A collaborative process of developing mathematical models for water quality management

在英国农村社区在管理国家自然资源方面面临相当大的挑战的情况下，通过合作和可持续的进程开发数学模型，以便在水质管理的背景下提供决策支持。粮食系统的长期可持续性是英国政府粮食战略的核心问题1，而欧盟水框架指令(WFD；2000/60/EC)要求在2015年前使该国大部分水体保持“良好”的生态状况。这些国家政策优先事项和环境立法制约因区域关切而得到加强，包括农村景观的娱乐价值、农村社区的生活质量和健康、农村企业和农村就业的生存能力，特别是在食品生产和旅游业以及生物多样性方面。除私营和公共部门的责任和任务外，志愿部门在谈判和满足相互冲突的需要方面尤其重要3。巨大的压力和复杂的环境需要科学的工具来支持自然资源的管理。通过使复杂性变得可理解和可管理，数学模型对于实现这一目标至关重要。然而，越来越多的证据表明，仅从研究角度开发的模型往往不会在实践中使用4，尤其是因为1 Defra(2010)。粮食2030年。Http://www.defra.gov.uk/foodfarm/food/pdf/food2030strategy.pdf(24.05.2010)；取决于新政府的政策和优先事项2 REU(2005年)。正在展开的研究议程。Http://www.relu.ac.uk/news/briefings/RELU Brief3 24pp.pdf(24.05.2010)3史密斯、L.E.D.、H.库克、A.Inman、D.Benson和A.Jordan(2010年)。下沉还是游泳？调查英格兰和威尔士的社区集水区组织。水与环境2010，CIWEM年会，4月28-29日，伦敦，UK4 Nilsson，M.，A.Jordan，J.Turnpenny，J.Hertin，B.Nykvist和D.Russel(2008)。公共政策制定中政策评估工具的使用和不使用：对三个欧洲国家和欧盟的分析。政策科学41(4)：335-355第13页，最终用户期望与可交付成果模型之间的不一致。申请者目前由英国研究委员会资助的研究表明，如果采用一种新的合作模型开发过程，其中产品是根据最终用户的需求量身定做的，并且涉及到决策和交付必要行动的关键利益相关者，这种情况可以扭转5。这一过程确保了模型的可信度和科学严谨性，允许通过结合利益相关者的知识来改进模型，并从那些决定或受决策影响的人那里建立对模型的信任。存在着相当多的知识经济机会，可以转移这一模式开发的合作进程，加强公共部门和志愿部门的能力，并在研究机构和这些部门之间建立长期关系，以确保这一进程的可持续性。

Transferring a collaborative and sustainable process of developing mathematical models for decision support in the context of water quality managementRural communities in the UK face considerable challenges in managing the country’s natural resources. Long-term sustainability of the food system is a central concern of the UK Government’s food strategy1, whereas the EU Water Framework Directive (WFD; 2000/60/EC) demands ‘good’ ecological status of most of the country’s water bodies by 2015. These national policy priorities and environmental legislation constraints are augmented by regional concerns, including the recreational value of the rural landscape, the quality of life and the health of rural communities, the viability of rural businesses and rural employment, especially in food production and tourism, and biodiversity2. Along with the responsibilities and mandates of the private and public sectors, the voluntary sector in particular is seen as important in negotiating and meeting conflicting needs3. The multitude of pressures and the complexity of the environment require scientific tools to support the management of natural resources. Mathematical models are essential for achieving this by making complexity comprehensible and manageable. However, there is growing evidence that models developed from a research perspective alone are often not used in practice4, not least because of1 Defra (2010). Food 2030. http://www.defra.gov.uk/foodfarm/food/pdf/food2030strategy.pdf (24.05.2010); subject to policies and priorities of the new government2 RELU (2005). The Unfolding Research Agenda. Rural Economy and Land Use Programme Briefing Series No. 3. http://www.relu.ac.uk/news/briefings/RELU%20Brief3%2024pp.pdf (24.05.2010)3 Smith, L. E. D., H. Cook, A. Inman, D. Benson and A. Jordan (2010). Sinking or swimming? Surveying community based catchment groups in England and Wales. Water and Environment 2010, CIWEM’s Annual Conference, April 28th-29th, London, UK4 Nilsson, M., A. Jordan, J. Turnpenny, J. Hertin, B. Nykvist and D. Russel (2008). The use and non-use of policy appraisal tools in public policy making: an analysis of three European countries and the European Union. Policy Sciences 41(4): 335-355Page 3 of 13incoherence between end-user expectations and model deliverables. Current UK Research Councils-funded research by the applicants shows that this situation can be reversed if a novel collaborative process of model development is adopted where the product is tailored to the end-user needs and those stakeholders key in making decisions and delivering the necessary actions are involved5. This process ensures credibility and scientific rigour of models, allows improvement of models by incorporating stakeholder knowledge, and builds trust in models from those deciding or affected by the decisions. Considerable KE opportunities exist for transferring this collaborative process of model development, strengthening capacity in the public and voluntary sectors to take it up, and building long-term relationships between research institutions and these sectors to ensure sustainability of the process.