This focused on my experience as an Engineer in the Mahaweli River basin. Simultaneously, Floods & droughts are the major problems in this basin, I tried to use the upper reservoirs to control these disasters by finding the reasons and ways to manage these difficulties by using gathered knowledge at ICHARM. This helps me to understand the conflict among stakeholders, and find the reasons and solutions for efficient water management in the system, by developing a physical model based on policies.

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.

The study provides valuable insights into the use of cutting-edge technologies for real-time extreme flow modelling and disaster risk reduction strategies in data-scarce regions. The methodology presented here improved forecasting lead time and accuracy of real-time satellite precipitations. This highlights the practical implications of public domain datasets and models for informed decision-making. The study can complement informed decision-making for flood preparedness in transboundary basins.

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.