Hazards SEES: Understanding Cross-Scale Interactions of Trade and Food Policy to Improve Resilience to Drought Risk

Hazards SEES：了解贸易和粮食政策的跨尺度相互作用，以提高对干旱风险的抵御能力

• 批准号: 1832393
• 负责人: Lyndon Estes
• 金额: $ 156.32万
• 依托单位: Clark University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-11-17 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832393&HistoricalAwards=false
• 关键词: Hazards; SEES; Understanding; Cross; Scale

Food security in regions affected by drought is influenced by a complex set of interactions between hydrological, agricultural, and social systems. Previous models examining the impact of drought on food security have not incorporated food trade and food movements at fine spatial scales, yet these components are critical parts of regional food systems. In sub-Saharan Africa droughts and floods account for approximately 80% of fatalities and 70% of the economic losses that are due to natural hazards. Zambia is particularly vulnerable to droughts, having high levels of malnutrition, poverty, income inequality, exposure to HIV/AIDS and malaria, and low levels of educational attainment. Zambia's agricultural production is rain-fed, which further increases vulnerability in the region. With the extreme vulnerability of the region, Zambia serves as an ideal place to study how the interactions between drought risk, crop production, trade, and policy affect food security. By incorporating the effects of trade and policy into predictive hydrological and agricultural models, this project is improving existing early warning systems for famine which rarely assess the capacity for a region to ameliorate drought via food transfers and trade. This project's goal is to understand the effect of drought hazards in subsistence agriculture using a novel integrative framework that merges data, models, and knowledge of drought risk and crop production; their interactions with the dynamics of trade-based and aid-based responses; and their effect on household food security and consumption. We are addressing three questions: 1) What are the spatio-temporal scales of drought risk across Zambia and how does risk transfer into agricultural impacts? 2) What is the role of trade and domestic food policy on food security at local to national levels? 3) Can drought impacts be more effectively reduced by integrating an understanding of policy and food transfers into an agricultural drought early warning system? To answer these questions, we are collecting biophysical data to characterize historical droughts and their impacts on regional agriculture; examining household and market level data to characterize food security outcomes, market prices, and food sourcing; using complex network analysis to characterize food trade and flows; assessing market integration associated with price fluctuations and infrastructure to determine economic exposure and resilience at the household, community and district levels; examining how policies at the national scale constrain decisions at the local scale; and developing computational models for high resolution predictions and to explore probabilistic solutions for resource allocation and risk management. This project is the first to create an integrated model of food trade, household consumption and crop production at such fine spatial scales built on an empirical foundation in each dimension.

受干旱影响地区的粮食安全受到水文、农业和社会系统之间一系列复杂相互作用的影响。以前研究干旱对粮食安全影响的模型没有在精细的空间尺度上纳入粮食贸易和粮食流动，但这些组成部分是区域粮食系统的关键部分。在撒哈拉以南非洲，干旱和洪水约占自然灾害造成的死亡人数的80%和经济损失的70%。赞比亚特别容易受到干旱的影响，营养不良、贫困、收入不平等、艾滋病毒/艾滋病和疟疾感染率高，受教育程度低。赞比亚的农业生产依靠雨水，这进一步增加了该地区的脆弱性。由于该地区的极端脆弱性，赞比亚是研究干旱风险、作物生产、贸易和政策之间的相互作用如何影响粮食安全的理想场所。通过将贸易和政策的影响纳入预测水文和农业模型，该项目正在改进现有的饥荒预警系统，这些系统很少评估一个地区通过粮食转移和贸易改善干旱的能力。该项目的目标是利用一种新的综合框架，将干旱风险和作物生产的数据、模型和知识结合起来，了解干旱灾害对自给农业的影响；它们与以贸易和援助为基础的反应动态的相互作用；以及它们对家庭粮食安全和消费的影响。我们正在解决三个问题：1)赞比亚干旱风险的时空尺度是什么？风险如何转化为农业影响？2)贸易和国内粮食政策在地方和国家层面对粮食安全的作用是什么？3)将对政策和粮食转移的理解纳入农业干旱预警系统，是否能更有效地减少干旱的影响？为了回答这些问题，我们正在收集生物物理数据来描述历史干旱及其对区域农业的影响；检查家庭和市场层面的数据，以确定粮食安全结果、市场价格和粮食来源的特征；利用复杂网络分析表征食品贸易和流动；评估与价格波动和基础设施相关的市场一体化，以确定家庭、社区和地区各级的经济风险和复原力；研究国家层面的政策如何制约地方层面的决策；开发高分辨率预测的计算模型，探索资源分配和风险管理的概率解决方案。该项目是第一个在如此精细的空间尺度上创建食品贸易、家庭消费和作物生产的综合模型，该模型建立在每个维度的经验基础之上。