Untitled Document

Review of model-based tools with regard to the interaction of water management and agriculture

Review of model-based tools with regard to the interaction of water management and agriculture

Harmoni-CA is a research project supported by the European Commission under the Fifth Framework Programme and contributing to the implementation of the Key Action "Sustainable Management and Quality of Water" within the Energy, Environment and Sustainable Development. EVK1-CT-2002-20003.

This report is the sole responsibility of the author(s) and does not represent the opinion of the European Commission, nor is the European Commission responsible for any use that might be made of the information appearing herein.

List of abbreviations.. VI
List of tables and figures.. VIII
Executive summary.. IX
1. Introduction.. 1
2. The Water Framework Directive and the Common Agricultural Policy.. 4
2.1 Water use and agriculture. 4
2.2 The Common Agricultural Policy reform... 8
2.3 The Water Framework Directive. 9
2.4 The CAP and the WFD.. 11
3. Categorisation of existing tools and models related to water and agriculture. 14
3.1 Agronomic tools. 15
3.2 Hydrology and water quality tools. 18
3.3 Land use and economic tools. 24
3.4 Web portal on water-related tools. 32
4.. Case studies: examples of good application.. 37
4.1 ARID cluster and WaterStrategyMan.. 37
4.2 The German Elbe River Basin case study.. 39
4.3 The case study of the Piave River Basin in Italy.. 40
5.. Conclusions.. 43
References.. 47

Annex 1: EU-funded projects related to water and agricultural modelling.. 54
Annex 2: The Common Agricultural Policy.. 56
Annex 3: Measures to implement the WFD and the CAP.. 59
Annex 4: Monetary valuation.. 61
Annex 5: A categorisation of tools and models for water management and agriculture 62

List of abbreviations [1]

List of tables and figures

Figure 1: Example of a conceptual model of water management in the agricultural system.. 6

Table 1: Gap between scientists, policy-makers and water managers. 2
Table 2: WFD policy objectives, agri-environmental instruments and possible effects on water and agriculture 12
Table 3: Examples of rules associated with nodes in a hydrological model 19
Table 4: European web portal, including toolbox for water 33
Table 5: Types of models used in SEAMLESS. 36
Table 6: EU-funded projects related to water and agricultural modelling. 55
Table 7: Good agricultural and environmental practice. 60
Table 8: Monetary valuation. 61
Table 9: Information sheet on agricultural and water related models. 63

Executive summary

This document is primarily directed at water and agricultural managers who wish to find out about agricultural policy reform and existing models and tools that support joint water and agricultural management processes. It may also be beneficial to water authorities, water irrigation and reclamation boards, farmers associations and NGOs. The goals of the document are manifold:

Interaction between the Common Agricultural Policy and the Water Framework Directive

Agriculture plays a central role in water management, since it is a significant utiliser of water resources in Europe, accounting for around 30% of total use. In southern Europe, water is a fundamental agricultural input, with irrigation accounting for over 50% of demand. Furthermore, agriculture and forestry, which cover more than three-quarters of the area of the European Union, play a key role in determining the rural economy and environmental quality. Environmental pressures due to agricultural activities, including water pollution, are often viewed as a serious problem in many areas.

Due to an agreement on the Mid-Term Review of the CAP reached in June 2003, the Common Agricultural Policy (CAP) has adopted a new model for European agriculture. This model reflects the multifunctional role played by farming, integrating economic viability, food safety, social balance and environmental concerns. The key elements of the reform, which completely changes the way in which the EU supports its farm sector, are: adoption of a single farm payment for EU farmers aid paid to producers will no longer be dependent on type of production, thus decoupling aid from, thus removing the causes of indirect environmental damage; enforcement of cross-compliance, which makes direct payments conditional on specific requirements; strengthening Rural Development (RD) policy, into which instruments directly concerned with environmental outcomes are inserted.

The WFD and RD policy both adopt planning processes. However, important differences arise between them, of which scale and time could cause major problems. Win-win situations for both policies require close attention in the implementation phase; representatives from different authorities should interact to create a common vision of agricultural and environmental problems.

This review focuses on over fifty available tools that have a wider application, have been developed and applied in the context of EU-funded projects, or that present specific aspects of interest to support the implementation of the WFD. To categorise and summarise these tools, a framework based on four critical dimensions (spatial scale, irrigation measures, agricultural measures and economic analysis) is adopted. The tools are categorised into three classes:

This review demonstrates how most tools tend to shift towards a new class, embracing holistic integrated Decision Support Systems (DSS). This follows the observed trend in modelling, which is changing from monodisciplinary to multidisciplinary approaches, in which several domains are integrated.

The non-exhaustive list can support the identification of models and tools to address specific issues, including the correct consideration of domains, scales and types of measures. A table in the annex summarises the relevant information and includes each tools website and contact details.

Further information is provided, referring interested readers to a dedicated web portal that offers comprehensive, shared European information, such as WISE, the Water Information System for Europe. Since innovation in computational technology will further enhance the frontier of modelling, web portals are a key instrument for water and agricultural managers to access updated information.

Three examples of good application are presented. The selected case studies have been carried out recently in different European water basins in the context of EU-funded projects. The projects are:

The case studies give an insight into relevant questions such as: How can tools improve transparency in decision-making? How can tools support water managers in their present tasks? How can various management options be compared in terms of their ecological, economic and social impact?

Models and tools to support the participatory implementation process of the WFD

The final section of the review explores considerations of how models and tools should be used to support the implementation process of the WFD.

Good practice in model application deserves continual attention. In fact, the credibility and impact of the information and insight that modelling aims to generate are highly dependent on the quality of the modelling exercise.

The political process-oriented nature of water management requires an adaptive approach, which should also consider how models and tools should be used. A multilevel approach in modelling is recommended. At a higher level, conceptual models can support the definition of a common conceptual framework for cross-disciplinary work involving authorities, managers, stakeholders and researchers. At lower levels, quantitative models can support specific analyses exploring the strength of interactions and the sensitivity of the system to changes. The information produced, clarifying the areas of greatest uncertainty and influence on system evolution under different assumptions, can help prioritise field research and support water and agricultural management. However, it cannot offer definitive solutions, since uncertainty and subjectivity are intrinsic to all decision processes, which tools can reduce but not eliminate.

Since water pollution caused by agricultural activities is not specific to irrigated agriculture, the design of policies capable of increasing water quality, while preserving the economic and social sustainability of agricultural systems, requires a clear understanding of the complex relation at different scales from the field/farm up to region catchments and basins. Such understanding can be favoured by a combination of existing tools used by multidisciplinary teams of well-trained people with adequate data in the participatory process.

The definition of packages of integrated measures addressing quality and quantity issues can be supported by tools. However, there is no general solution, since measures are case-dependent. Various tools include specific routines to support the economic analysis requested by the WFD in one or more of the addressed aspects, ranging from the economic analysis of water use, cost recovery and pricing schemes, up to the evaluation of benefits to the environment and society, and eventually of disproportionate cost. Nonetheless, the support provided by such tools is highly dependent on how they are used at present, it is incumbent on the Member States to decide how such analyses and valuations should be carried out; no common guidelines are defined.

The translation of the experience gained in research to the management domain will probably be a long process, in which support by the scientific community should be considered essential. In order to bridge the gap to real-world decision processes, the following recommendations are deemed important:

This report follows the 2^nd Policy Workshop of Harmoni-CA/WP5: Interaction of the Common Agricultural Policy and the Implementation of the Water Framework Directive at European and Regional Levels, which was held on 4-5 April 2005 in Brussels. The Harmoni-CA Document: HCA-WP5-2005-Re05/Final Version-Deliverable No. D 5.3.2 20.04.05 by Ilke Borowski and Johannes Heeb summarises: The workshop gave 30 agricultural and water managers from European, national and regional authorities the chance to get their hands on tools/models which may support their management activities during the implementation of the European Water Framework Directive and the Common Agricultural Policy. During the workshop an intensive exchange between the developers of the presented tools/models took place. Seven existing and easily accessible tools/models were presented and evaluated according to management questions which were defined by the participants with regard to the changing conditions under the WFD and the CAP. During the workshop the discussion of the seven presented tools/models showed that most of the tools/models can support the joint water and agricultural management processes in some regard. However there was no tool/model identified which was considered fully capable to sufficiently answer all questions raised by the policy makers with regards to the interaction of CAP and WFD. Also, no combination of the presented tools/models was able to do so. The main gaps of the tools/models were identified in terms of the general integration of different domains like water quality, quantity, ecology but especially of economic evaluation means (Borowski and Heeb, 2005, p. 3).

The report includes a to-do list for tool/model developers, which contains a summary of the demands identified during the workshop from the policy side:

The difficulties that model-based tools have in supporting practical water management are further explored in Borowski and Hare (2007).

The existing gap between scientists and policy-makers is confirmed by Mysiak et al. (2006) (see Table 1):

The present report offers a broader review on tools and models, addressing both water management and agricultural management issues. It also responds to the mission of Harmoni-CA/WP5 to establish and maintain dialogue between tool/model developers and policy-makers to improve the use of tools/models in management processes.

2.1 Water use and agriculture

Agriculture is a significant user of water resources in Europe, accounting for around 30% of total use. This is particularly true in the Mediterranean region (including Greece, Italy, Portugal and Spain), where irrigated agriculture, although it covers only 20-25% of the total cultivated surface, accounts for about 50% of total agricultural production and 45-81% of the total water demand[2].

Furthermore, agriculture and forestry, which cover over three-quarters of the area of the European Union, play a key role in determining the rural economy and the environment.

Agricultural systems changed radically in the second half of the previous century. Diversified evolution patterns emerged and unforeseen negative consequences developed over time. On the one side, specialisation of holdings took place in both livestock and arable sectors, based on farm enlargement and capital intensive farming methods, which exerted great pressure on the environment; on the other side, decline and abandonment occurred.

A variety of driving forces that underlie farmers management decisions influenced this process: technological development, changes in market conditions, alterations in the costs of labour, land and other factors of production, modification of the socio-cultural environment, structural changes and a range of different public policies, including the CAP itself.

In the market economy, the comparative profitability of farming, which is highly influenced by the CAP, forced farmers to pursue financial objectives. Consequentially, traditional practices were often abandoned in favour of intensive ones: the substitution of labour with capital and of organic with industrial inputs increased farm productivity at the cost of environmental sustainability. As a consequence, water pollution due to agricultural activities is often considered a serious problem in many areas.

However, agriculture is not a homogeneous sector. In most regions, farms that adopt intensive management practices exerting great environmental pressure coexist with others that are environmentally friendly. In many cases, the latter group is dwindling in size, although only marginally in economic terms. This implies the need for targeted interventions in order to focus on appropriate management at the farm level. This would lead to favouring long-term sustainability through the balanced development of rural areas.

Devising policies that are not only capable of reducing consumption and increasing water quality but also of preserving the economic and social sustainability of agricultural systems requires a clear understanding of the complex relation between water and agriculture. This task can be enhanced by constructing conceptual models that favour interdisciplinary dialogue and the definition of a common vision among experts, stakeholders and decision-makers. Estimating the effects of a policy measure requires the identification of the causal links between the implementation of the measure and its ultimate impact on human activities and the environment. A conceptual framework for examining such links can be found in the DPSIR (Driving forcePressureStateImpactResponse) approach proposed by the European Environment Agency (EEA) for the description of environmental pathways. In a policy-making context, this approach can help policy-makers to conceptualise and structure their decisions on potential alternative measures, according to the cause-effect relationships.

- Point and diffuse sources of pollution are connected with agriculture and farming, although they are not specific to irrigated agriculture; there is strong evidence that in many regions rain-fed agriculture and intensive animal breeding without land are the main causes of environmental impact, e.g. nitrates and other pollutants.

- Concerning agricultural irrigation, it is important to understand how farmers use water and make decisions in response to external stimuli. From an economic perspective, water is a production factor, which substantially enlarges farmers sets of choices in terms of available crops and processes (Ward and Michelsen, 2002). Irrigation has other important effects, such as the higher quality of production and risk reduction due to uncertain and unstable climate conditions, particularly for fruit, vegetables and other high-value crops. Furthermore, water enables farmers to standardise production over space and time, which is becoming a stringent market requirement, while the quantitative increase of production is merely a secondary effect.

- Water demand in agriculture is linked to agronomic factors (Doorenbos et al. 1979). On the one hand, crops have a different effect on evapotranspiration, resistance to stress and water/yield response. On the other hand, agricultural practices, cropping patterns and irrigation methods can significantly influence water requirements at the farm level and in terms of soil characteristics.

Figure 1: Example of a conceptual model of water management in the agricultural system

- Climatic conditions impact on water demand and availability in many ways. For instance, temperature influences plants evapotranspiration, water needs and rain distribution, and quantity is a key factor regarding water availability and water quality, since scarcity is generally linked to a higher concentration of pollutants in the resource.

- Economic factors operate at both macro and micro levels. At the macro level, the rate of growth of gross domestic product (GDP), the distribution of income in society and population growth are key drivers for demand in food, which can be differentiated into quality and quantity, and into perceptions of and the demands placed on the rural environment. For instance, demand for recreation in rural areas, and hence for environmental quality, is higher in rich societies where basic needs have already been satisfied. At the micro level, prices and costs at the farm level, which vary between crops and farms, as well as investment and operating costs for irrigation equipment influence farmers choices.

- Social and institutional factors play a central role in water management and should be considered with due care. All stakeholders represented by Farmers Unions, Water Users Associations, Water Authorities, Water Boards and NGOs should be involved in the participatory process of the implementing the WFD.

- Policy factors, which represent a response of society to impact, play a wide range of roles. There are many instruments that model water and agriculture (see section 2.2).

- Agriculture is a multifunctional activity that should be assessed in a multicriteria framework. Relevant dimensions are:

- the economic dimension: quantified at the micro level by the income produced by farm type and at the macro level by the contribution of the aggregate sector to GDP.

- the social dimension: represented not only by employment induced but also by the cultural aspects linked to rural life,

- the environmental dimension, which is particularly complex: positive and negative indirect effects are both present. On the one hand, positive externalities are that appreciated landscapes[3] depend on water availability in agriculture, biodiversity conservation and soil protection. On the other hand, soil erosion, soil and water pollution and subsidence sometimes pose serious problems.

- the dimension of food production: this traditional objective of agricultural activity still plays an important role. This needs to be assessed properly by considering the high value of European production with reference to food quality and safety, due to the strict rules enforced by the CAP. For example, genetically modified crops (GMO crops) cannot be cultivated due to precautionary principle; there are limits to pesticide concentrations on fruit and vegetables, which are much more stringent for organic farming, while imported crops and food do not follow the same requirements.

- Water distribution networks deserve specific attention. Many water distribution networks are old, operating under very poor conditions with low maintenance, if at all. In such cases, high losses (up to 50%) are frequent. Measures focusing on water management at the farm level cannot address this problem. However, water savings could be achieved by investing in infrastructure.

- Demand should be satisfied using water derived from legal sources, such as irrigation networks and authorised basins, drills and rivers. However, hidden sources are a real option in many situations. The use of hidden water as an alternative to legal sources is particularly relevant, considering that economic instruments (e.g. water prices, water quotas, etc.) can only be applied to the legal uses and the cost of enforcing an effective monitoring policy to reduce illegal behaviour could be extremely high.

- The groundwater recharge effects of agricultural irrigation are another critical issue to be considered. If water is not polluted, runoff and percolation are a positive externality. In such cases, the environmental benefits induced by an increase in irrigation efficiency (e.g. due to a shift from surface to sprinkler irrigation) or the reduction of irrigation itself may be questionable.

2.2 The Common Agricultural Policy reform

Since its establishment, the whole concept of the CAP and its method of operationalisation have greatly changed through successive reforms. The integration of environmental issues into other EU policies, such as the CAP, is part of a long process dating back to the 1980s. It is legally bound in the Treaty of the European Community (TEU): Environmental protection requirements must be integrated into the definition and the implementation of (all) the Community policies and activities in particular with a view to promoting sustainable development[4]. The Agreement on the Mid-Term Review of the CAP, reached in June 2003, gives form to a new European model for agriculture, reflecting the multifunctional[5] role that farming plays, and integrating economic viability, food safety, social balance and environmental concerns. The key elements of the reform, which completely changes the way in which the EU supports its farming sector, are:

1. Adoption of a Single Farm Payment (SFP) for EU farmers: aid paid to producers will no longer be dependent on type of production, thus decoupling it from or removing the causes of indirect environmental damage[6].

2. Introduction of a cross-compliance rule, which makes direct payments conditional on adherence to specific requirements[7].

3. Strengthening of the RD policy, in which instruments directly concerned with environmental outcomes are inserted[8].

The new more decentralised model of agricultural policy grants Member States greater freedom by reducing the risk of distorting competition or renationalising the CAP. The reform should secure multifunctional, sustainable and competitive agriculture throughout Europe[9].

2.3 The Water Framework Directive

The 2000/60/EC Directive, known as the Water Framework Directive (WFD), establishes a framework for common action in the field of water policy in Europe. Its main goal is to raise the water quality of nearly all bodies of water to a good status by 2015. The directive is an important element of European environmental policy.

In the 1990s, economic instruments were increasingly suggested and recommended to enhance the sustainability of the environment. They found their full legitimacy in the Rio Declaration on Environment and Development by the United Nations in 1992. The WFD has a similar emphasis. In fact, it calls for the application of economic principles, i.e. the polluter pays principle, and cost recovery for water services, with the inclusion of environmental and resource costs. The directive clearly recommends economic approaches and tools, and the consideration of economic instruments to achieve its environmental objectives in the most effective manner.

The WFD identifies a strict time schedule for key tasks aimed to develop and implement River Basin Management Plans (RBMP). Moreover, article 5 of the WFD requires that each Member State shall ensure that an economic analysis of water use is undertaken for each river basin district or part of an international river basin district falling within its territory, according to the technical specifications set out in Annexes II and III. This should be completed within four years of the Directive coming into force.

The principle of the cost recovery (Art. 9) of water services, including supply, environmental and resource costs[10] should be adopted in accordance with the polluter pays principle.

Furthermore, Art. 9 requires that Member States shall ensure by 2010 that water pricing policies provide adequate incentives for water users to use water resources efficiently, thereby contributing to the environmental objectives of the WFD.

Economic analysis can also justify derogation, including the designation of a water bodys status, (Art. 4) if disproportionate costs can be demonstrated. The affected groups ability to pay should be considered in the cost assessment.

What emerges from the previous articles is that different aspects are addressed, ranging from the economic analysis of water use, cost recovery and pricing schemes, to the evaluation of benefits to the environment and society, and eventually disproportionate costs.

The following activities, which involve economic components, should be undertaken in the implementation process:

The economic valuation of benefits is a challenging task, since benefits are many and very different in nature. A reduction of water treatment costs is a market benefit that can easily be valued. Since the goal of the WFD is to achieve higher water quality, which translates into more environmental services, many benefits are of a non-market nature. Non-market benefits could be linked to use, such as an increase in open-access recreation, but they may also be values that individuals simply relate to higher environmental quality.

Until now, Member States are left to operationalise the form of analyses and valuations. No common rules or methodologies have yet been defined. Hence, the Member States are free to adopt the procedure they wish to apply.

Finally, the WFD also requires an integrated participatory water resources policy, which high-quality computer-based tools could support.

2.4 The CAP and the WFD

Both the WFD and the RD adopt planning processes. However, important differences emerge, of which scale could pose a major problem: the WFD identifies River Basins (RB) as the proper planning scale, whereas the CAP follows a national/regional approach[11]. Win-win situations for both policies require that great attention is paid in the implementation phase. They also require representatives from different authorities to interact, in order for them to construct a common vision of agricultural and environmental problems.

The first column of Table 2 shows different policy objectives of the WFD: the quality objective identified in the good water status; the quantity objective related to a reduction in water demand and the economic objective related to the recovery of costs for services. Specific policy instruments are identified in the second column: some are compulsory and others are not, some belong to agricultural policy (A) and others to water policy (W), others still are a combination of both. The main effects are reported in the final column.

Table 2: WFD policy objectives, agri-environmental instruments and possible effects on water and agriculture

Many of the previous instruments require the definition of specific measures (for more detailed information on agricultural measures, see Annex 3). Many agricultural measures aim to wholly or partly improve or protect water quality (e.g. agricultural measures to reduce the use of pesticides and fertilizers) or water quantity (e.g. measures to reduce irrigation). Specific actions and measures could involve land use activities, requiring changes in land use and management (e.g. development of low-input farming systems, such as organic farming, changing from arable to grassland, investments to improve the state of irrigation infrastructure and allowing farmers to shift to improved irrigation techniques). Some instruments, such as buffer strips, crop diversity and rotation, are agronomic in nature; others, such as taxes on pollutant input, are economically-oriented.

Past experience suggests the adoption of an approach that combines schemes. Such an approach would integrate broad and shallow measures seeking widespread basic services with other narrow and deep measures that pursue clearly defined, more demanding, targeted benefits in particular priority areas.

When combined schemes are adopted, given the systemic nature of the environment, it is impossible to isolate the specific contribution of a specific measure to a given objective; instead, multicriteria valuation is used to identify the advantages and disadvantages of alternative schemes. The WFD requires that the cost-effectiveness of such alternatives should be considered, which implies rather complex economic analysis.

It is essential to integrate and coordinate between the two policies at the implementation level, in order to reduce or avoid the risk of conflict, and to take advantage of the potential of RD programmes to deliver the WFDs objectives. Future RD budgets suggest that some kind of prioritisation of objectives will be necessary, since funds are limited. On the other hand, close attention should be paid to the design of the RBMP, since it can also have a huge impact on RD. In this respect, the WFD comprises tools that can be used to mitigate conflicts: public participation, economic analyses and derogations. Alternatives should be considered when the most cost-effective measures involve disproportionate costs for rural communities, which could put the sustainability of agricultural activity at risk.

There are so many tools related to water and agriculture that it is virtually impossible to offer an exhaustive review. The approach adopted in this report is to focus on available tools that have a wider application, that have been developed and applied in the context of EU-funded projects or that provide specific aspects of interest to support the implementation of the WFD.

All of the investigated tools are summarised in the table shown in Annex 5, giving the following information: tool name, brief description, spatial scale, irrigation measures, agricultural measures, economic analysis, type of measures included, link to the tools website, contact details, further characterisations and previous applications.

To categorise and summarise the tools, we adopt a framework based on four critical dimensions: spatial scale, followed by the implementation of irrigation and agricultural measures, and concluding with an economic analysis.

To synthesise the highly inhomogeneous information from the previous four dimensions, we have adopted a simplified classification approach. The spatial scale represents the geographic unit of the tool in many cases, such a dimension is not unique; the predefined levels are: farm, catchment, sub-basin, basin, region, State and Europe. Two distinct dummies (YES/NO) identify the tools capability to analyse irrigation and agricultural measures. A three-position scale is adopted to classify the economic analysis; the code reflects the economic approach adopted in the tool: MI = micro economic, MA = macro economic, OA = other approach.

Tools can embed one or more models, which are a simplified representation of a system (or process or theory) intended to enhance our ability to understand, predict, and possibly control the behaviour of the system (Neelamkavil, 1988).

A few decades ago, tools were mainly monodisciplinary, used to describe relatively simple problems in specific domains of the economy, agronomy, ecology, hydrodynamics, groundwater or surface water quality. In the past decade, we gradually moved towards more multidisciplinary approaches to problem-solving, in which several domains are integrated.

Due to its demand to integrate groundwater, surface water, ecological and economic aspects of water management at the river basin scale (holistic approach), and due to the explicit requirement to study the impact of alternative measures (human interventions), the WFD seems to support this trend of exploiting more sophisticated, integrated models.

By following the adoption of the integrated water resources management paradigm, in which public participation is a key element, the WFD moreover explicitly calls for public participation and active stakeholder involvement in the process of water resources management, and hence also in the modelling process (Pahl-Wostl, 2002). There is widespread agreement that stakeholder involvement does not imply active participation in the technical modelling itself, but rather appears as a demand to be able to understand and review the various assumptions and their implications for the modelling results (Refsgaard et al. 2005).

The tools have been classified into three classes, considering the original core of the software:

Most tools, however, are developing towards a new class, embracing holistic integrated DS.

3.1 Agronomic tools

This group contains agronomic models to study crop yield response to water and chemicals, plant protection models and tools to support the process of feed planning and budgeting. The observed trend in this group of models and tools is also towards stronger integration.

Such tools are even more relevant in agriculture-intensive areas, where the environmental impact of rural development plans, manure and fertilizer management and of agrotechniques involving the use of agrochemicals can be assessed.

There are many versions of software available to model, and therefore predict, the agronomical, environmental and economic consequences of the complex interactions between crop management, soil and the atmosphere. Few of these guarantee a simple approach; most utilise complex relationships, e.g. models that allow the simulation of stochastic scenarios (Acutis et al., 2000; Peralta and Stckle, 2001), which can be useful in the estimation of probabilities associated with the occurrence of events. For further references, see: Donatelli et al., 1997; Johnsson et al., 2002; Lewis et al., 2003; Ten Berge et al., 2000; Wolf et al., 2003.

Many of these tools were developed in the United States of America. Examples include:

The EPIC Erosion Productivity Impact Calculator model (Williams 1990; Williams 1995) is a widely used simulation tool for agricultural policy analysis. The model, originally developed by the US Department of Agriculture (USDA), is now maintained by the Texas A&M Blacklands Research Center. EPIC is a field-scale model that can be adapted to a large range of crop rotations, management practices and environmental conditions. The model was designed to assess the impact of soil erosion on crop productivity (Williams, Jones, and Dyke 1984). The new version is called Environmental Policy Integrated Climate (Mitchell et al. 1996), reflecting the evolution of the tool. Exemplary applications include estimations of soil erosion from water and wind, and climate change impacts on crop yield and soil erosion. EPIC is also used as part of Agricultural Policy/Environmental eXtender APEX, a tool for managing whole farms or small watersheds to obtain maximum production efficiency and maintain environmental quality. Examples of its application include: terrace systems, grass waterways, strip cropping, buffer strips/vegetated filter strips, crop rotation, fertilizers, irrigation, liming, furrow diking, drainage and waste management (feed yards, dairies with or without lagoons).

Another interesting tool is CropSyst (Stckle et al., 2003), which is a cropping system simulation model, distributed free of charge. The model was developed as an analytic tool to study the effect of cropping system management on productivity and the environment. The model simulates the soil water budget, the soil-plant nitrogen budget, crop canopy and root growth, dry matter production, yield, residue production and decomposition and erosion. Management options include: cultivar selection, crop rotation (including fallow years), irrigation, nitrogen fertilization, tillage operations and residue management. A link to economic and risk analysis models is under development. Four input data files are required to run CropSyst: location, soil, crop and management files. The separation of files makes it easier to link CropSyst simulations to Geographical Information System (GIS)[12] software. CropSyst provides a platform for simulating crop rotations, an automatic management events scheduler and the possibility to run multiple simulations in connection with a GIS. All these characteristics make CropSyst ideal for scenario simulations; other models simulate crop growth processes with more detail but have lower or no flexibility in specifying routine management techniques.

CREAMS Chemicals, runoff and erosion from agricultural management systems is a field-scale model for predicting runoff, erosion and chemical transport from agricultural management systems. It is applicable to field-sized areas.

GLEAMS, Groundwater Loading Effects of Agricultural Management Systems, can simulate edge-of-field and bottom-of-root-zone loadings of water, sediment, pesticides and plant nutrients from complex climate-soil-management interactions. The tool provides estimates of the impact of management systems (e.g. planting dates, cropping systems, irrigation scheduling and tillage operations) on the potential for chemical movement. GLEAMS can be useful in long-term simulations for pesticide screening in soil/management. It can track the movement of pesticides with percolated water, runoff and sediment. The upward movement of pesticides and plant uptake are simulated with evaporation and transpiration. Degradation into metabolites is also simulated for compounds that have potentially toxic bi-products. Erosion in overland flow areas is estimated using a modified Universal Soil Loss Equation. Erosion in chemicals and deposition in temporary impoundments, such as tile outlet terraces, are used to determine sediment yield at the edge of the field[13].

AGNPS, the Agricultural Non-Point Source Pollution Model, is a computer model developed jointly by the USDA Agricultural Research Service and the Natural Resources Conservation Service to predict non-point source pollutant loads within agricultural watersheds.

The Agricultural Production System Simulator, or APSIM, is another well-known tool to simulate biophysical processes in farming systems. The tool, developed in Australia by the Commonwealth Scientific and Industrial Research Organisation (CSIRO), integrates models derived from fragmented research efforts, enabling comparisons to be made on a common platform. The system includes plant, soil and management modules. These modules consider a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH[14], erosion and a full range of management controls. APSIM resulted from a need for tools that provide accurate predictions of crop production in relation to climate, genotype, soil and management, while addressing long-term resource management issues. It relates to the economic and ecological outcomes of management practices in the face of climate risk.

MicroLEIS DSS, A Land Evaluation Decision Support System for Agricultural Soil Protection, is a computer-based set of tools for the orderly arrangement and practical interpretation of land resources/agricultural management data, developed and applied in Spain. The DSS is an agro-ecological system. Its major characteristics are: data and knowledge engineering through the use of a variety of databases and innovative modelling techniques; the scaling-up of process knowledge from the micro scale to the landscape scale; land evaluation; use of monthly meteorological data and standard information; an integrated agro-ecological approach, combining biophysical data with agricultural management experience; software development for PC platforms, web- and GIS-based versions.

CROPWAT is a Decision Support System (DSS) used for irrigation planning and management, developed by the Land and Water Development Division of the FAO. It is intended to be a practical tool to help agro-meteorologists, agronomists and irrigation engineers perform standard calculations for evapotranspiration and crop water use studies and, more specifically, to devise and manage irrigation schemes. It allows the assessment of production under rain-fed conditions or deficit irrigation. Standard crop data are included in the program, and climatic data can be obtained for 144 countries through the CLIMWAT database. CLIMWAT is a climatic database that can be used in combination with the computer program CROPWAT. It allows the immediate calculation of crop water requirements, irrigation supply and irrigation scheduling for various crops for a range of climatological stations worldwide.

SIMIS, the Scheme Irrigation Management Information System, is a tool designed to facilitate the management tasks of irrigation schemes. This program, developed by the FAO, is not limited to water aspects, but covers all major issues of day-to-day management activities, including the control of maintenance, accounting, water fees and other relevant tasks. FAO advice states that SIMIS should no longer be supported.

The creation of web systems to promote the dissemination of agronomic information is a promising element to support resource management. Unfortunately, however, the following interesting applications do not have an English version:

PlanteInfo is an information and decision support system for farmers and agricultural advisers, developed and applied in Denmark. Most of the information is generated dynamically with models using frequently updated databases. A subscription system enables personalised information to be accessed. For example, since the geographic location of a user's home is known after login, local weather data are used for model calculations. PlanteInfo can store users previously entered information, such as fields, crops and actions, for future use. PlanteInfo also has a public version, which contains the facilities visible in the menu.

IRRINET is an example of agrometeorology that integrates data from different sources, up to personalised, guided irrigation scheduling for farmers. Guided irrigation scheduling is based on water balance models at the plot level, based on local weather data and information on specific agro-techniques. The service has been employed in Northern Italy since 1985, and yields an average 20% reduction in water consumption.

3.2 Hydrology and water quality tools

Models describing water flows, water quality and ecology are being developed and applied in increasing number and variety. The observed trend in the past decade is towards increasingly sophisticated computerised systems, integrating watershed processes that operate at different spatial and temporal scales, simulation models and decision-making approaches.

These tools have been developed for a variety of purposes, such as the prevention of water shortages (drought), surpluses (floods) and water impairment (pollution). The complexity of model-based water management has extended even further, as integrated system dynamics and stochastic simulations models, known as ecohydrological models, represent the state of the art of formal modelling (Reca, 2001). Ecohydrology combines the study of hydrological, biogeochemical and ecological processes and their interrelations in soil and water bodies. This type of model for a river catchment contains a hydrological module as its basic element and a vegetation sub-model, which usually includes further sub-models for biogeochemical cycles (carbon, nitrogen, phosphorus) with an appreciable level of complexity. The previous sub-models are usually combined to include interaction and feedback between processes, such as water and nutrient drivers for plant growth, water transpiration by plants, nutrient transport with water, etc.

Many earlier tools adopted nodal network approaches, which are a common framework for considering water allocation problems (see, for example, McKinney et al., 1999; Rosegrant et al., 2000; Merritt et al., 2004; Letcher et al., in press; Jakeman and Letcher, 2003; Fedra and Jamieson, 1996). In this type of model framework, a river basin is represented as a series of nodes. Nodes represent points where extraction and other activities that impact the stream are aggregated and modelled for a region. Regions refer to land or users attached to a node. Depending on the problem addressed by the model, regions may be defined by physical boundaries (e.g. sub-catchment areas) or by social, economic, technical and political boundaries. One example of this type of boundary is the property areas of irrigators who extract along a reach of a stream between two nodes. Flows are generally routed from upstream nodes to downstream nodes. Thus the impact of upstream land and water use activities on downstream users is modelled.

Examples of rules associated with nodes in a hydrological model are given in Table 3:

The reliability of process-based models, their flexibility and level of integration have improved in the past decade (Krysanova et al., 2005; Quinn et al., 2004; Hattermann et al., 2004; He, 2003; Krysanova, Hattermann, Wechsung, in press).

The United States Environmental Protection Agency (USEPA) supports and recommends that state and federal agencies use a set of models available within a framework called Better Assessment Science Integrating Point and Non-point Sources (BASINS). Created in 1996 with subsequent releases in 1998, 2001, and 2004, the tool is a multipurpose environmental analysis system designed for use by agencies to conduct watershed and water quality-based studies. BASINS integrates environmental data, analytical tools and modelling programs to support the development of cost-effective approaches to watershed management and environmental protection, including Total Maximum Daily Loads (TMDLs).

BASINS 4.0 and BASINS 3.1 represent two co-existing versions. In BASINs 3.1, the watershed loading/water quality embedded model is the Soil Water Assessment Tool (SWAT) (Arnold et al., 1993; Di Luzio et al., 2002), developed by the United States Department of Agriculture-Agriculture Research Service (USDA-ARS). The SWAT model was created in an attempt to simulate processes as physically and realistically as possible. Most of the model inputs are physically based (that is, based on readily available information). It is important to note that SWAT is not a parametric model with a formal optimisation procedure (as part of the calibration process) to fit any data. Instead, a few important variables that are not well defined physically, such as the runoff curve number and Universal Soil Loss Equation (USLE) cover and the management factor (such as the C factor, which quantifies the vulnerability of specific land use to water erosion), can be adjusted to provide a better fit. SWAT has been applied in numerous hydrological and/or non-point source pollution studies (http:// www.brc.tamus.edu/swat/swat-peer-reviewed.pdf), including in Europe.

BASINS 4.0 uses an open source GIS software architecture, which can easily be shared with other GIS software. BASINS 4.0 includes all of the functionalities of BASINS 3.1, except the AGWA[15] and SWAT models. Furthermore, it has the ability to quickly develop and create "plug-in" functions to update or enhance the watershed analysis process and monitor the environment. Both tools adopt QUAL2K, the River and Stream Water Quality Model, as their water quality model.

MIKE BASIN (MB) is a commercial, versatile GIS-based water resource and environmental modelling package produce by DHI[16]. It provides a simple, yet powerful framework for managers and stakeholders to address multi-sectoral allocation and discharge issues in a river basin. MB represents all elements of water resource modelling: users, reservoirs, hydropower, surface water, groundwater, rainfall-runoff and water quality[17]. By default, MB aims to study water allocation within a basin; however, a water quality option and a module for simulating groundwater can also be selected. The first step in setting up a river basin model is to define an underlying model river network upon which the node references can be based. Overlays with other features used in ArcView outside MB can also be performed, e.g. shaping files of river systems, thematic maps, etc. Water demand as processes/activities (irrigation area and public/industrial water supply) can be incorporated into the model. The model allows users to define the priorities of river diversions and water extractions (water rights) from multiple reservoir systems, as well as priorities for water allocation to multiple usages from individual extraction points. The model output comprises information on the performance of each individual reservoir and irrigation scheme within the entire simulation period, illustrating the magnitude and frequency of water shortages. The Groundwater module consists of a simple physical model of an aquifer, which is conceptualised as a linear reservoir that exchanges water with water users and surface water bodies. Water balance is analysed according to pumping, recharge, seepage from rivers and discharge to rivers. The first three are assigned by the user as time series. Furthermore, time series of river flow at all nodes are simulated, enabling users to determine the combined impact of selected schemes on river flows. In order to tailor MB to the requirements of the WFD, attributes for representing the range of treatment options at all point sources are currently being incorporated, and the model itself has been extended by a water quality module. The soil erosion assessment module uses two well-known methods for simple source erosion assessments: the Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE). Non-point pollution, including N and P-pollution from mainly agricultural areas, may be simulated in different ways at a more advanced level using the Daisy model.

RIBASIM River Basin Simulation Model is a generic model package to analyse the behaviour of river basins under various hydrological conditions, produced by Delft Hydraulics. The software includes a graphical user interface, a database, a simulation program and a tool for the analysis of results. The model package is a comprehensive, flexible tool that links the hydrological water inputs at various locations to specific water users in the basin. The tool describes a basin in terms of water sources and uses. It performs simulations of water allocation along a certain time horizon. It can be useful to identify possible water use conflicts between different types of users, such as farmers or industries, to study the sustainable development of the river basin itself and to plan adequate measures to solve conflicts or generally improve the status of the water resource.

WaterWare, Water Resources Management Information System, is an integrated, model-based information and decision support system for water resources management. WaterWare Release 5.1 is fully accessible from the internet. This DSS can address a wide range of issues, such as: determining the limits of development; evaluating the impact of new environmental legislation; deciding what, where and when new resources should be developed; assessing the environmental impact of water-related development; formulating strategies for river and groundwater pollution-control schemes, etc. The tool supports the integration of databases, GIS, simulation models, optimisation models and analytical tools into a common, easy-to-use framework.

SWIM, the Soil and Water Integrated Model, is a simulation tool for hydrological cycles, erosion, vegetation growth and nutrient transport in watershed at the meso scale, developed in Germany. The aim of SWIM is to analyse climate change and the impact of land use change on hydrology and water quality at the regional scale. The tool is based on two previously developed models, SWAT (Arnold et al., 1993) and MATSALU, which is a system of four coupled models developed for the Matsalu Bay watershed in Estonia (Krysanova et al., 1989). SWIM includes modules from both predecessors, endeavouring to combine their advantages (hydrological submodel and GRASS interface from SWAT; spatial disaggregation scheme and nutrient modules from MATSALU), and to avoid over parameterisation. A simplified EPIC approach (Williams et al., 1984) is used to simulate all crops and natural vegetation, using parameter values for each plant type from the database.

SPAW, Soil-Plant-Air-Water, simulates the daily hydrology of agricultural fields and ponds, including wetlands, lagoons and reservoirs. The objective of the SPAW model is to understand and predict agricultural hydrology and its interaction with soils and crop production, without the undue burden of computation time and input details. Field hydrology is represented by daily climatic descriptions of rainfall, temperature and evaporation; a layered soil profile with automated water characteristics; annual crop growth; and management with crop rotation and irrigation. Pond, lagoon and wetland simulations that have agricultural watershed fields or producer operations as their water source provide daily inundation levels, controlled by multiple input and depletion processes. Data input and file selection are by graphical screens. Simulation results are both tabular and graphical. Typical applications include analyses of crop water status, deep seepage, wetland inundation duration and frequency, lagoon designs and water supply reservoir reliability.

SWIM, Soil Water Infiltration and Movement, is a tool for simulating the infiltration, evapotranspiration and redistribution of water, developed by CSIRO Land and Water in Australia. The overall purpose of the model is to address issues relating to the soil water and solute balance. As such, it is a research tool that can be integrated into laboratory and field studies concerned with soil water and solute transport. It is also eminently suitable for management and education.

In the Netherlands, the RIZA (Rijksinstituut voor Integraal Zoetwaterbeheer en Afvalwaterbehandeling) has developed a set of coherent models to support the policy management of groundwater resources in the country. These models compute the hydrological effects of interventions on saturated and unsaturated zones, as well as the effects on agriculture, drinking water supply and nature.

LEACHM, the Leaching Estimation and Chemistry Model, is a suite of simulation models describing the water and chemical regime in the soil root zone, developed and applied in Australia. The suite consists of four simulation models and several utilities. The simulation models utilise numerical solution schemes to simulate vertical water and chemical movement. They differ in their description of chemical equilibrium, transformation and degradation pathways. Water regimes, pesticides, nitrogen and phosphorus and salinity in calcareous soils are simulated.

Ecohydrological models are highly relevant to studying the impact of agricultural on water systems. For instance, they can be used to quantify diffuse losses of N and P. The EU-funded project EUROHARP compared nine different methodologies and created a total of 17 study catchments across gradients in European climate, soils, topography, hydrology and land use. These methodologies are applicable at the catchment scale and are currently used by European research institutes to inform policy-makers at national and international levels.

Low Flows 2000 is a catchment-based water resource decision support tool for the United Kingdom. It is a decision support tool designed to estimate river flows at ungauged sites and to support the development of catchment and regional water resources. It is the standard software system used by the Environment Agency and the Scottish Environment Protection Agency to provide estimates of river flows, as represented by annual and monthly flow duration statistics, for any river reach in the UK.

NIRAMS, the Nitrogen Risk Assessment Model for Scotland, is a GIS-based model to calculate losses of nitrogen from diffuse pollution. Estimates of annual residual N (by crop) are leached to surface and groundwaters by hydrological flows and routed to the stream system. The system uses nationally available data sets on land use, soils, topography and meteorology. It was developed within the ArcView GIS. The model was delivered to the Scottish Executive Environment and Rural Affairs Department and the Scottish Environmental Protection Agency.

NL-CAT, Nutrient Losses at catchment scale, is a tool capable of simulating phosphorus and nitrogen losses in both the soil and surface water, developed and applied in the Netherlands to replace the previous model stone (Wolf et al., 2003). The model chain was constructed to evaluate the impact of different types of measures on the improvement of the surface water quality at the catchment scale. The surface water model consists of the two important key components, the Soil Water Atmosphere Plant (SWAP) and the Agricultural NItrogen Model (ANIMO), in combination with a surface water quantity and quality module. The SWAP module generates hydrological input to the ANIMO module, and simulates the nutrient cycle in soil and the nutrient leaching to groundwater and surface waters. Surface water discharges are simulated by a specific module, while simulation of surface water quality processes and retention within a (large) catchment is performed by the nutrient cycles in small surface waters (NUSWALITE) module. An erosion module based on the modified and revised Universal Soil Loss Equations is implemented in a GIS environment. NL-CAT is capable of simulating phosphorus and nitrogen losses in both the soil and surface water.

DRIPS, Drainage runoff input of pesticides in surface water, is a GIS-based DSS, developed on behalf of the German EPA (Environmental Protection Agency/Umweltbundesamt) for the exposure assessment of agriculturally used pesticides in surface waters. The tool estimates the quantity of pesticide input from non-point sources via surface runoff, tile drainage and spraydrift. Furthermore, the resulting predicted environmental concentration of pesticides in surface waters (PECsw) can be calculated, considering the mean daily inputs of substances into river basins, characterised by their daily discharge. A graphical user interface (GUI) was created to provide users of the DSS with easy access to the models algorithms. Model parameters can be modified by users in order to generate customised scenarios, predicting PECs for a choice of field crops, orchards or vineyards. Results are available as grid cell maps for the territory of Germany. The model aims to enable users to predict expected pesticide concentrations in river basins, thereby creating estimates of the probability of a quality target being exceeded. The results, illustrated in maps, can be used to identify hot spots of diffuse pesticide input. The water management industry can base its own measurements on these findings (Rpke, Bach and Frede, 2004).

TRK is a tool developed in Sweden for nitrogen (N) and phosphorus (P) gross and net load calculations, retention and source apportionment. The TRK system supports calculations of concentration and area losses of diffuse sources (for N from arable land using the dynamic soil profile model SOILNDB), calculations of the water balance (using the distributed dynamic HBV[18] model) and N transport and retention processes in water (using the HBV-N model). The results are presented in the GIS, and source apportionment is carried out for each sub-basin as well as for whole river basins. Results from the system have been used for international reports on transport to the sea, the assessment of the reduction of the anthropogenic load on the sea and for guidance on effective measures to reduce the load on the sea at the national scale. The tool is applied in Nordic countries and Sweden.

WetSpa, Water and Energy Transfer between Soil, Plants and Atmosphere, is a GIS-based hydrologic model that simulates hydrological processes continuously, both in space and time. Its aim is to simulate the hydrological behaviour of catchments with regard to flood prediction, land use and climate change scenario analysis and water management. The pollutant transport module aims to simulate the transport of phosphorus through a catchment. Domains covered include hydrology, land use, climate change, water management and phosphorus transport.

EMS-I Environmental Modeling System Inc, including the Groundwater Modeling System (GMS software), Surface-water Modeling System (SMS software), and Watershed Modeling System (WMS software). For further information, see: http://www.ems-i.com/index.html.

BOSS International offers hydrology and hydraulics software - http://www.bossintl.com/.

3.3 Land use and economic tools

Another important group is represented by spatial models, where integration is again the paradigm. Integration of economic and ecological information in a spatial context is recognised as a valuable approach for strategic policy development and decision-making (e.g. Tiwari et al., 1999). Several conceptual frameworks encompassing the science, methods of capturing data and responses, and the human-biophysical dimension of problems have recently become the focal point of interdisciplinary research and analysis.

Lambin et al. (2000) categorise land use (LU) and land cover change (LC) models into five classes:

1. Empirical-statistical: uses multivariate statistical analyses of relevant factors to identify the causes/drivers of LU change. This type of model suffers from obvious limitations, since there is no reason why any statistically identified set of LC factors will apply robustly (or at all) outside the region or space/time slice from which they were identified.

2. Stochastic: a transition matrix quantifying probability describes how different LU types change from one to another. Since probabilities are determined from an analysis of the past, they can suffer from the empirical problems of a lack of robustness/generality, and of modelling data rather than the world.

3. Optimisation: LU change is modelled as a process, whereby one measure is optimised (e.g. income per unit land). The approach assumes that actors behave rationally and are in search of the best solution.

4. Dynamic process-based: a more complex type of model that uses representations of social, economic and biophysical processes to simulate LC. Such complexity can require substantial effort to develop, verify and validate the data. However, the models can overcome the problems of previous approaches, and provide more insight.

5. Integrated: this type of model combines the characteristics of the above four categories.

In recent years, there has been a rapid expansion of interest and research into spatial decision support systems (SDSS), to which all the previous methods are applied. To varying degrees, these approaches attempt to

- deliver outputs as spatial data that define biophysical, economic and social constraints;

- use new methods to translate factor layers into standardised inputs for problem criteria definition;

The consideration of socioeconomic decisions and impact components requires the inclusion of decision models that need to represent the key land use, water use and management decisions made in the catchments, e.g. agricultural production decisions, industrial and urban water use decisions, reforestation and urbanisation decisions. The specific decisions to be simulated and the types of models used to represent these decisions will depend on the spatial and temporal scales at which these decisions are to be modelled as well as on the types of activities present in the catchments. For example, even where extractive uses such as irrigation direct from the stream are considered, this decision may be modelled differently depending on whether the decision is posed as a short-run decision, considering capital to be constrained, or a long-run decision where capital investment decisions are included in the model. Additionally for some issues a representative farm model, simulating decisions by an individual farm, may be used, whereas for larger scale studies, or studies where trade-offs between different industry users are to be considered, aggregated regional production models may be used. In either case, it is the relevant land and water use decisions that are being represented. Letcher et al. (in press).

A key element is the separation of the economic theory into two branches: macro and micro.

Macroeconomics is the study of aggregated variables addressing the state of the whole economy. The focus is on price levels, employment levels, economic output in real and monetary terms, the quantity of money in the economy, overall consumption, savings, investment, wage levels, etc. The aim is to provide an insight into guiding the formation of economic policy. The following tools implement macro-economic theory in operational models:

AGLINK is a multi-country and commodity dynamic model of world agriculture, developed by the OECD Secretariat in close co-operation with its Member States. The overall design of the model focuses primarily on the potential medium-term influence of agricultural policy on agricultural markets. AGLINK is a partial equilibrium model, primarily of major OECD commodity markets. AGLINK estimates supply, demand and prices. Non-agricultural sectors are not modelled, and are treated as exogenous to the model. Since 2004, this modelling system has been enhanced by the FAOs development of the COmmodity SImulation Model (COSIMO), which represents agricultural sectors in a large number of developing countries. The AGLINK-COSIMO modelling system is currently one of the most comprehensive partial equilibrium models for global agriculture. The model is one of the tools used in the generation of baseline projections underlying the OECD-FAO Agricultural Outlook.

CAPRI the Common Agricultural Policy Regional Impact Analysis is an agricultural sector model covering both the whole of EU27 and Norway at the regional level (250 regions) and global agricultural markets. The following environmental indicators are covered by CAPRI: balances for N, P and K; emissions of ammonia, methane and N2O; global warming potentials. CAPRI users work in research institutions and EU Commission services.

WATSIM the World Agricultural Trade Simulation Model is a recursive-dynamic, spatial world trade model for agricultural commodities. In its current version, it covers 12 regions and 29 commodities. Simulations run from the year 2000 to 2010. Policies covered are ad-valorem and specific tariffs, tariff rate quotas (TRQs), safeguards (flexible tariffs), export subsidies and production quotas. These policies are explicitly modelled by formulating the model as an MCP (mixed complementarity problem). The most important application of WATSIM is the medium-term analysis of trade policy changes.

GTAP The Global Trade Analysis Project is one of the most relevant projects in this field. GTAP is a global network of researchers and policy-makers who are conducting a quantitative analysis of international policy issues with the goal of improving the quality of the quantitative analysis of global economic issues within an economy-wide framework.

Micro-economics explores economic agents, in this case farmers, and their behaviour and interrelation. The interpretation of a systems behaviour is an important classification criteria:

Neoclassical economic theory describes decision-makers (e.g. farmers) as income maximisers, which implies a homogeneity assumption in preferences (Varela-Ortega et al., 1998; Iglesias et al., 2004).

In an alternative multicriteria (MC) perspective, the farmers decision-making processes are simultaneously driven by various attributes related to economic, social, cultural and natural dimensions (Amador et. al, 1998; Romero, 1989). Such attributes include the maximisation of income, the minimisation of risk, the maximisation of leisure time, the minimisation of managerial problems, etc. (Sumpsi et al. 1996). A decision-maker tries to satisfy all these criteria at the same time, and the choice is a compromise reached despite conflicting objectives (Berbel and Rodriguez, 1998; Gomez-Limn et al., 2002).

Other approaches follow a systems behaviour paradigm, including: agent-based modelling, cellular automata and related models that focus on complex spatial interactions; network theory and dynamical systems.

The previous approaches are adopted by different tools working at the micro scale, where a farm model describes the production possibilities (e.g. agricultural practices and management options) by engineering production functions that follow an approach, known as the primal representation of technology. With this approach, inputs and outputs including externalities are expressed in physical terms. This implies the possibility to measure and evaluate the effects of different sources of change on the environment as well as on the socio-economic dimension. The approach allows changes in soil and irrigation management practices, changes in the use of farm input and natural resources, and how agri-environmental measures and environmental regulations may constrain actions taken by farmers (Yaron and Dinar, 1982; Flichman et al., 1995; Doppler et al., 2002; Iglesias et al., 2003; Yang et al., 2003; Bazzani et al., 2005). An alternative approach is positive mathematical programming (PMP), which derives unknown production functions from observed choices through the statistical calibration of the model (Howitt, 2001). PMP has generated numerous applications and extensions at different investigation levels, several of which are reported in Heckelei and Britz (2005).

The EU WADI project (The sustainability of European irrigated agriculture under Water Directive and Agenda 2000) is a recent example of economic modelling in agriculture to analyse the sustainability of irrigated agriculture in Europe in the context of post-Agenda 2000 CAP Reform and of the Water Framework Directive (website: http://www.uco.es/grupos/wadi/). The research, conducted in five European countries, adopts a MC model-based approach, focusing on representative farms. Scenarios are used to anticipate the possible future state, related to macro-economic and institutional conditions. Irrigated agriculture is assessed in terms of sustainability, taking into account the multi-functional dimension. A set of indicators offers an insight into economic, social and environmental dimensions. The agricultural model is composed of a collection of microeconomic mathematical programming models, each representing the optimising farmers behaviour at the farm level. Simulation results are aggregated according to farm localisation, type and size at higher territorial levels. The conclusion of the WADI project deserves attention: Future demands for agricultural economists and operational researchers imply a demand for models capable of generating detailed microanalyses based upon diversity in farming systems. Such diversity appears to be greater than ever, as conventional agriculture faces up to organic farming, and as various technologies (GMOs, etc.) compete for consumer markets; global equilibrium may not reflect diversity in the adaptation of strategies and the impact of measures. For this reason, we need to encourage the development and adoption of simple models of irrigated agriculture that are capable of simulating changing policy scenarios and measuring the impact of such changes on social, economic and environmental indicators. Agricultural economic models may help us to understand the value and cost of water and the multiple links between uses, consumption and pollution, by simulating the way in which these aspects are connected through the farming systems and their adaptation to external scenarios modelling can support the definition of institutional measures that will facilitate the achievement of objectives (e.g. markets, quotas, economic support), by identifying incentive-and institutionally compatible alternatives and supporting their choice through simulations Models could play a major role in the analysis and management of conflict of water use as well as in the analysis of the potential benefits of cost-sharing. Berbel (2004) pg. 217.

A recent contribution analyses the implications and applications for the European WFD of hydro-economic modelling in river basin management (Heinz et al., 2007). Four main applications are discussed:

To support policy, the socio-economic sub-system needs to include a component that describes the relevant social and economic impact of change in other system components, such as the impact on farm income and employment. In some cases, local impacts are aggregated and transferred to a higher scale model to assess the impact on the regional economy. Again, the scale and range of impacts to be considered dictates the type of modelling approach used. The choice (and subsequent implementation of the chosen option) represents the final phase of the decision-making process. This stage can be supported by multi-criteria decision analysis (MCDA). Once the criteria for evaluation have been determined, options can be compared and assessed against their expected impacts using Multi-Criteria Analysis (MCA) evaluation techniques.

The European school of MCDA (Roy, 1996) has created extensive literature and diverse methodologies for the application of MCDA, including the ELECTRE[19] family. Alternative approaches to MCDA are the Analytical Hierarchy Process (AHP) (Saaty, 1980) on the one hand, and an array of cognitive methods on the other. These approaches address the decision-making process in detail, and deal with a limited, clearly defined set of alternatives[20].

Many computer-based approaches have been developed to deliver MCDA, or elements thereof, in a range of forms, e.g. MACBETH[21], Intelligent Decision System IDS[22] routines in IDRISI[23] or MULINO-DSS, and more recently in NetSyMod (Network Analysis - Creative System Modelling - Decision Support), which is an operational tool that aims to support and guide decision-makers at each step of the overall decision-making process, from problem conceptualisation to the choice of the best policy to solve it.

Many existing tools have added socio-economic modules to their environment, and economic studies have also ensued (see: Ward et al., 1996; Rosegrant e al., 2000; Cai and Rosegrant, 2004; Reimund et al., in press). Examples include:

The Decision Support for Irrigation (DSIrr) is a support tool for scenario analysis using simulation approaches and bio-economic optimisation models. Scenarios evaluate a full range of water development and management options, taking account of multiple and competing uses of water. Scenarios can also describe agricultural policy or other exogenous drivers. A multi-scale modelling approach is adopted, and different types of farms can be aggregated to create a model network. The individual models are specialised to address specific questions and reflect heterogeneity between farms. Farm preferences can be described using a multi-attribute approach. Changes in irrigation and farm practices are considered. Standard procedures assess the impact of alternative water pricing schemes and of reduction in water allotment. The tool allows the CAP to be simulated, including decoupling subsidies, eco-conditionality and agri-environmental measures. However, case-by-case implementation is required. A set of indicators is quantified to assess socio-economic and environmental impacts at farm and regional levels. The tool, which was developed and applied in Italy, can easily be linked to other models.

FARMIS assesses the impact of the Mid-term Review policy reform on German agriculture by simulation approaches and optimisation models based on the Farm Accountancy Data Network (FADN)[24]. The model network includes different models that are updated and combined with each other as necessary. The individual models are specialised to address specific questions (for example, regional impacts, farm impacts, market impacts). Comparative-static analysis is conducted, where the main purpose is to analyse the sectoral effect of policy measures addressing the farm level.

The Interactive Component Modelling System (ICMS) is a framework in which to embed models and tools for the analysis and presentation of environmental options for environmental managers. It applies scenarios as model inputs, which take into account achievable policy/management drivers and socio-economic capacity for change, as well as uncontrollable system shocks. The DSS computes indicators, covering a spectrum of biophysical and socioeconomic impacts for each scenario as model outputs. The tool was developed in Australia and is being applied in Asia.

The Integrated Water Resource Assessment and Management (IWRAM) software contains two modelling toolboxes that utilise a nodal network structure for catchment analysis: a Biophysical Toolbox (erosion, streamflow, crop) and an Integrated Modelling Toolbox, which links models of household decision-making to allow for the consideration of socio-economic and environmental trade-offs of many development and policy scenarios. Previous applications were performed in Northern Thailand.

The Spatial Decision Support System (SDSS) provides watershed economic analysis by maximising the profit of a representative farm assumed to cover the whole watershed with the constraints of production technology, resource, sediment control objectives and sustainable utilisation. The tool includes two major types of models: static and dynamic. Each model type supports variations in plant growth, grazing and ranch operations. Upland erosion is estimated through RUSLE2 and the sediment yield of a watershed is estimated from upland erosion and sediment delivery ratios. The tool was developed and is being applied in the United States of America.

WaterStrategyManDSS (WSM DSS) is a GIS-based Decision Support System developed for the WaterStrategyMan Project. It aims to assess the state of a water resource system in terms of sources, usage, water cycles (pathways) and environmental quality. In addition, it evaluates the effects of actions on the basis of different scenarios, alternatives and policies. Water allocation is performed according to a set of demand and supply priorities, reflecting pricing systems, social preferences, environmental constraints and development priorities. WSM DSS includes the following types of management options: supply enhancement options, which are intended to increase available water quantities during drought, are concerned with structural interventions that attempt to enhance water supply; demand management options, aiming to decrease water demand through various conservation techniques and use limitations; socio-economic measures to mitigate impacts, such as pricing and changes in regional development; methods to produce management strategies through combinations of control measures seeking optimum and efficient solutions. Applications have been carried out in the Mediterranean region.

LADSS, the Land Allocation Decision Support System, is a farm-scale land use planning tool being developed in the United Kingdom to assist in the case-based investigation of policy and environmental change impacts on land use systems. The tool supports strategic, farm-scale, land use planning by suggesting possible combinations of land use to meet multiple objectives. LADSS provides a framework within which the financial, social and environmental consequences of changes in land use can be evaluated. It acts as a channel for technology transfer from land use scientists to land managers, and facilitates the inclusion of practitioner knowledge into models of land use systems.

The DSS for the Elbe River Water Quality Management includes models, spatial and non-spatial data and analysis tools under a user-friendly GIS-based interface. The tool confronts decision-makers with possible measures, as well as multiple management objectives. DSS helps water managers to formulate policy for river basin management and to take appropriate action to realise policy objectives. Furthermore, the DSS is especially suited to support participative decision-making.

The management of Regional German River Catchments (REGFLUD) is a project that addresses the problem of diffuse pollution. The overall objective is to develop and apply multi-criteria scientific methods to set up a DSS aimed at reducing diffuse pollution in river catchments, subject to economic feasibility and social acceptability. A model network is constructed, consisting of an agricultural sector model, a water balance model and a denitrification model that enables policy measure analyses to be performed. Alternative agri-environmental measures were carried out by a benefit-cost approach based on interviews regarding the social acceptability of alternative measures. Alternative forms of farm management regarding nutrient surplus were analysed as a guide for water management.

AQUATOOL is a generalised DSS for water resource planning and operational management, developed in Spain. The model simulates the operational management of the system on a monthly basis. It is responsible for water allocation to water uses, and considers the connected use of surface water and groundwater. Operating policies are defined by the following variables: target, minimum and maximum volumes of reservoirs, inter-reservoir relationships and priorities of use, minimum flow in rivers, flow requirements for hydroelectric plants, targeted water demand for each agricultural, industrial and domestic area and demand priorities used in water allocation.

AgriBMPWater is a tool designed to compare Best Management Practices (BMPs) in terms of environmental efficiency, economic cost and potential acceptability by farmers. It adopts negotiation-based implementation methods.

DANUBIA is a DSS currently under development in the Global Change in the Hydrological Cycle (GLOWA)[25] - Danube project. Upon completion, DANUBIA will be able to simulate water-related issues of environmental management under ecological, economic and cultural aspects, such as flood risk and protection, agriculture, water quality and quantity, tourism and water, as well as water and climate. It will examine the sustainability of the proposed solution scenarios.

A tool that adopts a different approach is PlayAgriPoliS, a policy simulation game implementing an agent-based model that establishes a link between agricultural policy reform and structural changes. Although PlayAgriPoliS is currently under development, a beta version is currently available for download.

The Water Evaluation and Planning system (WEAP) is a user-friendly software tool applied in the USA that follows an integrated approach to water resource planning. The tool supports the identification and evaluation of the impact of climate change on water for agriculture, and entails alternative strategies to study the cost of water in watersheds. The tool supports the assessment of water supply augmentation through an inter-basin transfer within a firm yield analysis and the development of supply and demand balances.

SIGRIA, the Information System on Water Management for Irrigation, is an integrated set of tools developed in Italy by the Istituto Nazionale di Economia Agraria (INEA) for the Ministry of Agriculture and for regional governments. SIGRIA is used: to plan new infrastructure, including dams and water distribution networks; identify and solve competitive situations for water by different users; mitigate the effects of annual droughts; develop and implement new policies on water pricing. At the local level, SIGRIA is a key component of information systems for irrigation managed by reclamation consortia. SIGRIA is based on GIS technologies and includes: a detailed map on land cover/use, identifying all irrigated areas and crops grown per season; an irrigation suitability map; all irrigation water networks, from the water source (dam river, etc.) to the farm or group of farms, including a database on the technical features of the network; extensive databases on the features of irrigation (i.e. crops, farms, costs) at the local level; a linear programming model on the optimum allocation of resources for irrigation for certain areas, at farm and basin levels, and a model on local water requirements by crops, depending on soil and weather data.

3.4 Web portal on water-related tools

Water managers, decision-makers, extension agents, regulatory agencies, planning organisations, consultants, students, researchers and environmental groups pose a number of questions, such as:

Are new user interfaces, general databases or other time-saving devices available?

Which applications can I take as a reference to address my problem in water management or water policy?

Consistent and comprehensive answers to the previous questions are essential for the practical and wide-spread application of models and tools.

Many existing models have been used or developed in the context of projects funded by the EU in recent years, and others are soon forthcoming (see Annex A for a list of relevant projects).

The importance of spreading existing information to all actors, updating it and making it easily available is crucial. For this reason, the EU has funded specific projects to create a European-wide comprehensive, shared web-based data and information management system for water, including river basins, with the primary purpose of consolidating information for potential users (Table 4).

The Register of Ecological Models (REM), a meta-database for existing mathematical models in ecology. It is a co-operative service of the University of Kassel and the GSF - National Research Center for Environment and Health) -
http://eco.wiz.uni-kassel.de/ecobas.html

The Hydroarchive website is an open source toolbox for model optimisation, evaluation and hydrological modelling, including model codes for rainfall runoff modelling - http://www.sahra.arizona.edu/software/index_main.html.

The Hydrologic Modeling Inventory is maintained through a cooperative effort between the Bureau of Reclamation and Texas A&M University - http://hydrologicmodels.tamu.edu/

The Archives of Models and Modeling Tools[26] of the Surface-water quality and flow Modeling Interest Group (SMIG) of the US Department of the Interior | US Geological Survey -
http://smig.usgs.gov/SMIG/model_archives.html

The Surface Water and Water Quality Models Information Clearinghouse (SMIC) is a database of the descriptions and features of environmental surface water and water quality models, and abstracts of projects using such models -
http://smig.usgs.gov/SMIC/

A quite different tool is AQUASTAT the FAO's global information system on water and agriculture. This information system consists of many databases, including: dams, institutions, river sediment yields, the state of water resources and agricultural water use by country and region, climate, a global map of irrigated areas - http://www.fao.org/nr/water/aquastat/main/index.stm

As far as water and agricultural models and tools are concerned, two new projects are relevant:

The first, Open Modelling Interface and Environment (OpenMI), aims to create a standard for model linkage in the water domain. It is being developed by the EU-funded HarmonIT project[27]. Specific objectives are that the mechanisms design should:

The assumption is that integrated catchment management requires integrated analysis that can be supported more effectively by integrated modelling systems. These can be developed and maintained better if they are based on a collection of interlinked models. OpenMI intends to launch a new era in integrated water management, as quoted from their main website.

- The second, the System for Environmental and Agricultural Modelling; Linking European Science and Society SEAMLESS, is an EU FP6 Integrated Project set up in response to a research and policy need formulated by the European Commission. The project aims to develop an integrated framework called SEAMLESS-IF that allows the ex-ante assessment of agricultural and environmental policies and technological innovations. The framework will have multi-scale capabilities, ranging from field and farm scales to the EU25 and the globe; it will be generic, modular and open, using state-of-the art software[28]. This computer system will include models that simulate effects on the environment and on economic developments, besides procedures that enable the assessment of the social aspects of sustainability. SEAMLESS-IF will assess and compare, ex-ante, alternative agricultural and environmental policy options, allowing:

The tool will enable the translation of policy questions to alternative scenarios that can be assessed through a set of indicators capturing the key economic, environmental, social and institutional issues of the questions at stake. The indicators in turn are assessed using an intelligent linkage of quantitative models designed to simulate aspects of agricultural systems at specific scales, i.e. point or field scales, farm, region, EU and world scales. Application of the models requires pan-European databases for environmental, economic and social issues. Some indicators, particularly social and institutional ones, will be assessed directly from data or via a post-model analysis. The software backbone of the SeamFrame project will link models designed for different scales and domains, and will facilitate the reuse, maintenance and documentation of models. The types of models[29] used in SEAMLESS are shown in table 5:

Prime users of SEAMLESS Integrated Framework are the Directorates General (DG Agriculture, Environment and Economics and Finances) of the European Commission, the JRC and the European Environment Agency (EEA). It is also the intention to make the tool useful to national/regional policy-making agencies, farmers organisations (e.g. COPA) and NGOs. A third important future user group is the scientific community. At present, in September 2007, Prototype 1 of SEAMLESS-IF can be obtained for free from the project website.

This section contains three reference case studies on how tools can support the implementation of the principles of the WFD in agriculture.

The selected case studies have all been implemented recently in the context of EU-funded projects in different European water basins.

4.1 ARID cluster and WaterStrategyMan

The so-called ARID cluster[30] includes three research projects on integrated and sustainable Water Resources Management in arid and semi-arid regions:

- WaterStrategyMan (WSM - Developing Strategies for Regulating and Managing Water Resources and Demand in Water Deficient Regions), website: http://environ.chemeng.ntua.gr/wsm/

- Medis (Towards Sustainable Water Use on Mediterranean Islands: Addressing Conflicting Demands and Varying Hydrological, Social and Economic Conditions), website: http://www.uni-muenster.de/Umweltforschung/medis/

- Aquadapt (Strategic Tools to Support Adaptive, Integrated Water Resources Management under Changing Utilisation Conditions at Catchment Level: A Coevolutionary Approach).

The first project was selected because it represents a good example of how tools can support participatory processes to develop strategies for regulating and managing water resources and demand in water-deficient regions. The project recognises that the existing framework of water management infrastructures, the natural environment, water supply (production) and consumption, institutional and socio-economic conditions are the main factors in determining the appropriate strategies that may lead to improved water resources management. Interactions between the main components of the socio-economic and environmental systems determine the issues analysed by the WaterStrategyMan DSS. With the assistance of GIS and properly customised databases, the objective of the DSS is to:

The DSS considers the differences between quantity and quality dimensions in water management and the development of alternative options and long-term scenarios. It establishes a broad framework on the existing knowledge on IWRM practices, while highlighting the importance of regionalisation and the relevant cultural context. The economic analysis in the WSM DSS (Water Management Schemes DSS) consists of a tentative implementation of the principles associated with the estimation of Full Water Costs and its components. The aim of the Evaluation Module is to facilitate the comparison of alternative WMSs, which incorporate different scenarios and/or strategic options. Each schemes score is defined as the value of a Relative Sustainability Index, which is derived from specific statistical criteria that are calculated for each scheme and based on a predefined list of indicators.

The project has made a great contribution to the development of methodologies to support the economic analysis requirement of the WFD. It pays special attention to the evaluation of direct and indirect costs of water use, the estimation of appropriate water prices and the comparison of alternative water management scenarios, using an integrated multi-criteria approach that is able to represent general guidelines for improved water management practices in water-deficient regions.

4.2 The German Elbe River Basin case study[31]

The German Elbe river basin project was also a success. River basin management has become increasingly complex in recent decades. Demands made by society regarding the ecological and chemical quality of stretches of water, the use and protection of water bodies, pollution by numerous substances as well as flood protection issues have led to the development of new views and strategies with regard to (the making of) policy for river basin management. The objective of this project was to develop a DSS for the Elbe river basin. Such a DSS helps water managers to formulate policy for river basin management and to take appropriate measures to realise policy objectives[32]. Simulation models are used to assess the efficiency of measures, such as reforestation, changes to agricultural practices or the efficiency of wastewater treatment plants to achieve management targets. MONERIS (MOdelling Nutrient Emissions in RIver Systems) and GREAT-ER (Geography-referenced Regional Exposure Assessment Tool for European Rivers) are integrated into the Elbe-DSS to assess nutrient and pollutant loads. MONERIS calculates nutrient inputs from diffuse and point sources at a sub-catchment scale of about 1000 km2. GREAT-ER is a tool to assess the exposure of point source emissions that considers fate in sewage treatment plants as well as degradation and transport in rivers. Both models make long-term predictions, but differ in their spatial scales. An ad hoc procedure has been created to link them. The DSS allows the distribution of diffuse nutrient emissions calculated from MONERIS and point source emissions from GREAT-ER to the river network, where further elimination and transport processes are calculated. The tool consists of a GIS-based user interface, which allows flexible easy-to-use access to predefined scenarios, measures and models. A database management system (DBMS), a model-based management system (MBMS) and a knowledge-based toolbox are integrated into the graphical user interface. Various data sources are integrated into the DSS, including: land cover (EEA, 2004), a digital terrain model (GLOBE Project), soil properties, hydrological and meteorological data (Federal Agencies), census data (Federal Statistical Office), wastewater treatment data and discharge consents (Federal and State Environmental Agencies) and monitoring data (various sources). All spatial data sets are processed with a GIS to produce a consistent geo-referenced data basis, which is coupled to the simulation models (Matthies et al., 2006).

A participatory approach involving local actors, experts and decision-makers was carried out to identify the issues to be addressed in the DSS:

Results from the study show that various governments, non-governmental organisations and institutions have been able to benefit from the DSS. The Elbe DSS could act as a prototype for other river catchments.

4.3 The case study of the Piave River Basin in Italy

This study was developed within the EU-MEDA project ISIIMM (Institutional and Social Innovations in Irrigation Mediterranean Management), which focuses on irrigation and water management. It addresses a wide range of related issues, such as relationships with the environment, management policies and the adaptation of local societies to local problems. The Italian case study area is the Piave River Basin. In the basin, a pilot area represented by a small zone located to the northwest of Treviso was identified for its relevance to the topic. In this area, reorganisation of the current water management system is in urgent need, due to conflicts regarding use of the same water bodies for different purposes within and outside the area. In particular, a programme of measures is being developed to substitute the existing irrigation systems and network based on open canals and furrow irrigation with an integrated pressurised dual system to distribute non-potable water of high quality for irrigation and other services, such as fire prevention, car washing, etc. With regard to irrigation, the methods would shift from current low-efficiency surface infiltration to more efficient methods, adopting sprinkler irrigators at the farm level.

The methodology adopted is based on simulation techniques implemented via bio-economic models in the Decision Support for IRRigation DSIrr (Bazzani, 2005a, 2005b), integrated within the NetSyMoD approach to manage the involvement of stakeholders, build conceptual models, and decision support through the mDSS4[33] software tool.

By integrating agronomic and engineering information with economic models and by favouring a joint consideration of water and agricultural policy, DSIrr enabled users to estimate ex-ante land use variations. This approach also allowed the consideration of equity issues concerned with the distribution of cost and benefit among farm typologies upon adoption of economic instruments, such as water pricing or other measures;

mDSS allowed the evaluation of the two alternatives in question (whether or not to reorganise the distribution and irrigation systems) within the contexts of three possible scenarios, by integrating the criteria and weighting expressed by stakeholders at the NetSyMoD workshop and the quantitative socio-economic indicators, which were supplied by DSIrr.

The study showed that, even in a small region that is far from homogeneous reality, agriculture is a complex system that can be described more accurately using a hierarchical decomposition approach. This complexity should be taken into account if the potential cost of water in agriculture is to be estimated and sound measures defined.

The adopted sustainability indicators highlight the side-effects of water policy in terms of their economic, social and environmental impact, and show that different farming systems have specific responses to water policy. In fact, the agricultural adaptation process integrates variation in land use, production processes, irrigation levels and technology, differentiated by type of farm. In addition, the scenario analysis clarifies the connection between water and agricultural policy.

The research confirmed the usefulness of the DSIrr simulation tool and its integration with mDSS into the NetSyMoD framework, to support decision-makers by integrating water and agricultural policy analysis. The conjoint analysis of the two policies proved to be essential to identify a sustainable path and design sound intervention for the agricultural sector, which considers cost recovery and the polluter pays principle and is sustainable to the agricultural sector, as well as being beneficial to the environment and society.

The case study can offer an insight into relevant issues, such as: how tools can improve transparency in decision-making, how tools can support water managers in their present tasks, how different management options can be compared in terms of their ecological, economic and social impact.

The use of toolboxes and models is mentioned in several places in the Water Framework Directive document and in various guidance documents, although the use of models is not obligatory. A key issue is if and how tools can support water and agricultural managers in their effort to comply with WFD requirements. To answer the previous questions, this review describes over fifty tools related to water and agriculture, taking into consideration agronomic, hydraulic, land use and socio-economic dimensions. What emerges is a complex, unclear picture.

In the past decade, research has led to the creation of many tools, some of which have reached the stage of operational implementation and can address specific aspects of the complex relation between water and agriculture. In many cases, different tools address the same problems and issues, and the differences between models are minor.

The new computational technology continues to enhance the frontier of modelling. Most new tools are DSS, GIS-based, integrated and user-friendly, with a beautiful front end. Nonetheless, the embedded complexity is very high. There is a strong need, which goes beyond the scope of this review, to evaluate the conceptual core of such tools; the EU project EUROHARP is a good example of the specific field considered.

The WFD adopts a basin approach that can be supported by the last generation of integrated hydrological tools, which are primarily concerned with the representation of the physical world by GIS. Such tools are often weak with regard to economic analysis, which could be addressed using other models and tools.

The integrated modelling approach adopted by tools, including hydrology and water quality models, agronomic models, land use and economic models, requires expertise from various domains. They should be performed by teams of people from a variety of disciplines. This, however, could create new problems, as recent experiences have shown. A multidisciplinary approach could complicate working processes communication problems are often present and no common vision is guaranteed.

A growing need for quality assurance in modelling has emerged among professionals in this field (Refsgaard, 2002). Quality assurance is defined by NRC (1990) as the procedural and operational framework used by an organisation to manage a modelling study to assure the technically and scientifically adequate execution of all tasks included in the study and to assure that all modelling-based analysis is reproducible and defensible. Good practice in model development and application deserves close attention. In fact, the credibility and impact of the information and insight that modelling aims to generate are highly dependent on the quality of the modelling exercise. It is crucial for model acceptance and is a necessity for long term, systematic accrual of a good knowledge base for both science and decision-making. The complexity and uncertainty inherent in management for better sustainability outcomes make the pursuit of good practice especially important, in spite of limited time and resources Jakeman, Letcher and Norton (2006: p. 602).

The aspect of good practice in modelling can become a real problem when modelling moves from the research to the management domain. Managers and interest groups are not scientists working in sharply defined areas of research, but people generally pressurised to use models to manage complex situations. They usually do not have a modelling or quantitative background, and therefore find it difficult to judge their quality or appropriateness, as the previous authors observed.

The conflict of interest among actors is another critical issue that is well identified by McGlade (2002: p. 4) Significantly, these conflicts operate at local, regional, national and European scales and reflect fundamental differences in perception and value systems. Thus a crucial issue, for any conception of sustainable management, is the need to understand the socio-environmental driving forces of change at different spatio-temporal scales. What this means is an ability to assess the resilience of socio-natural landscapes to a variety of human and naturally induced pressures - effectively, developing an understanding of the variable sensitivities of ecological, economic and socio-cultural processes, so as to anticipate likely future outcomes and possible unforeseen evolutionary trajectories.

That water managementis closely related to political processes is well clarified by Pahl-Wostl (2006: slide 2), who suggests that Adaptive management is needed as a systematic process for continually improving management policies and practices by learning from the outcomes of implemented management strategies.

There is great need for a new approach, which could progress from traditional, purely quantitative modelling towards a multilevel approach, as Sendzimir et al. (in press) recommend. At a higher level, the definition of a common conceptual framework for cross-disciplinary work involving authorities, managers, stakeholders and researchers and this task can be achieved by conceptual models. Such systemic models identify components (variables) and clarify structures (web of interactions, feedback loops and delays), but, operating in qualitative terms, they do not quantify the implications of different policies or processes on system dynamics. At lower levels, quantitative models can support specific analysis, exploring the strength of interactions and the sensitivity of the system to change. The information produced, clarifying the areas of greatest uncertainty and influence on the systems evolution under different assumptions, can help prioritise field research and support water and agricultural management.

This approach may be particularly useful for implementing the WFD in the agricultural sector, where analyses at different scales are needed to quantify aggregate impacts at the basin scale, such as non-point pollution or water demand, and to design and assess alternative packages of measures, both in agricultural and water, addressing specific problems at farm and field scales.

Even if in recent years important progress has been made in modelling and tools, this is not enough to guarantee that tools are able to effectively support implementation of the WFD at the operational level across Europe, at least in the agricultural sector.

The recent reform of the Common Agricultural Policy is perhaps a significant barrier, since many measures, such as the decoupling of subsidies, are new. Furthermore, the measures to implement such policies are very locality-dependent and, in many cases, have not yet been defined. What emerges from this review is that many existing tools are unable to address these policies. There is a clear need for new tools to conduct an ex-ante assessment of agricultural and environmental policies and technological innovations. The integrated framework SEAMLESS-IF, with its multi-scale capabilities ranging from field and farm scales to the EU25 and the world, including models that simulate effects on the environment and on economic developments, besides procedures that enable the assessment of the social aspects of sustainability, could represent an important tool in the near future to address agricultural policies.

The economic analysis requirement of the WFD, which addresses different aspects ranging from the economic analysis of water use, cost recovery and pricing schemes, to the evaluation of benefits to the environment and society and eventually of disproportionate costs, introduces further complexity for modelling and tools. This is because the methodological framework has not yet been defined. In fact, a multiplicity of approaches, methods and techniques exist to address specific aspects of the monetary or non-monetary valuation, but no common guidelines are available. Even if many tools exist, no one seems capable of fully addressing the economic and policy aspects related to the implementation of the WFD in agriculture. Distinct aspects seem relevant, as far as economic analysis is concerned:

At present, the integration of different tools, as the case studies show, can improve transparency in decision-making and favour the comparison of different management options in terms of their ecological, economic and social impact. All of the described tools may be beneficial to this process, if used properly. However, the choice of tool is highly dependent on local circumstances, among which previous experience in modelling, trained staff and data availability are critical.

The translation of the experience gained in recent research to the management domain will probably be a long process, in which support by the scientific community should be viewed as essential. The following recommendations are considered important to bridge the gap to real-world decision processes:

The suggested approach could solve the problem at the national level, favouring an enforceable, transparent, reproducible, auditable process. However, this could conflict with the European dimension. Nationally based approaches, which vary throughout Europe, could create a situation in which the resulting assessments and decisions are not fully comparable between countries.

Since innovation in computational technology will further enhance the frontier of modelling, dedicated web portals offering comprehensive, shared European information, such as WISE Water Information System for Europe, are a key instrument for water and agricultural managers and other interested parties to access updated information.

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Annex 1: EU-funded projects related to water and agricultural modelling

Annex 2: The Common Agricultural Policy

The Common Agricultural Policy (CAP) has a long history that goes back to the Treaty of Rome, the founding document of what has become the European Union (EU), signed in 1957[34].

There is evidence that the effect of this intervention has been multi-fold and sometimes contradictory: a clear conflict between agricultural and environmental goals has emerged. Production subsidies in the form of price support to agricultural commodities have generally encouraged more intensive production patterns based largely on machinery, genetic seed, industrial fertilizers and pesticides, which increased yields, but also environmental pressures. Water demands (direct effect) and surface water and groundwater pollution from the run-off of agricultural chemicals (indirect effect) are both relevant in this context.

A variety of driving forces, which underlie farmers management decisions, influence this process: technological development, changes in market conditions, changes in the costs of labour, land and other factors of production, modification of the socio-cultural environment, structural changes and a range of different public policies, including the CAP itself[35].

Since its establishment, the whole concept of the CAP and the way in which it works have greatly changed, due to successive reforms. Environmental integration into other EU policies, including the CAP, is part of a long process dating back to the 1980s. It is legally bound in the Treaty of the European Community (TEU): Environmental protection requirements must be integrated into the definition and the implementation of (all) the Community policies and activities in particular with a view to promoting sustainable development[36]. The Agreement on the Mid-Term Review of the CAP, reached in June 2003, gives a clear shape to a new European model for agriculture in the years ahead, reflecting the multifunctional[37] role that farming plays, and integrating economic viability, food safety, social balance and environmental concerns. Reg. (EC) No. 1782/2003[38] the reference document for the reform defines:

- Single payment scheme: income support decoupled from production (Art. 1) based on entitlements over the 2000-02 reference period (Art. 33) is maintained to provide farmers with a fair income. Farmers shall receive a payment entitlement per hectare, which is calculated by dividing the reference amount by the three-year average number of all hectares entitling them to direct payments in the reference period (Art. 43). Any payment entitlements accompanied by eligible hectares[39] shall entitle the farmer to the payment (Art . 44)[40]. Member States shall constitute a national reserve of payment entitlements to assist new farmers. Premium rights can only be transferred under certain conditions; transfers will support the national reserve (Art. 42), which could be used in order to avoid land being abandoned and the maintenance of rural areas[41].

- Cross-compliance[42]: direct payments to farmers are made subject to certain requirements (Art. 3) in the following areas: public, animal and plant health, the environment and animal welfare (Art. 4). Requirements, however, are not defined on a Community-wide basis but in accordance with criteria set by the Member States[43]. In particular, Member States areobligedto define at national or regional levels, minimum requirements for good agricultural and environmental conditions, taking into account the specific characteristics of the areas concerned, including soil and climatic conditions, existing farming systems, land use, crop rotation, farming practices and farm structures (Art. 5). Member States have to set up a farm advisory system[44] by 1 January 2007, advising farmers on land and farm management (Art. 13), and implement control systems to ensure compliance with the statutory management requirements and good agricultural and environmental conditions (Art. 25). Where it is found that farmers do not comply with the eligibility conditions, the payment or part thereof shall be subject to reductions and exclusions, graduated according to the severity, extent, permanence and repetition of non-compliance (Art. 24).

- Rural development, which forms the second pillar of the CAP and aims to set new political objectives, is strengthened[45]. All instruments linked to RD policy are grouped into one single instrument, designed to:

- increase the competitiveness of the agricultural sector through support for restructuring;

- enhance the environment and countryside through support for land management, including co-financing rural development actions related to Natura 2000 nature protection sites; and

- enhance the quality of life in rural areas, promoting the diversification of economic activities through measures targeting the farm sector and other rural actors.

In order to achieve a better balance between policy tools designed to promote sustainable agriculture by market policies, the first pillar and those designed to promote RD (a system of progressive reduction of direct payments), is introduced on a compulsory Community-wide basis Modulation (Art. 10)[46].

Annex 3: Measures to implement the WFD and the CAP

The programmes of measures can be considered as the principal mechanism for the implementation of the environmental objectives of the WFD, and have to be established by 2009 and made operational by 2012 (Art. 11 WFD). They should be based on risk assessment (Art. 5 WFD). The WFD distinguishes between basic measures (minimum requirements), including the so-called combined approach for point and diffuse sources (Art. 10 WFD), and supplementary measures. The former include the implementation of a number of environmental directives that directly or indirectly assist in the protection of water (Annex VI, Part A WFD). On the agricultural side, cross compliance links the CAP to European environmental directives (Annex III) by 1.1.2005. Some of these appear in both lists: the conservation of wild birds; the protection of the environment, and in particular of the soil, when sewage sludge is used in agriculture; the protection of waters against pollution caused by nitrates from agricultural; the conservation of natural habitats and of wild flora and fauna[47]. This creates common ground for both policies[48].

River basin programmes of measures can also include ad hoc measures. In this regard, the design of upcoming RD programmes (2007-2013) is an opportunity to support the WFD in the agricultural sector. Axis 2 concerning Environment and land management can be used to devise directly targeted measures. However, other measures concerning Improving competitiveness of farming and forestry (Axis 1) and Improving quality of life and diversification (Axis 3) offer opportunities to contribute indirectly to WFD delivery.

The Common Agricultural Policys agri-environmental programmesare often subdivided into different schemes, each made up of a series of measures. Agricultural and RD policies include a rich set of tools. A basic distinction is made between Good Farming Practices (GFP) and Agri-Environment Schemes (AES), aiming to reach higher environmental quality levels. Member States have to specify verifiable standards representing baselines to be respected for both measures. GFP should ensure that farmers observe mandatory environmental requirements in line with the Polluter Pays Principle, and therefore aim to prevent negative environmental effects (e.g. water pollution). Penalties should normally apply in enforcing the avoidance of negative environmental effects below the reference level of GFP. Conversely, incentives would be offered to reward positive environmental effects above this level. This is the AES case that have to go beyond usual GFP (e.g. a water status higher then the minimum requirement). The scheme provides payments to farmers in return for an environmental service to compensate higher cost and/or lower income which the farmer suffers to comply with the regulation[49].

Annex IV of Reg. 1782/2003 specifies the good agricultural and environmental conditions referred to in Art. 5:

The definition of the reference level may change over time and will vary between Member States and regions according to local environmental conditions, legal traditions and the definition of property rights. AES follow a number of basic principles, which are optional and site-specific, and which require structured and long-term approaches to monitoring and evaluation, and proper payment levels[50]. They are a highly refined tool for environmental integration. They are able to achieve certain environmental results that other instruments are unable to achieve. However, in order to be implemented correctly, they must be enforced, and the existing administrative capacity of Member States must be upgraded.

Annex 4: Monetary valuation

Monetary valuation of environmental goods and services has a long tradition where different methods are developed and applied to put monetary values on environmental services via economic models. Table 8 (adapted from Pearce and Turner, 1990) summarises the characteristics of the available methods.

All of the previous methods can support economic analysis in the implementation of the WFD. Some are particularly suitable for the valuation of external costs. It should be clear that they require a case-by-case approach and specific application in order to capture costs and benefits accurately.

Environmental values can also be inferred through meta-analysis from existing studies. This method is known as value transfer or benefit/cost transfer. However, in this approach, the risk of potential estimation errors is high. Previous studies must be carried out before this approach can be applied.

Annex 5: A categorisation of tools and models for water management and agriculture

The following table describes over 50 existing tools related to water management and agriculture. It provides a starting point in the selection of models for particular applications.

1. Tool name
2. Brief description
3. Group
4. Spatial scale
5. Irrigation measures
6. Agricultural measures
7. Economic analysis
8. Examples of measures addressed
9. Link to the website
10. Contact
11. Further characterisation
12. Previous application

The Group code identifies the main core of the tool: A = Agronomic, H = Hydrology, E = Economic. Most information is condensed in the description and characterisation. To synthesise very inhomogeneous data, a few characteristics have been reported as dummies (YES/NO) to identify the capability to analyse irrigation measures and agricultural measures. A code that reflects the economic theory embedded in the tool (MI = micro, MA = macro, OA = other approach) is used to synthesise available information on the economic analysis.

If a cell is left blank, the model does not seem to have that particular function.

The author apologises for any misrepresentations that may be indicated in the table, and also if he was unable to determine that the model had a particular feature[53].

Additional information on the tool (e.g. data needs, time scale, computation time step, arrangement and costs) is available from the website given in the table or by contacting the reference person or institute.

Tool name	Short description	Group	Spatial scale	Irrigation measures	Agricultural measures	Economic analysis	Type of measures	Web page	Contact	Further characterization	Previous application
AGLINK	A multi-country and commodity economic model	E	EU/State/Region	NO	NO	MA	CAP	www.oecd.org/	OECD Secretariat	AGLINK is a dynamic supply-demand model of world agriculture, developed by the OECD Secretariat in close co-operation with Member countries. The overall design of the model focuses particular attention to the potential influence of agricultural policy on agricultural markets in medium term. AGLINK is a partial equilibrium model, primarily of major OECD commodity markets. AGLINK estimates supply, demand and prices. Non-agricultural sectors are not modelled, and are treated as exogenously to the model.	OCDE
AGNPS - Agricultural Non Point Source Pollution Model	AGNPS is a computer model developed to predict non point source pollutant loadings within agricultural watersheds.	A	Farm/Catchment	YES	YES	OA	Crop rotation, Tillage operations, Fertilization schemes, Pesticide applications, Filter strips	www.geog.uni-hannover.de/phygeo/grass/agnps.html	Ronald L. Bingner rbingner@ars.usda.gov	It contains a continuous simulation, surface runoff model designed to assist with determining BMPs, the setting of TMDLs, and for risk & cost/benefit analyses.	USA
AgriBMPWater	A systems approach to environmentally acceptable farming	E	Farm/Catchment	YES	YES	OA	Farm management and agricultural practices. Water management	www.bordeaux.cemagref.fr/public/agribmpwater/index.html	ramon.laplana@bordeaux.cemagref.fr	This tool aims at providing planners with a grid which would allow a comparison between Best Management Practices (BMPs) in terms of environmental efficiency, economic cost and potential acceptability by farmers. It adopts negociative implementation methods.	France
ANIMO - Agricultural Nutrient Model	Dynamic simplified process-based model to simulate N leaching from the soil surface to ground and surface waters.	A	Farm/Catchment	NO	YES	NA	Farm management and agricultural practices	www.sc.dlo.nl/wateruk/index.htm	J.G.Kroes: j.g.kroes@sc.agro.nl	ANIMO operates as a multi-layer model with the soil surface and groundwater forming the upper and lower system boundaries, respectively. The main processes simulated by the model are: Nitrogen: mineralisation of N, immobilisation of NH4, NO3 uptake by plants (excess and limited) nitrification of NH4, denitrification of NO3, volatisation of NH4, NO3 leaching Phosphorus. ANIMO can be linked to any hydrological model for the calculation of fluxes and changes in moisture content	The Netherlands
APSIM - Agricultural Production System Simulator	A tool to simulate biophysical processes in farming systems	A	Field/Farm	NO	YES	OA	Farm management and agricultural practices	www.apsim.info/apsim/Downloads/	apsim-help@csiro.au	APSIM is structured around plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. APSIM resulted from a need for tools that provided accurate predictions of crop production in relation to climate, genotype, soil and management factor while addressing the long-term resource management issues. It relates to the economic and ecological outcomes of management practices in the face of climate risk.	Australia
AQUASTAT	AQUASTAT is FAO's global information system on water and agriculture	H	Catchment/Basin	YES	NO	NA	To be defined case by by case	www.fao.org/ag/agl/aglw/aquastat/main/index.stm	FAO mailto:Land-and-Water@fao.org	The information system consists of: Databases - Database on African dams; Database on institutions; Database on river sediment yields; Countries and regions - Standardized text by country and by region on the state of water resources and agricultural water use; Climate - A tool to provide climate estimates for the land surface of the globe; Water resources - Review of the statistics of renewable water resources by country; Agricultural water use - Review of agricultural water use by country; Irrigation - Global map of irrigated areas, which is a spatial dataset on areas equipped for irrigation	Many basin
AQUATOOL	A generalised DSS for water resource planning and operational management	E	Catchment/Basin			OA	Land use and water management	www.upv.es/aquatool/	Universidad Politecnica de Valencia, Spain - Manuel Pulido mapuve@hma.upv.es	The SIMGES Fortran-coded mathematical model performs the simulation of the operational management of the system on a monthly basis. It is responsible for the water allocation to water uses and considers the conjunctive use of surface water and groundwater. Operating policies are defined by the following variables: target, minimum and maximum volumes of reservoirs, inter-reservoir relationships and priorities of use, minimum flow in rivers, flow requirements for hydroelectric plants, targeted water demand for each agricultural, industrial and domestic areas and their demand priorities that are used in the water allocation.	Many basin
BASINS - Better Assessment Science Integrating point and Nonpoint Sources	A multi-purpose environmental analysis system that integrates a GIS, national watershed data, environmental assessment and modeling tools	H	Catchment/Basin	YES	YES	OA	Land use, water management	www.epa.gov/waterscience/basins/index.html	Modeling and Information Technology Team Standards and Health Protection Division Office of Science and Technology - U.S. Environmental Protection Agency Mailcode - 4305T - 1200 Pennsylvania Ave., NW Washington, DC 20460	BASIN facilitates examination of environmental information, supporting analysis of environmental systems, and providing a framework for examining management alternatives for watersheds. It runs on a non-proprietary, open source, free GIS systemArcView GIS Base. Cartographic, Environmental, Environmental Monitoring, Point Source/Loading data - models: Pollutant Load (PLOAD), Soil and Water Assessment Tool (SWAT), Windows Hydrological Simulation Program-Fortran (WinHSPF) and Enhanced Stream Water Quality Model (QUAL2) GenScn, GENeration and analysis of model simulation SCeNarios	Many basin
CAPRI - Common Agricultural Policy Regional Impact Analysis	Economic model to conduct CAP analysis	E	EU/State/Region	NO	NO	MA	CAP, environmental aspects included	www.agp.uni-bonn.de/agpo/rsrch/capri/capri_e.htm	Dr. Wolfgang Britz Diplom-Agraringenieur Nussallee 21, Haus 1, Raum 14 Tel.: ++ 49 - 2 28 - 73 25 02 wolfgang.britz@ilr.uni-bonn.de	CAPRI is an agricultural sector model covering both the whole of EU27 and Norway at regional level (250 regions) and global agricultural markets. The following environmental indicators are covered by CAPRI: - Balances for N,P,K - Emissions of Ammonia, Methan and N2O - Global Warming potentials. CAPRI users both work in research institutions and EU Commission services.	Europe
CREAMS - Chemicals, runoff and erosion from agricultural management systems	It is a model for predicting runoff, erosion, and chemical transport from agricultural management systems	A	Field/Farm	YES	YES	NA	Cropping systems management	www.wiz.uni-kassel.de/model_db/mdb/creams.html	R.Wayne Skaggs skaggs@eos.ncsu.edu	CREAMS is a field scale model for predicting runoff, erosion, and chemical transport from agricultural management systems. It is applicable to field-sized areas. CREAMS can operate on individual storms but can also predict long term averages (2-50 years). The model must be phyysically based and not require calibration for each specific application, 2) the model must be simple, easily understood with as few parameters as possible and still represent the physical system relatively accurately, 3) the model must estimate runoff, percolation, erosion, and dissolved and adsorbed plant nutrients and pesticides and, 4) the model must distinguish between management practices. Based on these objectives, since the management practices were usually on a field basis, the size of a field to represent the scale of the model was needed.	USA
CropSyst Suite - Cropping Systems Simulation Model	CropSyst is a is a user-friendly, conceptually simple but sound multi-year multi-crop daily time step simulation model	A	Field/Farm	YES	YES	NA	Cropping systems management	www.bsyse.wsu.edu/cropsyst/	Developer: Claudio O. Stckle Phone: (509)335-3826 FAX: (509)335-2722 e-mail: stockle@wsu.edu	CropSyst is a is a user-friendly, conceptually simple but sound multi-year multi-crop daily time step simulation model. The model has been developed to serve as an analytic tool to study the effect of cropping systems management on productivity and the environment. The model simulates the soil water budget, soil-plant nitrogen budget, crop canopy and root growth, dry matter production, yield, residue production and decomposition, and erosion. Management options include: cultivar selection, crop rotation (including fallow years), irrigation, nitrogen fertilization, tillage operations (over 80 options), and residue management. The model is currently written in Turbo Pascal 6.0 for MS-DOS using an object oriented programming approach.	Different countries
CROPWAT -Crop and water	A computer program for irrigation planning and management	A	Filed/Farm	YES	YES	NA	Cropping systems management	www.fao.org/ag/agl/aglw/tools.stm	The Water Resources, Development and Management Service of FAO, Viale delle Terme di Caracalla, 00100 Rome, Italy Tel: +(39) 06 57055541, Fax: (39-06) 57056275	CROPWAT is a decision support system developed by the Land and Water Development Division of FAO. It is meant as a practical tool to help agro-meteorologists, agronomists and irrigation engineers to carry out standard calculations for evapotranspiration and crop water use studies, and more specifically the design and management of irrigation schemes. It allows the assessment of production under rainfed conditions or deficit irrigation. Standard crop data are included in the program and climatic data can be obtained for 144 countries through the CLIMWAT-database.	Different countries
DANUBIA decision support system	The GLOWA-Danube project has the objective to develop, to apply and to exploit integrative techniques for the modelling of the water cycle in the Upper Danube catchment.	E	Catchment/Basin	YES	YES	OA	To be defined case by by case	www.glowa-danube.de/	Prof. Dr. Wolfram Mauser Department of Earth and Environmental Sciences - Chair for Geography and Geographical Remote Sensing University of Munich Luisenstrae 37 D - 80333 Munich phone: ++49 89 2180 6682	Upon completion, DANUBIA will be able to simulate water-related issues of environmental management under ecological, economical and cultural aspects, such as flood risk and protection, agriculture and water quality and quantity, tourism and water as well as water and climate. It will examine the sustainability of the proposed solution scenarios. DANUBIA will contribute to provide optimal solutions for a sustainable environmental management in large, heterogeneous catchments.	Danube basin
DRIPS - Drainage Spraydrift and Runoff Input of Pesticides in Surface Waters	A decision support system estimating the quantity of diffuse pesticide pollution in German river basins.	H	Catchment/State	YES	YES	NA	Pesticides management		University of Giessen, Department of Natural Resources Management, Heinrich-Buff-Ring 26-32, D-35392 Giessen, Germany. bjoern.roepke@agrar.uni-giessen.de	The GIS based decision support system DRIPS has been developed to estimate the predicted environmental concentration (PECsw) of pesticides in surface waters resulting from diffuse sources. PECsw can be calculated on a catchment scale by quantifying the expected mean daily inputs of pesticides via surface runoff, tile drainage and spraydrift for various types of river basins characterized by their daily discharges. DRIPS is fitted with a Graphical User Interface (GUI) to provide easy access to the model algorithms. Model parameters like dose rate, DT50, Koc and date of pesticides application, etc. can be modified by the user in order to generate customized scenarios predicting PECsw for a choice of field crops, orchards and vineyards. Results are available as grid cell maps for the territory of Germany with high temporal and spatial resolution.	German river basin
DSIrr - Decision Support for IRRigation	Agricultural and water economics and policy analysis	E	Farm/Catchment	YES	YES	MI	Cropping systems management, water pricing, quota and markets, taxes, subsidies decoupling, agri-env. schemess	www.bo.ibimet.cnr.it/index.php?id=346&L=3	Guido M. Bazzani CNR IBIMET via Gobetti, 101 40129 Bologna, Italy fax. +39 051 6399099 tel. +39-051-6398016 g.bazzani@ibimet.cnr.it	DSIrr is support tool for scenario analysis using simulation approaches and optimisation bio-economic models. Scenarios evaluate a full range of water development and management options, and take account of multiple and competing uses of water. Scenario can also describe agricultural policy or other exogenous drivers. A multi-scale modelling approach is adopted and different types of farms can be aggregated to create a model network. The individual models are specialised to address specific questions and reflect heterogeneity between farms. Farm preferences can be described using a multi-attribute approach. Changes in irrigation and farm practices are considered. A set of indicators is quantified to assess socio-economic and environmental impacts at farm and regional level. The DS can be linked to other tools.	Italy
DSS for the Elbe River Water Quality Management	River basin management	E	Catchment	YES	YES	OA	Agricultural practices - Land use, water management	www.riks.nl/projects/Elbe-DSS	Dr. S. Kofalk, at the Bundesanstalt fr Gewsserkunde (BfG), Mainzer Tor 1, 56068 Koblenz, Phone: +49 (261) 13065330.	Models, spatial and non-spatial data and analysis tools under a user-friendly GIS-based interface. The tool confronts the decision maker with possible measures as well as multiple management objectives. DSS helps the water managers to formulate policy for river basin management and to take appropriate measures to realise policy objectives. It could also be a very useful tool for the implementation of EU-WFD. Furthermore the DSS is especially suited to support participative decision making.	Germany
EPIC - Erosion Productivity Impact Calculator	Assess the effect of soil erosion on productivity. Predict the effects of management decisions on soil loss, water quality, and crop yields	A	Filed/Farm	YES	YES	MI	Agricultural practices	www.brc.tamus.edu/epic/	Jimmy Williams williams@brc.tamus.edu (254)774-6124 USDA/ARS Grassland Soil and Water Research Laboratory 808 East Blackland Road Temple, TX 76502	EPIC predict the effects of management decisions on soil, water, nutrient, and pesticide movements and their combined impact on soil loss, water quality, and crop yields for areas with homogeneous soils and management. Weather, surface runoff, return flow, percolation, ET, lateral subsurface flow and snow melt. Water erosion; Wind erosion; N & P loss in runoff , nitrogen leaching; Organic N & P transport by sediment; N & P mineralization, immobilization and uptake; Denitrification; Mineral P cycling; N fixation; Pesticide fate and transport; Soil temperature; Crop growth and yield for over 80 crops; Crop rotations; Tillage, Plant environment control (drainage, irrigation, fertilization, furrow diking, liming); Economic accounting; Waste management (feed yards dairies with or without lagoons).	Many countries
FARMIS	FARMIS is a comparative-static process-analytical programming model	E	EU/State/Region	NO	YES	MI	CAP and policy measures	www.fal.de/nn_797028/EN/institutes/BW/research/fieldsactivity/ag1__en.html	Dir. u. Prof. Dr. Werner Kleinhan Federal Agricultural Research Centre (FAL) Institute of Farm Economics - Bundesallee 50 38116 Braunschweig Germany Phone: ++49 (0) 531 596 5151 E-mail: werner.kleinhanss@fal.de	Impacts of the Mid-term Review policy reform on German agriculture can be assessed by using simulation approaches and optimisation models based on FADN data. The model network includes different models which are kept current and combined with each other as necessary. The individual models are specialised to address specific questions (for example, regional impacts, farm impacts, market impacts). Comparative-static analysis is conducted with the main purpose is to analyse the sectoral effect of policy measures addressing the farm level.	Germany
GLEAMS - Groundwater Loading Effects of Agricultural Management Systems	The program simulates water quality events on an agricultural field.	A	Filed/Field	YES	YES	NA	Farm level management decisions on water quality	http://arsserv0.tamu.edu/models.htm, http://arsserv0.tamu.edu/nrsu/glmsfact.htm	Kevin King USDA, ARS Resource Center, 808 E. Blackland Rd., Temple, TX 76502 king@brcsun0.tamu.edu	GLEAMS is a continuous simulation, field scale model. It consists of four major components: hydrology, erosion/sediment yield, pesticide transport, and nutrients. GLEAMS was developed to evaluate the impact of management practices on potential pesticide and nutrient leaching within, through, and below the root zone. It also estimates surface runoff and sediment losses from the field. GLEAMS was not developed as an absolute predictor of pollutant loading. It is a tool for comparative analysis of complex pesticide chemistry, soil properties, and climate.	Numerous climatic and soil regions of the world
GTAP - Global Trade Analysis Project	Quantitative analysis of global economic issues within an economy-wide framework	E	EU/State/Region	NO	NO	MA	CAP trade and policy	https://www.gtap.agecon.purdue.edu/about/project.asp	Hertel, T.W. Center for Global Trade Analysis 403 West State Street West Lafayette IN 47907-2056 United States	GTAP (Global Trade Analysis Project) is a global network of researchers and policy makers conducting quantitative analysis of international policy issues. GTAP's goal is to improve the quality of quantitative analysis of global economic issues within an economy-wide framework. GTAP offers a variety of products, including: data, models, and utilities for multi-region, applied general equilibrium analysis of global economic issues.	Europe
ICMS - Interactive Component Modelling System	Integrated Scenario Modelling for Managing Catchments	E	Catchment	YES	YES	MI	Agricultural practices - Infrastructure investment, Farm Dams, Environmental Flows, Sleeper licence activation	www.clw.csiro.au/products/icms/	Letcher, R.A. Centre for Resource and Environmental Studies The Australian National University,Canberra ACT 0200, Australia Rebecca@cres.anu.edu.au	The DSS is a framework in which to embed models and tools for analysis and presentation of environmental options for environmental managers. It applies scenarios as model inputs which take into account achievable policy/management drivers and socioeconomic capacity for change, as well as uncontrollable system shocks. The DSS computes, as model outputs, indicators covering a spectrum of biophysical and socioeconomic impacts for each scenario.	Namoi River
IRRINET	The web system entails a complete dissemination of information in agrometeorology	A	Filed/Farm/Catchment	YES	YES	NA	Agricultural practices	www.consorziocer.it	Consorzio di Bonifica di Secondo Grado per il Canale Emiliano Romagnolo Via Ernesto Masi, 8 - 40137 Bologna Tel. 051/42 98 811 - Fax 051/39 04 22 Email: cer@consorziocer.it	Through a channel from the Po river water is made available over a 3000 Km2 area and the water resources (68m3/s) allow to satisfy the irrigation needs. Water is furnished together with the information for its rational and sustainable utilization. The web system entails a complete dissemination of information in agrometeorology up to a personalized irrigation guided scheduling for farmers based on water balance models at plot level. The service is active from 1985 and on average favour a reduction of 20 % in water consumption.	Italy
IWRAM - Integrated Water Resource Assessment and Management	An integrated modelling toolbox for considering impacts of development and land use	E	Farm/Catchment	YES	YES	MI	Farm management, development and land use	icam.anu.edu.au/projects/water_management.html	Tony Jakeman Integrated Catchment Assessment and Management Centre Canberra ACT 0200,Australia Tony.Jakeman@anu.edu.au	The IWRAM contains two modelling toolboxes utilising a nodal network structure for catchment analysis: a Biophysical Toolbox (erosion, streamflow, crop) and an Integrated Modelling Toolbox, which links models of household decision making to allow for consideration of socioeconomic and environmental trade-offs of many development and policy scenarios.	Mae Chaem catchment in Northern Thailand.
LADSS - Land Allocation Decision Support System	LADSS is a computer based rural land use planning tool	E	Farm/Catchment		YES	OA	Land use stategic planning	www.macaulay.ac.uk/LADSS/	http://www.macaulay.ac.uk/	LADSS is a farm-scale land use planning tool being developed within the Integrated Land Use Systems group of The Macaulay Institute in order to assist in the case-based investigation of policy and environmental change impacts on land-use systems. The tool supports strategic, farm-scale, land use planning by suggesting possible combinations of land uses to meet multiple-objectives Provides a framework within which the financial, social and environmental consequences of changes in land use may be evaluated. Demonstrates an approach to the integrating of spatial data and analysis methods with land use systems models Acts as a channel for technology transfer from land use scientists to land managers and facilitates the inclusion of practitioner knowledge into models of land use systems.	United Kingdom
LEACHM - Leaching Estimation and Chemistry Model	LEACHM refers to a suite of simulation models describing the water and chemical regime in the soil root zone.	H	Farm/Catchment	YES	YES	NA	Agicultural practices	eco.wiz.uni-kassel.de/model_db/mdb/leachm.html	Dr. J.L. Hutson School of Earth Sciences The Flinders University of South Australia GPO Box 2100, Adelaide SA 5001 Phone: (08) 8201 2616 email: john.hutson@es.flinders.edu.au	The LEACHM suite consists of four simulation models and several utilities. The simulation models utilize similar numerical solution schemes to simulate vertical water and chemical movement. They differ in their description of chemical equilibrium, transformation and degradation pathways.LEACHW describes the water regime only. The other simulations describe pesticides (LEACHP), nitrogen and phosphorus (LEACHN), and salinity in calcareous soils (LEACHC).The models simulate chemical fate and transport in transient-flow field situations as well as in laboratory columns subject to steady-state or interrupted flow.Water flow and solute transport is described by the Richards and convective-dispersion equations, or by a modified Addiscott mobile/immobile capacity (tipping-bucket) concept.	Australia
Low Flows 2000	A catchment-based water resource decision support tool for the United Kingdom	H	Catchment	YES	YES	NA	Abstraction licensing	www.ceh.ac.uk/products/software/CEHSoftware-LOWFLOWS2000.htm	M.G.R. Holmes: mgrh@ceh.ac.uk	Low Flows 2000 is a decision support tool designed to estimate river flows at ungauged sites and to aid the development of catchment and regional water resources. It is the standard software system used by the Environment Agency and the Scottish Environment Protection Agency for providing estimates of river flows, as represented by annual and monthly flow duration statistics, for any river reach in the UK. The software and underpinning science have been widely published in the scientific literature. The CEH Low Flows 2000 system is now licensed to Wallingford HydroSolutions (WHS) for distribution and further development. WHS was set up in 2004 to maximise the transfer of CEH water research to the user community.	United Kingdom
MB - Mike Basin	MB is professional engineering software package for integrated river basin planning and management	H	Basin/Catchment	YES	YES	OA	Point and non-point source management alternatives - Land use	www.crwr.utexas.edu/gis/gishyd98/dhi/mikebas/Mbasmain.htm	Danish Hydraulic Institute (DHI) Lilla Bommen 1 S-411 04 Gteborg Sweden Phone: + 46 31 80 87 90	The DSS integrates GIS, data bases and models to provide an user-friendly tool, capable of evaluating alternative options for compliance considering the legislative requirements, technical options for improvements, environmental impacts and economic/financial implications. MIKE BASIN provides a mathematical representation of the river basin encompassing the configuration of the main rivers and their tributaries, the hydrology of the basin in space and time, existing as well as potential major schemes and their various demands of water. The natural river system is schematised and represented with a node-branch structure.	Many basino
MicroLEIS DSS - A Land Evaluation Decision Support System for Agricultural Soil Protection	A computer-based set of tools for an orderly arrangement and practical interpretation of land resources/agricultural management data.	A	Farm/Catchment	YES	YES	NA	Agricultural management, Land resources	leu.irnase.csic.es/microlei/manual2/overview.htm	Prof. D. de la Rosa - IRNAS, Instituto de Recursos Naturales y Agrobiologa de Sevilla Avenida de Reina Mercedes, 10. 41012 Sevilla - Espaa. Telfono: 954624711 Fax: 954624002	MicroLEIS is a agro-ecological system. It major characteristics are: data and knowledge engineering through the use of a variety of databases and innovative modelling techniques; scaling-up of process knowledge from the micro-scale to the landscape-scale; land evaluation; use of monthly meteorological data and standard information; integrated agro-ecological approach, combining biophysical data with agricultural management experience; software development for PC platforms and Web- and GIS-based versions.	Spain
MONERIS - MOdelling Nutrient Emissions into RIver Systems	MONERIS is a semi-static GIS-based emission model for point and diffuse sources of nutrients	H	Catchment	YES	YES	NA	To be defined case by by case			MONERIS calculates the emissions into surface waters via several independent pathways for separate catchments, which are topologically linked in a tree-like structure. Input data are taken from various sources (e.g. statistical yearbooks, emission inventories, digital maps etc). Those data are preprocessed to give specific values for every catchment.	Many basino - Danube River
MULINO - MULti-sectoral, INtegrated and Operational decision support system for sustainable use of water resource at the catchement scale	Operational tool aiming at supporting and guiding the Decision Makers in each step of the overall decision making process, from problem conceptualisation to the choice of the best policy to solve it.	E	Catchment	YES	YES	OA	To be defined case by by case	siti.feem.it/mulino/	Carlo Giupponi Dipartimento di Produzione Vegetale Via Celoria, 2 - 20133 Milano - ITALY tel. +39.02.503.16596 - carlo.giupponi@unimi.it	The tool integrates social, economic and environmental modelling techniques with GIS capabilities, a geo-referenced database and a multi-criteria approach for evaluating simulation results. The core structure of the tool is based on the Driving Forces-Pressure-State-Impact-Response	Many basin
NetSyMod - Network analysis creative System Modelling Decision Support	Operational tool aiming at supporting and guiding the Decision Makers in each step of the overall decision making process, from problem conceptualisation to the choice of the best policy to solve it.	E	Catchment/Basin	YES	YES	OA	To be defined case by by case	www.netsymod.eu/mdss/	netsymod@feem.it	mDSS4, originally developed in the context of the project MULINO (MULti-sectoral, INtegrated and Operational Decision Support System for Sustainable Use of Water Resources at the Catchment Scale) and further developed and applied with a contribution of several other projects (including DSS-GUIDE, TRANSCAT, NOSTRUM-DSS, NEWATER and BRAHMATWIN) is a generic DSS developed to assist water authorities in the management of water resources. It can help to better understand or explain (to stakeholders) the problem at hand, to facilitate public participation required by the WFD, to take the edge of the conflict related to alternative water uses, to extend collaboration with and within different stakeholder groups	Many basin
NIRAMS - Nitrogen Risk Assessment Model for Scotland	GIS-based model to calculate losses of N from diffuse pollution.	H	Catchment	YES	YES	NA	Fertilization schemes	www.macaulay.ac.uk/MRCS/gis/gis3_nirams.html	Ann Malcolm - Macaulay Research Consultancy Services Ltd - Craigiebuckler - Aberdeen AB15 8QH United Kingdom Tel: +(44) (0) 1224 498200 Email: a.malcolm@macaulay.ac.uk	Estimates of annual residual N (by crop) are leached to surface and groundwaters by hydrological flows and routed to the stream system. The system uses nationally available land use, soils, topography and meteorology data sets and has been developed within the ArcView 3.2 Geographic Information System (GIS). The model has been delivered to the Scottish Executive Environment and Rural Affairs Department (SEERAD) and the Scottish Environmental Protection Agency (SEPA).	Scotland
NL-CAT - Nutrient Losses at catchment scale	NL-CAT is capable of simulating phosphorus and nitrogen losses in both the soil and surface water.	H	Basin/Catchment	YES	YES	NA	Crop rotation, Tillage operations, Fertilization schemes, Filter strips	www.euroharp.org/toolbox/onemodel_slide.php?mod=21	Oscar.Schoumans@wur.nl	The model chain NL-CAT (Nutrient Losses at catchment scale) was built in order to evaluate the impact of different type of measures on the improvement of the surface water quality at catchment scale. The surface water modeling consist of the two important STONE components SWAP and ANIMO in combination with a surface water quantity and a surface water quality module. The SWAP module generates hydrological input to the ANIMO module simulates the nutrient cycle in soil and the nutrient leaching to groundwater and surface waters. Surface water discharges are simulated by the SURFACE WATER module while simulation of surface water quality processes and retention within a (large) catchment is performed by the NUSWALITE module. An erosion module P-USLE based on the modified and revised Universal Soil Loss Equations is implemented in a GIS-environment.	The Netherlands
PlanteInfo	PlanteInfo is a information and decision support system for farmers and agricultural advisers.	A	Fileld/Farm	YES	YES	NA	Agicultural practices	www.planteinfo.dk	planteinfo@agrsci.dk	Most of the information is generated dynamically with models using frequently updated databases. A subscription system enables personalised information. For example, since the geographical location of the user's home is known after login, local weather data are used for model calculations. PlanteInfo can store previously entered information, like fields, crops and actions for the user for future use of the system. PlanteInfo also has a public version, which contains the facilities you see in the menu. Unfortunately, only a few facilities have English versions.	Denmark
PlayAgriPoliS	A policy simulation game	E	Region/Catchment		NO	OA	CAP Macro policy	www.iamo.de/PlayAgriPoliS/playagripolis_start.html	Kathrin Happe, Institute of Agricultural Development in Central and Eastern Europe (IAMO) mailto:kellermann@iamo.de	It is an agent-based modeling approach to establish a link between agricultural policy reform and structural change. PlayAgriPoliS is currently under development. A beta version of 0.91 is now available for download.	Central and Eastern Europe
QUAL2K - River and Stream Water Quality Model	QUAL2K is a river and stream water quality model	H	Fileld/Catchment	YES	YES	NA	Point and non-point loads and abstractions	www.epa.gov/ATHENS/wwqtsc/html/qual2k.html	EPA U.S. Environmental Protection Agency	QUAL2K (or Q2K) is a river and stream water quality model. The channel is well-mixed vertically and laterally. Steady state hydraulics. Non-uniform, steady flow is simulated. Diurnal water-quality kinetics. All water quality variables are simulated on a diurnal time scale. Heat and mass inputs. Point and non-point loads and abstractions are simulated. Q2K is implemented within the Microsoft Windows environment.	Many basin
REGFLUD - Management of Regional German River Catchments	The REGFLUD-project has overall objective to set-up a DSS aimed at reducing diffuse pollution in river catchments subject to economic feasibility and social acceptability	E	Farm/Catchment	YES	YES	OA	Reduction of nitrate - Institutional arrangements	www.rwi-essen.de/	Dirk Huchtemann - Rheinisch-Westflisches Institut fr Wirtschaftsforschung (RWI) Rhine-Westphalia Institute for Economic Research Hohenzollernstr. 1-3, 45128 Essen, Germany (e-mail: dirk.huchtemann@rwi-essen.de)	A model network consisting of an agricultural sector model, a water balance model, and a groundwater residence time/ denitrification model that enables consistent status-quo as well policy measures analyses. Evaluation of alternative agri-environmental measures with a benefit-cost approach based on interviews about the social acceptability of alternative measures. Analysis of alternative forms of organisation regarding an efficient and likewise nutrient surplus oriented water management. Summary and provision of results within an online DSS for the interested public.	Germany
RIBASIM - River Basin Simulation Model	RIBASIM is a generic model package for analyzing the behaviour of river basins under various hydrological conditions..	H	Basin/Catchment	YES	YES	OA	Water allocation, re-use of drainage water by downstream users	www.wldelft.nl/soft/ribasim/int/index.html	Delft Hydraulics ribasim.info@wldelft.nl	Windows-based software with a graphical user interface, a database, a simulation program and a tool for the analysis of results. The model package is a comprehensive and flexible tool which links the hydrological water inputs at various locations with the specific water-users in the basin. The tool describes a basin in terms of water sources and uses and to perform a simulation of the water allocation along a certain time horizon. It can be helpful in identifying possible water use conflicts among different types of uses, such as farmers or industries, in studying the sustainable development of the river basin itself and in planning the adequate measures to solve conflicts or generally improve the water resource status	Many basin
RIZA tools for groundwater management in the Netherlands	Simulation models representing system dynamics and addressing one or more issues in water policy	H	Catchment		YES	OA	Water and land management	www.rijkswaterstaat.nl/rws/riza/home/mona/download/pdf/tools.pdf	RIZA, Lelystad, The Netherlands	RIZA has developed a set of coherent models to support the policy management of the groundwater resources in the Netherlands. These models compute the hydrological effects of interventions on the saturated and unsaturated zone as well as the effects on agriculture, drinking water supply and nature.	The Netherlands
SDSS - Spatial Decision Support System	The tool assess the economic and environmental impacts from various best management practices (BMPs) in reducing sediment yield on rangeland watersheds.	E	Catchment	YES	YES	MI	Best management practices (BMPs) in reducing sediment yield on rangeland watersheds.	www.tucson.ars.ag.gov/sdss/	Yanxin Duan (520) 670-6381 x163 yduan@tucson.ars.ag.gov	The models provide the watershed economic analysis, by maximizing the profit of a representative ranch assumed to cover the whole watershed with the constraints of production technology, resource, sediment control objectives and sustainable utilization. There are two major types of models, static and dynamic. Each model type supported variations in plant growth, grazing and ranch operations. Upland erosion was estimated through RUSLE2 and the sediment yield of a watershed was estimated from upland erosion and sediment delivery ratios.	USA
SIGRIA- Information System on Water Management for Irrigation	The tool is used to plan new infrastructures; identify and solve situations of water conflict; mitigate the effects of annual droughts; develop and implement new policies.	E	Basin/Catchment	YES	YES	MI	SIGRIA is a component of information systems for irrigation managed by reclamation consortia		Guido Bonati INEA-Istituto Nazionale di Economia Agraria, Via Barberini 36, Roma Italy bonati@inea.it	SIGRIA is based on GIS technologies and includes: a detailed map on land cover/use identifying all irrigated areas and crops grown per season; an irrigation suitability map; irrigation water networks, from the water source (dam river, etc. ) to the farm or group of farms, including a database on the technical features of the network; extensive databases on the features of irrigation (i.e. crops, farms, costs). For certain areas a linear programming model on the optimal allocation of resources for irrigation at farm and basin level and a model on local water requirements by crops are available.	Italy
SIMIS - Scheme Irrigation Management Information System	Facilitating the management tasks of irrigation schemes.	A	Farm	YES	YES	MI	Day-to-day water management activities	www.fao.org/ag/agl/aglw/simis.stm	FAO mailto:Land-and-Water@fao.org	This program is not limited to the water aspects but covers all the major issues of the day-to-day management activities and also includes control of maintenance, accounting, water fees and other relevant tasks. sector components; crop water requirements; irrigation plan; water delivery scheduling; accounting; water fees; control of maintenance activities; performance indicators.	Many basins
SME - Spatial Modeling Environment	An integrated toolsuite for spatial modeling	E	Basin/Catchment	YES	YES	MI	Agicultural practices, Land management practices, Water management	www.uvm.edu/giee/SME3/	Robert Costanza International Institute for Ecological Economics Center for Environmental Science University of Maryland System rcostanz@zoo.uvm.edu	This environment allows users to develop models in a user-friendly, graphical environment, requiring very little knowledge of computers or computer programming. Automatic code generators construct spatial simulations and enable distributed processing over a network of parallel and serial computers, allowing transparent access to state-of-the-art computing facilities. The modeling environment imposes the constraints of modularity and hierarchy in program design, and supports the archiving of reusable modules in our Simulation Module Markup Language (SMML)	Many basins
SPAW (v6.02.75) - Soil-Plant-Air-Water	SPAW is a daily hydrologic budget model for agricultural fields and ponds (wetlands, lagoons, ponds and reservoirs).	H	Field/farm	YES	YES	NA	Multiple landscape and ponding variations	http://hydrolab.arsusda.gov/SPAW/Index.htm	Dr. Keith E. Saxton - USDA - Agricultural Research Service, in cooperation with Department of Biological Systems Engineering Washington State University, Pullman, WA Email: ksaxton@wsu.edu	The objective of the SPAW model was to understand and predict agricultural hydrology and its interactions with soils and crop production without undue burden of computation time or input details. The SPAW computer model simulates the daily hydrologic water budgets of agricultural landscapes by two connected routines, one for farm fields and a second for impoundments such as wetland ponds, lagoons or reservoirs. Climate, soil and vegetation data files for field and pond projects are selected from those prepared and stored with a system of interactive screens. Typical applications include analyses of crop water status, deep seepage, wetland inundation duration and frequency, lagoon designs, and water supply reservoir reliability.
SWAT - Soil and Water Assessment Tool	SWAT is a river basin scale model developed to quantify the impact of land management practices in large, complex watersheds.	H	Basin/Catchment	YES	YES	NA	Land management practices, Water management	www.brc.tamus.edu/swat	Agricultural Research Service of the US Department of Agriculture	It aims at assisting the Decision Maker in storing and managing water demand and supply information, in forecasting water demands, water availability, waste generation and water costs and in evaluating water development and management options. It is physically based and it is particularly suitable for predicting the effects of land use management, as well as climatic and vegetative changes on water, sediment, and agricultural chemical yields in large complex watersheds with varying soils, land use, and management conditions for a long time horizon (up to a hundred years).SWAT is a public domain model actively supported by the USDA Agricultural Research Service at the Grassland, Soil and Water Research Laboratory in Temple, Texas, USA.	Many basins also in Europe
SWIM - Soil Water Infiltration and Movement	Tool for simulating infiltration, evapotranspiration and redistribution	H	Basin/Catchment	YES	YES	NA	Agricultural practices	www.clw.csiro.au/products/swim/	CSIRO Land and Water Bag 10 Clayton South VIC 3169 Australia	The overall purpose of the model is to address issues relating to the soil water and solute balance. As such it is a research tool that can be integrated in laboratory and field studies concerned with soil water and solute transport. It is also eminently suitable for management and education.	Many basins
SWIM- Soil and Water Integrated Model	A simulation tools for hydrological cycle, erosion, vegetation growth and nutrient transport in mesoscale watershed	H	Basin/Catchment	YES	YES	NA	Land use change Agricultural practices Water management		Valentina Krysanova Potsdam Institute for Climate Impact Research P.O.Box 601203, Telegrafenberg 14412 Potsdam, Germany Phone: +49-(0)331-288-2515 Fax: +49-(0)331-288-2600 email: valen@pik-potsdam.de	SWIM aims to analyse climate change and land use change impacts on hydrology and water quality at the regional scale. SWIM is based on two previously developed models - SWAT (Arnold et al, 1993) and MATSALU (Krysanova et al., 1989). SWIM includes modules from both predecessors, trying to combine their advantages (hydrological submodel and GRASS interface from SWAT; spatial disaggregation scheme and nutrient modules from MATSALU), and to avoid overparametrization. A simplified EPIC approach (Williams et al., 1984) is used for simulating all the crops and natural vegetation, using parameter values for each plant type from the database.	Germany
TRK (N) - TRK (SOILNDB/HBV-N)	A tool to simulate N-losses	H	Basin/Catchment	YES	YES	NA	Nutrient management and the effect on N-losses - Land use changes and water measures	euroharp.org/pd/pd/models/TRK-short.htm	Helene Ejhed, IVL Svenska Miljinstitutet AB/ IVL Swedish Environmental Research Institute, Sweden helene.ejhed@ivl.se	The TRK system combines; 1. Preparation of areal distribution of different land-use categories and positioning of point sources using GIS; 2. Calculations of concentration and areal losses of diffuse sources (for N from arable land by using the dynamic soil profile model SOILNDB); 3. Calculations of the water balance (by using the distributed dynamic HBV model) and N transport and retention processes in water (by using the model HBV-N). The results are presented in the GIS, and source apportionment is made for each sub-basin as well as for the whole river basins. The results from the system have been used for international reports on the transport to the sea, for assessment of the reduction of the anthropogenic load on the sea and for guidance on effective measures for reducing the load on the sea on a national scale.	Nordic countries and Sweden
WATERWARE - A Water Resources Management Information System	WaterWare is an integrated, model-based information and decision support system for water resources management.	H	Basin/Catchment	YES	YES	OA	Strategies for river and groundwater pollution-control schemes	www.ess.co.at/WATERWARE	Environmental Software & Services GmbH, Advanced Computer Applications (ESS-ACA)	WaterWare is a comprehensive decision-support system (DSS) for integrated river basin planning capable of addressing a wide range of issues such as: determining the limits of development; evaluating the impact of new environmental legislation; deciding what, where and when new resources should be developed; assessing the environmental impact water-related development; formulating strategies for river and groundwater pollution-control schemes; etc. WaterWare supports the integration of databases, GIS, simulation and optimization models, and analytical tools into a common framework. WaterWare Release 5.1 is fully web based access.	Many basins:
WATSIM - World Agricultural Trade SImulation Model	CAP macro level, World Agricultural Trade SImulation Model	E	EU/State/Region	NO	NO	MA	Import/export	www.agp.uni-bonn.de/agpo/rsrch/watsim/wats_ov_e.htm	Institute for Agricultural Policy, Market Research and Economic Sociology - Bonn University, Nuallee 21, D-53115 Bonn FAX.: +49-228-982 29 23 Dr. Arnim Kuhn, arnim.kuhn@ilr.uni-bonn.de Dr. Wolfgang Britz, wolfgang.britz@ilr.uni-bonn.de	WATSIM is a recursive-dynamic, spatial world trade model for agricultural commodities. In its current version, it covers 12 regions and 29 commodities. Simulations are running from the year 2000 to 2010. Policies covered are ad-valorem and specific tariffs, tariff rate quotas (TRQs), safeguards (flexible tariffs), export subsidies, and production quotas. These policies are explicitly modelled by formulating the model as an MCP (mixed complementarity problem). The most important application of WATSIM is the medium-term analysis of trade policy changes.	Many basins
WEAP - Water Evaluation And Planning system	WEAP is a user-friendly software tool that takes an integrated approach to water resources planning.	E	Catchment	NO	NO	OA	Alternative water development and allocation scenarios.	www.weap21.org/	Stockholm Environment Institute's Boston Center at the Tellus Institute, USA	The identification and evaluation of the impacts of climate change on water for agriculture, recreation, hydropower generation, water for municipal and industrial use, habitat function and health, biodiversity, water purification alternative strategies to study the water costs in watersheds. The tool support: the assessment of water supply augmentation through an inter-basin transfer within firm yield analysis; the resolution of water use conflicts in river basins; the development of supply and demand balances	Many basins
WetSpa - A distributed model for Water and Energy Transfer between Soil, Plants and Atmosphere	GIS-based hydro-logic model	H	Catchment	YES	NO	NA	Land use change	www.tiszariver.com	info@tiszariver.com	The WetSpa model is a GIS-based hydro-logic model, which simulates hydrological processes continuously both in space and time with the aim to simulate the hydrological behaviour of a catchment with regard to flood prediction, landuse and climate change scenario analysis and water management. The pollutant transport module aims to simulate the transport of phosphorus through a catchment. Domain covered: hydrology, landuse and climate change, water management, phosphorus transport.	Europe
WSM - WaterStrategyManDSS	A DSS for water planning and management of water in arid regions	E	Farm/Catchment/Basin	YES	YES	MI	Supply enhancement. Demand management. Socio-economic measures.	environ.chemeng.ntua.gr/wsm/	Dionysis Assimacopoulos assim@chemeng.ntua.gr	The GIS-based Decision Support System developed for the WaterStrategyMan Project (WSM DSS) aims to assess the state of a water resource system in terms of sources, usage, water cycles (pathways) and environmental quality. In addition, it evaluates the effects of actions, on the basis of different scenarios, alternatives and policies. Water allocation is performed according to a set of demand and supply priorities reflecting the pricing system, social preferences, environmental constraints and development priorities. The WSM DSS entails four types of management options: supply enhancement, demand management, socio-economic measures, management strategies.	Greece

I am grateful to three referees comments which improved the paper. Thanks also go to Ilke Borowski and Britta Kastens for their helpful assistance and comments. Needless to say all remaining errors are mine.

Guido M. Bazzani
CNR IBIMET
via Gobetti, 101
40129 Bologna, Italy
fax. +39 051 6399099
tel. +39-051-6398016
E-mail: g.bazzani@ibimet.cnr.it

[1] Abbreviations of the models and tools are not included in this list but are provided in the text.

[3] Irrigation networks are often used to drain excess water in the rainy season, which is an important environmental service.

[4] The 5th Environmental Action Programme refers to sustainable development as development which meets the needs of the present without compromising the ability of future generations to meet their own needs. This entails preserving the overall balance and value of the natural capital stock and taking a long-term view of the real socio-economic costs and benefits of consumption and conservation. The achievement of balanced and sustainable development, together with the promotion of economic and social progress and a high level of employment, represents the first overall objective of the Union (Art. 2 of the TEU).

[5] The term conveys that agriculture provides a variety of non-marketable outputs and services of good public character, which are valuable to the well-being of society.

[6] Member States have the option to decouple between 2005 and 2007; however, to deflate its impact and prevent the abandonment of production, states can maintain a limited link between subsidies and production under well-defined conditions and within clear limits.

[7] The SFP is linked to regulations in the fields of the environment, public, animal and plant health and animal welfare; farmers are sanctioned for non-compliance (partial or entire reduction of direct support). Beneficiaries of direct payments are also obliged to keep their land in good agricultural and environmental condition.

[8] RD forms the second pillar. The shift from the first to the second pillar is strengthened by another innovative measure: modulation, which makes an additional RD fund available, thanks to a 5%reduction in direct payments for bigger farms.

[9] This is predicted to have a significant impact on the European farm sector. TheEU will probably lose most of its share of the world export market for dairy products. Exports of coarse grains are expected to fall. The EU will also import far more beef and poultry.

The supply costs (direct or financial costs) of water services include the costs of providing and administering these services. They include all operation and maintenance costs, and capital costs (principal and interest payment), and return on equity, if appropriate (p.70).

[11] The different timetables stipulated by the WFD and the CAP create further difficulties.

[12] A GIS is a computer system capable of capturing, storing, analysing and displaying geographically referenced information, that is, data identified according to location. Practitioners also define a GIS as including the procedures, operating personnel and spatial data that go into the system.

[15] AGWA is an ArcView extension which parameterises the SWAT and KINEROS hydrologic simulation models, runs the models and visually imports the results.

[16] DHI Water & Environment is an independent research and consultancy organisation, formed by a merger of the Danish Hydraulic Institute, VKI - Institute for the Water Environment and the Danish Toxicology Centre, see also http://www.dhigroup.com/Contact/AboutDHI.aspx.

[18] HBV is the abbreviation of the (Swedish) name of the department of Sweden's Meteorological and Hydrological Institute, where the model was developed.

[20] Optimisation approaches are another important branch of the MCDA, which in some ways follows a bounded rational paradigm (Spronk and Veeneklaas, 1983).

[24] FADN consists of an annual survey carried out by the Member States of the European Union. The services responsible in the Union for the operation of the FADN collect accountancy data every year from a sample of agricultural holdings in the European Union. Derived from national surveys, the FADN is the only source of micro-economic data that is harmonised, i.e. the book-keeping principles are identical in all countries.

[25] The German Federal Ministry of Education and Research (BMBF) launched the GLOWA programme to identify new research strategies in the field of global change, in particular with regard to the aim of sustainable development.

[27] The project is funded within the Fifth Framework Programme and contributes to the implementation of the Key Action Sustainable Management and Quality of Water website: http://www.openmi.org/

[28] The project is being carried out by a consortium of 30 partners, led by Wageningen University (NL), e-mail: seamless.office@wur.nl website: http://www.seamless-ip.org/

[29] A description of the types of models used in SEAMLESS and selected characteristics can be found in SEAMLESS No. 010036 Deliverable number: PD1.2.1, 2 June 2005.

[30] Arid cluster comprises three projects supported by the European Commission under the Fifth Framework Programme, contributing to the implementation of the Key Action "Sustainable Management and Quality of Water" within Energy, Environment and Sustainable Development. The main source for this example is represented by the respective websites.

[32] The study was carried out by the Universities of Twente/Enschede and Osnabrck and the institutes RIKS and INFRAM from the Netherlands, based on a feasibility study by the Federal Institute of Hydrology (BfG).

[33] In mDSS4, m stands for multicriteria and the number 4 identifies the version.

[34] The Treaty of Rome was signed by France, West Germany, Italy, the Netherlands, Belgium and Luxembourg. The treaty identified the following objectives, among others: to increase agricultural productivity; to ensure a secure food supply at reasonable prices; and to give the agricultural community a fair income. These aims were to be achieved through a free internal market with high domestic prices. The CAP is one of the main European policies, at least in terms of resources.

[35] National and regional economic, social, environmental, fiscal and land use policies can influence farmers decisions,

[36] The 5th Environmental Action Programme refers to sustainable development as development which meets the needs of the present without compromising the ability of future generations to meet their own needs. This entails preserving the overall balance and value of the natural capital stock and taking a long-term view of the real socio-economic costs and benefits of consumption and conservation. The achievement of balanced and sustainable development, together with the promotion of economic and social progress and a high level of employment, is the first overall objective of the Union (Art. 2 of the TEU).

[37] The term conveys that agriculture provides a variety of non-marketable outputs and services of good public character, which are valuable to the well-being of society.

[38] Council Regulation (EC) No. 1782/2003 of 29 September 2003 establishing common rules for direct support schemes under the Common Agricultural Policy and establishing certain support schemes for farmers and amending Regulations (EEC) No. 2019/93, (EC) No. 1452/2001, (EC) No. 1453/2001, (EC) No. 1454/2001, (EC) No. 1868/94, (EC) No. 1251/1999, (EC) No. 1254/1999, (EC) No. 1673/2000, (EEC) No. 2358/71 and (EC) No. 2529/2001.

[39] Eligible hectare shall mean any agricultural area of the holding taken up by arable land and permanent pasture except areas under permanent crops, forests or used for non-agricultural activities (Art. 44). In order to avoid distortions of competition- fruit and vegetables, including potatoes, are excluded from production on eligible land expect, when regionalisation is implemented.

[40] Set-aside entitlements are also implemented (Art. 53) following Art. 6(1) of Regulation (EC) No. 1251/1999 .

[41] The CAP also adopts a financial discipline, with a view to ensuring that the amounts for financing the CAP respect annual ceilings (Art. 11). A maximum guaranteed area should be prescribed and proportional reductions applied if this area is exceeded, concentrated in Member States that overshoot their area.

[42] Commission Regulation (EC) No. 796/2004 of 21 April 2004, which lays down detailed rules for the implementation of cross-compliance, modulation and the integrated administration and control system provided for in Council Regulation (EC) No. 1782/2003, establishing common rules for direct support schemes under the Common Agricultural Policy and establishing certain support schemes for farmers.

[43] For new Member States, access to the new single payments is not necessarily subject to conditionality. Commission Regulation (EC) No. 795/2004 of 21 April 2004 lays down detailed rules for the implementation of the single payment scheme [Official Journal L 141 of 30.04.2004].

[44] The system should help commercial farmers to become more aware of material flows and on-farm processes relating to the environment, food safety, animal health and welfare.

[45] Council Regulation (EC) No. 1698/2005 of 20 September 2005 on support for rural development by the European Agricultural Fund for Rural Development (EAFRD).

[46] All direct payment amounts to be granted in excess of EUR 5000 shall be reduced for each year until 2012 by the following percentages: 2005: 3%, 2006: 4%, 2007-12: 5% . The annual budget allocated to the first pillar over this period is EUR 40.5 billion. It has also allotted EUR 14 billion to RD and to veterinary and plant health measures.

[47] Council Directive 79/409/EEC of 2 April 1979 on the conservation of wild birds (OJ L 103, 25.4.1979, p. 1) Art. 3, 4(1), (2), (4), 5, 7 and 8 2. Council Directive 86/278/EEC of 12 June 1986 on the protection of the environment, and in particular of the soil, when sewage sludge is used in agriculture (OJ L 181, 4.7.1986, p. 6) Art. 3 4. Council Directive 91/676/EEC of 12 December 1991 concerning the protection of waters against pollution caused by nitrates from agricultural sources (OJ L 375, 31.12.1991, p. 1) Art.s 4 and 5. Council Directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild flora and fauna (OJ L 206, 22.7.1992, p. 7).

[48] Indirect market measures (e.g. food labelling and quality assurance initiatives) can play an important role as a driver to support environmental objectives.

[49] AEM are co-financed by the EU and the Member States with a contribution from the Community budget of 85% in Objective 1 areas and 60% in others. Agri-environment payments are not considered to be trade-distorting subsidies in WTO; they have Green Box status.

[50] Agri-environmental contracts compete economically with the most profitable land use, so payment levels have to be set sufficiently high to attract farmers to join schemes, while avoiding over-compensation. This requires the calculation of appropriate payment levels.

[51] This is not always true. In some cases, mitigation may not be possible at all, or on the contrary it could be higher than necessary, leading to an over-estimation of environmental costs. Environmental quality levels, such as the Directives Objectives, should be taken as references.

[52] The most commonly used measures are willingness to pay WTP to avoid environmental costs or to obtain an environmental benefit, and willingness to accept WTA to support an environmental cost or renounce an environmental benefit. The choice of measure is not neutral - income distributions and levels influence these values.

[53] The author hopes that readers will send him additional information, enabling him to update the information.

Scientists	Policy-makers	Water managers
Knowledge among modellers and Decision Support System developers on the demands made on them by the WFD is often limited	Policy-makers wish to use models but often have a significant lack of confidence in them (black boxes)	Water managers need tools that reflect their national or federal river basin planning policies
Developing new models or adapting existing ones for reuse is usually timeconsuming, and therefore expensive	DSS tools are usually perceived as tools that potentially limit decision-making capabilities
Funding mechanisms do not facilitate long-term efforts, nor the efficient integration and exploitation of existing knowledge	Policy-makers have limited time; they are put under pressure by deadlines imposed by the implementation of the WFD
	At least empirical cognitive models are always available in competent administrations, and are used for decision-making

Type	Purpose	Specification Required
Abstraction	Enforces a water user (water supply, irrigation, hydropower) to receive enough water to cover its demand, as given in the users input time series	Upstream node on river as water source and downstream user node
Minimum flow	Enforces minimum flow at nodes	Relevant node on river (no downstream node), time series of flow requirement
Reservoir storage	Enforces storage in reservoirs up to flood control level	Relevant reservoir node (no downstream node, no time series)
Reservoir target level	Enforces water levels in reservoirs	Relevant reservoir node (no downstream node), time series of target levels
Specified abstraction	Enforces a water user to receive enough water to cover its demand, as given in a separate time series (overriding input time series)	Upstream node on river and downstream user node, time series of demand

Tool name	Water Information System for Europe	Harmonised Modelling Tools for Integrated Basin Management	Harmonising Quality Assurance in model-based catchment and river basin management	River Basin Manager's Toolbox - Model Evaluation Tool
Acronym	WISE	Harmoni-CA	Harmoni-QuA	MET
Description	WISE is a portal that compiles data and information collected at EU level by various institutions or bodies.	Harmoni-CA is a European-wide forum bringing together the scientific and political world involved in integrated basin management and the implementation of the WFD	The HarmoniQuA project has developed a computer-based Modelling Support Tool (MoST) to provide a user-friendly guidance and quality assurance framework.	MET aims to test and demonstrate the use of integrated models applied to selected intensively studied river basins.
Website	http://www.water.europa.eu/	http://www.harmoni-ca.info/	http://www.harmoni-ca.info/	http://www.rbm-toolbox.net/toolbox3/
Objective	The primary objective is to create a comprehensive, shared European data and information management system for water, including river basins, following a participatory approach.	To establish a communication forum and define general methodology and guidance documents. Joint use of monitoring and modelling. Integrated assessment and the science-policy interface.	HarmoniQuA aims to provide a user-friendly computer-based guidance and QA framework for use in model-based river management.	The objective of the BMW project is to establish a set of criteria to assess the appropriateness of integrated models for use in the implementation of the WFD.
Additional information	WISE is a partnership between the European Commission (DG Environment, Joint Research Centre and Eurostat) and the European Environment Agency. The web portal http://www.wise-rtd.info/ links websites with a focus on information relevant to the implementation of the WFD, such as (CIS) guidance documents, selections of ICT tools, methodologies and results of research projects (e.g. the CatchMod cluster). Information is offered at European, national and regional levels, as well as for river (sub-)basins.		MOST is a DS that prompts users with the appropriate 'next step' in the modelling process and provides an audit trail to check previous decisions. The approach targets management at catchment and river basin scales with the overall goal of improving the quality of modelling and therefore enhancing the confidence of all stakeholders in them. The tool is freely available at: http://harmoniqua.wau.nl/public/Product/software.htm	The MET toolbox provides information on models and other tools required in the implementation of the Water Framework Directive (WFD) and helps model users to select appropriate tools for their specific needs. The Model Catalogue provides information on the characteristics of various models, specifically designed for questions and problems arising in the context of the WFD.

Tool name	EUROHARP	Standardisation of River Classifications
Acronym	EUROHARP	STAR
Description	The Toolbox provides factual and searchable information on the nine quantification tools (models) and the 17 European catchments tested within the EUROHARP project.	Framework method for calibrating different biological survey results against ecological quality classifications to be developed for the Water Framework Directive
Website	http://euroharp.org/index.htm	http://www.eu-star.at/
Objective	The primary objective is to provide end users (national and international European environmental policy-makers) with a thorough scientific evaluation of nine contemporary Quantification Tools for diffuse losses.	Supporting multidisciplinary teams in projects that use models for water management
Additional information	Quantification Tools within this framework are methodologies for quantifying diffuse losses of nutrients (N and P) from land sources to surface waters. They range from simple empirical and statistical models to more advanced scientific process-based models. Different Quantification Tools have been developed in different countries. They vary significantly in their (i) level of complexity, (ii) representation of system processes and pathways, and (iii) resource requirements (data and time). Quantification Tools should aim to be accurate and responsive to changes in land use and land management. Furthermore, they should be influenced by geophysical factors (topography, hydrology), biochemical factors (soils) and climatic factors (rainfall, temperature), as well as providing end users (policy-makers, implementers and evaluators) with information at appropriate time scales to assess compliance with remediation measures.	The STAR software comprises programs for - data storage and the evaluation of hydromorphological features (STAR RHS) - data storage and the evaluation of macrophyte samples (STAR MTR) - data storage of invertebrate and diatom samples (AQEMdip) - metrics calculation and the data evaluation of invertebrate samples (AQEM European Stream Assessment Program) - uncertainty/error estimation for assessments of ecological status class based on multiple metrics and EQRs (STARBUGS) - guidance in devising monitoring programmes (MONSTAR)

Title	Acronym
FP VI
A Regional Model for Integrated Water Management in Twinned River Basins	RIVERTWIN
Development and Testing of Practical Guidelines for the Assessment of Environmental and Resource Costs and Benefits in the WFD	AQUAMONEY
Groundwater Artificial recharge Based on Alternative sources of wateR: aDvanced INtegrated technologies and management	GABARDINE
Integrated decision support system for risk assessment and management of the water-sediment-soil system at river basin scale in fluvial ecosystems	RAMWASS
Integrated Project to Evaluate the Impacts of Global Change on European Freshwater Ecosystems	EURO-LIMPACS
Mitigation of Water Stress through new Approaches to Integrating Management, Technical, Economic and Institutional Instruments	AQUASTRESS
New Approaches to Adaptive Water Management under Uncertainty	NEWATER
Participatory multi-Level EO-assisted tools for Irrigation water management and Agricultural Decision-Support	PLEIADeS
Science-Policy Interfacing in support of the Water Framework Directive implementation	Spi-Water
Understanding river-sediment-soil-groundwater interactions for support of management of waterbodies (river basin & catchment areas)	AQUATERRA
Water scenarios for Europe and for neighbouring states	SCENES
System for Environmental and Agricultural Modelling; Linking European Science and Society	SEAMLESS
FP V
A decision support system to quantify cost/benefit relationships of the use of vegetation in the management of heavy metal polluted soils and dredged sediments	PhytoDec
Afforestation management in North-Western Europe - influence on nitrogen leaching, groundwater recharge, and carbon sequestration	AFFOREST
An environmental soil test to determine the potential from sediment and phosphorus transfer in run-off from agricultural land	DESPRAL
Analysis, synthesis and transfer of knowledge and tools on hydrological drought assessment through a European Network	ASTHyDA
ARID CLUSTER: Strengthening complementarity and exploitation of results of related RTD projects dealing with water resources use and management in arid and semi-arid regions	ARID
Benchmark models for the Water Framework Directive	BMW
Computer aided rehabilitation of water networks	CARE-W
Data assimilation within a unifying modeling framework for improved river basin water resources management	DAUFIN
Developing strategies for regulating and managing water resources and demand in water deficient regions	WaterStrategyMan
European water management between regulation and competition	AQUALIBRIUM
European water regimes and the notion of a sustainable status	EUWARENESS
Evaluation and improvement of water quality models for application to temporary waters in southern European catchments	TempQsim
Evaluation of alternative techniques for determination of water budget components in water-limited, heterogeneous land-use systems	WATERUSE
Floodplain biodiversity and restoration 2: integrated natural science and socio-economic approaches to catchment flow management	FLOBAR2
Freshwater integrated resource management with agents	FIRMA
Guidelines for the organisation, use and validation of information systems for evaluating aquifer resources and needs	GOUVERNE
Harmonised modelling tools for integrated basin management	HarmoniCA
Harmonised techniques and representative river basin data for assessment and use of uncertainty information in integrated water management	HarmoniRiB
Harmonising collaborative planning	HarmoniCOP
Harmonising quality assurance in model-based catchment and river basin management	HarmoniQuA
Human effects on nutrient cycling in fluvial ecosystems: development of an expert system to assess stream water quality management at reach scale.	STREAMES
Integrated assessment tools to gauge local functional status within freshwater ecosystems	TARGET
Integrated evaluation for sustainable river basin governance	ADVISOR
Integrated nitrogen model for European catchments	INCA

ABM	Averting Behaviour Models
AES	Agri-Environment Schemes
BMPs	Best Management Practices
CAP	Common Agricultural Policy
CR	Contingent Ranking
CSIRO	Commonwealth Scientific and Industrial Research Organisation
CV	Contingent Valuation
DPSIR	Driving forcePressureStateImpactResponse
DS	Decision Support
DSS	Decision Support Systems
EEA	European Environment Agency
EU	European Union
FADN	The Farm Accountancy Data Network
FAO	Food and Agriculture Organization of the United Nations
GFP	Good Farming Practices
GIS	Geographic Information Systems
GUI	Graphical User Interface
HPM	Hedonic Pricing Models
ICT	Information and Communication Technology
IT	Information Technology
K	Potash (potassium)
MCA	Multi-Criteria Analysis
MCDA	Multi-Criteria Decision Analysis
N	Nitrogen
NGO	Non-Governmental Organisation
P	Phosphorous
PC	Personal Computer
PEC	PEsticides Concentration
RB	River Basin

RBMP	River Basin Management Plans
RD	Rural Development
RDM	Recreational Demand Methods
RUSLE	Revised Universal Soil Loss Equation
SDSS	Spatial Decision Support Systems
SFP	Single Farm Payment
SPS	Single Payment Scheme
TEU	Treaty of the European Community
TMDLs	Total Maximum Daily Loads
USDA-ARS	United States Department of Agriculture-Agriculture Research Service
USEPA	United States Environmental Protection Agency
USLE	Universal Soil Loss Equation
WFD	Water Framework Directive
WTA	Willingness To Accept
WTP	Willingness To Pay

Issue	Standards
Soil erosion: protect soil through appropriate measures	Minimum soil cover Minimum land management reflecting site-specific conditions Retain terraces
Soil organic matter: maintain soil organic matter levels through appropriate practices	Standards for crop rotations where applicable Arable stubble management
Soil structure: maintain soil structure through appropriate measures	Appropriate machinery use
Minimum level of maintenance: ensure a minimum level of maintenance and avoid the deterioration of habitats	Minimum livestock stocking rates or/and appropriate regimes Protection of permanent pasture Retention of landscape features Avoidance of the encroachment of unwanted vegetation on agricultural land

Methods	Assumption
Market	Prices for goods and services traded in markets capture environmental values.
Cost-based valuation	Costs of maintaining an environmental benefit is a reasonable estimation of preventive and/or mitigation measures[51].
Revealed preference	Environmental values can be indirectly inferred via econometric approaches from observed behaviours. This group includes: Recreational Demand Methods (RDM): recreation is a function of the quality of the environment. Improvements to or deterioration in good (water) quality may enhance or reduce recreational opportunities (e.g. number of visits in a given period). Hedonic Pricing Models (HPM) require the existence of a linked market (e.g. real estate that capture environmental values). Averting Behaviour Models (ABM) are when people adopt defensive behaviour in response to environmental damage (e.g. new filter for water).
Stated preference	Values[52] are inferred directly, eliciting consumer preference on either hypothetical or experimental markets. Methods include: Contingent Valuation (CV). Contingent Ranking (CR).