In the heart of East Africa, a groundbreaking initiative is taking shape, poised to revolutionize how communities and industries, particularly the energy sector, prepare for and mitigate climate-related disasters. Led by A. D. Msusa from the Department of Geospatial Sciences & Technology at Ardhi University in Dar es Salaam, Tanzania, a team of researchers has developed a climate-smart web GIS app designed to provide early warnings for flood and drought risks. This innovation is not just a technological marvel but a beacon of hope for enhancing disaster resilience and reducing economic losses.
The app, which leverages the Palmer Drought Severity Index (PDSI) and deep learning neural networks based on geospatial weather data, uses a convolution long-short-term memory (ConvLSTM) model to predict drought conditions in Dodoma. For flood predictions, the team integrated data from the Global Flood Awareness System (GloFAS) to forecast flood occurrences in Dar es Salaam. “The goal was to create a localized solution that fits the Tanzanian and East African environment,” Msusa explained. “Existing systems, while innovative, often don’t address the specific needs and conditions of our region.”
The implications for the energy sector are profound. Droughts and floods can severely disrupt energy infrastructure, from hydroelectric power plants to transmission lines. Early warnings provided by this app can enable energy companies to take preemptive measures, such as securing backup power sources or reinforcing infrastructure, thereby minimizing downtime and financial losses. “This tool is not just about saving lives; it’s about safeguarding livelihoods and economic stability,” Msusa added.
The development process was meticulous, employing the Rapid Application Development (RAD) methodology within the Microsoft .NET framework. The app captures and disseminates critical information on flood and drought risks, empowering communities and industries to make informed decisions. The team validated their findings using observed flood points identified and mapped through a participatory approach involving vulnerable community members. This collaborative effort ensures that the app is not only technologically robust but also socially relevant.
The results were telling. Areas highly prone to flooding were identified, and drought conditions in Dodoma’s Chamwino, Bahi, and Central Dodoma regions were pinpointed as high-risk zones. The successful development of this web-based GIS app marks a significant milestone in disaster risk reduction (DRR) efforts. Msusa and his team recommend integrating GIS and early warning tools into existing policies, establishing monitoring and evaluation frameworks, and further improving the app to enhance its effectiveness.
Published in the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, this research is set to shape future developments in the field. The app’s success could inspire similar initiatives across the globe, particularly in regions vulnerable to climate-related disasters. As the energy sector continues to grapple with the impacts of climate change, tools like this web GIS app offer a glimmer of hope, paving the way for a more resilient and sustainable future.