DEVELOPMENT OF A NEAR REAL-TIME WARNING AGRICULTURAL SYSTEM FOR DISASTER PREDICTION

Abstract

The effects of disasters are not uniform across all individuals and communities. One’s preparedness and socioeconomic factors determine how much they will pay. Preparedness plays a crucial role in reducing the impact of disasters and aiding in their management and recovery. However, effectively preparing for unforeseen disasters becomes difficult when there is insufficient knowledge and expertise. Without accurate predictions and timely alerts about disasters, a community's level of readiness remains extremely low. Namibia has experienced various unavoidable climate-related dangers over time, making it vulnerable in the future. Inconsistencies in disseminating weather information and early disaster notifications are factors that obstruct the mitigation of climate-related disasters. Furthermore, disaster early warning system implementation has been slower in most African countries due to limited technical resources. Another notable challenge is upholding internationally standardized early warning systems in rural settings without overlooking the dynamics of the rural community, which leads to system ineffectiveness. Therefore, this study employed a mixed-methodology approach to gather qualitative and quantitative data from local farmers through the use of questionnaires to review the readiness to adopt early warning systems in northern Namibia, assess available technical resources, study the existing disaster mitigation practices in Namibia. Subsequently, historic and near real time weather data was collected from weather agencies, which ultimately designed and developed an early warning system to enhance resilience and preparedness for hazards and risks in farming communities by issuing comprehensive and timely alerts. The study confirmed the dire need for disaster prediction systems in Namibia, although it also highlighted pressing accessibility concerns that future researchers could study, especially under-resourced potential users.

Keywords

• agriculture
• disaster
• early warning
• mitigation