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

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:
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
项目状态:
已结题
起止时间:
2017 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
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
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
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]
通讯作者: Comber A
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
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
DOI: 10.1016/j.scitotenv.2017.07.044
发表时间: 2017-12
期刊: The Science of the total environment
影响因子: --
作者: [Ting Li;Y. Lü;B. Fu;A. Comber;P. Harris;Lianhai Wu]
通讯作者: Ting Li;Y. Lü;B. Fu;A. Comber;P. Harris;Lianhai Wu
Modelling and managing critical zone relationships between soil, water and ecosystem processes across the Loess Plateau
  • 批准号:
    NE/N007476/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $8.21万
  • 财政年份:
    2016
  • 负责人:
    Alexis Comber
  • 依托单位:
Geographical Information Science (GIS). Masters Training Grant (MTG) to provide funding for 5 full studentships for two years.
  • 批准号:
    NE/H525697/1
  • 项目类别:
    Training Grant
  • 资助金额:
    $15.68万
  • 财政年份:
    2009
  • 负责人:
    Alexis Comber
  • 依托单位:
MSc Geographical Information Systems
  • 批准号:
    NE/E523213/1
  • 项目类别:
    Training Grant
  • 资助金额:
    $17.98万
  • 财政年份:
    2006
  • 负责人:
    Alexis Comber
  • 依托单位:
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SERS探针诱导TAM重编程调控头颈鳞癌TIME的研究
  • 批准号:
    82360504
  • 项目类别:
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  • 资助金额:
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  • 批准年份:
    2023
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    82305023
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    30万元
  • 批准年份:
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  • 负责人:
    王萌
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基于MRI的机器学习模型预测直肠癌TIME中胶原蛋白水平及其对免疫T细胞调控作用的研究
  • 批准号:
    --
  • 项目类别:
    面上项目
  • 资助金额:
    52万元
  • 批准年份:
    2022
  • 负责人:
    李文政
  • 依托单位:
结直肠癌TIME多模态分子影像分析结合深度学习实现疗效评估和预后预测
  • 批准号:
    62171167
  • 项目类别:
    面上项目
  • 资助金额:
    57万元
  • 批准年份:
    2021
  • 负责人:
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