Enhancing Resilience to Agricultural Drought in Africa through Improved Communication of Seasonal Forecasts (ERADACS)

通过改进季节性预报通信 (ERADACS) 增强非洲农业干旱的抵御能力

基本信息

批准号：
NE/P015352/1
负责人：
Tristan Quaife
金额：
$ 20.12万
依托单位：
University of Reading
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%2FP015352%2F1
关键词：
Enhancing Resilience Agricultural Drought Africa

项目摘要

ERADACS is a novel, multi-disciplinary project that brings together: - a light-weight but powerful forecast system, state-of-the-art land surface data assimilation using NASA soil moisture data - new methods for visualizing and communicating forecasts, co-developed with farmers in Africa- socioeconomic studies on building resilience through early warning and incentivizing action on forecastsThe project will be led by the University of Reading and carried out in partnership the Kwame Nkrumah University of Science and Technology (KNUST), a leading Ghanaian university; and Evidence for Development, a well-established NGO.The impact of agricultural drought on the world's poorest communities can be devastating. Changes in weather patterns due to changing climate can mean that decisions about when to plant and how to manage crops based on experience of weather in recent years are not reliable. Timely forecasts of the developing likelihood of agricultural drought have the potential to have a significant positive impact on the lives of small-scale farmers and their surrounding communities during such events. The ERADACS project will develop a forecast system for agricultural drought using multiple streams of satellite data, the Met Office land surface model (JULES) and state-of-the-art mathematical techniques (Data Assimilation) to combine these. The resulting forecast will use climatological information from the 30 year TAMSAT data record to predict likely trajectories of rainfall. These seasonal forecasts will be produced across Ghana and made available openly via the TAMSAT website. Beyond the lifetime of the ERADACS project we will sustain the forecast system via the operational TAMSAT platform. A key aspect of the ERADACS project will be a pilot of how this information might be useful to specific communities in Ghana that are reliant on subsistence farming practices. We will visit and collect socioeconomic information from a number of communities to establish their vulnerability to agricultural drought as well as using serious game play to elicit likely responses. Our forecasts, and their likely uncertainties, will be discussed with the farmers and we will trial different methods of presenting this data. We will use feedback from these groups to refine the means of communication and to tailor the information produced from the forecast system. The work in Ghana will be carried out by KNUST and Evidence for Development, both of whom have many years experience of capacity building in Africa.

Eradacs是一个新颖的多学科项目，汇集在一起： - 一种使用NASA泥浆水分数据的轻巧但有力的预测系统，最先进的陆地表面数据同化 - 用于可视化和沟通的新方法，可视化和交流，通过与早期的工艺发展进行探索，并与农民共同开发，并在较早的工程上进行探索，并在劳动上进行探索，并在沃尔德上进行了探索，从而实现了早期的稳定性，使得逐渐实现稳定的范围，以实现较大的努力，使其在沃克上的稳定性，并不与加纳大学领先的大学（KNUST）合作进行了合伙企业。以及发展的证据，一个公认的非政府组织。农业干旱对世界上最贫穷社区的影响可能是毁灭性的。由于气候变化而导致的天气模式的变化可能意味着近年来根据天气经验来管理何时种植以及如何管理农作物的决策是不可靠的。及时预测农业干旱的发展可能性有可能在此类事件中对小型农民及其周围社区的生活产生重大积极影响。 ERADACS项目将使用多个卫星数据，MET办公室地面模型（Jules）和最先进的数学技术（数据同化）来开发一种用于农业干旱的预测系统。由此产生的预测将使用TAMSAT数据记录30年的气候信息，以预测可能的降雨轨迹。这些季节性预测将在加纳各地进行，并通过Tamsat网站公开提供。除了ERADACS项目的一生之外，我们还将通过操作Tamsat平台维持预测系统。 ERADACS项目的一个关键方面将是该信息如何对加纳的特定社区有用的试点，这些社区依赖于生存耕作实践。我们将访问并收集许多社区的社会经济信息，以建立他们对农业干旱的脆弱性，并使用认真的游戏来引起可能的回应。我们的预测及其可能的不确定性将与农民讨论，我们将试用不同的方法来介绍此数据。我们将使用这些小组的反馈来完善交流手段，并调整预测系统中产生的信息。加纳的工作将由诺斯特（Knust）和发展证据进行，他们在非洲都有多年的能力建设经验。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

TAMSAT-ALERT v1: A new framework for agricultural decision support

TAMSAT-ALERT v1：农业决策支持的新框架

DOI：
10.5194/gmd-2017-316
发表时间：
2018
期刊：
影响因子：
0
作者：
Asfaw D
通讯作者：
Asfaw D

Impact of remotely sensed soil moisture and precipitation on soil moisture prediction in a data assimilation system with the JULES land surface model

DOI：
10.5194/hess-22-2575-2018
发表时间：
2018-04
期刊：
Hydrology and Earth System Sciences
影响因子：
6.3
作者：
E. Pinnington;T. Quaife;E. Black
通讯作者：
E. Pinnington;T. Quaife;E. Black

A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa.

DOI：
10.1038/sdata.2017.63
发表时间：
2017-05-23
期刊：
Scientific data
影响因子：
9.8
作者：
Maidment RI;Grimes D;Black E;Tarnavsky E;Young M;Greatrex H;Allan RP;Stein T;Nkonde E;Senkunda S;Alcántara EMU
通讯作者：
Alcántara EMU