A Statistical Summary of ground water mineralization in the Aquifer of Intercalary Continental (Algerian Septentrional Sahara)

A Statistical Summary of ground water mineralization in the Aquifer of Intercalary Continental (Algerian Septentrional Sahara)

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Energy (2017) 000–000 386–392 EnergyProcedia Procedia119 00 (2017) www.elsevier.com/locate/procedia

International Conference on Technologies and Materials for Renewable Energy, Environment and International Conference on Technologies and21-24 Materials Renewable Energy, Environment and Sustainability, TMREES17, Aprilfor 2017, Beirut Lebanon Sustainability, TMREES17, 21-24 April 2017, Beirut Lebanon

A Statistical Summary of ground water mineralization in the The 15th Internationalof Symposium Districtmineralization Heating and Coolingin the A Statistical Summary groundonwater Aquifer of Intercalary Continental (Algerian Septentrional Sahara) Aquifer of Intercalary Continental (Algerian Septentrional Sahara) Assessing the feasibility of using the heat demand-outdoor Liela Sahri*aa ; Imed Eddine Nezliaa & Rabah Kechichedbb; Slimane Benhamida.Acc Liela Sahri* ; function Imed Eddine Nezli & Rabah Kechiched Slimane Benhamida.A temperature for a long-term district ;heat demand forecast Geology of Sahara Laboraory, Ouargla University, 30000, Algéria a a

b Geology of Sahara Laboraory, Ouargla University, Ouargla University, 30000, Algéria 30000, Algéria

a b Ouargla University, 30000, Algéria I. Andrića,b,c*, A. Pinaa, P. Ferrão , J. Fournier ., B. Lacarrièrec, O. Le Correc ANRH-DRSAlgeria b

c

c ANRH-DRS- Algeria E-mail :[email protected],[email protected] IN+ Center for Innovation, Technology and Policy:[email protected],[email protected] Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal E-mail b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France Abstract a

Abstract

This study deals with the mineralization in the Intercalary Continental aquifer (CI) located at the Algerian Septentrional Sahara. This studyanalysis deals with mineralization in the Intercalary aquiferin(CI) located at thethe Algerian Septentrional Sahara. Statistical wasthe performed on summarized data fromContinental different studies order to identify origin of that mineralization Statistical analysis performed on summarized data analysis from different studies in to identify the wells origin such of that inAbstract a regional scale.was Therefore, multivariate statistical were applied onorder 488 representative as:mineralization (1) Principal in a regionalAnalysis scale. Therefore, multivariate statistical analysis were applied on 488 representative wellshighlight such as: the (1) Principal Component (PCA) and (2) Ascending Hierarchical Classification (CAH). Obtained results chemical District heating networks areand commonly addressed in the literature as oneinfluence of the most effective solutions for decreasing the Component Analysis (PCA) (2) Ascending Hierarchical (CAH). Obtained results highlight the chemical typology of ground water. The multivariate statistics indicate aClassification significant of evaporates on water mineralization as greenhouse gas emissions frommultivariate the building sector. These systems require high investments which through heat typology ground water. The statistics indicate significant influence ofrecorded evaporates on returned water mineralization as well as theofdominance of chloride-sodium facies. However, the ahigh water temperatures in are the eastern part of thethe basin well as the dominance of chloride-sodium facies.also However, high water temperatures recorded part of the basin sales. Due to the of changed climate conditions and renovation policies, heatconfirms demandin inthetheeastern could decrease, suggest hydrolysis silicates that contributes inbuilding that the mineralization. This study rather thefuture lithological host of suggest hydrolysis of silicates that contributes also in that mineralization. This study confirms rather the lithological host of prolonging the investment return period. aquifer as a main source of water mineralization. aquifer as ascope main source of water mineralization. The main of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand © 2017 The Authors. Published bylocated Elsevier forecast. The district of Alvalade, in Ltd. Lisbon (Portugal), was used as a case study. The district is consisted of 665 © 2017 The Authors. Published by Elsevier Ltd. ©buildings 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Euro-Mediterranean Institute for Sustainable Development (EUMISD). that vary in both construction period and typology. Three scenarios (low, medium, high) and three district Peer-review under responsibility of the Euro-Mediterranean Institute for weather Sustainable Development (EUMISD). Peer-review under responsibility of the Euro-Mediterranean Institute for Sustainable (EUMISD). renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, Development obtained heat demand values were Keywords: PCA; aCAH; Hydrolysis; Intercalary continental, Algeria. comparedMineralization; with results from dynamic heat demand model, previously developed and validated by the authors. Keywords: Mineralization; CAH; Intercalary continental, Algeria. The results showed thatPCA; when onlyHydrolysis; weather change is considered, the margin of error could be acceptable for some applications (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). 1.scenarios, Introduction 1.The Introduction value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease in the numberIntercalary» of heating hours of 22-139h during the heating season (dependingformations on the combination weather and The «Continental aquifer is hosted in sand slightly argillaceous aged of of Neocomien, The «Continental Intercalary» aquifer is hosted in sand slightly argillaceous formations aged of Neocomien, renovation scenarios considered). On the other hand, function intercept increased for 7.8-12.7% per decade (depending on the Barremien, Aptien, and of the Albien[1-12]. The aquifer has an extension from the North to South (from the Saharan coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and Barremien, Aptien, and of the Albien[1-12]. The aquifer has an extension from the North to South (from the Saharan Atlas to the Tassili of Ahaggar) and from West to East (the Guir-Saoura valley to the Libyan Sahara)(Fig.1).The improve accuracy of heat demand estimations. Atlas to the Tassili of Ahaggar) and from West to East (the Guir-Saoura valley to the Libyan Sahara)(Fig.1).The aquifer recharge of the “Continental Intercalary” is ensured from Piedmont of the Saharan Atlas representing about

aquifer recharge The of the “Continental Intercalary” is ensured from Piedmont of themain Saharan Atlas about 7.7 m3/s[10-9]. sedimentary formation of the basin constitutes the natural source of representing acquisition of the © 2017 The Authors. Elsevier Ltd. 7.7 m3/s[10-9]. The Published sedimentary formation of the basinofconstitutes natural mainand source of acquisition the major chemical elements. Webydenote the heterogeneity chemical the concentrations distribution.In this of study, Peer-review underelements. responsibility the Scientific Committee ofofThe 15th International Symposium on District Heating major chemical We ofdenote the heterogeneity concentrations and distribution.In thisand study, statistical methods were applied on chemical analyses on fourchemical hundred and eighty-eight (488) representative samples Cooling. methods were applied on chemical analyses on four hundred and eighty-eight (488) representative samples statistical 1876-6102 2017demand; The Authors. Published Elsevier Ltd. Keywords:©Heat Forecast; Climatebychange 1876-6102 2017responsibility The Authors. ofthe Published by Elsevier Ltd.Institute for Sustainable Development (EUMISD). Peer-review©under Euro-Mediterranean Peer-review under responsibility ofthe Euro-Mediterranean Institute for Sustainable Development (EUMISD).

1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.

1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Euro-Mediterranean Institute for Sustainable Development (EUMISD). 10.1016/j.egypro.2017.07.122

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of water from wells from the “Continental Intercalary ground water “in order to identify the origin of these elements. Nomenclature CI Continental Intercalary TC Complex Terminal PCA Principal Component Analysis CAH Ascending Hierarchical Classification F1 Factorial axis 1 F2 Factorial axis 2 ANRH-DRS Algeria National Water Resources Agency-South-Algeria Regional Directorate 2.Presentation of studied area This study is focused on the aquifer of Continental Intercalary which covers a vast area and it extends from the Saharan Atlas to theTassili of Ahaggar and from the Guir-Saoura valley to the Libyan desert (Fig.1). According to Amajor N–S structure, the M’zab dorsal, this aquifer is divided into two sub-basins (occidental and oriental)[1-13]. Sevral geological studies were performed on the aquifer by many authors [12]. These studies show that the Continental Intercalary is characterized by sandy and argilo-sandy formations dating the Neocomien, Barremien, Aptien, and of the Albien (Fig.2). Whearas, faults of Amguid-Albiod are the origin of vertical exchanges between this aquifer and the Complex Terminal[5]. From top to bottom, « CI » aquifer begins with Albien formation, while its substrtum is represented by the Hercynian unconformity under Tademaït and the tinhert plates (Fig.2).

FIGURE. Hydrogeologic Map of aquifers system CI and CT. [13].

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FIGURE 2. Schematic cross-section of the Continental Intercalaire aquifer in Algeria and Tunisia, showing the main aquifer horizons [14].

3. Material, objective and methods 3.1. Sampling This study is summary of several data obtained on The Continental Intercalary (CI) aquifer many authors:ANRHDRS (2012); Edmunds (2003); Nezli (2009)and it aims to use all data to understand the chemical behavior of ground water. We use in this study 488 representative data representing major elements of water samples from boreholes (Fig.3). 3.2. Methods used Statistical methods were used in this study, in order to analyze massive data that have. The statistical processing is carried out in two ways: • Monovariate data analysis: It based on the determination of the central position statistics (mode, median, mean) and distribution (variance, standard deviation) and variation ratio of chemical elements (variables). • Bivariate data analysis: It focused on the correlation ratio and the test of their significance. This ratio is ranging from -1 to +1 • Multivariate data analysis (variables ≥ 2): it represented by two methods: - Principal Components Analysis (PCA) is an exploratory multivariate statistical technique. It used to simplify complex data sets [2-3-8]. Given (m) observations on n variables, the main target of PCA analysis is toreduce the dimensionality of the data matrix by finding r new variables, where r is less than n. Termed principal components, these r new variables together account for as much of the variance in the original n variables. Each principal component is a linear combination of the original variables, and so it is often possible to attribute meaning to what the components represent as well as the analysis of other types of expression data [7-6]. - Ascending Hierarchical Classification (AHC): This method consists of defining a class aggregation criterion that can be defined by measuring (1) the degree of resemblance (2) dissimilarity which can exist between samples [11]. This method consists to classify "p" variables and "n" observations by the construction of adistances matrix between variables and observations and calculating the distances between separated groups of variables or observations. Groups whose distance is the lowest meet together in a couple (according to this criterion) and the process is repeated until a complete regrouping of classes [4]. A dendrogram or classification can represent the Ascending Hierarchical Classification (AHC).

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FIGURE 3.Situation of studied wells. (From laboratory’s data)

4. Results and discussions 4.1. Elementary statistics Elementary statistics of major elements were presented in the Table 1. This table shows a significant statistical heterogeneity according high variance and standard deviation of all elements. Table 1. Elementary statistics of major elements (mg/l) of representative data from Continental Intercalary MEAN

Ca2+ Mg2+ Na+ K+ ClSO 4 2SiO 2 HCO 3 -

120.376 74.402 274.478 28.757 418.086 452.191 9.038 130.743

MEDIANE

106.5 69.75 255.0 23.25 380.0 425.5 7.50 135.5

MINIMUM

MAXIMUM

9 3 15 4 17.5 0 0 9

1110 365 860 600 1500 2100 68 265

RANG

VARIANCE (S2)

STANDARD DEVIATION

MEAN +2S

1101 362 845 596 1482.5 2100 68 256

6268.133 1541.851 18198.422 1134.129 49172.168 68121.422 127.213 1998.431

79.172 39.266 134.902 33.677 221.748 261.001 11.279 44.704

278.718 152.935 544.281 96.111 861.582 974.193 31.596 220.150

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4.2. Correlations Correlation matrix has been performed (Table. 2). This table presents correlation ratio between different major elements. Indeed, the highest correlation ratio (r = 0.91) is recorded between Cl- and Na+ highlighting the chloride sodium occurrence in water (NaCl). The presence of sulfated ions in water is mainly related to the dissolution of gypsums formation (r Ca2+/SO 4 2- = 0.69). Table 2. Correlation matrix between major elements Ca2+ Ca2+ Mg2+ Na+ K+ ClSO 4 2SiO 2 HCO 3 -

1.000

Mg2+ 0.503 1.000

Na+

K+

Cl-

0.479 0.576 1.000

0.106 0.447 0.195 1.000

0.470 0.609 0.912 0.309 1.000

SO 4 20.685 0.731 0.709 0.125 0.583 1.000

SiO 2 0.172 0.216 0.259 0.006 0.291 0.226 1.000

HCO 3 0.211 0.248 0.059 -0.055 0.027 0.208 0.036 1.000

3.3. Principal component analysis (PCA) Principal component analysis (PCA) applied on the major elements, aims to identify associations of major elements in “CI” groundwater (Fig. 4). The factorial axis (F1) shows a variance of 46.98% which represents the mineralization axis. These mineralization associations are positively correlated with (F1) such as: CPA indicates the common origin of Na+and Cl- (Halite). The Ca2+and SO42- correlation is a proxy for gypsum. We denote that Mg2+is correlated higher with SO42-than with carbonates (Ca2+) suggesting the Mg2+origin rather from evaporates and not from carbonates. Bicarbonates HCO3- appear inert and are distanced from the other elements, but represent also the mineralization origin of water. Silica SiO2is in opposition of potassium K+ which indicates that last is originates from silicates hydrolysis.

FIGURE 4. CPA components highlighting mineralization association of “CI” ground water.

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3.4. Hierarchical classification analysis CAH Hierarchical classification analysis (CAH) performed on major elements show the followings families: • The first-family represents the evaporitic pole (Na+, Cl- and SO 4 2-) It shows high concentrations of chlorides, sulfates and sodium corresponding to gypsum (CaSO 4 .2H 2 O) and the halite (NaCl); • The second-family represents silicates (SiO 2 and K+); • The Third family is characterized by the presence of carbonates pole (Ca2+, Mg2+ and HCO 3 -) corresponding to the facies of limestone (CaCO 3 ) and dolomites (CaMg (CO 3 ) 2 ). CAH analysis indicates the evaporitic formation is the main origin of groundwater mineralization giving water chloride-sodium facies. However, high water temperatures, especially in the eastern part of the basin suggest probably the influence of silicate hydrolysis on water mineralization.In other word, CAH dendrogram indicates the evaporate contribution into water mineralization that confirms CPA also. Carbonates are presented together indicating the calcite and dolomites presence while evaporates are principally in abundance. The K+ and SiO2pole confirms the silicate contribution by hydrolysis and that explains the K+ enrichment in water supported by temperature Dendrogramme de 8 Variables Méth. de Ward Dist. Euclidiennes

25000

Dist. Agrégation

20000

15000

10000 1 5000

0

3

2 SO42-

Cl -

Na +

SiO2

K+

HCO3 -

Mg 2+

Ca 2+

FIGURE 5. Hierarchical classification analysis (CAH) of the major elements showings mineralization families (1: evaporates; 2: silicates; 3:

carbonates).

Conclusion

This study was carried out on ground water of the “Continental Intercalary” (CI) in order to characterize their chemical behavior and the origin of mineralization. Statistical methods were used to analyze chemical data such as: (1) Principal Component Analysis (PCA) and (2)Ascending Hierarchical Classification (AHC).These statistical treatments were performed on 488 water samples covering a vast area of the Algerian Sahara. Obtained results highlight a significant heterogeneity of the origin of the mineralization acquired. The major control of this mineralization is ensured by the evaporate formations that provide the chloride facies of water. This study suggests probably the effect of temperature helping the hydrolysis of silicates formation especially in the eastern part of the basin. These results can be used to ensure a selective and rational exploitation of the water.

References [1] [2]

A Cornet, Introduction to Saharan hydrogeology. In Geog. Phys. And Géol. Dyn,VI, 1964, pp. 5-72. A Basilevsky,Statistical Factor Analysis and Related Methods, Theory and Applications. capter 3.John Wiley & Sons. New (1994). New York, NY, 1992. [3] Bs. Everitt, g. dunn, Applied Multivariate Data Analysis. Oxford University Press,

York:

392

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[4] G. Saporta, Probability Data Analysis and Statistics. 1st Edn., Téchnip, Paris, ISBN: 2-7108-0565-0, (1990), pp. 493. Nezli, S. Achour, B. Hamdi-aïssa, Hydrogeochemical approach to study the water fluoridation of the Terminal Complex aquifer in the low Algerian Valley of M’ya (Ouargla), Courrier du Savoir . N°09, (2009), pp.57-62. [5] JC. Craig, Eberwine, JH. Calvin, JA. Wlodarczyk, B. Bennett, GD end Finnell, RH,. Developmental expression of morphoregulatory genes in the mouse embryo: an analytical approach using a novel technology. In Biochem Mol Med, 60 (2) , (1997), pp. 81–91. [6] J. Vohradsky, Xm. Li, CJ. Thompson, Identification of procaryotic developmental stages by statistical analyses of two-dimensional gel patterns. Electrophoresis,18(8):1418–28, (1997). [7] K. Pearson, On Lines and Planes of Closest Fit to Systems of Points in Space. Phil Mag. 1901, pp.559 –572. [8] M. Ould baba sy, M. besbes, Holocene recharge and present recharge of the saharan aquifers. A study by numerical modeling, (International Symposium Management of large aquifers - May 30-June 1, Dijon, France, 2006),. [9] M. Ould baba sy, Recharge and paleorecharge of the northern Sahara aquifer system. Doctoral Thesis in Geology. Faculty of Sciences of Tunis. Tunisia, 2005, pp. 277. [10] M. Templ, P. FILZMOSER and C. REIMANN, Cluster analysis applied to regional geochemical data: Problems and possibilities. Applied Geochemistry, 23: 2198–2213, (2008). [11] N.Gouscov, The hydrogeological problem of the artesian basin of the OuedRhir. In The geology and problems of water in Algeria. XIXth International Geological Congress T.II, (1952), pp. 16. [12] UNESCO,ProjectReg 100. Study of the water resources of the northern Sahara. Report on the results of the project, Paris, 1972, pp. 100. [13] W.M Edmunds, P. Shand, A.H. Guendouz, A.S. Moulla, A. Mamou, and K. Zouari, Recharge characteristics and groundwater quality of the Grand Erg Oriental basin . in British Geological Survey,Walling ford, final report. (1997).