European drug policies in context

Henri Bergeron and Renaud Colson

European drug policies in historical context

For much of human history psychoactive substances were geographically confined products, the use of which was restricted by limited availability and both formal (religious and political rituals) and informal regulation. Some of these mind-altering substances were propelled outside their traditional settings by the development of global commerce in the seventeenth and eighteenth centuries. Tobacco, coffee, opiates, cannabis, alcohol or coca became global commodities thanks to the rise of maritime European empires [START_REF] Mills | Drugs and Empires: Essays in Modern Imperialism and Intoxication[END_REF]. Quickly escaping the therapeutic realm, psychoactive substances entered into nonmedical use. Wide popular consumption at times occasioned social alarm and political controversy. Yet official intervention long remained scarce.

Not only did the spread of psychoactive substances appeal to European elites, who sometimes indulged in the new intoxicants and often turned them into fashionable commodities, but it also served the interests of the wealthy and powerful who promoted the use of these products in the colonies and at home as a way to corrupt their opponents, pacify their soldiers and soothe their workers. In an era of laissezfaire economics with little control over private enterprise, the world's governments were mainly concerned with how best to tax the traffic, not how to suppress it (Courtwright, 2002, p. 165).

In the course of the nineteenth century, objections to non-medical drug use grew more vocal, invoking individual harm, social costs and moral considerations which generated increased regulatory pressure. Gradual medico-technological advances and the progressive 'medicalisation of political power' (Withington, 2014, p. 20) gave rise to the framing of drugs as a regulatory concept [START_REF] Seddon | Inventing Drugs: A Genealogy of a Regulatory Concept[END_REF]. The association of particular substances with deviant groups or ethnic minorities fuelled social anxieties harnessed by moral entrepreneurs. By the beginning of the twentieth century the movement to restrict the production, the trade and the use of psychoactive substances gained momentum, both at national and international levels. European drug policies were born out of this great historical about-face which precipitated the shift in priorities of Western political elites from the promotion of intoxicants to their partial prohibition. International activism to form a global response to drug abuse actually preceded, and heavily influenced, the development of comprehensive domestic regulation of psychoactive substances in European states.

European powers in international drug policy

The negotiation of the 1912 Hague Opium Conventionthe first treaty which set the trajectory of a century of drug control effortsshowed the lack of enthusiasm of European powers for an American drug control initiative which could endanger their economic interests. While colonial powers such as France and the United Kingdom defended their government monopolies of opium in their colonies, Portugal pledged to protect the Macao opium trade, and Germany, Switzerland and the Netherlands, which possessed pharmaceutical industries, objected to limitations on manufactured drugs (McAllister, 2000, pp. 31-32). Eventually, the 1912 Convention preamble stated that the international community was 'determined to bring about the gradual suppression of the abuse of opium, morphine and cocaine', but the treaty was a non-binding document with no implementation mechanisms.

Other conventions were negotiated in the following decades leading to the creation of a functional bureaucratic structure in order to implement this treaty framework, first organised under the banner of the League of Nations and then transferred to the United Nations in 1946. International law formalised a distinction between global licit markets controlled by oversight bodies and the illicit markets against which, initially, no enforcement response was designed at the global level. The configuration of this international drug control system owes much to the competition between states advocating an absolutist prohibitionist approach, led by the United States, and those promoting international regulation in order to manage commodity flows and encourage better domestic management of the issue. The majority of European states, which followed that second strand, led the opposition to strong supervisory bodies in the organisation of the licit market. European states also resisted American plans to secure an international agreement over an end to 'all non-medical and scientific drug use'.

The Second World War changed the balance of power in international drug control. Before the end of the conflict, the US extracted commitments from Britain, France and the Netherlands to end opium monopolies, and new American predominance strengthened the position of control advocates. 1 The aim of drug supply minimisation which characterised the first drug control treaties was consequently reinforced with plans of bringing synthetic narcotics under control 1 In the following years, influential prohibitionist figures such as Henri Anslinger, the American representative to the Commission on Narcotic Drugs from 1945 to 1970 and possibly the most prominent actor in international drug control circles in the twentieth century, and Charles Vaille, a French civil servant singleminded in his focus on supply control, set the tone for the future of the regime (McAllister, 2000, pp. 89-90 and 168).

(1948 Synthetic Narcotics Protocol) and limiting agricultural production (1953 Opium Protocol). Yet the negotiation of the 1961 Single Convention on Narcotic Drugs shows that under the leadership of British officials, the majority of European states adopted the cause of 'regulatory moderation' in defeat of the American hard line (McAllister, 2000, p. 195). This development turned out to be temporary as the 1971 Convention on Psychotropic Substances and the 1988 Convention against Illicit Traffic in Narcotic Drugs and Psychotropic Substances revealed a renewed resolve for international drug control, with the promotion of an ambitious target of eradication of non-scientific and non-medical use and the encouragement of states to pursue more aggressive domestic policies in the implementation of this objective. Here again, most European powers (with the exception of France and then Italy) defended a minimalist approach to the further development of the global drug prohibition regime as a whole (Friedrichs, 2008, pp. 113-133). But this did not prevent a strongly punitive interpretation of the drug control regime coming to dominate in the international arena in the last decades of the twentieth century.

European Union drug policy

Though framed as an international necessity from the early twentieth century, drug control was hardly a subject of regional cooperation in Europe before the 1970s. It was only when the threat of a 'drug epidemic' developed in the late 1960s that concern over this issue grew and an intergovernmental 'co-operation group to combat drug abuse and illicit trafficking in drugs' was set up in 1971, at the initiative of the French President Georges Pompidou, as France was going through a moral panic about drug abuse. The Pompidou group, which originally consisted of seven European countries -France, Belgium, Germany, Italy, Luxembourg, Netherlands, United Kingdomwas created to allow states to share their experience and knowledge in the field of drug abuse and drug trafficking. This informal group was incorporated by the Council of Europe in 1980, a time when the then European Communities (EC) had no stake in drug policies.

Although still active, the Pompidou group, which has extended to new countries and now includes 38 states, has suffered from competition with the European Union.

The 1980s saw the development of transnational political interest in the drug issue in the European public sphere as demonstrated by a variety of resolutions and reports of the European Parliament. The creation, in 1989, of the European Committee to Combat Drugs (CELAD), an ad hoc political committee established by the European Council to coordinate drug-related activities within the EC, gave drugs a more prominent place on the European political agenda [START_REF] Estievenart | The European Community and the Global Drug Phenomenon: Current Situation and Outlook[END_REF]. With drug-related matters formally added to the area of competence of the European Union in 1991 (Maastricht Treaty), an EU drug policy slowly came into being (on this issue, see the chapter in this volume by Martin Elvins). The dynamics of European decision-making on drugs are complex. Beyond the objective of tackling drug traffickinga criminal activity which might benefit from the abolition of internal borders within an integrated unionthe need to respond to European public opinion anxious about drug-related crime and addiction motivated European politicians to take action (Boekhout van Solinge, 2002, pp. 80-90). Once set in motion by the European Council, the Council and the Commission have produced a number of policy documents promoting harmonisation between Member States (discussed by Caroline Chatwin in her chapter).

The development of an EU drug policy is in line with a general constitutional evolution transforming the EU into a guarantor of the security and health of the nationals of the Member States. The Treaty on the functioning of the European Union explicitly provides regulatory powers to fight 'illicit drug trafficking' (Art. 83(1) TFEU) and reduce 'drugs-related health damage' (Art. 168 (1) TFEU). With a view to promoting research and facilitating evidence-based decision making, the institutionalisation of an EU drug policy included the establishment of a European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) (for the origins and development of this institution see the chapter by Henri Bergeron). Three 'strategies' were successively adopted by the European Council2 presenting a comprehensive approach linking drug supply reduction, drug demand reduction, European coordination and international cooperation. Notwithstanding the Europeanisation of drug policy, national specificities still prevail in institutional responses to the drug issue in Europe.

Diversity of European domestic drug policies

In spite of their obligation to abide by the global prohibition regime and their shared commitment to EU policies, each European state has developed their own way of dealing with drug use and drug trafficking (Boekhout van [START_REF] Van Solinge | Dealing with Drugs in Europe. An Investigation of European Drug Control Experiences: France, the Netherlands and Sweden[END_REF]. Within the international drug control framework, textual ambiguity allows states some leeway in the implementation of global prohibition. EU action, meanwhile, remains limited in scope and power. On the one hand, illicit drugs remain an area where subsidiarity reigns supreme and the autonomy of Member States prioritised, except when the objectives of the proposed action are not sufficiently achievable at the national level. On the other hand, when specific measures are eventually adopted by the Union, they either bring limited added value compared to international law [START_REF] Kert | Content and Impact of Approximation: The Case of Drug Trafficking[END_REF], or belong to the realm of soft law and appear toothless. No wonder, then, that at first sight plurality seems to prevail in European domestic drug policies.

The range of drug policy models is often highlighted by reference to the Swedish and the Dutch examples, two countries at either ends of a continuum from a very punitive form of drug prohibition to the most tolerant (see the chapters on Sweden by Johan Edman, and on the Netherlands by Jean-Paul C. Grund and Joost J. Breeksema). But there is more to European diversity than coffee shops in the Netherlands and a Swedish policy of zero tolerance. And any attempt to describe European drug policies by reference to a scale of punitiveness falls short of conveying the complexity of the matter. The drugs issue cuts across a spectrum of controversial topics ranging from basic rights and freedoms, through public health policies including HIV prevention, to criminal justice responses. And each of these areas is influenced by national traditions and depends on the domestic politico-cultural environment.

When it comes to developing policy responses, the extent of the drugs problem itself seems to have less of an influence than institutional and political determinants among which are: political values, a particular notion of citizenship, the organisation of a given political system, specific legal and administrative traditions and institutional power balances, the role of expertise and the weight of science in shaping/framing public policy, degrees of independence and involvement of the medical profession and pharmacists, the access of social movements to the locus of public power and the legitimacy of these actions (compare the chapters on Denmark by Esben Houborg, and on Italy by Grazia Zuffa).

Many studies claim that the particularities of national public policies are due primarily to such singularities, which reflect cultural habitus. [START_REF] Berridge | European Drug Policy: The Need for Historical Perspectives[END_REF] points out that common historical patterns can be discerned in the policies and policy instruments used in European countries (e.g., the laws passed against drug use and sale in the 1920s, then again in the 1970s, and those passed in the 1980s and 1990s in response to the HIV/AIDS epidemic), but most existing studies have drawn attention instead to the formal diversity of these relatively synchronous policy responses (compare the chapters on France by Ivana Obradovic, and on the United Kingdom by Susanne MacGregor). What should be emphasised here is that beyond their diversity, European drug policies are very much in a state of flux: most of them were subject to many reforms in recent decades and they now display a certain level of convergence.

Convergence of European drug policies

Starting in the mid-1980s in some European countries (see the chapter on Switzerland by Frank Zobel), and in the remainder from the following decade, the drug policies of European countries were reformulated through the beefing up of health and social provisions and by the design and extensive implementation of so-called 'risk reduction' instruments which most Member States had until then resisted [START_REF] Bergeron | Sociologie de la drogue[END_REF]. It gradually became clear in European countries that the strategic requirement that treatment cure drug addiction and, in some countries, the hysterical attempt to require abstinence, was not compatible with the risks implied by the growing HIV/AIDS epidemic. It is true that the implementation level of these policies (i.e., degree to which user populations are covered) and the accessibility of their programmes still differ considerably by country and 'setting' (e.g., prison, treatment centres). Some measures are still subjects of controversy, such as the controlled distribution of heroin or medically supervised injection centres. Still, it can be said that a number of important harm and risk-reduction instruments (distribution of sterile injection equipment, extensive distribution of substitution substances, 'low threshold' treatment centres, targeted prevention campaigns, and so on) have now become part of the 'legitimate' strategy of most European states (see the chapter by Dagmar Hedrich and Alessandro Pirona). The European Union, meanwhile, officially recognised the importance of harm reduction measures by way of a Council recommendation adopted in 2003. 3 This overall policy approach signifies that Member States have recognisedand (to varying degrees) are willing to assume the political consequences of that recognitionthat drug use is not, as was thought in the 1970s and 1980s, a disease but, indeed, a lasting anthropological fact of Western societies, and that not only its causes but also its risk-heavy consequences have to addressed.

Another example of convergence in European drug policies is the legal status granted to the use of drugs (without any aggravating circumstances) or to possession of drugs for personal use. In terms of both legislation and policies, European countries were deeply divided only 20 years ago as to appropriate responses for discouraging the use or possession of controlled substances for personal use. Rooted in history and tradition, penal justice emerges within a national context which overwhelmingly determines its character (Colson and Field, 2016, pp. 1-10), and we can observe an array of very different regimes when it comes to criminal justice systems in Europe. Nonetheless, recent developments within those systems reflect a tendency in which drug use offences are no longer punishable by prison sentences, with the complementary understanding that treatment and reintegration measures are to be preferred (see the chapter by Brendan Hughes). In a growing number of countries, drug use is no longer considered an offence (in this volume see the chapters on Germany by Tilmann Holzer, and on Spain by Cristina Díaz Gómez and Emiliano Martín González) thus allowing the development of grassroots drug users social clubs (see the chapter by Tom Decorte and Mafalda Pardal). Even in countries where it is heavily policed, personal use repression policy can be said to have undergone relative de facto (as opposed to de jure) depenalisation (see the chapter on Belgium by Christine Guillain), a process rendering unlikely the punishment with a court sentence of legally punishable behaviour.

The rise of harm reduction and partial and uneven decriminalisation of drug use in Europe followed such a multiplicity of paths that one may be tempted to emphasise differences over similarities. While some European governments have been early active proponents of a public health oriented approach in drug policy (see the chapter on Portugal by Caitlin Hughes), others still defend a morally inspired approach at the expense of harm reduction policies and continue prosecuting drug users (see the chapter on Poland by Kasia Malinowska). And the links between drug policy and other public policies, such as criminal, social or public health policy, vary between different countries. But in this landscape characterised by heterogeneity, commonalities have increased (see the chapter by Franz Trautmann) and in most European jurisdictions there has been a drift towards a more common approach to drug policy which includes the political recognition of a common experience of the drug phenomenon and a growing commitment to give the policy debate a scientific and rational foundation (as exemplified by the common European position during the last Special Session of the General Assembly of the United Nations on the world drug problem). 4 In this respect, the existence of shared elements of expertise has contributed to increasing the similarities between European drug policies.

Purpose and structure of the book

Dutch tolerance towards cannabis and Swiss emphasis on harm reduction, once considered European exceptions to a punitive orthodoxy maintained by UN bureaucracy, are no longer a regional singularity. And the EU is no longer the only constituted intergovernmental structure to promote a move towards more pragmatic approaches. 5 Signs of soft defection and systemic breaches now come from outside Europe and official calls to establish alternative regulatory regimes for drug control are now heard in other regions of the world [START_REF] Bewley-Taylor | International Drug Control: Consensus Fractured[END_REF][START_REF] Boister | Waltzing on the Vienna Consensus on Drug Control? Tensions in the International System for the Control of Drugs[END_REF]. The long dominant punitive interpretation of the treaty system promoted by UN bodies under the influence of the United States has lost its appeal: the Special Session of the United Nations General Assembly on the world drug problem held in April 2016 may well have reaffirmed the commitment of the international community to a traditional prohibitionist approach, 6 but it hardly conceals the growing tensions within the drug control regime.

New ways of governing addiction are gathering momentum and this is the time to take stock of European experiences. While the ideological context, bureaucratic politics and the policymaking process often seem to impede any deviation from the path initially set by public policy entrepreneurs, other historical phases offer examples of windows of opportunity for a policy change. After a long period during which they were shaped by a grammar of public order, moral decline and medical treatment, two decades ago European drug policies entered a new phase.

The purpose of this book is to describe the origins and the outcomes of the slow transformation by which new priorities have emerged in European drug policy. The contributions to this volume reflect the various contexts and different outcomes which characterise domestic policies in Europe, and trace a gradual convergence in the emergence of a model favouring public-health strategies over a strictly penal approach to combating drugs.

Reflecting the diversity of functions generally assigned to comparative research, the book has two distinct, although related, goals. In terms of analytical purpose, it aims at describing drug policies in a variety of settings. From a more evaluative perspective, it also critically assesses these policies in order to increase knowledge about various national approaches and provide tools to reformers in search of successful models. Whereas a substantial proportion of social science research strives to develop indicators to measure the success of drug policies, this collection does not rely on a single evaluative approach. On the contrary, it highlights the weight of cultural tradition in policy-making and the impossibility of promoting a one-size-fits-all policy. The development of new metrics to measure drug policies is fundamental to continuous improvement in addiction governance [START_REF] Ritter | Methods for Comparing Drug Policies: The Utility of Composite Drug Harm Indexes[END_REF]. But one should remember that policy transfers and legal transplants cannot be successfully undertaken without paying attention to local environment. The politico-cultural contexts from which policies, ideas and practices emerge have a significant impact on their potential for adaptation [START_REF] Newburn | Criminal Justice and Political Cultures[END_REF].

In the light of increasing evidence of the complexity of 'policy convergence', this book analyses the social and institutional conditions of drug policy reform in Europe from a variety of perspectives. It provides a transnational perspective as well as national case studies and offers a broad-stroke comparative analysis of European trends. The first part investigates the genealogy and the framework of European Union drug policy; it also offers a critical account of the governing tools used to promote European harmonisation (Part 1: Regional dimensions of European drug policies). The second part is devoted to case studies on twelve European Member States (Part 2: Domestic drug policies in Europe). These chapters describe the diverse evolutionary patterns followed by national drug policies in Europe starting with their origins and development from the early twentieth century onward in relation to the specific national history of drug use. Each of these chapters outlines the legal regime in force and delineates the drivers of change and conservative forces in current policy (including national, international and transnational institutions and advocacy groups…). The third part of the book provides an insight on contemporary trends in European drug policies (Part 3: Trends and prospects in European drug policies).

The contributions to this volume leave no doubt as to the importance of the ongoing shift in European drug policies. Policy makers in European countries increasingly share a common understanding of the drug phenomenon and even if they may differ on the most appropriate responses, there is a growing commitment, in what is a highly ideological area, to give drug policy a rational foundation.

From a public policy perspective, the development of harm reduction and the slow decriminalisation of drug use have mostly been the result of gradual and non-coordinated institutional transformation rather than major change as a result of explicit political choice. This incremental process of 'layering', adding new rules alongside existing institutions, has been cumulatively transformative but has left the prohibitionist framework almost intact. The question remains: how can the law confer legal status to harm reduction measures and drug users be fully included in the political community when drugs remain illegal? The legal paradox is often ignored, all the more as it can be circumvented in everyday politics. But the contradiction remains and will not be resolved unless we advance the reasoned debate on alternative options including de jure decriminalisation and regulated legalisation.

The last one was issued in 2012: European Council (2012) EU DrugsStrategy (2013-20). Official Journal of the European Union C 402/1, 29.12.2012, pp. 1-10.

Council Recommendation of 18 June 2003 on the prevention and reduction of healthrelated harm associated with drug dependence, Official Journal of the EuropeanUnion L 165, 3.7.2003, pp. 31-33.

United Nations, Special Session of the General Assembly UNGASS 2016, European Union common position on UNGASS 2016. Available from: https://www.unodc.org/docum

Henri Bergeron and Renaud Colson Copyright Material -Provided by Taylor & Francis


Meryem Jabrane

Abdessamad Touiouine

Abdelhak Bouabdli

Saïd Chakiri

Ismail Mohsine

Vincent Valles

Laurent Barbiero
email: laurent.barbiero@get.omp.eu

Abdessamad Touioui

Data Conditioning Modes for the Study of Groundwater Resource Quality Using a Large Physico-Chemical and Bacteriological Database, Occitanie Region, France

Keywords: groundwater resource, groundwater management, large database, log-transformation, Occitanie, France

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Groundwater is a major source of freshwater for the world's population and is used for domestic, agricultural and industrial purposes. About one-third of the world's population, mainly but not only in arid or semi-arid countries relies on groundwater for drinking water [START_REF]Groundwater-More About the Hidden Resource[END_REF]. However, this resource is threatened by various types of contamination, such as pathogenic bacteria, toxic metals, hydrocarbons, organic contaminants, pesticides, nanoparticles, microplastics and other emerging contaminants, which present a potential risk to human health and ecological services [START_REF] Li | To Make the Water Safer[END_REF]. Driven by the European Water Framework Directive (WFD) in 2000 [3-5], many countries have made the effort to inventory the water resource and monitor the quality of water intended for human consumption [START_REF] Danielopol | Present state and future prospects for groundwater ecosystems[END_REF][START_REF] Edmunds | The natural (baseline) quality of groundwater: A UK pilot study[END_REF][START_REF] Hinsby | European case studies supporting the derivation of natural background levels and groundwater threshold values for the protection of dependent ecosystems and human health[END_REF][START_REF] Masciale | Assessing Natural Background Levels in the Groundwater Bodies of the Apulia Region (Southern Italy)[END_REF][START_REF] Nakić | Ambient Background Values of Selected Chemical Substances in Four Groundwater Bodies in the Pannonian Region of Croatia[END_REF][START_REF] Quevauviller | Science-policy integration needs in support of the implementation of the EU Water Framework Directive[END_REF][START_REF] Smith | Groundwater-surface water interactions, nutrient fluxes and ecological response in river corridors: Translating science into effective environmental management[END_REF][START_REF] Urresti-Estala | Determination of background levels on water quality of groundwater bodies: A methodological proposal applied to a Mediterranean River basin (Guadalhorce River, Málaga, southern Spain)[END_REF][START_REF] Wendland | A procedure to define natural groundwater conditions of groundwater bodies in Germany[END_REF]. This directive has only reinforced an initiative that has been carried out for more than 30 years in France, where the information is stored in a database called "Sise-Eaux", managed by the regional health agencies (https://data.eaufrance.fr/concept/sise-eaux, 20 January 2019 accessed on). The regular updating of this database has generated a volume of data that now enables us to study and spatialize the processes behind the variability in water quality, which offers the possibility of targeted, more effective and less costly management. In this context, and although many parameters are regularly monitored, fecal contamination, detected by the presence of fecal germs, particularly Escherichia Coli and Enterococcus, constitutes the vast majority of cases of non-compliance with water intended for human consumption [START_REF] John | Review of Factors Affecting Microbial Survival in Groundwater[END_REF][START_REF] Pachepsky | Escherichia coli and Fecal Coliforms in Freshwater and Estuarine Sediments[END_REF][START_REF] Pandey | Contamination of water resources by pathogenic bacteria[END_REF]. This non-compliance with the drinking water standards, often due to strong contamination, which is, however, rare and punctual, is reflected by extreme values in the databases, i.e., nonnormal distribution. In Geoscience studies, the normality of the distribution is sometimes verified for aspects related to the physics of the environment, such as geophysical studies or spatial variations in water content, etc., but more rarely for aspects of chemical quality [START_REF] Haslauer | Including land use information for the spatial estimation of groundwater quality parameters-2. Interpolation methods, results, and comparison[END_REF][START_REF] Haslauer | Interpolation of Regional Groundwater Quality Parameters With Categorical and Real-Valued Secondary Information in the State of Baden-Württemberg, Germany[END_REF], and even less so for the mechanisms responsible for the bacteriological quality of water. The two latter cases present a large amplitude of spatial variability, ranging from several hundred km (spatial variations linked to large geological structures) to very local variations for certain processes affecting, for example, nitrates with millimetric hot spots, or even smaller ones for the denitrification process. For the wide regions, the diversity of environments and processes involved in groundwater quality can lead to frequency distributions that are far from normal. Each environment may or may not have a normal distribution, but when aggregated, the distribution in the data set is likely to deviate from a normal distribution. The frequency distribution of water characteristics can then be considered as the sum of distributions of different environments, each with its own mean and standard deviation. For studies on a smaller spatial scale, such as for groundwater bodies or up to medium size basins, the spatial variability is generally limited [START_REF] Masciale | Assessing Natural Background Levels in the Groundwater Bodies of the Apulia Region (Southern Italy)[END_REF][START_REF] Frollini | Groundwater quality trend and trend reversal assessment in the European Water Framework Directive context: An example with nitrates in Italy[END_REF][START_REF] Pantaleone | Hydrogeology of continental southern Italy[END_REF][START_REF] El Osta | Groundwater Suitability for Drinking and Irrigation Using Water Quality Indices and Multivariate Modeling in Makkah Al-Mukarramah Province, Saudi Arabia[END_REF][START_REF] Masoud | Evaluation of groundwater quality for agricultural under different conditions using water quality indices, partial least squares regression models, and GIS approaches[END_REF]. The normality assumption is a prerequisite that does not provide a strong constraint and has little impact on the estimation of uncertainties in the calculations, for example for the mapping of environmental features. This point is usually only addressed by geostatisticians [START_REF] Webster | Geostatistics for Environmental Scientists[END_REF]. The assumption of data normality is, therefore, a generally forgotten aspect in the study of mechanisms responsible for the variability of water quality, but in the presence of extreme values, these can mask certain processes, and therefore, alter the analysis that is made of the database.

The aim of this work is to compare different conditioning options for bacteriological and physicochemical groundwater data, to assess the degree of agreement with a normal distribution model, to evaluate the impact of extreme values on the multivariate processing of the data, in particular by Principal Component Analysis, as well as on the study of the spatial structure of the information. In order to ensure a large disparity of environments on a regional scale, the region chosen for the study is the Occitanie region located in southern France. This vast region has the particularity of being astride two large basins (Atlantic and Mediterranean sides), two distinct climatic sectors (Oceanic and Mediterranean), and presenting a varied lithology.

Materials and Methods

Study Area

The Occitanie region covers an area of 72,724 km 2 and has a population of 5.8 million inhabitants. It is bounded to the south by the Mediterranean Sea and the Pyrenean ridgeline, to the east by the Rhône valley, to the north by the Massif Central, and to the west, it covers the upper and middle basin of the Garonne River. It thus straddles two major climatic regions corresponding to its Atlantic side with an oceanic influence (Köppen Cfb, Cwb, Cfc), while its eastern part has a Mediterranean climate (Köppen Csa, Csb). The range of altitudes is very high, from 0 to 3300 m. The lithology is extremely variable, with ancient crystalline basement formations in the Massif Central and the Pyrenees, folded or unfolded sedimentary formations, and recent Languedocian coastal plains. This ensemble covers practically all geological periods with a variety of rocks, namely Cenozoic detrital sedimentary rocks that extend from the Aquitaine basin to the Mediterranean basin, Mesozoic carbonate sedimentary rocks in the Causses, the North Montpellier Garrigues, the Corbières and the Pyrenean foreland, and plutonic, volcanic and sedimentary rocks of varying degrees of metamorphism representing the crystalline massifs (Massif Central, Pyrenees and Montagne Noire).

Database

The data were extracted from the national SISE-EAUX database, managed by the Regional Health Agencies since 1990, according to the procedure described by Tiouiouine et al. [START_REF] Tiouiouine | Dimension reduction and analysis of a 10-year physicochemical and biological water database applied to water resources intended for human consumption in the provence-alpes-cote d'azur region, France[END_REF]. Due to the management of the database by the Regional Health Agencies, these extractions are necessarily carried out according to the administrative division of the French regions, and in the context of this work, on the whole of the Occitanie region. All analyses were performed by laboratories with international accreditation and certification of analytical quality. The extraction concerned the period of about 11 years, more precisely the data acquired between 22 January 2007 and 18 December 2018. Only the analyses of raw water were kept, i.e., before any treatment. For each water sample taken, several analysis reports could have been realized, namely, complete with several hundreds of parameters, standard with about 30 parameters, or a routine follow-up, with only about ten parameters. The result is a matrix with some empty cells that need to be conditioned before processing. After the manual correction of errors during data entry in the database and the elimination of empty cells, a matrix consisting of 8110 observations and 15 parameters was used for this study. These samples came from 1972 sampling points, i.e., an average of 4.1 samples for each sampling point, and spread over 106 groundwater bodies delimited by the French Geological Survey (BRGM) in the BDLISA database (https://bdlisa.eaufrance.fr/, accessed on 7 February 2022). The selected parameters were Enterococci, E. coli, Electrical Conductivity, Na + , Ca 2+ , Mg 2+ , Cl -, SO 4 2-, HCO 3 -, NO 3 -, Fe, Mn, As and the pH, which was added after transformation into H + concentration to avoid mixing variables with logarithmic and non-logarithmic units. The detection limit was applied to values below it. In this work, which is based on correlations or frequency distributions, the choice of the unit of the variables does not matter. The concentrations of major ions are in Mole L -1 , those of trace elements are in mg L -1 , and in units per 100 mL for the bacteriological variables.

All observations are georeferenced and their location is presented in Figure 1. The difference in the density of groundwater collection points can be explained by several factors. The karstic sectors such as the Causses du Quercy or Grands Causses in the north-western and north-eastern parts of the region, respectively, have few boreholes due to very deep aquifers and difficult access. On the other hand, the western part of the Pyrenean sector should normally have a higher density of drilling, which is not the case. In this mountainous area, there is a multiplicity of small water points, which are often incompletely monitored, i.e., only a few parameters, and many of these water points were thus eliminated during the cleaning of the database to eliminate empty cells. It is also possible that the database extraction is incomplete, but we decided to process it anyway because it represents a large amount of information.

Mathematical Tools

For each parameter, four types of data conditioning were compared, namely, the raw data, a logarithmic transformation, a square root transformation, and a transformation aiming to reinforce the role of the chemical profile independently of the dissolved load. Previous work on a similar database in south-eastern France [START_REF] Tiouiouine | Dimension reduction and analysis of a 10-year physicochemical and biological water database applied to water resources intended for human consumption in the provence-alpes-cote d'azur region, France[END_REF] has indeed highlighted a variability of processes responsible for water quality that have been identified using the water chemical profile. For this data conditioning, the bacteriological, minor elements and nitrate data are unchanged, i.e., expressed in concentration, but the values of the major ion variables have been divided by the electrical conductivity of the solutions, i.e., by a quantity proportional to the sum of cations and/or anions. This procedure is roughly equivalent to replacing the major ion concentration with the anionic or the cationic profile. The objective of this transformation further referred to as "chemical profile transformation", is to temper the role of the total concentration, which usually appears as the main factor of variability in principal component analyses on hydrochemical databases [START_REF] Tiouiouine | Dimension reduction and analysis of a 10-year physicochemical and biological water database applied to water resources intended for human consumption in the provence-alpes-cote d'azur region, France[END_REF][START_REF] Barbel-Périneau | Karst flow processes explored through analysis of long-term unsaturated-zone discharge hydrochemistry: A 10-year study in Rustrel, France[END_REF][START_REF] Helena | Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga River, Spain) by principal component analysis[END_REF][START_REF] Rezende Filho | Hydrochemical variability at the upper paraguay basin and pantanal wetland[END_REF][START_REF] Tiouiouine | Determining the relevant scale to analyze the quality of regional groundwater resources while combining groundwater bodies, physicochemical and biological databases in southeastern france[END_REF].

Mathematical Tools

For each parameter, four types of data conditioning were compared, namely, the raw data, a logarithmic transformation, a square root transformation, and a transformation aiming to reinforce the role of the chemical profile independently of the dissolved load. Previous work on a similar database in south-eastern France [START_REF] Tiouiouine | Dimension reduction and analysis of a 10-year physicochemical and biological water database applied to water resources intended for human consumption in the provence-alpes-cote d'azur region, France[END_REF] has indeed highlighted a variability of processes responsible for water quality that have been identified using the water chemical profile. For this data conditioning, the bacteriological, minor elements and nitrate data are unchanged, i.e., expressed in concentration, but the values of the major ion variables have been divided by the electrical conductivity of the solutions, i.e., by a quantity proportional to the sum of cations and/or anions. This procedure is roughly equivalent to replacing the major ion concentration with the anionic or the cationic profile. The objective of this transformation further referred to as "chemical profile transformation", is to temper the role of the total concentration, which usually appears as the main factor of variability in principal component analyses on hydrochemical databases [START_REF] Tiouiouine | Dimension reduction and analysis of a 10-year physicochemical and biological water database applied to water resources intended for human consumption in the provence-alpes-cote d'azur region, France[END_REF][START_REF] Barbel-Périneau | Karst flow processes explored through analysis of long-term unsaturated-zone discharge hydrochemistry: A 10-year study in Rustrel, France[END_REF][START_REF] Helena | Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga River, Spain) by principal component analysis[END_REF][START_REF] Rezende Filho | Hydrochemical variability at the upper paraguay basin and pantanal wetland[END_REF][START_REF] Tiouiouine | Determining the relevant scale to analyze the quality of regional groundwater resources while combining groundwater bodies, physicochemical and biological databases in southeastern france[END_REF].

Multiple correlations were established between E. coli levels, as the explained variable, and the other parameters, as explanatory variables, with the exception of Enterococcus. The objective was to measure the degree of relationship between the bacteriological and physicochemical characteristics according to the data conditioning mode. The results are expressed as the percentage of variance explained (r 2 ) by the multiple regression according to the conditioning mode of the data.

A Principal Component Analysis (PCA) was performed in order to reduce the dimension of the data space by losing a minimum of the information contained in the database [START_REF] Tiouiouine | Determining the relevant scale to analyze the quality of regional groundwater resources while combining groundwater bodies, physicochemical and biological databases in southeastern france[END_REF]. The analysis was conducted using the correlation matrix. Under these Multiple correlations were established between E. coli levels, as the explained variable, and the other parameters, as explanatory variables, with the exception of Enterococcus. The objective was to measure the degree of relationship between the bacteriological and physicochemical characteristics according to the data conditioning mode. The results are expressed as the percentage of variance explained (r 2 ) by the multiple regression according to the conditioning mode of the data.

A Principal Component Analysis (PCA) was performed in order to reduce the dimension of the data space by losing a minimum of the information contained in the database [START_REF] Tiouiouine | Determining the relevant scale to analyze the quality of regional groundwater resources while combining groundwater bodies, physicochemical and biological databases in southeastern france[END_REF]. The analysis was conducted using the correlation matrix. Under these conditions, the factorial axes resulting from this analysis are orthogonal to each other and thus carry information related to independent processes [START_REF] Tiouiouine | Dimension reduction and analysis of a 10-year physicochemical and biological water database applied to water resources intended for human consumption in the provence-alpes-cote d'azur region, France[END_REF][START_REF] Helena | Temporal evolution of groundwater composition in an alluvial aquifer (Pisuerga River, Spain) by principal component analysis[END_REF][START_REF] Rezende Filho | Impacts of lithological and anthropogenic factors affecting water chemistry in the Upper Paraguay River Basin[END_REF].

Quantile-quantile (QQ) plots were then constructed to visually compare the residuals of each distribution to a normal distribution of the same mean and standard deviation [START_REF] Marden | Positions and QQ Plots[END_REF]. The diagonal on these plots represents the normal character of the distribution. The closer the points of the studied data distribution are to the diagonal, the closer the distribution is to normality. In addition, we applied the Kolmogorov-Smirnov normality test, which is adapted to high-dimensional statistical distributions [START_REF] Steinskog | A Cautionary Note on the Use of the Kolmogorov-Smirnov Test for Normality[END_REF]. This test examines the largest difference between the empirical cumulative distribution function and a specified normal distribution, in this case, one with the same mean and standard deviation. To appreciate the importance of the abnormal values we used the Z score defined by:

Z = |x -M|/σ, (1)
Water 2023, 15, 84 5 of 16

where x is the measured value for a given parameter, M is the mean, and σ is the standard deviation. Z values greater than 2.5 and 10 are considered extreme and highly extreme, respectively. The principal components group together the independent variability factors, and thus correspond to macro parameters that can be spatialized, in the same way as the other parameters [START_REF] Rezende Filho | Impacts of lithological and anthropogenic factors affecting water chemistry in the Upper Paraguay River Basin[END_REF][START_REF] Bouramtane | Statistical approach of factors controlling drainage network patterns in arid areas. Application to the Eastern Anti Atlas (Morocco)[END_REF]. For data spatialization and cartographic representations, experimental variograms were calculated and fitted to models by the least squares method. All the variograms were calculated under the same conditions, i.e., with the same number of points constituting the variograms, whatever the chosen data conditioning. It should be noted that the samples were not collected on the same date, so the semi-variance includes both temporal and spatial semi-variance.

Results

Extreme and Highly Extreme Values

For the bacteriological parameter E. coli, 55 samples had Z-score values greater than 2.5, and 15 of them had values greater than 10, up to 42.5. After square root and log transformation, the Z-score range decreased sharply with a maximum of 19 (7 samples with Z-score > 10) and 3.8, respectively. Note, that for the parameter E. coli, using raw data, square root-or Log-transformation, there were no extreme low values. All denoted high bacterial contamination.

Multiple Regression

The explained variance (R 2 ) by the multiple regression between E. coli levels and other non-bacteriological parameters is presented in Table 1. With the raw data or the chemical profile transformation, a very weak correlation with the E. coli content was observed, limited to 6% and 7.5% of explained variance, respectively. On the other hand, using the square root transformation, a clearer correlation was detected with a percentage of explained variance that amounted to 26%. Finally, this percentage almost doubled with the log transformation of the data (49%). For the continuation of the study, only three conditioning modes will be kept for comparison, namely, the raw data, the square root transformation and the log transformation, since the enhancement of the chemical profile does not bring any significant improvement compared to the raw data.

PCA Using the 3 Data Conditioning Modes

The results of the PCAs conducted with the three different modes of data conditioning are summarized in Table 2. Whatever the data conditioning procedure, the significance of the factorial axes was more or less the same, without any major difference (Figure 2): the first factorial axis reflected the water mineral load, with electrical conductivity and major elements on the positive side, and less soluble minor elements on the negative one. The second factorial axis conveyed the fecal bacterial load positively correlated to Fe and Mn metals. For the log conditioning, the pH had a significant effect on this second axis, which is not the case for the analysis with the raw data. The third factorial axis showed an opposition between samples with a Na-Cl chemical profile on the one hand and a Ca-HCO3 profile on the other. Finally, the fourth factorial axis reflected arsenic contents in all cases.

the raw data, the square root transformation and the log transformation, since the enhancement of the chemical profile does not bring any significant improvement compared to the raw data.

PCA Using the 3 Data Conditioning Modes

The results of the PCAs conducted with the three different modes of data conditioning are summarized in Table 2. Whatever the data conditioning procedure, the significance of the factorial axes was more or less the same, without any major difference (Figure 2): the first factorial axis reflected the water mineral load, with electrical conductivity and major elements on the positive side, and less soluble minor elements on the negative one. The second factorial axis conveyed the fecal bacterial load positively correlated to Fe and Mn metals. For the log conditioning, the pH had a significant effect on this second axis, which is not the case for the analysis with the raw data. The third factorial axis showed an opposition between samples with a Na-Cl chemical profile on the one hand and a Ca-HCO3 profile on the other. Finally, the fourth factorial axis reflected arsenic contents in all cases.

Raw data

Square root transf. Log transf.

Water 2023, 15, x FOR PEER REVIEW 7 of 18

Distribution of Water Samples in Factorial Score Plots

The distribution of samples in the PC1/PC2 and PC3/PC4 factorial plans were plotted for the three modes of data conditioning in Figure 3. The difference in the distribution of the scatterplots was notable. In the case of raw data, a small number of extreme values monopolized most of the information and thus the variance, regardless of the origin of the variability, i.e., dissolved load, bacterial load, or other parameters. It resulted in factorial plans with large areas without observations, bounded only by a few rare points, while almost all the observations of the database (more than 7000) were grouped in a small central area. On the other hand, after the logarithmic transformation or to a lesser extent the square root transformation, the extreme values played a much more moderate role plans with large areas without observations, bounded only by a few rare points, while almost all the observations of the database (more than 7000) were grouped in a small central area. On the other hand, after the logarithmic transformation or to a lesser extent the square root transformation, the extreme values played a much more moderate role and the observations were spread over the factorial planes, which allowed us to better visualize the diversity of the information contained in the database.

Distribution of Water Samples in Factorial Score Plots

The distribution of samples in the PC1/PC2 and PC3/PC4 factorial plans were plotted for the three modes of data conditioning in Figure 3. The difference in the distribution of the scatterplots was notable. In the case of raw data, a small number of extreme values monopolized most of the information and thus the variance, regardless of the origin of the variability, i.e., dissolved load, bacterial load, or other parameters. It resulted in factorial plans with large areas without observations, bounded only by a few rare points, while almost all the observations of the database (more than 7000) were grouped in a small central area. On the other hand, after the logarithmic transformation or to a lesser extent the square root transformation, the extreme values played a much more moderate role and the observations were spread over the factorial planes, which allowed us to better visualize the diversity of the information contained in the database.

Raw data

Square root transf. Log transf.

Inertia of the Principal Components

The cumulative inertia of the principal components is presented in Table 3 up to PC7 and can be compared in Figure 4 for the three modes of data conditioning. With the raw data, we observe that the first PC accounted for only 28% of the variance, while it accounted for 33 and 34% for the log-or Square root-transformed data, respectively. There was thus a significant gap between the different modes of data conditioning. If we consider the four main factorial axes, the gap appeared to be even larger, going from 60% with the raw data to 71.5% with a logarithmic transformation of the data, with the square root transformation giving an intermediate result (68.4%).

(a) (b)

Inertia of the Principal Components

The cumulative inertia of the principal components is presented in Table 3 up to PC7 and can be compared in Figure 4 for the three modes of data conditioning. With the raw data, we observe that the first PC accounted for only 28% of the variance, while it accounted for 33 and 34% for the log-or Square root-transformed data, respectively. There was thus a significant gap between the different modes of data conditioning. If we consider the four main factorial axes, the gap appeared to be even larger, going from 60% with the raw data to 71.5% with a logarithmic transformation of the data, with the square root transformation giving an intermediate result (68.4%).

Inertia of the Principal Components

The cumulative inertia of the principal components is presented in Table 3 up to PC7 and can be compared in Figure 4 for the three modes of data conditioning. With the raw data, we observe that the first PC accounted for only 28% of the variance, while it accounted for 33 and 34% for the log-or Square root-transformed data, respectively. There was thus a significant gap between the different modes of data conditioning. If we consider the four main factorial axes, the gap appeared to be even larger, going from 60% with the raw data to 71.5% with a logarithmic transformation of the data, with the square root transformation giving an intermediate result (68.4%).

Frequency Distribution

The Q-Q plots are shown in Figure 5 for some key parameters, namely EC representing mineralization, E. coli, sensitive to bacteriological contamination, Fe sensitive to redox processes and As concentration. The frequency distribution differs somewhat depending on the parameter. For the different bacteriological and physicochemical parameters, the Kolmogorov-Smirnov normality tests indicate a non-normal distribution, which can be visualized on the Q-Qplot (Figure 5). There is an important dissymmetry linked to the existence of some high values. The logarithmic transformation leads to a change in scale, compacting the axes for the extreme values and dilating the axes for the low values. The distribution then approached a normal distribution, although the normality test was still negative for all parameters. The square root transformation also resulted in a similar contraction of the high values and dilation of the low values but gave intermediate results between using the raw data and the log transformation.

Variograms and Mapping

The variograms for the macroparameters (PC1 to PC4) and for the three modes of data conditioning are presented in Figure 6. All experimental variograms were fitted by spherical models whose characteristics are summarized in Table 4. These fitted models were applied to draw up the distribution maps of the PCs over the entire Occitanie region. Whatever the parameters, the variograms calculated on the log-transformed data showed little irregularity unlike the variograms calculated on the raw data. Again, the square root transformation was intermediate between the raw data and the log-transformed data. The reduced sill/Nugget ratio increased between raw data (8.4 and 3.3), square root transformation (10.8 and 4.3) and Log-transformation (11.6 and 6.1) for PC1 and PC2 respectively, while this was not true for the following PCs. were applied to draw up the distribution maps of the PCs over the entire Occitanie region. Whatever the parameters, the variograms calculated on the log-transformed data showed little irregularity unlike the variograms calculated on the raw data. Again, the square root transformation was intermediate between the raw data and the log-transformed data. The reduced sill/Nugget ratio increased between raw data (8.4 and 3.3), square root transformation (10.8 and 4.3) and Log-transformation (11.6 and 6.1) for PC1 and PC2 respectively, while this was not true for the following PCs. The mode of data conditioning generated significant differences on the maps obtained by kriging (Figure 7). In particular, when using the raw data, the few extreme values induced large homogeneous color ranges that prevented distinguishing the nuances of local variability, except by arbitrarily modifying the color scales. With the transformation of the data, by logarithm and to a lesser extent by square root, these drawbacks disappeared and the spatial variabilities were revealed, both local and regional.

(d) (e) (f) (g) (h) (i) (j) (k) (l)

Raw data

Differences were not observed for all parameters. For example, for electrical conductivity and major ions, we noted the absence of extreme values. Thus, the distribution maps of PC1 and PC3 mainly influenced by these parameters showed a well-distributed scale between the minimum and maximum values. These two PCs are also characterized by a long range in the variograms due to the influence of lithology. The conditioning of the data only moderately alters the appearance of the maps. This was not the case for bacteriological parameters or minor elements, mainly represented by PC2, nor even for nitrogenous pollution represented by PC4, and for which the extreme values shifted the scale towards the high values, the lowest color range covering most of the area. There is also a much shorter range in these PCs due to the local influence of processes on trace elements or nitrogenous forms. The log transformation allows a better distribution of colors and reveals the local or regional character of the pollution. The mode of data conditioning generated significant differences on the maps obtained by kriging (Figure 7). In particular, when using the raw data, the few extreme values induced large homogeneous color ranges that prevented distinguishing the nuances of local variability, except by arbitrarily modifying the color scales. With the transformation of the data, by logarithm and to a lesser extent by square root, these drawbacks disappeared and the spatial variabilities were revealed, both local and regional.

Raw data

Square root transf. Log transf.

PC1

Water Differences were not observed for all parameters. For example, for electrical conductivity and major ions, we noted the absence of extreme values. Thus, the distribution maps of PC1 and PC3 mainly influenced by these parameters showed a welldistributed scale between the minimum and maximum values. These two PCs are also characterized by a long range in the variograms due to the influence of lithology. The conditioning of the data only moderately alters the appearance of the maps. This was not The choice of transforming the data before studying the frequency distribution may face different difficulties. One of these is reported by O'Hara and Kotze [START_REF] O'hara | Do not log-transform count data[END_REF] and concerns the fact that in many cases there are zero values. However, for the concentration of dissolved elements, an element always exists at least in trace amounts, and therefore, the value of zero is very implausible. With zero values, the logarithmic transformation is impossible because log (0) does not exist. To get around this problem, we made two choices when preparing the database: On the one hand, observations with missing values were eliminated from the processed database, and on the other hand, the detection limit replaced the values that were below it. Indeed, some analytical laboratories report a value below the detection limit, and others assign a value of 0, but in reality, the only certainty is that the value is between 0 and the detection limit. Feng et al. [START_REF] Feng | Log-transformation and its implications for data analysis[END_REF] mentioned that if the original data follow a log-normal or approximately normal distribution, then the log-transformed data follow a normal or approximately normal distribution and the log transformation removes or reduces the skewness. The data from many studies, however, do not approximate the lognormal distribution and applying this transformation does not reduce the skewness of the distribution. One of the key criteria is skewness, which is related, for example, to the existence of extremely high or extremely low values relative to the mean in a data set. The larger the database (several thousand or tens of thousands of observations), i.e., covering a longer period of time or a larger and heterogeneous region, the more likely it is to contain extreme values, thus generating a skewed distribution. It also appears that the use of PCA without prior data conditioning is not an alternative to data conditioning. Indeed, since the PCs are a linear combination of the original parameters they maintain the problems associated with the presence of extreme values and a highly skewed frequency distribution of the data.

Given this observation, what are the options for ensuring that the information carried by these extreme values does not mask a large part of the information contained in the database? The first phase would, therefore, be a diagnostic phase aiming at identifying whether these extreme values are high or low. In the case of high values, the corresponding observations can be eliminated, resulting in a net loss of information in the database. However, this information, although atypical, is often local, with a high impact on a small number of observations, but probably interesting, and is an integral part of the analyzed database. Another solution is to limit the extreme values, which generally concern only one or two parameters (most often bacteriological parameters or metals) out of a few dozen observations. The loss of information is less. The third option is a data transformation, which must have the following properties. This transformation must be continuous, dilate the gaps between the weak values, and contract those between the strong values in order to make the distribution more symmetrical and thus rebalance the weight of useful information. Several possibilities exist. The first is to apply an inverse function (1/x), which results in reversing the order of the data but is only applicable when the extremes correspond to strong values, without values close to zero. A second option is a transformation by the square root or any other power between 0 and 1. This transformation will have the effect of dilating the weak values and contracting the strong values but may be insufficient, or less efficient than a logarithmic transformation, as we observed on the Occitanie dataset. Note, that for inverse or log transformations there is the problem of undefined null values, a point we discussed above.

Impact on Process Analysis

The main difference between PCA on raw data and transformed data, and in particular on log-transformed data, is that the effect of extreme values is reduced. The dispersion of the observations is thus distributed in the first score plots of the PCA, making it possible to better represent the significance of the factorial axes, without the interfering effect of a small number of samples. This results in better visualization and efficiency of the analysis, which is measured, on the Occitanie database treated in this work, by the percentage of variance explained by the first four factorial axes, increasing from 60 to 71.5%. With or without transformation of the data, the first score plot PC1-PC2, which carries about half of the information, reflects the same realities (minerality and fecal contamination of the water), the same processes, but in a much more efficient way with log conditioning. Similarly, for the third and fourth PCs, the significance of the axes (chemical profile and nitrogen pollution, respectively) is more or less the same whether the data are in log or not, but the information is more condensed and efficient. As these axes act as macro-parameters, they reflect associated processes that are more clearly defined.

The importance of data conditioning on the percentage of variance explained is in line with that of comparisons on distributions and their deviation from the normal distribution. However, two points should be kept in mind. [START_REF]Groundwater-More About the Hidden Resource[END_REF] In the case of data from very different natural environments, as is the case with water quality data acquired on a regional scale, in various geological, climatic and land use contexts, the distribution cannot be truly normal because it is composed of the superposition of distributions of data from different environments, each with its own distribution. For illustration, if we look at the EC parameter in the Occitanie region, the range is between 20 and 50 µS cm -1 for mountainous crystalline basement areas, 250 and 500 µS cm -1 for karst environments, and 800 and 1000 µS cm -1 within coastal plains. In this case, the log transformation can be very useful to simply approximate the set of values to a normal distribution. (2) Although the deviation from a normal distribution is troublesome, the consequences are less severe than for the calculation of principal components. Indeed, in the processing of large databases such as SISE-EAUX [START_REF] Tiouiouine | Dimension reduction and analysis of a 10-year physicochemical and biological water database applied to water resources intended for human consumption in the provence-alpes-cote d'azur region, France[END_REF], dimensional reduction is an essential step for the synthetic mapping of groundwater quality data at the regional scale. It is part of a proven procedure for grouping groundwater bodies that are similarly more or less vulnerable to contamination via similar mechanisms [START_REF] Tiouiouine | Determining the relevant scale to analyze the quality of regional groundwater resources while combining groundwater bodies, physicochemical and biological databases in southeastern france[END_REF]. The more information the main factorial axes convey, the more efficient the dimensional reduction, and the better the clustering of groundwater body families and consequently the analysis of the mechanisms responsible for the variability of the chemical composition of the water within each groundwater body family. Log transformation of data is, therefore, necessary for large databases that are likely to have extreme values, not for approximation to a normal distribution, but for a better dimensional reduction in the data hyperspace and clustering of groundwater bodies, which will facilitate analysis of the processes responsible for quality variability. The advances of this study carried out on Occitanie are currently being introduced in other French administrative regions (Provence-Alpes-Côte d'Azur, Bourgogne-Franche Comté, Auvergne-Rhône-Alpes, etc.) as well as in the territory of Corsica. Taking into account the extreme values in the databases, but attenuating their weight, allows a better vision of the spatial and temporal variability, leading to a better grouping of groundwater bodies intended for human consumption.

Quality monitoring and surveillance by health agencies can thus be optimized, resulting in lower costs. Subject to the existence of similar databases in other European countries, the procedure could be applied there.

Although correlation is not proof of causality, the multiple correlations illustrate that the way in which the data are conditioned can reveal a correlation between fecal contamination and all the other parameters. The calculation of the R 2 (Table 1) quantifies this correlation and illustrates that Log conditioning is the most efficient. The square root conditioning reveals this correlation, but compared to the Log conditioning, it explains only half of the variance (26% vs. 49%). Such a proportion in the explained variance highlights that the extreme values monopolize a large part of the useful information conveyed by the factorial axes, masking the influence of the bulk of the database, which is revealed by the Log transformation. We also notice that the few samples with extreme values do not follow the same correlations between parameters as the majority of the other observations in the database. Indeed, if these correlations had been similar, the logarithmic or square root transformation would decrease their coordinates on the principal components, but would not change the percentage of variance explained. The increase in explained variance, therefore, reflects a reduction in statistical background noise [START_REF] Rezende Filho | Impacts of lithological and anthropogenic factors affecting water chemistry in the Upper Paraguay River Basin[END_REF] and an improvement in the definition of principal components for the majority of observations. We can also note an effect on the mapping of the main PCs. If the reduced sill/Nugget ratio increases between the raw data, square root and log transformation, this reflects that the essential and structured information is concentrated on the first factorial axes. In other words, with the log transformation, useful and spatially well-structured information is concentrated in the first axes while unstructured variability is redistributed to the following PCs. With the raw data, the unhelpful and spatially ill-structured information already contaminates the first factorial axes. Thus, the information contained in the extracted database is better structured in terms of variance distribution but also in terms of spatial distribution after log transformation rather than using the raw data without conditioning.

Conclusions

In large-dimension multiparametric databases on the quality of water intended for human consumption, the risk of the appearance of extreme values is high, especially for metals and bacteriological parameters. A few water analyses concentrate most of the information, which disturbs the study of the rest of the information. To this effect, the Log transformation appears to be the best option allowing (1) to reduce, without eliminating or limiting them, the influence of extreme values which otherwise have an important impact on the global variance, even if they are few in number; [START_REF] Li | To Make the Water Safer[END_REF] to highlight certain correlations between bacteriological and physicochemical parameters; (3) to significantly increase the readability of the factorial axes as well as the identification and the cartographic representation of the associated processes responsible for the variance within the database. Taking these results into account will improve the grouping of groundwater bodies according to physicochemical and bacteriological water characteristics, an aspect that will be addressed in future work for the Occitanie region, but also at other scales throughout the Rhone basin.

Water 2023 , 18 Figure 1 .

 2023181 Figure 1. Location of the Occitanie region in southern France. Elevation and groundwater sampling points and major subregions.

Figure 1 .

 1 Figure 1. Location of the Occitanie region in southern France. Elevation and groundwater sampling points and major subregions.

Figure 2 .

 2 Figure 2. Distribution of the variables in the main factorial plans.

Figure 2 .

 2 Figure 2. Distribution of the variables in the main factorial plans.3.3.2. Distribution of Water Samples in Factorial Score PlotsThe distribution of samples in the PC1/PC2 and PC3/PC4 factorial plans were plotted for the three modes of data conditioning in Figure3. The difference in the distribution of the scatterplots was notable. In the case of raw data, a small number of extreme values monopolized most of the information and thus the variance, regardless of the origin of the variability, i.e., dissolved load, bacterial load, or other parameters. It resulted in factorial

Figure 2 .

 2 Figure 2. Distribution of the variables in the main factorial plans.

Water 2023 , 18 Figure 3 .

 2023183 Figure 3. Distribution of the observation in the factorial plans PC1-PC2 and PC3-PC4 for raw data, square root transformation and log transformation.

Figure 3 .

 3 Figure 3. Distribution of the observation in the factorial plans PC1-PC2 and PC3-PC4 for raw data, square root transformation and log transformation.

Figure 3 .

 3 Figure 3. Distribution of the observation in the factorial plans PC1-PC2 and PC3-PC4 for raw data, square root transformation and log transformation.

Figure 4 .

 4 Figure 4. Variance (a) and cumulative variance (b) explained by the principal components using raw data, square root and logarithm transformation.

Figure 4 .

 4 Figure 4. Variance (a) and cumulative variance (b) explained by the principal components using raw data, square root and logarithm transformation.

Figure 5 .

 5 Figure 5. Quantile-quantile plots for Electrical Conductivity (a-c), E. coli (d-f), Fe (g-i) and As (j-l) for raw, square root-and log-transformed data.

Figure 5 .

 5 Figure 5. Quantile-quantile plots for Electrical Conductivity (a-c), E. coli (d-f), Fe (g-i) and As (j-l) for raw, square root-and log-transformed data.

18 PC4Figure 6 .

 186 Figure 6. Experimental variograms and fitted spherical models for PC1 to PC4 (distance in m).

Figure 6 .

 6 Figure 6. Experimental variograms and fitted spherical models for PC1 to PC4 (distance in m).

Figure 7 .

 7 Figure 7. Distribution of the first four factorial axes over the Occitanie region using raw data, square root transformation and log transformation of the data.

Figure 7 .

 7 Figure 7. Distribution of the first four factorial axes over the Occitanie region using raw data, square root transformation and log transformation of the data.

Table 1 .

 1 Percentage of variance explained by multiple regression between the bacteriological parameter E.Coli and the physicochemical parameters.

	Data Conditioning	R 2
	Raw data	0.0597
	Chemical profile transformation	0.0746
	Square root transformation	0.2582
	Log-transformation	0.4943

Table 2 .

 2 Variance explained by the main factorial axes (PCs) for 3 data-conditioning mode.

		Raw Data	Explained Variance Square Root Transf.	Log Transf.
	PC1	28.59	34.25	33.49
	PC2	13.09	16.68	21.21
	PC3	11.1	9.14	9.45
	PC4	7.29	8.32	7.37
	Sum	60.07	68.39	71.52
	3.3.1. Significance of the First Four Principal Components

Table 2 .

 2 Variance explained by the main factorial axes (PCs) for 3 data-conditioning mode.

		Raw Data	Explained Variance Square Root Transf.	Log Transf.
	PC1	28.59	34.25	33.49
	PC2	13.09	16.68	21.21
	PC3	11.1	9.14	9.45
	PC4	7.29	8.32	7.37
	Sum	60.07	68.39	71.52
	3.3.1. Significance of the First Four Principal Components

Table 3 .

 3 Table of variances for PC 1 to PC7 and 3 conditioning modes.

			PC1	PC2	PC3	PC4	PC5	PC6	PC7
		Eigenvalue	4.29	1.96	1.67	1.09	1.03	1	0.96
	Raw data	Variability (%)	28.59	13.09	11.10	7.29	6.85	6.65	6.38
		Cumulative %	28.59	41.68	52.78	60.07	66.92	73.58	79.95
		Eigenvalue	5.14	2.50	1.37	1.25	0.87	0.75	0.72
	Squ. root data	Variability (%)	34.25	16.68	9.14	8.32	5.83	5.02	4.79
		Cumulative %	34.25	50.94	60.07	68.39	74.22	79.24	84.03
		Eigenvalue	5.02	3.18	1.42	1.11	0.79	0.62	0.59
	Log. data	Variability (%)	33.5	21.21	9.45	7.37	5.25	4.16	3.93
		Cumulative %	33.5	54.71	64.16	71.53	76.78	80.93	84.86

Table 3 .

 3 Table of variances for PC 1 to PC7 and 3 conditioning modes.

			PC1	PC2	PC3	PC4	PC5	PC6	PC7
		Eigenvalue	4.29	1.96	1.67	1.09	1.03	1	0.96
	Raw data	Variability (%)	28.59	13.09	11.10	7.29	6.85	6.65	6.38
		Cumulative %	28.59	41.68	52.78	60.07	66.92	73.58	79.95
		Eigenvalue	5.14	2.50	1.37	1.25	0.87	0.75	0.72
	Squ. root data	Variability (%)	34.25	16.68	9.14	8.32	5.83	5.02	4.79
		Cumulative %	34.25	50.94	60.07	68.39	74.22	79.24	84.03
	Log. data	Eigenvalue	5.02	3.18	1.42	1.11	0.79	0.62	0.59

Table 4 .

 4 Characteristics of the spherical models fitted on the experimental variograms.

	Raw Data	Square Root Transf.	Log Transf.

Table 4 .

 4 Characteristics of the spherical models fitted on the experimental variograms.

	Raw Data	Square Root Transf.	Log Transf.

Table 4 .

 4 Characteristics of the spherical models fitted on the experimental variograms.

	Raw Data	Square Root Transf.	Log Transf.

This research received no external funding. The authors are very grateful to the Occitanie Regional Health Agency for helping in data extraction from the Sise-

All data here analyzed were extracted from the public Sise-Eaux database (https://data.eaufrance.fr/concept/sise-eaux, accessed on 20 January 2019). Eaux Database.

Conflicts of Interest:

All authors declare that they have no financial or non-financial conflicts of interest.


Chloé Laplantine

It is the appreciation of the relativity of the form of thought which results from linguistic study that is perhaps the most liberalizing thing about it. What fetters the mind and benumbs the spirit is ever the dogged acceptance of absolutes.

Perhaps the best way to get behind our thought processes and to eliminate from them all the accidents or irrelevancies due to their linguistic garb is to plunge into the study of exotic modes of expression. At any rate, I know of no better way to kill spurious "entities".

Why not push English, for instance, which is already spoken over a larger area than any other language of modern times, and which shows every sign of spreading in the world of commerce and travel? The consideration which gives rise to reflections of this sort, grounded in impatience as it is, looks for no more worthy solution of the difficulty than a sort of minimum language, a lingua franca of the modern world. Those who argue in this spirit invariably pride themselves on being 'practical,' and, like all 'practical' people, they are apt to argue without their host. ("The function of an international auxiliary language") It is, therefore, highly desirable that along with the practical labour of getting wider recognition of the international language idea, there go hand in hand comparative researches which aim to lay bare the logical structures that are inadequately symbolized in our present day languages, in order that we may see more clearly than we have yet been able to see just how much of psychological insight and logical rigour have been and can be expressed in linguistic form. One of the most ambitious and important tasks that can be undertaken is the attempt to work out the relation between logic and usage in a number of national and constructed languages, in order that the eventual problem of adequately symbolizing thought may be seen as the problem it still is. (« The function of an international auxiliary language") « Totality »

The Expression of the Ending-point relation in English, French, and German.

What is needed above all is a language that is as simple, as regular, as logical, as rich, and as creative as possible; a language which starts with a minimum of demands on the learning capacity of the normal individual and can do the maximum amount of work; which is to serve as a sort of logical touchstone to all national languages and as the standard medium of translation. It must, ideally, be as superior to any accepted language as the mathematical method of expressing quantities and relations between quantities is to the more lumbering methods of expressing these quantities and relations in verbal form. This is undoubtedly an ideal which can never be reached, but ideals are not meant to be reached: they merely indicate the direction of movement.

Were a language ever completely "grammatical," it would be a perfect engine of conceptual expression. Unfortunately, or luckily, no language is tyrannically consistent. All grammars leak.

a perfect hornet's nest of bizarre and arbitrary usages

A rigorous thinking out of the true content of a sentence as contrasted with its purely formal convolutions often reveals the humiliating fact that it could have been expressed with half the apparatus. Abstract nouns, in particular, are not nearly so useful or necessary as is generally assumed. There should, perhaps, be some provision for their formation, perhaps by means of some indefinite noun like thing or matter or way {e.g., wise way for wisdom), but the real point is that they can often be easily avoided, and with a gain in vividness. Thus, there is nothing in the sentence "The wisdom of old age chills youth" which is not as adequately expressed, and with a more intuitive impact, in such a sentence as "Wise old person make cold (to) young person" (or « The wise old make cold the young"). In other words, we must not too lightly assume that the grooves of thought which we are accustomed to in our European languages are the easiest or most natural in a universal sense. It may be worth our while to get into the habit of simplifying the pattern of our thought. We are likely to find that it is helped, rather than hindered, by the unassuming simplicity of such languages as Chinese. Much of our seeming subtlety in expression is really verbiage.

…. this is undoubtedly an ideal which can never be reached, but ideals are not meant to be reached : they merely indicate the direction of movement.

Tout y parlerait À l'âme en secret Sa douce langue natale. we are the dupes of our forms.

There is no doubt that the critical study of language may also be of the most curious and unexpected helpfulness to philosophy. Few philosophers have deigned to look into the morphologies of primitive languages nor have they given the structural peculiarities of their own speech more than a passing and perfunctory attention. When one has the riddle of the universe on his hands, such pursuits seem trivial enough, yet when it begins to be suspected that at least some solutions of the great riddle are elaborately roundabout applications of the rules of Latin or German or English grammar, the triviality of linguistic analysis becomes less certain. To a far greater extent than the philosopher has realized, he is likely to become the dupe of his speech-forms, which is equivalent to saying that the mould of his thought, which is typically a linguistic mould, is apt to be projected into his conception of the world. Thus innocent linguistic categories may take on the formidable appearance of cosmic absolutes. If only, therefore, to save himself from philosophic verbalism, it would be well for the philosopher to look critically to the linguistic foundations and limitations of his thought. He would then be spared the humiliating discovery that many new ideas, many apparently brilliant philosophic conceptions, are little more than rearrangements of familiar words in formally satisfying patterns.

There is no doubt that the critical study of language may also be of the most curious and unexpected helpfulness to philosophy. Few philosophers have deigned to look into the morphologies of primitive languages nor have they given the structural peculiarities of their own speech more than a passing and perfunctory attention. When one has the riddle of the universe on his hands, such pursuits seem trivial enough, yet when it begins to be suspected that at least some solutions of the great riddle are elaborately roundabout applications of the rules of Latin or German or English grammar, the triviality of linguistic analysis becomes less certain. To a far greater extent than the philosopher has realized, he is likely to become the dupe of his speech-forms, which is equivalent to saying that the mould of his thought, which is typically a linguistic mould, is apt to be projected into his conception of the world. Thus innocent linguistic categories may take on the formidable appearance of cosmic absolutes. If only, therefore, to save himself from philosophic verbalism, it would be well for the philosopher to look critically to the linguistic foundations and limitations of his thought. He would then be spared the humiliating discovery that many new ideas, many apparently brilliant philosophic conceptions, are little more than rearrangements of familiar words in formally satisfying patterns. In their recently published work on "The Meaning of Meaning" Messrs. Ogden and Richards have done philosophy a signal service in indicating how readily the most hardheaded thinkers have allowed themselves to be cajoled by the formal slant of their habitual mode of expression. Perhaps the best way to get behind our thought processes and to eliminate from them all the accidents or irrelevances due to their linguistic garb is to plunge into the study of exotic modes of expression. At any rate, I know of no better way to kill spurious "entities." ("The Grammarian and His Language") Wu-river stream mouth evening sun sink, North look Liao-Tung, not see home. Steam whistle several noise, sky-earth boundless, Float float one reed out Middle-Kingdom.

Single Algonkin words are like tiny imagist poems.

And yet in the recorded texts of primitive tradition and song there are many passages of unique vigor and beauty. The structure of the language often forces an assemblage of concepts that impresses us as a stylistic discovery. Single Algonkin words are like tiny imagist poems. We must be careful not to exaggerate a freshness of content that is at least half due to our freshness of approach, but the possibility is indicated none the less of utterly alien literary styles, each distinctive with its disclosure of the search of the human spirit for beautiful form. (Language)