A flood management plan for the Grand River North West basin in Mauritius was developed to address the risks associated with climate change-induced flooding. Historical and projected climatic data were analyzed to discern trends in flood occurrence. A hydrological model was constructed to simulate the basin’s response to extreme flood events, and a Geographic Information System-based model was created for flood vulnerability map using exposure, susceptibility and resilience indicators. 

To support decision-makers in flood disaster management, a real-time flood monitoring system was established in the Niger and Volta basins under the Water disaster platform to enhance climate resilience in Africa (WADiRE-Africa). The system utilized real-time satellite rainfall data to bridge the gap between data scarcity and inaccessibility and a hydrological model to simulate the inundation extents at basin and hotspot scales. Presently, the prototype system is under testing in both basins.

A strong correlation between extreme rainfall and damaged paddy area in the past period was observed and the floods may affect rice paddies when 1-d or 4-d rainfall exceeds 25 mm or 71 mm. Flood inundation and rice crop damage might be more severe in the future due to climate change than in the past period. The average rice crop damage per year is approximately two times higher for the future period than for past period, suggesting more serious rice crop damage in future due to climate change.

Early flash floods result from the abundant precipitation frequently lead to significant losses of agriculture in the north-eastern region of Bangladesh. Allocating necessary storage to provide spaces for excess water can save the crop. This study calculates the necessary storage with a new method: Flood duration curve (FDC); estimates water storage capacity by using satellite-based citizen science haor volume estimation technique and finally, investigates an alternate solution of the problem.

The study evaluated how well a GCM can reproduce the past weather patterns linked to the heavy rainfall events in Davao river basin by using raingauge and ERA5 data as reference. Our findings show that MRI-AGCM 3.2S reproduced similar weather patterns in JJA and DJF seasons as compared to ERA5 but due to small differences in configuration lead to biases in the local rainfall. This method can be also applied to other river basins and for evaluating how the future local rainfall will change.