Bridging the Knowledge Gap through Documenting Indigenous Early warning indicators in areas prone to climate-induced natural disasters in Zimbabwe

这项拟议的研究是一个后续项目，该项目的目的是清点津巴布韦Chimanimani，Chipinge和Buhera地区受飓风Idai影响的非物质文化遗产（ICH）资产。非物质文化遗产项目的一项调查结果是，就在飓风发生之前，在受影响的社区看到了一些当地的预警指标，但不幸的是，没有人注意到，他们无意中忽视了这些信号，或者正如叙述所描述的那样，其中一些人未能解释大自然发出的警告。忽视土著警报或信号的主要原因是对土著预警指标缺乏了解。因此，本研究建议进一步调查津巴布韦易受气候引起的自然灾害影响地区的土著预警指标。多年来，该项目的研究地点被观察到是脆弱的地区，包括Chimanimani、Chipinge和Buhera，这些地区容易发生飓风，而Muzarabani、Mbire和Binga地区则容易发生干旱。据报告，大自然会在灾害发生之前发出信号或警告，这一点在关于世界不同地区土著知识和预警系统的文献中得到了证实，例如，豪厄尔（2003年）关于孟加拉国;奥卢奇里（2019年）关于肯尼亚;环境署（2007年）关于斯威士兰、肯尼亚、印度尼西亚、泰国、日本等。因此，文献中有大量证据表明，存在着因地理区域而异的土著预警指标。拟议的研究旨在记录津巴布韦已确定地区的预警指标，目的是提供对预警指标的宝贵见解，并通过弥补当地在预警方面的知识差距来建设能力，使当地社区能够解释这些指标并采取适当行动。这些本地化的预警指标将纳入小学、中学和大学的政策和课程主流，拟议的研究将通过四（4）个工作包实施，这些工作包与目标部分概述的四（4）个目标相关联。工作包包括：（i）在六个地区编制本地预警指标清单（二）开发一个学习模块，包括制作一个纪录片录像，使用已确定的气候引起的自然灾害的土著预警指标，并促进将该模块纳入初级教育，（三）开发一个移动的或电子应用程序，以帮助传播和提高社区对已确定的津巴布韦气候引起的自然灾害的土著预警指标的认识，㈣促进将气候引起的自然灾害的本地预警指标纳入减少风险框架该研究将通过按性别分列的重点小组讨论、与社区中确定的知情成员进行的关键信息提供者访谈、利益攸关方讲习班和协商会议，进行定性调查和数据收集。所有讨论和访谈都将以当地语言进行，并进行录音、逐字记录和翻译成英文。数据分析将采用专题分析。将制作纪录片。

This proposed study is a follow-on project to a just ended project whose aim was to inventory the intangible cultural heritage (ICH) assets affected by Cyclone Idai in Chimanimani, Chipinge and Buhera districts in Zimbabwe. One of the findings of the ICH project was that there were a number of indigenous early warning indicators which were witnessed in the affected communities just prior to the cyclone, but unfortunately no one took heed, they inadvertently ignored the signals or as the narratives portray, some of them failed to interpret the warning that nature was sending them. The main reason for ignoring the indigenous warnings or signals was lack of understanding of the indigenous early warning indicators. This study therefore proposes to investigate further the indigenous early warning indicators in areas prone to climate-induced natural disasters in Zimbabwe. The areas that will be the study sites for the project, which have been observed to be vulnerable over the years, are Chimanimani, Chipinge and Buhera, which are districts prone to cyclones and Muzarabani, Mbire, and Binga districts, which are prone to droughts. Nature has been reported to send signals or warnings before a disaster strikes as attested in literature on indigenous knowledge and early warning systems in different regions of the world, that is, Howell (2003) on Bangladesh; Oluchiri (2019) on Kenya; UNEP (2007) on Eswatini, Kenya, Indonesia, Thailand, Japan, among other examples. There is therefore ample evidence in the literature that there are indigenous early warning indicators which vary across geographical zones. The proposed study seeks to document early warning indicators in the identified areas in Zimbabwe with the aim of providing valuable insights into early warning indicators as well as building capacity by bridging the knowledge gap in the local areas in early warning so that the local communities are able to interpret them and take appropriate action. These localised early warning indicators will be mainstreamed into policy and curricula at primary, secondary and tertiary level.The proposed research will be implemented through four (4) work packages, which are linked to the four (4) objectives outlined in the objectives section. The work packages include; (i) inventorying indigenous early warning indicators in six districts (Buhera, Chimanimani, Chipinge, Mbire, Binga, and Muzarabani) prone to climate-induced natural disasters in Zimbabwe, (ii) development of a learning module, including producing a documentary video, using the identified indigenous early warning indicators for climate-induced natural disasters and facilitate the incorporation of the module into primary, secondary and tertiary curricula in Zimbabwe, (iii) development of a mobile or electronic application to help disseminate and sensitisation of communities on the identified indigenous early warning indicators for climate-induced natural disasters in Zimbabwe, and (iv) facilitation of the incorporation of indigenous early warning indicators for climate-induced natural disasters into the risk reduction framework (SENDAI Framework) used in Zimbabwe.The study will use qualitative enquiry and data collection through gender-separated focus groupdiscussions, key informant interviews with identified knowledgeable members of the community, stakeholder workshops and consultative meetings. All discussions and interviews will be conducted in the local language, recorded, transcribed verbatim and translated to English. Data analysis will employ a thematic analysis. A documentary will be produced.