B Molle

F Brelle

J Bessy

D Gatel

Mr Bruno Molle

WHICH WATER QUALITY FOR WHICH USES? OVERCOMING OVER-ZEALOUS USE OF THE PRECAUTIONARY PRINCIPLE TO RECLAIM WASTE WATER FOR APPROPRIATE IRRIGATION USES Ψ

Keywords: water management, water scarcity, waste water reuse

The growing conflicts over water resources looks set to worsen in the context of climate change.

High quality groundwater resources ideally reserved for domestic uses are diminishing especially where urban centres are growing, as treatment facilities cannot always keep up. The farming sector could better manage water quality and quantity to produce food sustainably, keeping economic activity in rural areas. Purification techniques are progressing in efficiency at growing cost, removing the polluting load from effluent which is potentially useful for agriculture. Competing domestic and agricultural water uses can in fact be complementary as can be seen in green belt of megacities.

Policy making based on the precautionary principle are developed from existing regulations and guidelines. Because of the lack of scientific results, most often policies confuse prevention and precaution. A balanced application of the precautionary principle would enable a rational development of reuse schemes, preserving good quality resources and taking benefit from disposed minerals for crops. An economic approach along with risk assessment would avoid disproportionate costs to gain security. Consistent information and training should be organised to enhance public and worker awareness of risk management.

Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662 RÉSUMÉ Les conflits atour des ressources d'eau semblent résolus à empirer dans le contexte du changement climatique. Les ressources d'eau souterraine de bonne qualité réservées pour des utilisations domestiques diminuent alors que les centres urbains grandissent et que les équipements de traitement d'effluents ne peuvent pas toujours suivre. Le secteur agricole pourrait mieux gérer la qualité et la quantité d'eau qu'il utilise pour produire une alimentation durablement, maintenant une activité économique dans les espaces ruraux. L'efficacité des techniques de traitement progresse à des coûts croissants, alors qu'une partie de la charge de pollution de l'effluent serait potentiellement utile pour l'agriculture. Les utilisations domestiques et agricoles de l'eau qui sont concurrentes pourraient en fait être complémentaires comme on peut le voir dans les ceintures vertes des mégapoles.

Les politiques de gestion des effluents fondées sur le principe de précaution sont développées à partir de règlements existants et autres guidelines. À cause du manque de données scientifiques, le plus souvent ces politiques confondent prévention et précaution. Une application équilibrée du principe de précaution permettrait un développement raisonnable d'accords des pratiques de réutilisation, préservant les ressources de bonne qualité et bénéficiant des minéraux normalement rejetés pour les cultures. L'approche économique et d'évaluation du risque éviterait des dépenses disproportionnées pour gagner en sécurité. Une information cohérente et la formation des acteurs impliqués devraient permettre d'augmenter la capacité du public et des ouvriers à gérer une part du risque.

MOTS CLES: gestion de l'eau; pénurie, réutilisation d'eaux usées INTRODUCTION Conflict over water resources is a recurring theme in the media, backed up by scientific observations [START_REF] Pachauri | Statement by, the Chairman of the IPCC at the COP-17 Plenary[END_REF]. Clashes over water use look set to worsen in the light of climate change forecasts, with increasing variability expected, especially in Africa [START_REF] Dai | Drought under global warming: a review[END_REF].

Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662

WATER RESOURCES

Surface water provides three quarters of the world's domestic water. As low levels of water drop to severe levels, the polluting load on surface water increases [START_REF] Pachauri | Statement by, the Chairman of the IPCC at the COP-17 Plenary[END_REF]. While Mediterranean countries are particularly affected, the phenomenon is being increasingly observed in northern areas which are experiencing unusual periods of drought, as seen in spring 2011 in Belgium, western France, the UK and Ireland, and in the unforgettable fires in Russia in 20101 . Higher quality groundwater resources, which should ideally be reserved for domestic uses, can become extremely strained when used for irrigation. Tension on supply quantities can result in a dramatic drop in groundwater levels. Additionally, the quality of groundwater resources may be threatened by exposure to agricultural or industrial pollution, which spreads directly beneath the aquifer. Tensions may concern both the quantity and quality of the supply of water in coastal areas, where a drop in groundwater levels can lead to intrusion of brackish or salt water [START_REF] Green | Beneath the surface of global change: Impacts of climate change on groundwater[END_REF].

WATER USES

The steady growth of urban centres, often located on the shores of rivers or lakes, increases demand for high quality water along with output of wastewater. Since treatment facilities cannot always keep up with the pace of change, urban growth can cause acute strain on water intake and outflow, making it difficult to provide a high quality water supply that can be made suitable for drinking at acceptable cost over the long term.

The failings behind industrial disasters which receive high-profile media coverage have contributed to negative stereotypes of industry. Despite the efforts of many sectors to minimise their environmental impact -through measures that can be very costly due to a lack of purposedesigned technical solutions approved by regulations -society is inclined to view industry as a source of chemical and thermal pollution. Due to the wide ranging quality requirements for industrial water supplies, industries that incorporate their own specific water treatment processes into their activities are thus more conscientious about maintaining water quality.

Across the board, agriculture puts the greatest pressure on water resources in terms of Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662 volume. The farming sector is often accused -sometimes rightly -of mismanaging water quality and quantity and causing directly or inducing indirectly pollution. However, agriculture has made tangible advances in technological, social and organisational terms, in both North and South. While further progress is needed, focus must stay centred on the purpose of irrigation, which is to secure sustainable food production. It is important to remember that in most cases, agriculture is a crucial activity in rural areas. In developing countries, life without farming triggers an influx of rural migration to urban areas which is unmanageable in social, economic and public health terms.

Irrigated farming creates opportunities thanks to its capacity to cope with water of mediocre quality, especially for non-food crops. As an alternative to the standard approach of trying to curb pollution by making purification techniques more efficient -at spiralling costirrigation can make do with, and even reuse, part of the polluting load extracted from wastewater or released into the environment.

Notwithstanding crisis situations -which can often be resolved only through hard-hitting restrictions -it would seem that competing water uses can in fact be seen as complementary.

QUALITATIVELY MATCHING RESOURCES TO USES

Optimising the allocation of water to different uses according to corresponding quality requirements appears to be an appropriate way to tackle the burden on the water cycle. A number of factors need to be taken into consideration to ensure optimal management of supply volume and quality:

• requirements specific to each type of use (domestic, irrigation, bathing, industry, ecosystems);

• regional factors (especially given that environmental, economic and social balances are at stake), which should be considered individually as well as in relation to one another at territorial level;

• social acceptability, especially regarding reuse of treated wastewater;

• public health, which is of course a pre-requisite.

One method of optimisation is to reallocate groundwater to domestic use and surface water to and agricultural use, for example by setting up agreements within a region. This method is used to allocate groundwater in the Perpignan region of the Roussillon plain in Another method of optimisation is to channel poor quality water into suitable uses. To optimise the water cycle, water uses should be ranked in a hierarchy of quality requirements, from the most demanding (drinking water, fish farming) at the top, to the least demanding (biofuels, farming, fire fighting, etc.) at the end of the cycle. This method must be supported by a suitable technical and legislative framework. Such re-prioritising can reduce the polluting load (a waste product from one level can be used as input for the next level) while maintaining the environment's natural purification capacity.

Numerous examples of treated wastewater reuse are reported (firewood, timber, cereals, etc.). Regions suffering from water scarcity (Spain, Israel, Cyprus, Tunisia, Australia, California, etc.) have a history of using treated wastewater directly to maintain golf courses and landscapes on the outskirts of cities, or parks like in Madrid, and Palma de Majorca, as well as storing treated wastewater in contained aquifers. France has a relatively established track record in this area: for more than 15 years, 700 ha of cereal crops including seed production3 have been irrigated with recycled urban wastewater from Clermont-Ferrand, along with the effluent from a sugar processing plant.

However, it is important to account for the diversity of approaches. In southern countries, where the quantity of supply remains a problem, there is a political consensus on the reuse of treated wastewater, and readier acceptance of the associated risks. Conversely, in more temperate countries where the tension is felt less, or at least is highly variable, over-zealous application of the precautionary principle -now enshrined in European law (Maastricht treaty, 2005) -precludes policymakers from taking the least risk. Such risk aversion persists despite the lack of accurate, reliable scientific arguments. For example, Spanish regulations stipulate that wastewater reused for irrigation purposes must be analysed for Legionella; this requirement is founded on data from cooling towers, where conditions differ vastly from those of irrigation.

Californian regulations require reused wastewater to present a minimum residual chlorine content of 1 ppm.

The 2009 French report of 'Parliamentary Office to review scientific and technical decisions'4 found that adoption of the precautionary principle in the constitution had disconnected policy thinking from scientific thinking and prompted a number of adverse effects:

Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662 confusion between prevention and precaution; use of the precautionary principle for proven risks whose scope is unknown, and invoking the precautionary principle to address 'concerns considered as legitimate on the part of certain communities' which result from a legal precedent by which 'the mere presence of equipment5 now constitutes damage'.

This article highlights a number of scientific considerations which can help improve management of water resources through the use of treated wastewater. The precautionary principle, whose diverse interpretations are discussed in UNESCO's [START_REF] Comest | The precautionary principle -The world commission on ethics of scientific and technological knowledge[END_REF] report, should be applied strictly and in a well thought-out manner.

GUIDELINES AND REGULATIONS

World Health Organisation (WHO) Guidelines: A basis for regulation

The quality of water used for drinking, irrigation and recreational purposes exerts a significant influence on health throughout the world. Individual countries have consequently developed standards to protect public health. The water section of the World Health Organisation (WHO, 2006) has published a series of Guidelines which include an authoritative recognised assessment of health risks associated with water, as well as assessing the effectiveness of techniques to control these risks. Use of the term 'guidelines' is deliberate;

these are not international standards, and the recommended values are not mandatory limits. The aim is to provide a reasonable scientific basis for developing national standards. To date, the guidelines have served as the cornerstone for various national and regional directives, as well as more advanced legislation such as in California, which seeks to address specific constraints while tailoring regulations to local environmental, cultural, economic and social factors.

The WHO has designed an integrated approach (Figure 1) known as the Stockholm Framework, which combines risk assessment and risk management to tackle water-related diseases. Although the framework was developed for infectious diseases, it is equally applicable to diseases caused by water-related exposure to toxic chemicals. This model sets the assessment of health risks as the basis for defining health targets and determining guideline values. Such values may then be used for basic checks and to assess the combined impact of these practices on public health.

UN Food and Agriculture Organisation (FAO) Guidelines

The FAO has published numerous guidelines on water quality in the production of food (crops, livestock and aquaculture), fibre and energy. These guidelines cover three main issues: use of water in farming; the impact of agriculture on aqueous environments, and levels of quality throughout the food chain, from farm to fork. A number of different outcomes are sought:

• maximise yield by not hindering production with water of non-compliant quality;

• improve agricultural yield by reaping the benefits of nutrients (N and P) and organic matter present in treated wastewater;

• recommend specific practices to cope with poor quality water (crop types; irrigation techniques, and sanitary practices to minimise contamination of crops);

• uphold the productive capacity of the soil (crop growing practices, amendment, etc.);

• minimise or reduce the environmental impact further on in the cycle, and prevent contamination and the spread of contagious disease.

Each outcome is covered by technical guidelines and recommendations; in some cases specific standards are also referenced. The WHO and FAO have worked in close collaboration to jointly produce a reference document designed to help set health standards relating to reuse of wastewater and excreta in agriculture. This guide (UN Water Development Report, 2003) may serve as a reference document for government in drawing up regulations in these areas.

National regulations

Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662

An extremely diverse range of regulatory frameworks can be found at national level [START_REF] Huertas | Key objectives for water reuse concepts[END_REF]. Some examples are listed below.

At European level, there is no standard regulation governing the use of treated wastewater in irrigation. In France, the use of treated urban wastewater to irrigate crops and landscapes is regulated by the Law Decree of 2 August 2010. This decree sets out the health and technical conditions allowing for the use of treated wastewater for the purposes of irrigating crops and landscapes only. It describes four health quality levels, and stipulates restrictions on usage, distance and soil characteristics. The overriding goal of this regulation is to govern methods of sprinkler irrigation -the most common type of irrigation in France -in order to minimise risk of drift 6 and transport 7 .

Tunisia first set out conditions allowing for the use of treated wastewater in a Law Decree 8 passed in 1989. The quality standards applicable to use of this water for irrigation purposes were modelled on WHO guidelines.

The Australian Guidelines for Water Recycling [START_REF] Agwr | Overview of the Australian Guidelines for Water Recycling: Managing Health and Environmental Risks[END_REF] are not based on the findings of any post-treatment tests; these guidelines are instead modelled on a generic risk management framework which is applicable to any system for recycling treated wastewater, grey water or run-off.

In Israel, where the pressure on water resources has propelled the reuse of treated wastewater to the level of national priority, there is a policy to progressively substitute freshwater with treated wastewater in irrigation. In 2010, the Israeli parliament adopted a stringent new regulation that prescribes 38 biological and chemical parameters 9 .

Expertise and Standardisation Initiatives: The Road to International Consensus

The reuse of poor quality water entails complex interactions of environmental, social and health issues. International standards in this area can only be established by mobilising specialist expertise. Yet with the exception of security standards, ISO and other standards are merely reference documents whose application is voluntary. Such standards reflect international consensus reached by experts designated by participating countries. Israel, the world's most experienced country in this field, is currently convening the ISO PC253 project, 'Treated Wastewater Reuse for Irrigation'. In the course of discussions, a string of gaps in the scientific literature has come to light. There is a dearth of data on health risks and choice of technology.

6 Displacement of the wetted surface by the wind 7 Displacement of water beyond the wetted area in the form of small droplets which may produce aerosols and over-restrictive legislation. This unsuitable scale leads to the loss of a large proportion of potentially beneficial nutrients, minerals and complex molecules which could be extracted from

wastewater. Yet heavy metals, nitrogen, phosphorus and many other elements that are considered pollutants when released into the environment, may in fact be inputs for other activities. One potential course of action is to foster Green Economy practices that seek to draw maximum benefit from alternative sources of water and materials such as heavy metals, complex molecules such as polyphenols, and minerals10 . The payoff from harnessing these unexploited resources would help the 2.6 billion people living on untreated water to be connected to treatment facilities. This may contribute to reducing the number of people without Although the precautionary principle has rightly prevailed and been incorporated into law, it has failed to prevent the recent health crises listed above. The principle alone is not enough to prevent an accident from re-occurring. Instead, the system-based, sector-based or process-based approaches of quality management should be adopted, at least on a regional level (FAO, 2010). Risk assessment should be 'balanced' and 'reasonable' to counteract the irrational fears that can far too easily take hold in a society or community. A solid economic, or even macro-economic, approach should be taken in risk assessment, and there must be real political will to match disproportionate costs to the perceived security gain through analysis of suitable values.

In In this regard, the approach adopted by Israeli legislation merits particular attention.

Every element and stage in the reuse cycle is weighted for its protective capacities, in other words, the number of barriers to contamination. Under this system, tertiary treatment may score the same as a watering system that inhibits contact with produce. The risk prevention score is boosted by factors such as inedible peel on fruit, or cooking or any other form of processing.

Monitoring policy must remain reasonable at the risk of prohibiting all wastewater reuse due to costs. Flexible procedures, by which initially intensive monitoring could be gradually tapered down in the absence of alerts, would generate substantial cost savings in the area of analyses. Such savings should increase over time provided wastewater quality levels remain stable overall (except for daily or seasonal fluctuations), and insofar as the associated activities also remain stable. Elsewhere there is a greater safety gain to be achieved from training operators and automating monitoring processes than from increasing the number of analyses.

No real progress can be made unless a solid scientific communications strategy can win out over the media's often sensational and indeed anxiety-inducing portrayal. Proper insight into this cycle of reuse is needed to make it workable. However to date, wastewater treatment methods have been primarily designed to eliminate pollutants with no view to recycling. One intriguing example is phosphorus: this element is costly to remove from wastewater and has a significant impact on the environment. Yet only an estimated 70 years of accessible reserves of this essentially non-renewable, mined resource are left. A total of 75% of the world's degradable phosphorus is sourced from two countries, Morocco and Mauritania.

  Figure 1. A simplified integrated framework -repeat cycle (Bartram et al. 2001)

  access to drinking water (900 million in 2009), thus moving closer to achieving the Millenium Development Goals (MDG). Progress remains to be made in researching separation techniques to develop methods for selective purification of wastewater. Agricultural reuse of treated wastewater is an effective ready solution despite the lingering presence of risks related to managing wastewater quality. Understandably, politicians are hypersensitive to public opinion. Health alerts and scandals over the past two decades -asbestos, Escherichia coli, bird flu, HIV-infected blood, dioxins from incinerators and BSE -have prompted highly conservative application of the precautionary principle among the political class. The situation is compounded by the fearful reluctance of decision makers and state agents to expose themselves to liability proceedings. The end product of such fears is an extremely prudent body of legislation and regulations. As stated in the French parliamentary report cited above: 'The State can no longer merely manage risk; it has to manage social relations. […] The precautionary principle is becoming a tool to manage public opinion. This interpretation of the precautionary principle ultimately serves to Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662 disqualify scientific expertise.'

  Such a strategy should aim to dispel preconceived ideas and shed new light on figures, backed up by solid data supplied by transparent monitoring. It should help people, if not to reach a consensus, at least to grasp the challenges and risks involved, and understand the processes under the joint control of the health and food sector, administrations, consumer associations and Non Governmental Organisations (NGO).PROSPECTS FOR REDUCING/RECYCLING POLLUTANTS AND VIABLE TECHNIQUES: INTEGRATING IRRIGATION INTO THE TREATMENT CYCLEThe reuse of poor quality water offers prospects from both an economic and environmental point of view, since a waste product from one type of use can be an input for the next stage.

  -produced version of the article published inIrrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662 Such knowledge gaps may encourage legislators to apply the precautionary principle overzealously although existing long-term practices may well turn out to be harmless.

	DRAWBACKS OF THE PRECAUTIONARY PRINCIPLE: EXCLUSIVE HARDLINE
	APPLICATION
	Tertiary treatment facilities feeding into a wastewater reuse area are often scaled
	disproportionately due to the lack of recognised methods for risk assessment, risk of
	malfunction of treatment facilities (technical flaws, separation of networks, maintenance, etc.)

8 Law Decree No. 89 -1047 dated 1989, amended by Law Decree No. 93 -2447 dated 1993 9 Government Decision on Upgrading Effluent Quality Cabinet Decision of May 5, 2005: Upgrading Effluents for Unrestricted Irrigation and Discharge to Rivers Updated: 16/12/2007 Author

  this respect, the European Commission is reluctant to regulate the use of treated wastewater for irrigation purposes. Despite a patent need for such regulation in southern regions, such a need is not felt in the majority of EU member states. It is equally surprising that the Commission has not produced a regulatory framework linked to the Water Framework Directive (WFD), which sets out a quality scale for environments receiving outflow of wastewater from treatment plants, although no quality constraints exist for irrigation water sourced from such environments. However, certain aspects of the WFD have an influence on the potential for reuse of treated wastewater, namely, the introduction of municipal plans to conserve water resources; rollout of financial incentives by governments to reduce domestic water consumption, and a water pricing policy that approaches the real cost of water supply and treatment, while bearing in mind the positive externalities.Perceptions of treated wastewater as a resource reflect the widely divergent approaches in different countries. In arid climates, the overriding challenges are to manage the water resource and control the risk of soil degradation (primarily salinity). Conversely, the key challenge in temperate climates is protection of the environment. Alternative water resources are only sought at local level, where landscapes or farmland are located close to a treatment facility, and adequate winter leaching means that any risk to the soil is minimal. It is extremely risky to attempt a single approach to managing and reclaiming wastewater without accounting for local climatic conditions, not to mention social and environmental conditions. But first, greater insight is needed into the mechanisms at work in the interactions between the environment and methods of wastewater reuse. Gaps persist in many Author-produced version of the article published inIrrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662 areas of specialised research, physical (transport, run-off, drift or aerosols), chemical (solar activity, soil degradation, leaching) and biological (growth of biofilms in which pathogens may survive). These knowledge gaps stem from the use of raw data from other fields which is applied indiscriminately to the area of wastewater reuse.

	Potential Responses
	The responsibility lies with research to overcome reluctance and overly cautious reactions
	by tailoring risk assessment methods from the fields of industry and public health to this
	particular purpose.

Europe is facing the worst drought in century, April

2011, http://crisisboom.com/2011/04/26/europe-isfacing-the-worst-drought-in-century/

SAGENappes plio-quaternaires de la plaine du Roussillon, 2011.http://gesteau.eaufrance.fr/sage/nappes-plio-quaternaires-de-la-plaine-du-roussillon

L'irrigation au service de la gestion de l'eau, http://www.waternunc.com/fr/Horizons_Limagne.htm#irrig

 4 Le principe de précaution : bilan de son application quatre ans après sa constitutionnalisation, http://www.senat.fr/notice-rapport/2009/r09-025-notice.html

The equipment in question was a mobile telephone relay antenna

Toward a green economy, Water, Investing in natural capital, 2011. http://www.unep.org/greeneconomy/Portals/88/documents/ger/4.0_Water.pdf

http://www.raeng.org.uk/news/releases/shownews.htm?NewsID=685

Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002DOI: 10. /ird.1662 Exports are banned in China and other countries. The demand for phosphorus is growing in line with the spiralling demand for food; poor countries are experiencing a shortfall, while in rich countries excessive quantities are applied and blocked by the soil. There is an urgent need to recover this element which is essential to food production which, when released into the environment through wastewater, exacerbates the incidence of eutrophication in aqueous environments. At present, 'chemical' recovery is costly, and plant reuse from wastewater is tricky since levels present in reclaimed waters are constant whereas the needs of plants are not.

Advances in analysis and toxicology have revealed the impact on the environment and on human health of low doses of by-products from the processing of chemical consumer goods.

Fish are feminised by hormone derivatives, pesticide breakdown products are genotoxic, and many other chemicals are released in industry and household waste. The spread of these pollutants can lead to photodegradation, or exposure to biological and chemical oxidation in the soil [START_REF] Petrovic | Analysis, fate and removal of pharmaceuticals in the water cycle[END_REF][START_REF] Escher | Recent Advances in Environmental Risk Assessment of Transformation Products[END_REF]. A refined level of water treatment is therefore needed to ensure treated wastewater is suitable for agricultural purposes. Refined treatment will eliminate pollutants capable of passing through standard treatment cycles. However, certain chemicals, such as hormones used in animal health, may not be caught even by this soil-based filter [START_REF] Liqa | Drivers and Characteristics of Wastewater Agriculture in Developing Countries: Results from a Global Assessment[END_REF].

Treated wastewater contains nutrients that may be beneficial to plants, often substantially improving the energy balance scoring of crops. For example, if we look at fertilisation in an irrigated potato crop, its energy balance scoring varies from 60 -75% of the total scoring for the activity [START_REF] Ginoux | Performance environnementale des techniques d'irrigation, Analyse du cycle de vie comparative des systèmes d'irrigation[END_REF], and at least two-thirds of this value is for nitrogen. Although methods for extracting nutrients still need to be refined and made affordable, there is enormous potential at stake. Wastewater also offers a source of organic matter for impoverished 'modern' agricultural soils that receive little plant residues. Despite its rapid fermentation, wastewater organic content can help to improve soil quality toward greater salt tolerance and stimulate biological activity.

Project analysis is continually hampered by the relatively long distances between sites of production and potential consumption of treated wastewater. Green belts offer exciting potential for urban wastewater recycling by the small-scale crop growers who supply urban markets.

Quality requirements for fruit and vegetable irrigation are of course much more stringent but tend to be lower for landscapes and forests. Yet both offer viable opportunities for wastewater reuse, as is frequently prescribed in water management strategy plans such as the WFD.

Small-scale green belt crop growing presents a considerable health risk for both farmers and consumers in many sprawling southern cities where open sewers are commonplace. The solution is certainly not to abandon these methods of farming, which cater to real demand, but

Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662 instead to determine the technologies and practices required to render wastewater suitable for use. This technical approach should be accompanied by consumer education and training for farmers.

In rural areas with scattered habitats, such as Sub-Saharan Africa, irrigation affords opportunities to reuse wastewater treated in suitable decentralised treatment facilities, again with proper education and training.

We have highlighted above the paradox of the regulatory limitations in the use of treated wastewater in irrigation, despite the absence of any regulation on water quality for irrigation purposes. Even in northern countries, it is not unusual to find agricultural effluent pumped into rivers whose low water levels are sustained by outflow from treatment plants. A strict risk analysis would undoubtedly conclude, in spite of treatment plant monitoring regulations, that the health risk is no higher than if treated wastewater were converted into irrigation water via a defined, fully scaled and tested process. If only because crops irrigated with treated wastewater would be subject to monitoring, as would irrigation management, which is not the case in direct pumping from the river.

At the top of the cycle, urban wastewater is available in copious quantities and proves easiest to reuse in view of the fairly precise locations of outlets that could be fitted out for the purpose. Further down the cycle, the same urban centres consume farm produce such as fruits and vegetables, while green areas and forests, either in the city or its outskirts, are needed to balance out the urban environment and the lives of city dwellers.

Town planning schemes should therefore incorporate the city, its demand for water, food, materials and energy, need for recreational areas, generation of waste, and reuse of waste to satisfy demand, all at a 'proportionate' overall cost that is affordable in the long term. There is no reason why the principle of 'polluter pays' should not be upheld, which would make the treated wastewater resource free of charge at the source, at the stage of output from the treatment facility. The user of this water should cover the cost of the service, i.e. conveyance to the point of consumption at the required pressure and flow rate. However, this straightforward approach does not determine how to equally split overall costs, which can be more complex (FAO, 2010). The scientific approach must be combined with technical solutions based on socio-economic analyses.

SOCIAL HURDLES AND CONSENSUS AMONG STAKEHOLDERS

While the reuse of treated wastewater is generally accepted as a logical solution to alleviating the burden on water resources, surveys produce varying results depending on the level of water Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662 scarcity experienced locally (Brown and Davis, 2007) and where people are more closely affected by water reuse 11 . Individuals are prepared to reuse their own grey water, but not that of their neighbour. Agri-food businesses unwilling to stake their image prefer to implement a blanket ban on water reuse in specifications for their suppliers, dismissing the notion of checking procedures.

Groundwater recharge is a technique used to offset salt water intrusion or to generate an emergency water reserve; any immediate risk of contamination with treated wastewater may be curbed by leaching through the soil matrix. However, the practice of topping up groundwater recharge is severely frowned upon. Negative attitudes can only be changed over time by engaging the public and highlighting positive data without glossing over the risks [START_REF] Jeffrey | A Conceptual Model of 'Receptivity' Applied to the Design and Deployment of Water Policy Mechanisms[END_REF].

By 2008 [START_REF] Liqa | Drivers and Characteristics of Wastewater Agriculture in Developing Countries: Results from a Global Assessment[END_REF], 70% of cities in developing countries were using some wastewater, in many cases untreated. This helped to maintain nearly half of their green belt land, representing almost 20 million hectares of rice and vegetables, 70% of which was harvested and sold by women thus enhancing their emancipation. Consumers in these cities report that they prefer not to eat food produced with wastewater, but are generally unaware of the fact when they do so. These unofficially tolerated practices tend to evade detection even in countries with appropriate regulations. However, farmers themselves employ risk prevention strategies such as drip irrigation, washing produce, and selecting water according to 'intuitive quality criteria' such as smell and occasionally taste.

We are seeing a growing number of examples of water sharing or concerted water management adapted to quantity and quality requirements. In Jordan, where the King Abdullah Canal is the main source of freshwater for the city of Amman and for farmers in the Jordan Valley, this highly interdependent situation is the subject of historic negotiations within the country itself and with neighbouring Israel. Change is expected to continue in the short term due to spiralling urban populations, costs of water supply (conveyance and treatment), uncertainty about climate change and the continued drop in groundwater levels. Collectively, these factors will force the farming sector to adapt once again to using less water more efficiently [START_REF] Courcier | [END_REF].

Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662 CONCLUSION Effective management of water resources must address concerns of both quality and quantity.

Higher quality water should be reserved for human consumption and domestic use; poorer quality water can be allocated to less demanding uses. The water cycle can also be extended by reusing certain organic and mineral pollutants in crop growing. In this way, treated wastewater is reclaimed as a resource and a source of nutrients for plants, and no longer seen strictly as waste.

This approach comes naturally to countries where water resources are scarce, such as the southern and eastern Mediterranean, Australia, Spain and the south-western United States.

Consequently these countries present the greatest number of examples of organised reuse of treated wastewater. In northern countries, reliance on the precautionary principle gives rise to over-zealous and at times contradictory stipulations regarding the reclamation of treated wastewater in irrigation. For example systematically requiring that samples be analysed for Legionella irrespective of the techniques used for distribution, or for residual chlorine content, even though the presence of bacteria would be entirely acceptable.

Even in countries less vulnerable to water scarcity, where the urban sector needs a high quality water supply, it could make economic sense -to diminish reliance on faraway resources and costly treatment processes -to reserve the high quality water supply for the potable use.

Treated wastewater would then be used to meet the needs of agriculture, landscapes, recreational areas and sports grounds. Such re-allocation would also delay the onset of water stress in certain regions and help refine the treatment of outflow from treatment plants.

Such an exchange of services presents a major challenge in economic, environmental, social and scientific terms, and as such must be evaluated, financially and otherwise, by all stakeholders concerned. The additional costs incurred by substituting resources must be absorbed on a pro rata basis in relation to services rendered. As a matter of priority, costs of treatment must be equally distributed among effluent users and producers, with an exhaustive analysis of the environmental benefits.

Coherent regional policies incorporating use of this alternative resource should be brought into force. These policies should be based on a strict, reasonable approach to risk analysis and equitable distribution of all costs, justified by:

• the need for the water supply to be fit for the purpose in terms of quality; it follows that high quality water resources should be set aside for more demanding uses;

• the finding that certain sources of irrigation water in the environment are of inferior quality to wastewater that has been appropriately treated.

Author-produced version of the article published in Irrigation and Drainage, 2012, 61 (1), 87-94. The original publication is available at http://wileyonlinelibrary.com DOI: 10.1002/ird.1662

Such policies could be bolstered by conditioning public subsidies to encourage beneficiaries to extend the water cycle by applying a cascade of uses (communities and farmers), and by promoting water reuse to minimise risk to the environment while preserving soils. Research efforts must continue to seek insight into the challenges in terms of risks and solutions, in order to drive financial and environmental costs down to an acceptable level.

ACKNOWLEDGEMENT

This article has been prepared thanks to the contribution of various projects and cooperation:

Mediwat (Interreg MED N°2G-MED09-262) ; Onema-Afeid-Astee agreement.


P Degenne
email: pascal.degenne@cirad.fr

A Ait Lahcen

O Curé

R Forax
email: forax@univ.mvl.fr

D Parigot
email: didier.parigot@inria.fr

D Lo Seen

Modelling the environment using graphs with behaviour: do you speak Ocelet?

Keywords: Domain Specific Language, Landscape, Ocelet, Interaction graph, Relation

Environmental modelling often implies defining elements that relate and interact with each other, in a system that evolves with time. Ocelet is a domain specific environmental modelling language that was designed around a limited set of key concepts chosen to help modellers focus on their model, while leaving the implementation to an automatic code generation phase. Here, we focus more specifically on a concept called Relation in Ocelet that allows to build graphs that describe which elements of the model interact, and how. It is designed to be used in combination with two other main concepts: Entities (elements of the model) and Scenarios (describing the temporal evolution). Every Ocelet Relation can express one specific point of view of a system and several Relations can be combined to integrate different points of view in the same model. By its diversity, points of view convey expressive power: with different expert views on a system, at different spatial scales, or an environment sensed by its different components. Moreover, in this versatile design, a Relation defined for one specific model can be reused in a different modelling context. Libraries of generic interaction behaviours can thus be developed for efficient and reliable modelling practices. An example is given to illustrate how interaction graphs can be built, manipulated, and reused using Ocelet. Finally, we give insight into the code generation phase that produces the simulator.

INTRODUCTION

Interactions are at the heart of most environmental studies and the way they are modelled is strongly characterised by the modelling formalism used. In System Dynamics (SD), interaction operations can be performed between any of the components of the system, but the latter are generally not spatially represented. In Cellular Automata, interaction operations are defined by a set of rules applied to the cells of a tessellation, and every cell can only interact with its immediate neighbours. Agent based models (ABM) are more versatile and agents are allowed to interact with each other according to a set of locally defined rules. In the case of Discrete Events and Object Oriented design, there is no constraint on how the elements of a model can interact with each other, but this comes at the expense of complex programming for the modeller. When building environmental simulation models, Domain Specific Languages (DSL) are an interesting compromise between expressive power and a steep programming language learning curve. However, to our knowledge only few attempts have been made in this domain so far. [START_REF] Fall | A domain-specific language for models of landscape dynamics[END_REF] proposed SELES in which a landscape modelling language is used to define landscape states in the form of grid layers and a set of landscape events to make the model evolve with time. [START_REF] Gaucherel | A domain-specific language for patchy landscape modelling: The brittany agricultural mosaic as a case study[END_REF] designed L1, a DSL based platform for simulating the evolution of patchy landscapes. CAOS [START_REF] Grelck | Caos: A domain-specific language for the parallel simulation of cellular automata[END_REF]) is a DSL specialized in parallel simulation of cellular automata where space is represented in the form of a grid.

In these examples, a major constraint for the modeller is that space representation is imposed. This is not the case for Ocelet, a DSL developed for landscape and environmental modelling and simulation [START_REF] Degenne | Design of a domain specific language for modelling processes in landscapes[END_REF]). Ocelet was built by carefully selecting the most elementary concepts needed for spatio-temporal modelling. It offers the possibility of creating new modelling primitives based on these concepts, and to incrementally assemble them for developing complex models. The result is a DSL with increased expressivity where the complexities of implementation are left to a code generator. In this article we emphasise on the concept of interaction graphs, as used in Ocelet under the name of Relation. In the next section we explain how and why interaction graphs can be used to express relations in a model. We then briefly present the Ocelet modelling language, the associated code generation and development framework, and also how Ocelet can be used with an ontology language. Finally, based on an example, we present how a relation can be built, manipulated and reused within Ocelet.

RELATIONS AS INTERACTION GRAPHS

An interaction graph not only defines who are in relation (graph structure) but also how the elements relate (behaviour). When modelling the environment, we consider that working directly on interaction graphs can be useful for at least two reasons. First, acting at the most elementary level of the underlying data structure (a set of dynamic graphs) allows manipulating in a similar way different kinds of relations (aggregations, spatial, functional, ...) Second, the state of the model at any given time can be analysed using graph analysis algorithms to extract topological characteristics that emerge during the simulation. These may reflect some specificities of the model that would hardly be visible otherwise. Such analysis algorithms have for example been developed by [START_REF] Batagelj | Pajek -program for large network analysis[END_REF], [START_REF] Fuller | Lqgraph: A software package for optimizing connectivity in conservation planning[END_REF] or Saura and Torne [2009]. In this section, we describe the structure and the dynamic nature of relations or interaction graphs. We then explain how they are made to express behaviour, and how a relation developed in one case can be reused in another. Finally we outline how a relation holds the notion of a point of view.

Graph with dynamic structure and behaviour

Entities of a model can, at a given time, relate to each other in diverse ways. For example, neighbourhood (where two entities are considered neighbours if they are close enough for a given distance function), aggregation (where some entities are considered parts of a larger composite entity), connectivity (where entities can reach each other if a communication route exist between them), influence (where one entity can influence the behaviour of another one) are in fact relations.

For each relation, one can build a graph where the nodes are entities and the relations between entities are the arcs. In many environmental modelling cases the graphs needed are actually hypergraphs (each arc may connect more than two nodes). Such hypergraphs can be built explicitly. For example, if we have several groups of entities connected to each other in the form of simple graphs, one can establish another graph connecting those groups to each other at a broader scale. In that way, it is possible to consider the behaviour of entities within a group as well as between groups. But one can also build hypergraphs implicitly. For example, in the case of a spatial relation where an agricultural parcel is linked to each of its borders by one n-node arc, a graph is built using arcs linking more than two nodes. Such n-node arcs based graphs are de facto hypergraphs. Using n-node arcs can be a way to simplify the graph structure we have to manipulate in the model. Another aspect to take in consideration when modelling with interaction graphs is their dynamic nature. During a simulation, some entities can be added to the model, others can disappear, and individual relationships can be established or removed. This means that the interaction graphs are dynamic, with evolving numbers of nodes and arcs, and have changing graph topologies. Attached to the graph are semantics that specify what happens between the linked entities when they do interact: the kind of information they exchange, the actions one performs on the other, the effects produced by the interaction on the entities and on the arcs involved. In many types of environmental models, attaching behaviour to an interaction graph is not straightforward. Sometimes the graph structure is implicit (e.g. cellular automata based on tessellations) and only the be-haviour is specified. The programming work is then reduced but the specification of the behaviour is seriously constrained by the implicit graph structure. In other cases where the graph structure is more versatile, a greater power of expression is obtained but the lack of adapted tools makes the programming work difficult. In order to get the best of both solutions, it would be necessary to have ways to manipulate the graph structure and attach the behaviour semantics directly on that structure using one same appropriate modelling concept.

Roles and re-usability

It is rare when an environmental model is original in all its parts. The most common situation is to have some parts of the model that are similar to other already existing models. Re-usability has been a key concern in software development and modelling tools as well. In the case of behaviours attached to relation graphs, two situations can be considered:

Re-usability of a relation graph topology: It can be interesting to ready made relation graph structures such as the 3-neighbours situations found in triangulated irregular network, the 4 or 8-neighbours situations found in grids, or also star and circular shaped relationships just to name a few. Based on the well known characteristics of such structures, one could imagine a modelling tool that provides optimized implementations for them to be used in different models.

Re-usability of an attached behaviour:

In that case we wish to be able to reuse the definition of how entities interact with each other when they do, in different modelling situations. To make the behaviour definition adaptable to a different context, the interaction should not be specified using the entities relating with each other but using the role they play. It would then be possible to attach a behaviour definition to a different relationship graph where entities are able to play similar roles. It also means that a behaviour defined once can be instantiated several times, on different graphs, even in one same model.

Finally, it can be noted that by designing a modelling tool with re-usability concerns as described above, it becomes possible to build sub-model libraries (named primitives in Ocelet) and make them available for a modellers community.

Modelling your point of view

At least two cases can be identified where the notion of point of view can take the form of semantics attached to a graph. First, when specialists of several different fields work on the same environmental model, they may share the same entities but need to describe interactions between these entities differently according to their own expert view. The nodes of the graph could be shared, but the arcs and the behaviour attached to those arcs would reflect their different points of views on the model. Second, it happens that different entities of a model have different points of view on their environment and would then have to interact accordingly with that environment (see example section 4). Here again the nodes of a graph could be shared but the arcs and the behaviour attached to those arcs could be specific to every point of view.

THE OCELET LANGUAGE

The main concepts of the Ocelet domain specific language are presented here. The concept of Relation in Ocelet is then explained in more detail, showing how it addresses most of the concerns discussed in section 2. Models written in Ocelet are translated into a general purpose language through a code generation phase before a simulation can be run. The code generation aspect and the associated development platform, and the use of Ocelet with an ontology language are also briefly presented here.

Key concepts of the language

Three main concepts are at the core of the language. They are named Entity, Relation and Scenario:

• Entity: Entities are the basic elements that can be linked together to build a model. An entity may contain other entities, and is then called a composite entity. Entities that do not contain other entities are atomic entities. Entities have properties that can be used to reflect their state. Entities also provide Services which are published functions that can be called locally or remotely. The concept of entity is close to and inspired by the definition of Components in Service Oriented Architectures [START_REF] Szyperski | Component software: Beyond object-oriented programming[END_REF]).

• Relation: A relation is a connection between two or more entities that provide and require compatible services. It defines the nature of interactions between these entities and provides services for the activation of those interactions. This concept in detailed in paragraph 3.2

• Scenario: A scenario is a sequence of actions composed of service calls or relation expressions within a model or composite entity. A scenario is activated for a period of time.

Therefore the scenario expresses most of the temporal behaviour of a model or a composite entity.

In addition to these concepts, we have to mention a special category of atomic entities that is named Datafacer. A Datafacer is an atomic entity specialized in data access. The Datafacer provides different mechanisms for data persistence. Its implementation code can be written in a programming language other than Ocelet in order to optimize data access performances for every type of data sources that a model can integrate. Other concepts such as primary types (number, boolean, ...), tests and control instructions, are also available in Ocelet but they are not different from those of other programming languages such as C or Java, and therefore do not require specific descriptions here. It is also important to mention that even though Ocelet is not strictly an object oriented language, the elements (Entities and Relations) of a model have to be defined first and then instantiated within a Scenario allowing to create as many individual copies as necessary.

Relations are interaction graphs in Ocelet

The Relation concept as defined in Ocelet is an interaction graph very close to what was discussed in section 2: it contains the information of who is in interaction and also of how they interact.

As Relations have semantics attached to the arcs of their graph, they are constrained by the type of entities that can be linked. The definition of a Relation has to specify the role played by the different entities involved, like for example: relation RelationName[roleA, roleB] {...} The statement above defines a Relation of the most common kind: every arc of the graph links two nodes. The nodes will be entities; one entity playing role A and the other role B. Once defined, the Relation must be instantiated, and which entities playing role A and role B must also be stated for that instance: myInstance = RelationName[EntityA, EntityB];

The fact that Relations are defined using roles makes them reusable in different contexts. A Relation carefully designed with genericity in mind could then be used and adapted for several different models. To establish connections and actually build the graph, the predefined connect() and disconnect() services are available. For example, myInstance.connect(lake,river) implies that lake is an instance of EntityA, river is an instance of EntityB and an arc will be added to the Relation graph between them. Ocelet allows to define Relations holding hypergraphs directly by specifying more than two roles in the declaration statement, like for example: The definition above implies that the entities playing roleA for that Relation must provide the two services doSmthg() and getVal(), while the entities playing roleB must provide the service setVal(). getVal() and setVal() must also return and accept compatible types. These are verified when the Relation is instantiated. One important point to note is that only one call to the foo() service is necessary to activate all the arcs of the relation graph.

Code generation and development platform

Models written in Ocelet are not compiled directly, but are translated into a general purpose programming language first. For the target language we use Java, and the Ocelet development environment is integrated into the Eclipse platform in the form of Eclipse plug-ins. The code generated is based on components such as defined by [START_REF] Szyperski | Component software: Beyond object-oriented programming[END_REF] to better separate the functional (the code related to what the model is about) and non-functional (the components discovery and communication mechanisms) aspects, as well as on the Service oriented computing (SOC) paradigm as described by [START_REF] Papazoglou | Service oriented computing[END_REF]. SOC is a paradigm that uses services as fundamental elements for developing applications. The main purpose of this approach is to introduce the minimum dependencies between software bricks to promote their re-usability and their dynamic discovery and combination at run time.

For every Ocelet element, description files are generated that describe the services provided and required by that element. According to the description files, the component generator will produce non-functional code which will manage external communications based on sending or receiving messages synchronously or asynchronously. The assembly of components for a given application is not necessarily known at the start of a simulation and may change dynamically over time. Such a component framework provides an extensibility mechanism allowing the clear separation between the business logic and context-aware service interactions. The code generation allows modellers using Ocelet to take advantage of that dynamic execution environment without having to deal with implementation details.

Mapping Ocelet's concepts to an ontology language

The limited set of key concepts present in Ocelet have been selected to ease the work of the modellers but also to permit a mapping to an ontology language. We have chosen an ontology language, namely OWL2, which is based on Description Logics [START_REF] Baader | The description Logic Handbook : Theory, Implementation and Applications[END_REF]) and recommended by the W3C's Semantic Web working group. The mapping is relatively straightforward and enables to transform automatically one language to the other. Hence modellers either have the possibility to specify their models directly in OWL2, using an editor like Protégé, or to specify the model directly in Ocelet, using an Eclipse plug-in. Several advantages are provided by such an OWL2 serialisation of an Ocelet model. The main one consists in enjoying state of the art reasoning tools on standard inference services, i.e. detecting and repairing ontology inconsistencies and classifying the set of entities of a model. A second advantage corresponds to proposing an efficient storage and query solution for model instances. This aspect is particularly important considering that modellers will simulate temporal situations in any possible order. This feature will enable modellers to analyze the data stored in these data management systems directly with a query language or through applications using API for these query languages.

RELATIONS ILLUSTRATED

The development of the Ocelet DSL was based on the analysis of several very different modelling situations that are studied by our partners in different fields, such as the ecology of mangroves in French Guiana, the epidemiology of the Rift Valley Fever in Senegal, agricultural land dynamics in France and West Africa, and forest landscape dynamics in South India. But for the purpose of this paper, in order to particularly illustrate the use of Relations in Ocelet, we have used a simple and didactic example of a modelling situation.

4.1 Neighbourhood from a tree point of view

In this example, the objective is to model the progressive colonization of trees on a given landscape. A first version of the model contains two pieces of land crossed by a river. The trees growing on one side (Land 1) spread their seeds around their close neighbourhood (Fig. 1(a)).

In the model, we define a relation named DropSeeds to connect every tree to the land or river entities that are close enough to receive their seeds (Fig. 1 The Tree entity is entirely defined using Ocelet. It has position coordinates and a service getDroppedSeedLocations() that returns the positions of the seeds it produces. The Land and River entities are also defined using Ocelet but their shape are defined by data sources. Those data sources are accessed by an appropriate Datafacer. In particular, the Datafacer has a service that can provide the distance between a shape and a given location. It does not matter if internally the shapes are stored in vector or grid format, or if they are in a file or a database. It is the purpose of the Datafacers to hide the underlying data implementations, and they are expected to be optimized for the kind of data source they are dealing with. The DropSeeds Relation is defined as follows :

relation the role they can play for that Relation: seedEmitter and seedReceiver. At initialization, the Relation is instantiated with a statement: dropseed1 = DropSeeds [Tree,Land];

That statement specifies that for dropseed1 the seedEmitter role will be played by Tree entities and the seedReceiver role will be played by Land entities. Then, tree -land connections are established using calls to dropseed1.connect(). The resulting graph held by the dropseed1 instance of the Relation will be similar to the example shown in Fig. 1(b). During the simulation, a scenario calls the dropseed1.drop() service when necessary. One such call is enough for the code of that service to be executed on every arc belonging to the dropseed1 Relation graph. That service takes a list of seed positions from the seedEmitter and propose to the seedReceiver to accept those seeds if they are located within its area. The seed location tests are performed by the seedReceiver, through a Datafacer in the case of Land entities. Interactions between landscape elements are essential in environmental modelling. For this reason, we have taken special care in designing a versatile way of modelling them when developing our DSL-based approach. Ocelet has been designed to take advantage of modelling all different categories of relationship, including spatial and functionnal using one same programming paradigm (graphs with behaviour) and to offer the tools necessary for considerably simplifying what would otherwise be a tedious programming work. In Ocelet, a relation can be defined very simply by an interaction graph that both describes who is interacting and how. The behaviour attached to a graph can be activated on all the arcs at once with only one service call. That behaviour can also easily be made reusable for application in a different modelling context. This relatively simple way of defining a relation has been found to allow modelling a large variety of situations, and reusable primitives are being built with Ocelet to ease the modelling process. We believe that the possibilities offered by integrating network analysis features to Ocelet's relations, the capacity of building reusable modelling bricks, and to relate them with an ontology language, are promising research subjects to be investigated.

Neighbourhood from a bird point of view

Figure 1 :

 1 Figure 1: Trees dropping seeds in their close neighbourhood

Figure 2 :

 2 Figure 2: Adding a bird's neighbourhood point of view allows trees to spread across the river

  It can be noted that the DropSeeds Relation is defined not using Tree and Land entities, but using Degenne et al. / Modelling the environment using graphs with behaviour: do you speak Ocelet?

	DropSeeds[seedEmitter, seedReceiver] {
	service drop() {
	group[Position]
	seedsPos = seedEmitter.getDroppedSeedLocations();
	for (pos in seedsPos) {
	seedReceiver.acceptSeedAt(Pos);
	}
	}
	}

ACKNOWLEDGMENTS

This work was supported (in part) by the Agence Nationale de la Recherche (ANR) under Project No. ANR-07-BLAN-0121 (STAMP: Modelling dynamic landscapes with Spatial, Temporal And Multi-scale Primitives).


Malik Souded
email: malik.souded@inria.fr

Francois Bremond
email: francois.bremond@inria.fr

Optimized Cascade of Classifiers for People Detection Using Covariance Features

Keywords: People detection, Covariance descriptor, LogitBoost

People detection on static images and video sequences is a critical task in many computer vision applications, like image retrieval and video surveillance. It is also one of most challenging task due to the large number of possible situations, including variations in people appearance and poses. The proposed approach optimizes an existing approach based on classification on Riemannian manifolds using covariance matrices in a boosting scheme, making training and detection faster while maintaining equivalent performances. This optimisation is achieved by clustering negative samples before training, providing a smaller number of cascade levels and less weak classifiers in most levels in comparison with the original approach. Our work was evaluated and validated on INRIA Person dataset.

INTRODUCTION

Person detection is one of the most challenging task in computer vision. The large variety of people poses and appearences, added to all external factors like different points of view, scenes content and partial occlusions make this issue complicated. The importance of this task for many applications like people tracking especially in crowded scenes has motivated many researches. A lot of approaches were proposed as results of these research.

The most frequent scheme consists in using descriptors to modelize a person. To perform this modelization, an offline learning step is carried using these descriptors. Once the learning achieved and the classifier obtained, the detection is performed by testing all possible image subwindows.

In [START_REF] Papageorgiou | A trainable system for object detection[END_REF], Papageorgiou and Poggio used Haar-like features to train a SVM classifier. Viola et al. [START_REF] Viola | Detecting pedestrians using patterns of motion and appearance[END_REF] trained a cascade of Adaboost classifiers using Haar-like features too. In [START_REF] Dalal | Histograms of oriented gradients for human detection[END_REF], a new descriptor called Histogram of Oriented Gradients (HOG) was introduced by Dalal and Triggs and was used to train a linear SVM, providing very good people detector. Dala et al. associate this descriptor later in [START_REF] Dalal | Human detection using oriented histograms of flow and appearance[END_REF] with histograms of differential optical flow features outperforming the previous approach. Mu et al. have proposed new variants of well known standard LBP descriptor in [START_REF] Mu | Discriminative local binary patterns for human detection in personal album[END_REF]. They demonstrated the effectiveness of their Semantic-LBP and Fourier-LBP features in comparison to standard LBP for people detection. In [START_REF] Schwartz | Human detection using partial least squares analysis[END_REF], Schwartz et al. concatained HOG, color frequency and co-occurence matrices as one descriptor and employed Partial Least Square analysis for dimensionality reduction.

All the previous mentioned approaches can be classified as dense representation methods due to the detection method (dense search on images). Some other approaches use different detection method and can be categorized as sparse representation approaches. They consists of modeling the human body parts, detect them and achieve people detection using geometric constrains. In [START_REF] Mikolajczyk | Human detection based on a probabilistic assembly of robust part detectors[END_REF], dedicated Adaboost detectors were trained for several body parts. The final detection is obtained by optimizing the likelihood of part occurence along with the geometric relation.

Recently, Tuzel et al. [START_REF] Tuzel | Human detection via classification on riemannian manifolds[END_REF] propose a performant approach for people detection. Their approach uses covariance descriptors to characterise people. This characterisation is achieved by training a cascade of classifiers on a dataset containing human and non-human images. The training is done using a modified version of LogitBoost algorithm to deal with some specificities and constraints of covariance descriptors. One of the main covariance descriptor issues is the computing time of all related operators and metrics. It makes covariance descriptors difficult to use for real-time processing.

Yao and Odobez [START_REF] Yao | Fast human detection from videos using covariance feature[END_REF] have proposed three main contributions to this approach improving the efficiency of the training and detection stage, and providing better performances.

Because our approach is mainly based on these two last approaches, a brief recall about covariance descriptor computation, and a summary of the two cited approaches are described below.

The two approaches present some issues. In the next section, the main contribution of this paper, addressing these issues, is presented. Finally, the experimental results demonstrate that the proposed approach provides equivalent performances that the original ones while improving the processing time of the training and detection stage.

PEOPLE DETECTION USING COVARIANCE FEATURES

Region Covariance Descriptor

Region covariance descriptor is a powerful way to encode a large amount of information inside in a given image region. Il allows the encapsulation of a large range of different features in a single structure, representing the variances of each feature and the correlation between features.

Let I be an image of dimension W × H. We can extract at each pixel location x = (x, y) T a set of d features such as intensity, color, gradients, filter responses, etc.

For a given rectangular region R of I, let {z i } i..S be the d-dimensional feature points inside R. The region R is represented with the d × d covariance matrix of the feature points

C R = 1 S -1 S ∑ i=1 (z i -µ)(z i -µ) T (1)
where µ is the mean of the points z i and S the number of pixels within R

Used Features

In [START_REF] Tuzel | Human detection via classification on riemannian manifolds[END_REF] x + G 2 y . G denotes the foreground probability value (a real number between 0 and 1 indicating the probability that the pixel x belongs to the foreground), and G x and G y are the corresponding first order derivatives. These foreground features are obtained using a background subtraction technique which is restricted to moving people. These two features improve people detection performances and processing time in video sequences.

Fast Covariance Descriptor Computation

A large number of covariance descriptors are required to achieve the training of classifier cascade and for an effective process. The computation of all the feature sums, means and variances for each region has a high cost in term of processing time. To deal with this, Integral images are ideally suited to minimize the number of numerical operations.

Integral images are intermediate image representations used for the fast calculation of region sums [START_REF] Simard | Boxlets: A fast convolution algorithm for signal processing and neural networks[END_REF], [START_REF] Viola | Rapid object detection using a boosted cascade of simple features[END_REF]. Each pixel of the integral image is the sum of all the pixels inside the rectangle bounded by the upper left corner of the image and the pixel of interest.

Due to the symmetic nature of covariance matrices, only upper (or lower) triangle values are needed. In the case of 8-feature set, the covariance matrix will contain 36 different values, and 44 Integral Images are computed to speed up the computing process (8 integral images for the representation of each feature independently and 36 for the representation of product for each pair of features).

Covariance Normalisation

In order to enhance covariance descriptors robustness toward local illumination changes, a normalization step is performed on the covariance matrix. Let r be a subregion contained in a larger region of interest R.

First, both covariance matrices C r and C R are computed using integral representation. After that, the values of covariance matrix C r are normalized with respect to the standard deviations of their corresponding. features inside the detection window R as in [START_REF] Tuzel | Human detection via classification on riemannian manifolds[END_REF] The normalized covariance descriptor is denoted Ĉr .

LogitBoost Algorithmon Riemannian Manifolds

The classification process is performed using a cascade of classifiers which is trained using a LogitBoost algorithm on Riemannian Manifolds.

Standard LogitBoost algorithm on vector spaces:

As seen in [START_REF] Friedman | Additive logistic regression: a statistical view of boosting[END_REF], let {(x i , y i )} i=1...N be the set of training samples, with y i ∈ {0, 1} and x i ∈ R n . The goal is to find a decision function F which divides the input space into the 2 classes. In LogitBoost, this function is defined as a sum of weak classifiers, and the probability of a sample x being in class 1 (positive) is represented by

p(x) = e F(x) e F(x) + e -F(x) , F(x) = 1 2 N L ∑ l=1 f l (x). (3)
The LogitBoost algorithm iteratively learns the set of weak classifiers { f l } l=1...N L by minimizing the negative binomial log-likelihood of the training data:

- N ∑ i [y i log(p(x i )) + (1 -y i )log(1 -p(x i ))], (4) through Newton iterations.
At each iteration l, this is achieved by solving a weighted leastsquare regression problem:

∑ N i=1 w i f l (x i ) -z i 2 ,
where

z i = y i -p(x i ) p(x i )(1-p(x i ))
denotes the response values, and the sample weights are given by

w i = p(x i )(1 -p(x i )).

LogitBoost algorithm on Riemannian manifolds:

To train classifiers using covariance descriptors, this algorithm is not usable as it is. In fact, covariance descriptors do not belong to vector spaces but to the Riemannian manifold M of d × d symmetric positive definite matrices Sym + d . Based on an invariant Riemannian metric on the tangent space defined in [START_REF] Pennec | A riemannian framework for tensor computing[END_REF], let X and Y be two matrices from Sym + d , the following operators are defined and used to achieve training using LogitBoost on Riemannian manifold:

exp X (y) = X 1 2 exp(X -1 2 yX -1 2 )X 1 2 (5) log X (y) = X 1 2 log(X -1 2 yX -1 2 )X 1 2 (6) d 2 (X, Y) = trace log 2 (X -1 2 YX -1 2 ) (7)
which are respectively the exponential, the logarithm and the squared distance on Sym + d matrices.

exp(y) = U exp(D)U T and log(y) = U log(D)U T . y = UDU T is the eigenvalue decomposition of the symmetric matrix y and exp(D) and log(D) are obtained by applying exponential and logarithm functions respectively on the diagonal entries of the diagonal matrix D.

Tuzel et al. have introduced a modifications to the original LogitBoost algorithm to specifically account for the Riemannian geometry. This was done by introducing a mapping function h projecting the input covariance descriptors into the Euclidian tangent space at a point µ l of the manifold M :

h(X) = vec µ l (log µ l (X)) (8)
where:

vec X (y) = vec I (X -1 2 yX -1 2 ), and vec I (y) = [y 1,1 √ 2y 1,2 √ 2y 1,3 ... y 1,2 √ 2y 2,3 ... y d,d ] T .
The trained cascade consists of a list of ordered strong classifiers. Each strong classifier contains a set of weak classifiers. A weak classifier is defined by a sub-region of interest, the corresponding mean value of covariance descriptors of all positive samples and a regression function.

To train a level k of the cascade, a given number of weak classifiers are successively added. To add a weak classifier l to the current training classifier, 200 candidate weak classifiers are evaluated: 200 subwindows are randomly selected. Let r i be one of these subwindows and Ĉ j r i the corresponding normalized covariance descriptor on the sample j. For each subregion r i , the mean µ i of all the normalized covariance descriptors Ĉ j r i of the positive samples is computed using a gradient descent procedure described in [START_REF] Pennec | A riemannian framework for tensor computing[END_REF]. Using this mean µ i , all Ĉ j r i of all the samples are projected onto the tangent space using (8) obtaining vectors in Euclidean space. Using these vectors and the corresponding weights of all samples, a regression fucntion g i is computed.

The best weak classifier, which minimizes negative binomial log-likelihood (4), is added to the current training classifier. The weights and the probabilities of all the samples are updated according to the new added weak classifier. The positive and the negative samples are sorted in a decreasing order using their probabilities. The current strong classifier is concidered as fully trained if the difference between the probability of the (99.8%) th positive sample and the (35%) th negative sample is greater than 0.2.

In this case, the training of the current cascade level is achieved. The negative samples are tested with the new cascade and all correctly classified samples are removed from the training dataset. The next cascade level is trained using remaining negatives.

Main issues

The initial approach proposed by Tuzel et al. [START_REF] Tuzel | Human detection via classification on riemannian manifolds[END_REF] outperforme existing approaches of the state of the art by providing a lower rate of missdetections and false positives, but it has the disadvantage of being highly time consuming for the detection process and not applicable for real-time processing. In [START_REF] Tuzel | Human detection via classification on riemannian manifolds[END_REF], Tuzel et al. indicate that detection time on a 320 x 240 image is approximatively 3 seconds for a dense scan, with 3 pixel jumps vertically and horizontally. Note that training time is relatively long also (2 days in [START_REF] Tuzel | Human detection via classification on riemannian manifolds[END_REF]).

The most computationnally expensive operation during the training and the classification is eigenvalue decomposition. This decomposition is the basis of all operators in Sym + d . Eigenvalue decomposition of a symmetric d × d matrix requires O(d 3 ) arithmetic operations, so computing time increases quickly by using more features.

The feature subset selection approach, proposed by Yao and Odobez in [START_REF] Yao | Fast human detection from videos using covariance feature[END_REF] allows to work in a lower dimensional symmetric positive definite matrices, making eigenvalue decomposition faster and thereby improving all the training and classification processes.

We focus in our work on another way to make the classification faster while maintaining high classification performances. At the end, the obtained approach improve also the training stage.

Proposed Algorithm

Ordering negative training sample

Using large number of samples for the training process makes it very slow. Of course, the larger the training dataset is, the more performant the classifier cascade is. But most of the time, large number of negative samples contain very similar information. This problem is more frequent for the first cascade levels, where a new level is trained using false positives of previous levels. These false positives are generally resulting from successive small shifts of testing window on the image, providing very similar content.

One can suppose that using a smaller subset of randomly selected negative samples to train a given cascade level can be a good solution to speed up training. We can suppose that a randomly selected subset can be statistically representative of all remaining negatives.

We have tested this approach and we have observed that it effectively speeds up training and provides a lower number of cascade levels than [START_REF] Tuzel | Human detection via classification on riemannian manifolds[END_REF] but with longer classifiers (See Figure. 1,b), slowing down in comparison to the previous mentioned approaches. In fact, one cascade level consists of a set of weak classifiers. The response of one classifier is obtained after computing the output values of all its weak classifiers. It means than a long classifier containing a large number of weak classifiers takes more time to return a decision, so a cascade of long classifiers is very slow for detection.

The number of weak classifiers per cascade level depends mainly on the diversity of negative samples used for the training. The characterisation of positives and their separation from negativesl requires as many subregions of interest as the samples are diverse.

To illustrate the relationship between negative samples diversity and classifiers cascade structure, let us use a simple example which can be generalized to understand the concept. Suppose that we have to separate a person image from three non-person images: a sky image, a vertical barrier image and a lamppost image. Due to the poverty of texteures and gradiends on the sky image, a unique large covariance region is sufficient to separate the sky image from the person image, which has many gradients and a vertical shape. For vertical barriers, the previous region is not appropriate due to the vertical shape of the person. A smaller region around the person's head is more appropriate. The circular shape of the head provides a good separation. Now, for the lamppost, the two previous regions are not suitable. It is necessary to take a region on legs or around shoulders to encode curvatures. For this example, there are two methods to train the classifier. The first cascade is trained with one negative image at a time in the mentionned order. The second cascade is trained with the three negative images at the same time, using approriate parameters. The first method provides a cascade with three levels, each level containing one weak classifier corresopnding to one case (low texture level, vertical shapes only, circular shape at the top of vertical shape). The second method provides a cascade of a unique classifier containing three weak classifiers at least (the number can be larger du to the possible combinations).

Suppose now that we have to perform a people detection on a large image which contains only sky, a low textured road, some vertical barriers and some lampposts. Both cascades will provide equivalent detection performances, but the first one will be faster. This is because most of tested windows (sky and road) are rejected after evaluating only one covariance descriptor (the one of the first cascade level), while the second classifier cascade needs to evaluate three (or more) covariance descriptors for each tested window.

The average number of evaluated covariance descriptors using Tuzel et al. cascade (a) is 8.45 while the cascade in (b) needs more than 21 covariance descriptor evaluation.

We propose an approach using a shorter subset of negatives at each cascade level training to make it faster. Our approach provides shorter cascade with smaller classifiers on average (Figure.

Clustering on negative data

The idea consists in regrouping negative samples per groups containing similar contents in terms of covariance information, and train each cascade level by one group of similar samples. The previously described Logitboost algorithm achieves characterization of people against a group of negative samples faster when these negative samples are more similar. It also specialize each cascade level. This negative samples regrouping is achievd using clustering methods. We tried two methods to perform this clustering, the first one is applyed directely in Riemannian manifold while the second one is performed in the Euclidean space. A matrix containing the distances between all pairs of negative samples is computed. To compute the distance between two negative samples using covariance descriptors, each sample image is divided into a grid of 16 equal sub-regions. The final distance between the two samples is the sum of the 16 distances between each covariance descriptors pair using (7) (See Figure . 2). Once the distance matrix computed, a hierarchcal clustering is performed, providing a tree of negative samples (See Figure . 3)

Hierarchical clustering on covariance descriptors using covariance matrices distance

Clustering in projection space

The second clustering approach consists in projecting all negative samples to a tangent space. In this method, we use covariance descriptor of the whole image of each sample. The mean of all negative samples is computed and used to project all covariance descriptors to the Euclidean space. Finally Euclidean space, the clustering is performed using adaptive bandwidth mean shift filtering [START_REF] Comaniciu | Mean shift: A robust approach toward feature space analysis[END_REF]. (See Figure.

Train iteratively by each subset

After clustering, it is now possible to select the n most similar negatives samples. In the case of hierarchical clustering, we select first the cluster which contain n = 35 % of remaining negatives. we took this value according to Tuzel et al. parameters [START_REF] Tuzel | Human detection via classification on riemannian manifolds[END_REF], to have similar conditions and to be able to compare results. In the mean shift clustering on tangent space, we select the cluster containing the largest number of samples. This is motivated by the desire to eliminate the largest percentage of negative samples as soon as possible.

The training is now done by applying a clustering step on the negative samples, selecting the most similar negatives subset and use it for training. After achieving current level training, the new cascade is applyed to all the remaining negative samples, those used for training and the others. We observed that 80% to 95% of the negatives from the used subset are correctly classified and removed and a small part of unused negatives too.

The clustering is repeated on remaining negatives to train next levels.

Experimental Results

We conduct experiments on INRIA dataset to be able to compare our results with those of Tuzel et al. [START_REF] Tuzel | Human detection via classification on riemannian manifolds[END_REF].

The INRIA person dataset [START_REF] Dalal | Histograms of oriented gradients for human detection[END_REF] is devided to two subsets: a training set containing 2416 person annotations and 1218 person-free images and a test dataset with 1132 persons ans 453 person-free images. This dataset is quite challenging due to the various scenes, content, and persons appearence and poses.

Detection performances comparison

The detection performances were evaluated on two criteria: miss detection rate, given by The main consequence of this difference of structures is the detection time. Our cascade perform detection faster than the Tuzel el al. one. We have implemented both approaches with C++ and performed training and detection on an Intel(R) Core(TM) i7-920 Processor at 2.66-Ghz with 4Gbytes or RAM. The average time of detection on images of 320x240 is approximatively 2.3 seconds for Tuzel et al. while it is approximatively 0.5 seconds for our method.

In the same conditions, training time is also decreased by our approach. The training takes 22 hours for Tuzel et al. approach while it takes 9 hours for our approach.

Note finally that the clustering in tangent space provide better results for first cascade levels training, but after few levels, it becomes less precise. This can be explained by the fact that at the first level,negative samples are densly regrouped. The computed mean for tangent space projection is significant. After few level training, and removing correct classified negatives, the remaining negatives became sparse and computing a mean on sparse samples make it less signicative, the projection to tangent space is not suitable.

Conclusions

We have proposed an approach to optimize people detection using covariance descriptors. This approach consists in clustering negative data before training to obtain better classifier structure. The resulting detector is faster that original one and was trained in shorter time. The experimental results on a challenging dataset validate our approach.

Figure 1 :

 1 Figure 1: Comparison between structures of the cascade of classifiers: (a) Tuzel et al.(Tuzel et al., 2007); (b) trained with a random selection of negative subset; (c) our proposed approach: less cascade levels with less weak classifiers per level

Figure 2 :

 2 Figure 2: Used Squared distance computation between two negative samples for hierarchical clustering

  1, c ) in com-parison with the Tuzel et al. one (Figure. 1, a) making detection process faster. At the same time, the experimental results show that our approach provides similar detection performances than the original one.

Figure 3 :

 3 Figure 3: Hierarchical tree of clustered negative samples

Figure 4 :

 4 Figure 4: Clustering on tangent space

Figure 5 :

 5 Figure 5: Comparison with the methods of Dalal et al. (Dalal et al., 2006) and Tuzel et al. (Tuzel et al., 2007) on the INRIA data set.