Pathogen Risks in Agricultural Catchments: Towards International Collaboration And Learning in Modelling (PRACTICAL Modelling)

农业流域的病原体风险：建模方面的国际合作和学习（实用建模）

• 批准号: NE/M005860/1
• 负责人: David Oliver
• 金额: $ 4.77万
• 依托单位: University of Stirling
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FM005860%2F1
• 关键词: Pathogen; Risks; Agricultural; Catchments; Towards

Around the world the prediction of microbial water pollution is important for informing policy decisions in order to safeguard human health. However, modelling the fate and transfer of microbial pollutants, such as E. coli (& other pathogens) at different spatial scales poses a considerable challenge to the research and policy community. In the UK much research has focused on trying to understand the movement & survival of pathogens in environmental systems with a view that better knowledge and data on the behavioural characteristics of these micro-organisms will improve our ability to model and predict their interactions with, and responses to, the world around us. The NERC-funded project ReMOFIO (NE/J004456/1) provides an example of research undertaken in the UK to improve our understanding of the magnitude and spatial distribution of microbial risks in the landscape. In turn, this new knowledge has enabled the refinement of a simple modelling framework to allow for improved prediction of microbial risk on agricultural land, based on livestock numbers, farming practices and E. coli survival patterns under environmental conditions (e.g. rainfall and temperature fluctuations). However, our model is built using data common to the UK; this International Opportunity Fund (IOF) will allow us to test the NERC funded ReMOFIO model in landscapes typical of different catchment systems around the world and to determine how transferable the approach is beyond the UK in order to evaluate its global relevance.To do this we will use the 'PRACTICAL Modelling' IOF to establish a new international partnership, with the UK acting as a 'junction-box' connecting data and modelling skills from across Ireland, New Zealand and the USA. We have enlisted the expertise (and associated catchment data and modelling approaches) of three leading international scientists, in addition to other UK experts, in order to evaluate the wider application of data emerging from the ReMOFIO project. We will also investigate the potential for other models and tools to be linked to the ReMOFIO model to see if, conceptually, we can develop a more holistic model that becomes bigger than the sum of its internationally disparate parts. Part of our assessment will focus on the strengths and weaknesses of different modelling approaches that are currently being applied to assess pathogen risks in agricultural catchments. We will consider the transferability of these different approaches across contrasting agricultural systems typical of the UK, US, Ireland and New Zealand with a focus on the inherent differences in catchment characteristics (natural, managed, engineered and socio-economic), uncertainties of the underpinning data provided by international colleagues, and how these factors might impact on our ability to adopt or combine international modelling platforms.Ultimately, our international partnership will explore key questions that challenge scientists working in the field of microbial pollution from agriculture: how do the different pathways in the soil, that connect pathogen sources to water bodies, vary in space & time across different catchment types & how does this impact on microbial travel times through the environment; to what extent does the probability of pathogen die-off vary for different environmental conditions around the world; how do we integrate pathogen behavioural characteristics (e.g. their ability to persist or move in the environment) into risk-based models that are useful for policy-makers; and how will the export of microbial pollutants from the landscape alter under projected climate change? The PRACTICAL Modelling project will begin to tackle these important questions using an international forum and, collectively, we will develop a global 'roadmap' of research priorities and needs required for a co-ordinated response to improve the prediction of microbial risks in agricultural landscapes.

在世界各地，微生物水污染的预测对于为政策决策提供信息以保障人类健康非常重要。然而，对不同空间尺度的微生物污染物（例如大肠杆菌（及其他病原体））的命运和转移进行建模对研究和政策界提出了相当大的挑战。在英国，许多研究都集中在试图了解病原体在环境系统中的运动和生存，以便更好地了解这些微生物的行为特征和数据，从而提高我们建模和预测它们与环境系统中的相互作用的能力。对我们周围世界的反应。 NERC 资助的项目 ReMOFIO (NE/J004456/1) 提供了在英国进行的研究的一个例子，该研究旨在提高我们对景观中微生物风险的程度和空间分布的理解。反过来，这些新知识使简单的建模框架得以完善，以便根据环境条件（例如降雨和温度波动）下的牲畜数量、农业实践和大肠杆菌生存模式，改进对农田微生物风险的预测。然而，我们的模型是使用英国通用的数据构建的；该国际机会基金 (IOF) 将使我们能够在世界各地不同流域系统的典型景观中测试 NERC 资助的 ReMOFIO 模型，并确定该方法在英国以外的可移植性，以评估其全球相关性。为此，我们将利用“实用建模”IOF 建立新的国际合作伙伴关系，英国将充当连接爱尔兰、新西兰和美国各地数据和建模技能的“接线盒”。除了其他英国专家之外，我们还聘请了三位领先的国际科学家的专业知识（以及相关的流域数据和建模方法），以评估 ReMOFIO 项目中出现的数据的更广泛应用。我们还将研究其他模型和工具与 ReMOFIO 模型相关联的潜力，看看从概念上讲，我们是否可以开发一个更全面的模型，该模型比其国际上不同部分的总和还要大。我们评估的一部分将重点关注目前用于评估农业流域病原体风险的不同建模方法的优缺点。我们将考虑这些不同方法在英国、美国、爱尔兰和新西兰典型农业系统中的可转移性，重点关注流域特征（自然、管理、工程和社会经济）的内在差异、基础的不确定性国际同事提供的数据，以及这些因素如何影响我们采用或结合国际建模平台的能力。最终，我们的国际合作伙伴关系将探讨挑战农业微生物污染领域科学家的关键问题：不同的途径如何影响在土壤中，即将病原体源与水体连接起来，不同流域类型的空间和时间有所不同，这对微生物在环境中的传播时间有何影响；世界各地不同环境条件下病原体死亡的概率有多大差异；我们如何将病原体的行为特征（例如它们在环境中持续存在或移动的能力）整合到对政策制定者有用的基于风险的模型中；在预计的气候变化下，景观中微生物污染物的输出将如何变化？实用建模项目将开始利用国际论坛来解决这些重要问题，并且我们将共同制定一个全球研究优先事项和需求的“路线图”，以协调应对，以改进对农业景观中微生物风险的预测。

项目成果

Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments

• DOI: 10.1016/j.scitotenv.2015.11.086
• 发表时间: 2016-02-15
• 期刊: SCIENCE OF THE TOTAL ENVIRONMENT
• 影响因子: 9.8
• 作者: Oliver, David M.;Porter, Kenneth D. H.;Quilliam, Richard S.
• 通讯作者: Quilliam, Richard S.