities to protect their groundwater resources.

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This study examines the groundwater vulnerability of the Tata city region in the Anti-Atlas Mountains

76

of Morocco by incorporating geological and hydrogeological parameters into the DRASTIC Index.

77

Moreover, to study potential anthropogenic influences, the DRASTIC Index was extended with the

78

land cover parameter and the DRASTIC-Land Cover Index was computed. In order to evaluate the 3

79

influence of each parameter on the aquifer vulnerability, single-parameter sensitivity analysis was

80

performed. Based on the new obtained weights, the rescaled DRASTIC-Land Cover Index was calcu-

81

lated. Additionally, to verify the hydrogeological and anthropogenic vulnerability results, hydrochem-

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ical data was used. In this context a water quality assessment, in terms of drinking and irrigation pur-

83

poses, was assigned developing a new Water Quality Index. Finally, the relation between groundwater

84

quality and hydrogeological parameters as well as human impact was evaluated. Based on these find-

85

ings, recommendations for a sustainable groundwater management can be proposed and developed.

86

2

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2.1

88

The Wadi Tata catchment covers an area of 6000 km² and is part of the Lower Drâa catchment in the

89

Moroccan Anti-Atlas Mountains (Figure 1a). The catchment is drained by the intermittent Wadi Tata

90

from N to S as well as from the Wadi Si Rezzoug from E to SW. Additionally, some smaller streams

91

contribute to both wadis. Discharge is highly variable and strongly dependent on rainfall, since the

92

contribution from springs is less than 1 m³/s (Echogdali et al. 2018). The precise study site covers an

93

area of approximately 220 km² around the city of Tata (Figure 1b). The Tata plain is surrounded by the

94

mountainous regions of the Tagragra de Tata Inlier in the north and by the Jebel Tabanit and Jebel

95

Bani mountain chains in the central parts. The southern parts are characterized by the Saharan fore-

96

land. Whereas the topographic elevations of the Tata plain decrease from 750 m a.s.l. in the north to

97

550 m a.s.l. in the south, the steep-slope mountain ridges rise between 1000 and 1200 m a.s.l. (Figure

98

1c). The climate is influenced by hot and dry air masses from the Sahara resulting in continental and

99

arid conditions with an average annual temperature of 23.2 °C (Yazidi et al. 2001). Precipitation

100

amounts are less than 91 mm/a (Yazidi et al. 2001) and highly variable in terms of their frequency,

101

duration, and intensity as well as associated with orography. Land use is mainly limited to small hold

102

farmers within palm oases. Indeed, three areas of commercial land use were found in the northern and

103

eastern parts of the study site.

Methods

Study site

4

104 105 106

Figure 1: Topographic map of the Tata city region (based on GADM 2018, USGS2018 a, USGS 2018b). a Wadi Drâa catchment within Morocco, b Wadi Tata catchment, and c digital elevation model.

107

2.1.1

108

The Anti-Atlas Mountains form the northern margin of the Eburnean West African Craton (Faik et al.

109

2001). In the north of the study site, the Infra and Lower Cambrian series discordantly overlie the Pal-

110

aeoproterozoic Tagragra de Tata Inlier (Benziane et al. 2002a). Generally, the Lower Cambrian units

111

comprise limestones and dolomites with rarer interdigitations of sandstones, siltstones, and schists

112

(Buggisch and Heinitz 1984, Faik et al. 2001). A succession of alternating thin-bedded dolomites and

113

fine-grained clastics is present in the Schist-Carbonate Lie-de-Vin Series (tw1 and tw3) (Buggisch and

114

Heinitz 1984). The “Barre de Tata” (tw2), is a massive dolomite bank (Benziane et al. 2002b) with

115

pseudomorphs of gypsum and halite (Buggisch and Heinitz 1984). The massive dolomites of the Up-

116

per Lower Limestone and Dolomite Series (ki1) are overlain by the carbonates and marls of the Schist-

117

Carbonate Series (ki2), and limestones, interlayered with siltstones of the Schist Series (ki3), charac-

118

terize the Upper Lower Cambrian (Benziane et al. 2002b). The top of the Lower Cambrian is com-

119

posed of clayey sandstones of the Terminal Sandstone Series (ki4). South of Tata city, the Middle

Geology and hydrogeology

5

120

Cambrian Jebel Tabanit Series (ks1 and ks2) is represented by outcrops of sandstones and schists

121

(Choubert and Ennadifi 1970) forming the so called inner Feijas (Faik et al. 2001). As typically, for

122

the central Anti-Atlas region, the Upper Cambrian is not present in the study site (Faik et al. 2001).

123

The Ordovician is characterized by the Jebel Bani Series (or4 to or6), a prominent sandstone-quartzite

124

massif dividing the Anti-Atlas Mountains from the Southern external Feijas of the Wadi Drâa (Faik et

125

al. 2001). Silurian outcrops are overlain by talus fans and cones (qt) of the Jebel Bani and, therefore,

126

not present in the study site. The Lower Devonian units in the southern parts are represented by the

127

Schist Sandstone Series (di3 and di4) (Choubert and Ennadifi 1970). Quaternary sediments are wide-

128

spread across the Tata plain. Along the bed of the Wadi Tata the Lacustrine Terrace Series (ql) com-

129

prises four different terraces (Benziane et al. 2002a). Grain sizes of these poorly cemented sediments

130

are highly heterogeneous ranging from silt to gravel with rare carbonates also noted. The most abun-

131

dant terrace is of Saltenian age, comprising mainly sand and gravel with a prominent carbonate layer

132

of lacustrine origin (Beziane et al. 2002b). The Alluvial Series (qa) contains gravel and sand and forms

133

the recent wadibeds of the various streams and wadis across the study site (Beziane et al. 2002b).

6

134 135 136

Figure 2: Geological map including measurement and sampling locations (based on Benziane et al. 2002a, Yazidi et al. 2002, Choubert and Ennadifi 1970).

137

In terms of hydrogeology, the Infra and Lower Cambrian carbonates and Quaternary sediments form

138

the major aquifer systems of the study site (Yazidi et al. 2001). Karstification is poorly developed and

139

limited to water movement in fractured zones (Yazidi et al. 2001). The Cambrian aquifers are mainly

140

unconfined. However, the presence of siltstone layers can cause confined conditions. Within the Qua-

141

ternary sediments unconfined to leaky conditions occur. Hydraulic conductivities of Cambrian units

142

determined for the Kerdous Inlier range between 10-7 and 10-3 m/s (Heiß et al. 2017). According to the

143

Hydraulic Basin Agency of Souss Massa and Drâa (French: Agence du Bassin Hydraulique du Souss

144

Massa et Drâa (ABHSMD)) (2013), the transmissivity of the Quaternary aquifer is estimated to be

145

10 2 m²/s and wells show productivities ranging from 0.04 to 3 L/s.

146

2.2

147

The DRASTIC Index is a numerical ranking system to assess groundwater vulnerability by means of

148

seven geological and hydrogeological parameters: depth of water (D), net recharge (R), aquifer media

149

(A), soil media (S), topography (slope, T), impact of vadose zone (I), and hydraulic conductivity (C)

The DRASTIC Index

7

150

(Aller et al. 1987). Definitions and characteristics of these parameters were initially specified by Aller

151

et al. (1987). The most important assumptions made when assessing vulnerability with DRASTIC are

152

that the contaminant is introduced at the ground surface, flushed into groundwater by precipitation,

153

and has the mobility of water (Aller et al. 1987). According to the relative contribution of each geolog-

154

ical and hydrogeological parameter to potential contamination, a consensus Delphi approach was as-

155

signed resulting in weights ranging from 1 to 5 (Aller et al. 1987). Moreover, each parameter involves

156

several ratings, where e.g. D and T have a large range with values between 1 and 10. The DRASTIC

157

Index (Di) is calculated in a linear combination including all weightings (w) and rankings (r) of each

158

geological and hydrogeological parameter (Equation 1) (Aller et al. 1987):

159

Di = D r D w + R r R w + A r A w + SrSw + Tr Tw + I r I w + C r C w

160

By using this additive model, a numerical value for any hydrogeological setting can be defined, where

161

the highest index refers to the highest vulnerability and vice versa.

162

2.2.1

163

Given that anthropogenic activities, such as industry, fertilizer usage in agricultural areas, septic tanks,

164

and sewer systems can affect groundwater quality, and thus increase its pollution risk, several authors

165

(e.g. Secunda et al. (1998) and Al-Hanbali and Kondoh (2008)), introduced a land use or land cover

166

parameter (L) into the DRASTIC Index. This parameter is an extension to the initial DRASTIC Index

167

and includes for example a range of land cover classes such as urban, agriculture, natural vegetation,

168

water, evaporation pond, and bare land (Al-Hanbali and Kondoh 2008). The L parameter was

169

weighted by 5 due to the potentially high impact on groundwater (Secunda et al. 1998). Moreover,

170

ratings between 1 and 8 were implemented for each land cover class. Based on these ratings and

171

weightings, the extended calculation of the DRASTIC-Land Cover Index (DLi) is expressed as (Equa-

172

tion 2):

173

DLi = Di + Lr L w

174

Finally, the DRASTIC indices (Di) and DRASTIC-Land Cover indices (DLi) were classified into five

175

vulnerability classes of “very low“, “low“, “moderate“, “high“, and “very high“ (Table 1). These clas-

Eq. 1

Land Cover Parameter

Eq. 2

8

176

ses were calculated by dividing the minimum and maximum possible index value by five (number of

177

vulnerability classes).

178 179

Table 1: Classification scheme for the calculated DRASTIC indices (Di) and DRASTIC-Land Cover indices (DLi). Vulnerability class

Di

DLi

Very Low

26.0 – 66.0

31.0 – 78.0

Low

66.1 – 106.0

78.1 – 125.0

Moderate

106.1 – 146.0

125.1 – 172.0

High

146.1 – 186.0

172.1 – 219.0

Very high

186.1 – 226.0

219.1 – 266.0

180

2.2.2

Parameter determination

181

Depth to water (D) data was collected by direct measurements using electric contact gauges of water

182

levels in 44 wells in March 2018. Potential evapotranspiration (PET) was calculated according to the

183

Turc (1961) formula, since daily mean relative humidity was greater than 50 % (Equation 3).

184

Eq. 3

185

Thereby, PET is the daily potential evapotranspiration (mm/day), t is the daily mean air temperature

186

(°C), and Rg is the daily solar radiation (cal/cm²/d). Resultant and in combination with precipitation

187

data from November 2015 to October 2016 Net Recharge (R) was estimated. Aquifer Media (A) in

188

the northern study site was obtained using the 1:50000 scaled geological maps of Zawyat Si Nisser

189

(Yazidi et al. 2002) and Afouzar (Benziane et al. 2002a) and the according explanations (Yazidi et al.

190

2001, Benziane et al. 2002b). For the southern study site a 1:200000 scaled geological map of Akka-

191

Tafagount-Tata (Choubert and Ennadifi 1970) was used. Within the Quaternary sediments, aquifer

192

media was determined based on drilling logs provided by the Moroccan Province Agency of Equip-

193

ment, Transport, and Logistics (French: Direction Provinciale de l'Equipement, du Transport et de la

194

Logistique (DPETL)). Further information were gained during the field survey by measuring sedimen-

195

tological profiles. Soil Media (S) parameter data was obtained from a 1:1500000 scaled soil map (Ca-

196

vallar 1950) in combination with field observations. Using the STRM 1 Arc-second (USGS 2018a) as

197

a global digital elevation model with a 30 m spatial resolution in combination with QGIS terrain anal-

198

ysis, slopes (Topography, T) were calculated. The Impact of the Vadose Zone (I) was also classified 9

199

based on the geological maps (Yazidi et al. 2002, Benziane et al. 2002a, Choubert and Ennadifi 1970)

200

and drilling logs provided by the DPETL of Tata. Hydraulic conductivities (C) were determined

201

using a variety of methods depending of the specific characteristics of each series as well as on data

202

availability (Figure 2). For fractured hard rocks (Cambrian to Devonian), hydraulic conductivity was

203

calculated following the cubic law (e.g. Cook 2003) by measuring fracture aperture and spacing over a

204

1 m² scan window. Pumping tests (n = 4), infiltration tests (n = 5), and grain size analysis (n = 8) were

205

conducted to determine hydraulic conductivities in unconsolidated sediments (Quaternary). Land

206

cover (L) was determined using the 1:100000 scaled topographic maps of Tata (1970) and Tlêta de

207

Tagmoûte (1970) provided by the Moroccan agricultural ministry as well as Open Street Map data

208

provided by MapCruzin.com.

209

In this study, the DRASTIC Index was implemented using a combination of QGIS tools and lithostrat-

210

igraphical characterizations. Due to data scarcity for the Cambrian to Devonian series, the presented

211

DRASTIC classification refers to lithostratigraphical series as shown in Figure 2. This approach is

212

assumed to be appropriate since a literature review, field observations as well as laboratory analyses

213

and interpretations showed similar results for each lithostratigraphic hard rock series. Since for the

214

Quaternary Tata plain sufficient representative data was available, the DRASTIC parameters were

215

analyzed on the platform of QGIS using inverse distance weighted interpolation (IDW). In terms of

216

the IDW, data points are linearly weighted during raster calculations. This means that the influence of

217

one point relative to another declines with distance. Thus, in terms of IDW interpolation unevenly

218

spread input data, may not adequately represent the desired surface. Furthermore, output values are

219

limited to the range of the input values used to interpolate. In this study, a raster of 100 m in each di-

220

rection and a weighting coefficient of five was used. As the Tata plain is a populated area and, thus,

221

wells located within are used for drinking and irrigation water supply and the IDW would appear to be

222

the more detailed method, the presented combination approach is in compliance with the overall aim

223

of the presented study.

10

224

2.2.3

Sensitivity analysis

225

When assessing groundwater vulnerability by using overlay index methods, subjectivity is unavoida-

226

ble in the selection of weights and ranking values (Gogu and Dassargues 2000), although this strongly

227

affects the final vulnerability index. In terms of sensitivity analysis this influence is minimized.

228

Babiker et al. (2005) stated that the empirical weights introduced by Aller et al. (1987) might vary

229

according to the specific geological and hydrogeological characteristics of each study site. Thus, the

230

re-calculation of the effective weights is an important analytical step in index-based groundwater vul-

231

nerability assessments (Napolitano and Fabbri 1996, Babiker et al. 2005). To this end, single-

232

parameter sensitivity analysis according to Napolitano and Fabbri (1996) was performed. This evalua-

233

tion provides an essential tool in order to verify the influence of weights and ratings assigned for each

234

parameter on the DRASTIC Index (Gogu and Dassargues 2000). In this study, sensitivity analysis was

235

performed using the DRATIC-Land Cover Index. The obtained effective weight (Wx) compares the

236

initial empirical weights of the geological and hydrogeological parameters as well as the land cover

237

parameter with their actual effective weights and is calculated as (Equation 4) (Napolitano and Fabbri

238

1996):

239

Wx =

240

where xr and xw are the ratings and weights for parameter x (D, R, A, S, T, I, C or L) assigned in any

241

subarea and DLi is computed from Equation 2. Hence, the obtained effective weights were used to

242

calculate a rescaled DRASTIC-Land Cover Index (reDLi) representing the proper vulnerability map-

243

ping approach for the given geological, hydrogeological, and land cover characteristics of the Tata city

244

region.

245

2.3

246

In order to verify the aquifer vulnerability obtained from geological, hydrogeological, and land cover

247

parameters using the DRASTIC model, hydrochemical groundwater data was used as an actual pollu-

248

tion indicator. This linkage provides a large amount of qualitative data and can, therefore, be an effi-

xr ⋅ xw ⋅ 100 DL i

Eq. 4

Water Quality Assessment

11

249

cient tool in planning sustainable groundwater management strategies. Based on groundwater chemis-

250

try, a new developed Water Quality Index (WQi) for drinking and irrigation purposes was established.

251

The main aim of this approach was to transform a complex set of water quality data into information

252

that is both understandable and useful for the local population.

253

2.3.1

254

The WQi was used to evaluate the impact of natural and anthropogenic processes based on key physi-

255

cal and chemical parameters. These parameters were selected following the MATEE (2014) for drink-

256

ing and irrigation water purposes.

257

A newly developed classification scheme for the WQi was computed by using quality classes of ions

258

(ci), which are based on hydrochemical groundwater data. This means that for a certain concentration,

259

a quality class (Table 2) can be assigned for each parameter. These parameters are specific electrical

260

conductivity (EC), chloride (Cl-), nitrate (NO3-), and ammonia (NH4+). In terms of their usage, the

261

quality classes can be subdivided into five classes ranging from “very good“, “good“, “moderate“,

262

“restricted“ to “very restricted“ (Table 2).

263

In terms of drinking water quality, the groundwater quality class “very good“ can be used without

264

restriction (MATEE 2003). The quality classes “good“ and “ moderate“ need to be treated, depending

265

on the specific contaminant. In terms of irrigation water, the quality classes “moderate“ and “restrict-

266

ed“ are considered to be of sufficient quality (MATEE 2003). The quality class “very restricted“

267

should not be used for either drinking or irrigation water purposes (MATEE 2003). Elevated values of

268

specific electrical conductivity, ammonia, and chloride in groundwater are not of any concern with

269

regard to drinking water purposes (WHO 2011). In contrast, a guideline value for nitrate of 50 mg/L

270

was established (WHO 2011). Regarding irrigation water purposes, the classification of nitrate is in

271

compliance with the one introduced for Tunisia by Saidi et al. (2009). Further compliance is given

272

with Ayers and Westcot (1985) for the EC classification.

273 274

Table 2: Classification scheme for the Water Quality Index (WQi) based groundwater quality for drinking and irrigation purposes (following MATEE 2014).

Development of a Water Quality Index

Very Good

Good

Moderate

Restricted

Very Restricted

12

Parameter

Class 1 (ci = 1)

Class 2 (ci = 2)

Class 3 (ci = 3)

Class 4 (ci = 4)

Class 5 (ci = 5)

< 400

400 – 1300

1300 – 2700

2700 – 3000

> 3000

< 200

200 – 300

300 – 750

750 – 1000

> 1000

NO3 (mg/L)

< 5.0

5.0 – 25

25 – 50

50 – 100

> 100

NH4+ (mg/L)

< 0.1

0.1 – 0.5

0.5 – 2.0

2.0 – 8.0

< 8.0

EC (µS/cm) -

Cl (mg/L) -

275

In compliance with Pusatli et al. (2009) and Saidi et al. (2009) the WQi is calculated as (Equation 5):

276

WQi = ∑ (ci )2

277

where ci is the quality class obtained from the chemical concentration of the parameters (electrical

278

conductivity, chloride, nitrate, and ammonia) following Table 2. Hence, the minimum and maximum

279

WQi values are 5 and 100, respectively. This new classification approach has two major advantages: i)

280

to identify the overall water quality status and ii) to detect the parameter of most influence regarding

281

the suitability for usage.

282

Groundwater samples were taken in March 2018 from 44 wells within the Tata plain (Figure 2). Sam-

283

pling points were chosen for an appropriate spatial cover within the study site. Moreover, samples

284

were collected from different land use and land cover types. Hence, samples were taken in urban areas

285

and agricultural areas as well as in natural vegetation. The wells were either pumping wells or draw

286

wells as well as public, private, or from associations. Specific electrical conductivity and oxygen con-

287

tents were measured using the portable multi-meter WTW 3420. Hydrochemical analyses were carried

288

out at the Institute for Geosciences, University of Bonn, Germany using ion chromatography (Shimad-

289

zu HIC-6A) for nitrate and chloride concentrations and photometry (Cadas 100, Dr. Lange) for ammo-

290

nia concentrations. Additionally, measurements of δ15N-NO3 and δ18O-NO3 were conducted using

291

Isotope-ratio Mass Spectrometry (Isoprime TG100) to verify nitrate sources in groundwater for five

292

samples taken in urban areas. The isotope notations are expresses as δ per mil relative to the atmos-

293

pheric N2 (AIR) and Vienna Mean Ocean Water (V-SMOW) standards. Reproducibility is ±0.2‰ for

294

δ15N-NO3 and ±0.4‰ for δ18O-NO3. In order to evaluate geological sources of N-species and chloride

295

in groundwater, CNS (vario EL CUBE, elementar) and mineralogical analyses (D8 Advance, Bruker

296

AXS) were carried out for representative rock and sediment samples.

Eq. 5

13

297

3

Results and Discussion

298

3.1

299

The geological and hydrogeological parameters of the DRASTIC Index were analyzed on the platform

300

of QGIS (Figure 3a-g). The depth to groundwater and hydraulic conductivity parameters showed most

301

variations. The relative low depth to groundwater north of Jebel Bani is directly linked to the bottle-

302

neck of the Jebel Bani Massif, resulting in an elevation of the Quaternary aquifer (Yazidi et al. 2002).

303

The differences in hydraulic conductivities of the Quaternary sediments are linked to the unconformity

304

of the grain sizes, due to changes in sedimentation and depositional environments. Additionally, the

305

bottleneck of the Jebel Bani might have acted as a natural barrier and thus larger grain sizes were de-

306

posited north of the massif and consequently higher hydraulic conductivities were observed. Net re-

307

charge is very low, because annual potential evapotranspiration revealed averagely 1061 mm and is

308

thus greater than rainfall. Thus, the net recharge parameter war rated with 1. However, in arid regions

309

recharge areas can be linked to the presence of faults and coexisting areas between faults and the

310

drainage system (Al-Hanbali and Kondoh 2008). In these regions, water is assumed to infiltrate direct-

311

ly through the vadose zone and reach the water table. Consequently, since this increases vulnerability,

312

higher ratings have to be assigned. Regions of coexisting areas between faults and drainage system

313

exist in the northern part of the study, where the fractured Lower Cambrian series are present (Figure

314

2). Correspondingly, the ratings were adjusted by the factor of 3 in these regions. Topography parame-

315

ter, presented as slopes, was steep (> 18%) for the hard rock series (Cambrian to Devonian) and rela-

316

tively flat (2.5%) for the sediments (Quaternary). Soil media was absent for the hard rock series.

317

Whereas the Alluvial Series consisted of sand and gravel (rating of 9.5), the Lacustrine Series was

The DRASTIC Index of the Tata city region

14

318

characterized as loam and thus rated by 5.

319 320 321 322 323

Figure 3: Rating maps of the geological and hydrogeological DRASTIC parameters (a-g) and land cover (h). (based on Benziane et al. 2002a, Yazidi et al. 2002, Choubert and Ennadifi 1970, topographic maps Tata (1970) and Tlêta de Tagmoûte (1970) provided by the Moroccan Ministry for Agriculture, and Open Street Map).

324

The calculated DRASTIC indices in the Tata city region were relatively homogeneous in the range of

325

73 and 133, representing vulnerability classes of “low” and “moderate”. A distinction in the DRAS-

326

TIC indices is noticed between the Cambrian to Devonian hard rock series compared to the unconsoli-

327

dated Quaternary series (Figure 4a). Whereas, the DRASTIC indices of the hard rocks series ranged

328

between 70 and 103, representing solely ”low” vulnerability classes, the DRASTIC indices of the sed-

329

iment series ranged between 96 and 133, displaying vulnerability classes of ”low” to ”moderate”, with

330

most being ”moderate”. In fact, within the surrounding Cambrian to Devonian series, the relief is steep

331

(T parameter) and the groundwater level (D parameter) is estimated to be very deep (> 22.8 m), lead15

332

ing to the observed ”low” vulnerability class. In contrast, the groundwater level within the Quaternary

333

sediments of the Tata plain ranged between 5.2 m and 25.0 m (ratings of 3 to 7). In combination with a

334

rating of 7 for the aquifer media and 6 for the impact of vadose zone media, a ”low” to ”moderate”

335

vulnerability class was observed.

336

In terms of the spatial distribution of the vulnerability classes within the study site, 68.8% (151.3 km²)

337

of the total area, display a ”low” vulnerability and 31.2% (68.7 km²) a ”moderate” vulnerability class

338

(Table 3).

339

Table 3: Spatial distribution of the DRASTIC Index (Di) within the Tata city region. Di

340

Vulnerability class

Area (km²)

Area (%)

Moderate

68.7

31.2

Low

151.3

68.8

3.2 Land Cover Impact

341

Land cover within the Tata city region (Figure 3h) was rated according to Secunda et al. (1998) and

342

Al-Hanbali and Kondoh (2008). The Cambrian to Devonian hard rock series represented bare land.

343

Most of the Quaternary sediments (Lacustrine Series) were categorized as natural vegetation. Due to

344

several villages and oases within the Quaternary sediments parts of it displayed the land cover classes

345

urban and agriculture. Since the Wadi Tata is intermittent, the Alluvial Series can display bare land as

346

well as water. Given that throughout most of the year, and also during the field survey, the wadis were

347

dry, these areas were categorized as bare land for further calculations.

348

After extending the DRASTIC Index (Figure 4a) with the land cover parameter (L) (Figure 3h), the

349

calculated DRASTIC-Land Cover Index showed a different spatial distribution of vulnerability

350

(Figure 4b). Generally, the DRASTIC-Land Cover Index varied between 75 and 172. The vulnerabil-

351

ity class for the Cambrian and Devonian series increased to ”moderate”, but the Ordovician Jebel Bani

352

Series remained ”low”. Since all of the hard rock series were classified as bare land, this difference

353

could be linked to the geological and hydrogeological parameters of the series. For instance, the aqui-

354

fer media and impact of vadose zone for the Cambrian series was rated higher compared to the Ordo-

355

vician series (compare Figure 3c and f). In urban and agricultural areas, vulnerability remained in the 16

356

”moderate” class, but displayed values close to the ”high ”vulnerability class, as both land cover pa-

357

rameters being ranked by 8.

358

On the whole, the area of ”moderate” vulnerability increased up to 144.3 km² (65.6%) and the area of

359

”low” vulnerability decreased to 75.7 km² (34.4%) (Table 4).

360

Table 4: Spatial distribution of the DRASTIC-Land Cover Index (DLi) within the Tata city region. DLi

361

Vulnerability class

Area (km²)

Area (%)

Moderate

144.3

65.6

Low

75.7

34.4

3.3 Sensitivity of the Tata DRASTIC-Land Cover Index

362

The weightings of each parameter and its impact to compute the DRASTIC-Land Cover Index was

363

addressed using single-parameter sensitivity analysis. The analysis revealed that there are some devia-

364

tions of the initial effective weights of the DRASTIC parameters, introduced by Aller et al. (1987) and

365

Secunda et al. (1998), when compared to the calculated empirical weights for the Tata study site

366

(Table 5). For the Tata city region, the rescaled effective weights are in the order of: I > L > A > S > D

367

> C > R > T. Compared to the weights introduced by Aller et al. (1987), the net recharge for the Tata

368

city region tends to be less effective since the rescaled weight was 1.4. This can be explained by the

369

fact that recharge is low and thus the assigned ratings were 1 or 3. Likewise, the depth to groundwater

370

and hydraulic conductivity parameters point to be less effective. The low sensitivity towards the

371

groundwater depth is caused by the water table being > 22 m below surface in the hard rock series. In

372

contrast, aquifer media, soil media, and impact of vadose zone media tend to be more effective param-

373

eters, due to high ratings assigned for these parameters. The topography (slope) and land cover param-

374

eters showed effective weights close to the initial empirical weights.

375

17

376

Table 5: Statistics of the single-parameter sensitivity analysis and rescaled effective weights.

Parameter

Empirical Weight

Empirical Weight (%)

Average Effective Weight (%)

Standard deviation

Rescaled Effective Weight

D

5

17.9

12.7

3.1

3.6

R

4

14.3

4.9

4.0

1.4

A

3

10.7

14.8

2.1

4.1

S

2

7.0

14.1

5.9

3.9

T

1

3.6

4.5

2.2

1.3

I

5

17.9

22.4

4.6

6.3

C

3

10.7

9.2

3.7

2.5

L

5

17.9

17.4

9.5

4.9

377

Based on the calculated average effective weights, rescaled effective weights were implemented for

378

the specific geological, hydrogeological, and land cover characteristics of the Tata city region (Table

379

5). Using the new obtained effective weights for Equation 1, the rescaled DRASTIC-Land Cover In-

380

dex (reDLi) was recomputed. Generally, the rescaled DRASTIC-Land Cover indices increased into the

381

range between 98 and 196, showing low to high vulnerability classes (Figure 4c). The Cambrian to

382

Devonian hard rock series remained in or increased to the moderate vulnerability class. Within the

383

Quaternary sediments of the Tata plain vulnerability increased into moderate to high classes, especial-

384

ly in the southern central parts of the study site.

385 386 387

Figure 4: Groundwater vulnerability of the Tata city region based on (a) the DRASTIC Index (Di), (b) the DRASTIC-Land Cover Index (DLi), and (c) the rescaled DRASTIC-Land Cover Index (reDLi).

18

388

After the rescaling process, the moderate vulnerability class covers most of the study site with

389

130.7 km² (59.4 %). High and low vulnerable areas display 41.1 km² (18.7%) and 48.2 km² (21.9%),

390

respectively.

391 392

Table 6: Spatial distribution of the rescaled DRASTIC-Land Cover Index (reDLi) within the Tata city region. reDLi Vulnerability class

Area (km²)

Area (%)

High

41.1

18.7

Moderate

130.7

59.4

Low

48.2

21.9

393

3.4

Water Quality Index

394

As hydrochemical data can be used to verify the computed vulnerability indices, the WQi was calcu-

395

lated based on groundwater samples. The WQi varied between 7 and 60, indicating a wide range of

396

groundwater quality (Figure 5a). Regarding the spatial distribution of the WQi, most groundwater

397

samples showed low WQi’s (Figure 5a). Nevertheless, across the entire study site five elevated spots

398

were noted. These are restricted to urban areas, namely the villages of Ait Yassine, Tammacht, Ait

399

Werkane, Tiguissalt, and El Ayoun.

400

In terms of correlation analyses it appears, that nitrate is the most important chemical parameter on the

401

overall WQi. The comparison between the maps of the WQi and nitrate concentrations reveals that

402

areas with high WQi’s are related to elevated nitrate concentrations and vice versa (Figure 5a and b). A

403

comparable correlation was not observed in the case of the other hydrochemical quality parameters

404

with on exception. In El Ayoun (south eastern study site) a high WQi is related to elevated chloride

405

and sulphate concentrations. This elevation is caused by natural increasing salinity conditions towards

406

the Saharan foreland (Yazidi et al. 2001) and was confirmed by mineralogical and CNS analyses,

407

which showed the presence of evaporites within the Lacustrine Terrace Series. Ammonia, was in most

408

cases, close to or below the detection limit of 0.03 mg/L. This is a result of the rapid oxidation of NH4+

409

to NO3- in the presence of oxygen (Stadler et al. 2008). Thus, NH4+ input may not be identified sepa-

410

rately and was measured as NO3-. In Tigusissalt, groundwater showed a low oxygen content (1.8

411

mg/L) and, thus, an elevated NH4+ concentration of 4.4 mg/L was noticed. Geological sources for N19

412

species in groundwater from hard rocks and sediment can be excluded since CNS-analyses showed

413

values below the detection limit of 400 ppm. Nevertheless, N-input from soil cannot be excluded.

414 415 416

Figure 5: Spatial distribution of the (a) Water Quality Index (WQi) and (b) nitrate concentrations within the Tata city region.

417

Concerning the suitability of water for drinking and irrigation purposes, Figure 6 illustrates the corre-

418

lation between the different physical and chemical water quality parameters.

419

In terms of drinking water, the quality status is related more to elevated EC’s and NO3 rather than to

420

Cl and NH4+ (Figure 6a). However, 37 samples (84.1%) showed a good to moderate drinking water

421

quality with one or either both parameters being elevated when comparing nitrate with EC, chloride,

422

and ammonia. Six samples were of a restricted to very restricted quality regarding all of the parame-

423

ters. In the case of EC and nitrate, none and one sample were below the recommended drinking water

424

quality. With regard to Cl and NH4+ concentrations, four and five samples, showed values above the

425

recommended drinking water quality.

426

Water quality for irrigation purposes is good for 93.2% of the samples (Figure 6b). Three samples

427

showed a restricted degree on irrigation use, due to elevated EC’s and nitrate concentrations. High

-

-

-

20

428

salinities, in this case expressed as EC, can cause yield losses if salt accumulates in the root crop zone

429

(Ayers and Westcot 1985).

430 431 432

Figure 6: Correlation between physical and chemical parameters related to (a) drinking and (b) irrigation water purposes. Classification refers to quality classes from Table 2.

433

3.5

434

In order to verify if groundwater quality (WQi) is related to the geological and hydrogeological aquifer

435

vulnerability (DRASTIC) or to an anthropogenic impact (Land cover parameter), correlations were

436

calculated. In this context, the spearman rank correlation coefficient was applied, since it is not re-

437

strained by the general distribution form of the two variables and the sample sizes (Huan et al. 2012).

438

A correlation coefficient of +1.0 or -1.0 indicates perfect positive or negative correlation, and 0.0 indi-

439

cates no correlation.

440

The spearman rank correlation coefficient between the Di and the WQi was of the order of 0.4, indicat-

441

ing no significant linkage between the hydrogeological aquifer vulnerability and groundwater pollu-

Relation between Water Quality Index, DRASTIC, and Land Cover

21

442

tion. Areas of moderate Di’s can display areas of low and high WQi’s, but areas of high WQi’s are

443

always linked to areas with high Di’s (compare Figure 4a and Figure 5a). Similary, a low correlation

444

was observed between the DLi and WQi as the spearman rank correlation coefficient was 0.5. Again,

445

areas of moderate DLi’s can display areas of low and high WQi’s, but areas of high WQi’s are always

446

linked to areas with high DLi’s (compare Figure 4b and Figure 5a)

447

In terms of index-based vulnerability mapping it was shown that the land cover parameter has a pro-

448

found impact on groundwater vulnerability (e.g Secunda et al. 1998, Al-Hanbali and Kondoh 2008). It

449

has been widely recognized that elevated nitrate concentrations can be directly linked to anthropogenic

450

influences of urban and agricultural land cover classes (Huan et al. 2012). Thus, nitrate concentrations

451

present a good indicator for the impact of the land cover classes on groundwater quality. This is also

452

reflected in the results of this study, since nitrate was identified as the most influencing parameter

453

regarding water quality. Figure 7 superimposes nitrate concentrations, related to the water quality clas-

454

ses from Table 2, on the land cover map.

455 456 457

Figure 7: Relation between land cover and observed nitrate concentrations. Classification refers to quality classes from Table 2 (based on topographic maps Tata, Tlêta de Tagmoûte, Open Street Map).

458

Generally, distinct differences in nitrate concentrations were observed related to land cover (Figure 7

459

and Table 7). Groundwater in urban areas showed highest nitrate concentrations, especially. Nitrate

22

460

concentrations > 100 mg/L were restricted to urban areas. Lower elevated nitrate concentrations were

461

monitored within agriculture (oases) and natural vegetation land cover classes, being on average

462

15.1 mg/L and 14.3 mg/L, respectively. Wells were not present in bare land (hard rock series). Nitrate

463

concentrations were not related to groundwater depth. Moreover, no correlation between nitrate con-

464

centrations and type of well, either being public, private or from local associations, were noticed.

465

Table 7: Relation between land cover and nitrate concentrations. Nitrate concentration (mg/L) Land cover

Number of wells

Average

Minimum

Maximum

Urban

23

43.9

12.0

272.0

Oases

15

15.1

6.5

28.0

Natural vegetation

6

14.3

2.5

25.5

466

Since hydrochemical investigations showed most elevated nitrate concentrations in urban areas, con-

467

tamination might be ascribed to missing wastewater treatment systems as well as to waste depositional

468

sites (Assaf and Saadeh 2009). This was proven by isotopic composition of nitrate, which ranged be-

469

tween +13.1 and +22.0‰ for δ15N as well as between +3.2 and +7.8‰ for δ18O (Figure 8). This signa-

470

ture is distinctive for manure and septic waste as a potential contamination source (Kendall and Ar-

471

avena 2000, Saadou Oumarou et al. 2019). In manure, the main N compound is urea, which is con-

472

verted to nitrate in the unsaturated zone (Stadler et al. 2008). Thus, nitrogen may enter from point

473

sources through preferential flow path and is subsequently leached into groundwater. Since the Qua-

474

ternary aquifer showed hydraulic conductivities in the range of 10-4 m/s, contaminant transport is rap-

475

id. Within oases, nitrate concentrations were generally less elevated and can derive from fertilization

476

and, to a certain extent, from cattle grazing (Tagma et al. 2009). Moreover, a mixture of highly con-

477

taminated groundwater from urban areas with less contaminated groundwater from agricultural and

478

bare land can be assumed.

23

479 480 481

Figure 8: Stable isotope composition of dissolved nitrate in groundwater. Typical ranges for nitrate sources were adapted from Kendall and Aravena (2000).

482

4

483

The DRASTIC Index showed that most of the study site is characterized by a low vulnerability. Thus,

484

the characteristic geological and hydrogeological factors within the Tata city region provide a natural

485

protection against groundwater contamination. However, after implementing the land cover parame-

486

ters, the DRASTIC-Land Cover Index showed that most of the study site is of moderate vulnerability,

487

indicating a greater groundwater pollution risk caused by human hazards. Thereby, more vulnerable

488

areas occur along the oases and villages, representing agriculture and urban land cover classes.

489

Based on the geological, hydrogeological, and land cover characteristics of the Tata city region, the

490

results from the single-parameter sensitivity analysis showed that the net recharge and topography

491

(slope) parameters tend to be less significant. In contrast, the impact of vadose zone media and land

492

cover parameters have a significant impact.

493

Evaluation of water quality within the Tata city region was carried out using a newly developed Water

494

Quality Index. Thereby, groundwater showed mostly a good to moderate status in terms of drinking

495

water quality. In terms of irrigation, groundwater is of good quality. The relation between groundwater

496

quality and vulnerability mapping indicates that groundwater quality is related more to land cover than

497

to the specific geological and hydrogeological setting.

498

In terms of hydrochemical data evaluation, nitrate was revealed to be the most important chemical

499

parameter reducing the degree of usage. Elevated nitrate concentrations are restricted to urban areas.

500

Nitrate isotope composition showed that the contamination source resulted from the lack of a proper

501

sewage system in the villages. This was clearly evidenced by the fact that nitrate concentrations in

502

groundwater displayed values below 50 mg/L in Tata city, which has functioning a sewage system.

Conclusions

24

503

Finally, this study highlighted the absence of waste water treatment systems as the major source of

504

groundwater contamination within the Tata city region. Thus, there is a strong need to implement

505

management options in respect to wastewater treatment plants in the surrounding villages of Tata city.

506

Since this implementation is very cost-intensive a cheaper and more easily applicable approach would

507

be to increase the distance between the supply wells and domestic waste deposits (toilets, lavatory,

508

kitchen). Thereby, the developed groundwater vulnerability and water quality maps provide funda-

509

mental knowledge to identify appropriate locations for supply wells.

510 511

512

Conflicts of interest There are no conflicts of interest to declare.

Acknowledgments

513

The presented study is based on a field survey carried out in 2018. In this context, we like to thank our

514

colleagues Melissa Zerbes, Melf Starckjohann, and Laura Eck. Furthermore, we express our gratitude

515

to the collaborators and laboratory staff of the Institute for Geosciences, University of Bonn and of the

516

Applied Geology and Geo-Environment Laboratory of the Ibn Zohr University, Agadir. We are also

517

thankful to the Moroccan Province Agency of Equipment, Transport, and Logistics and the Hydraulic

518

Agencies of Souss-Massa and Draa-Oued Noun for providing data. Finally, we thank the anonymous

519

reviewers and the editors for their efforts to help improve the presentation of the study.

520

This research did not receive any specific grant from funding agencies in the public, commercial, or-

521

not-for-profit sectors.

522

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Index-based groundwater vulnerability and water quality assessment in the arid region of Tata city (Morocco) Highlights: •

Geological and hydrogeological conditions provide a natural protection against groundwater contamination.

•

Human hazards (land cover/use) have a profound influence on groundwater pollution.

•

New Water Quality Index is transferable and applicable to any drylands.

•

Water Quality Index for drinking and irrigation purposes, revealed nitrate to be the most influencing parameter regarding the suitability for usage.

•

Nitrate contamination result from the lack of a proper sewage system.

1

Index-based groundwater vulnerability and water quality assessment in the arid region of Tata city (Morocco) Laura Heiß*1), Lhoussaine Bouchaou2,3), Sokaina Tadoumant, Barbara Reichert1)

Conflicts of interest There are no conflicts of interest to declare.