Design and Simulation of a Flood Forecasting and Alerting System: A Focus on Rwanda

The absence of an effective early flood forecasting and alerting system in Sub-Saharan Africa is a threat that results in many losses, including fishery disturbance. Floods deposit water polluting sediments, and water pollution is a serious health threat. Every year, polluted water world-widely kills more people than all the rest sources of death, combined. Severe diseases such as cholera, giardia, and typhoid are spread by drinking polluted water. In the region of interest, Rwanda, policymakers are not alerted of the flood plague before its hazards and consequences to the community, including shortage of inhabitants and clean water. Approaches to implementing flood risk reduction exist elsewhere in the world, but there is still a need for an effective and smarter system for flood forecasting and alerting. Based on the Internet of Things (IoT), this research paper presents a designed and prototyped system that will collect data from the sensor nodes distributed in flood-prone areas on a real-time basis, and store data on the cloud server. It will then analyze the stored data to help decision-making. The study also demonstrates how the integration of data from multiple sources contributes to an improved level of accuracy. It also features an entity that provides warnings where the usage of the GSM module will assist in disseminating the warning messages in the form of SMS to the concerned end users. This will increase awareness of both policymakers and inhabitants for the breakout of the floods for further coordination activities. Both the simulation and prototyping results are presented. This study is open for improvement since it provides a base for future studies regarding flood forecasting and alerting systems in the area of interest and even beyond.