Real-time predictions of pesticide run-off risk which: multi-scale visualisations of water quality risks and costs

农药流失风险的实时预测：水质风险和成本的多尺度可视化

• 批准号: NE/P007988/1
• 负责人: Alexis Comber
• 金额: $ 25.74万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FP007988%2F1
• 关键词: Real; time; predictions; pesticide; run

This Research Translation Project develops a proof of concept to tests the value of real-time predictions of agro-chemical run-off risk at two scales of decision making: field scale for on farm decisions about agro-chemical applications risk and catchment scale for water company groundwater abstraction decisions. Agro-chemicals (fertilisers, pesticides, herbicides, etc) are less effective if they are washed away soon after they are applied. They can also negatively affect ground water quality and the environment. The farmer may have to re-apply the agro-chemical and water companies may have treat groundwater to meet drinking water quality standards, and in some cases change water abstraction locations. For both farmers and water companies additional costs are incurred. This project develops proofs of concept for 2 web-mapping tools to model the risk associated with agro-chemical applications: a catchment-scale tool to support water company decision making and a field-scale tool to support farmer decision making. Both tools combine live, real-time data from the Met Office on rainfall type and probability with landscape models of underlying soil, landform, drainage, land use etc. in order to model agro-chemical runoff risk. User-groups will feedback their experiences about the operational use and functionality of the tools to provide information for the modelling and programming teams to adjust the background engine and front-end functionality. The project outputs will include the specification of for national decision tools, targeted at farmers and water companies, to quantify the risks associated with a full set of common agro-chemical applications designed be accessed using desktop PCs and smartphones. Key Words: Agro-chemical run-off, water quality, environmental riskStakeholders: Defra, farmers, water companies, AHDB, SARIC members

该研究翻译项目开发了概念证明，以测试两种决策规模的农业化学径流风险的实时预测的价值：关于农场关于农业化学应用风险和水流规模的农场决策的现场规模公司地下水抽象决策。如果农业化学物质（肥料，农药，除草剂等）在施用后不久就被洗掉了，则效果不佳。它们还会对地下水质量和环境产生负面影响。农民可能不得不重新应用农业化学，水公司可能已经对地下水进行治疗以满足饮用水质量标准，在某些情况下，会改变抽象地点。对于农民和供水公司而言，额外的费用都会产生。该项目为2个网络映射工具开发了概念证明，以建模与农业化学应用相关的风险：一种支持水公司决策的集水区尺度工具和一种用于支持农民决策的现场规模工具。这两种工具都结合了来自大都会降雨类型的现场实时数据以及概率的实时数据，以及景观模型，土壤，地形，排水，土地利用等，以模拟农业化学径流风险。用户组将反馈他们关于工具的操作用途和功能的经验，以为建模和编程团队提供信息，以调整背景引擎和前端功能。该项目的输出将包括针对农民和水公司的国家决策工具的规范，以量化与全套通用农业化学应用相关的风险，并使用台式PC和智能手机访问。关键词：农业化学径流，水质，环境风险利益相关者：Defra，农民，水公司，AHDB，SARIC成员

项目成果

A Generic Approach for Live Prediction of the Risk of Agricultural Field Runoff and Delivery to Watercourses: Linking Parsimonious Soil-Water-Connectivity Models With Live Weather Data Apis in Decision Tools

实时预测农田径流和向水道输送的风险的通用方法：将简约的土壤-水-连通性模型与决策工具中的实时天气数据 API 联系起来

• DOI: 10.3389/fsufs.2019.00042
• 发表时间: 2019
• 期刊: Frontiers in Sustainable Food Systems
• 影响因子: 4.7
• 作者: Comber A

Peri-urbanization may vary with vegetation restoration: A large scale regional analysis

• DOI: 10.1016/j.ufug.2017.11.006
• 发表时间: 2018-01-01
• 期刊: URBAN FORESTRY & URBAN GREENING
• 影响因子: 6.4
• 作者: Fu, Wei;Lu, Yihe;Wu, Lianhai
• 通讯作者: Wu, Lianhai

Gauging policy-driven large-scale vegetation restoration programmes under a changing environment: Their effectiveness and socio-economic relationships.

• DOI: 10.1016/j.scitotenv.2017.07.044
• 发表时间: 2017-12
• 期刊: The Science of the total environment
• 作者: Ting Li;Y. Lü;B. Fu;A. Comber;P. Harris;Lianhai Wu

When multi-functional landscape meets Critical Zone science: advancing multi-disciplinary research for sustainable human well-being.

• DOI: 10.1093/nsr/nwy003
• 发表时间: 2019-03
• 期刊: National science review
• 影响因子: 20.6
• 作者: Luo Y;Lü Y;Fu B;Harris P;Wu L;Comber A
• 通讯作者: Comber A