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

• 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

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，汇集了：- 一个重量轻但功能强大的预报系统，利用美国航天局土壤湿度数据进行最先进的地表数据同化----预报可视化和交流的新方法，与非洲的农民共同开发通过预警和激励预测行动建立复原力的社会经济研究该项目将由阅读大学领导，该项目是与加纳的一所著名大学夸梅·恩克鲁玛科技大学（KNUST）和一个历史悠久的非政府组织“发展证据”合作开展的。农业干旱对世界上最贫穷社区的影响可能是毁灭性的。气候变化导致的天气模式变化可能意味着根据近年来的天气经验决定何时种植和如何管理作物是不可靠的。及时预测农业干旱可能性的发展，有可能在发生干旱时对小规模农户及其周围社区的生活产生重大的积极影响。ERADACS项目将开发一个农业干旱预报系统，利用多个卫星数据流、气象局陆面模型（JULES）和最先进的数学技术（数据同化）将这些数据流结合起来。由此产生的预报将利用TAMSAT 30年数据记录中的气候信息来预测降雨的可能轨迹。这些季节性预报将在加纳各地制作，并通过TAMSAT网站公开提供。在ERADACS项目的生命周期之后，我们将通过运行中的TAMSAT平台维持预报系统。ERADACS项目的一个关键方面将是一个试点，以了解这些信息如何对加纳依赖自给农业做法的特定社区有用。我们将访问和收集一些社区的社会经济信息，以确定他们对农业干旱的脆弱性，并使用严肃的游戏来引出可能的反应。我们的预测及其可能的不确定性将与农民讨论，我们将尝试不同的方法来呈现这些数据。我们会根据这些组织的意见，改善沟通方法，并根据预报系统所提供的资料，作出适当的调整。加纳的工作将由KNUST和发展证据组织开展，这两个组织在非洲能力建设方面都有多年的经验。

项目成果

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
• 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

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