In January 2015, extended periods of extreme rainfall caused a series of flood events throughout southern Africa. With little or no warning, the floods took communities by surprise, resulting in the displacement of over 230,000 residents and causing 276 fatalities (Government of Malawi, 2015). Parts of Malawi and Mozambique were amongst the hardest hit regions, with internally displaced people still residing in tented shelter camps as of August 2015. The meteorological situation was complex, with both riverine floods and flash floods occurring in various parts of the region within a narrow temporal frame.
In the days after the floods, humanitarian organizations and government level disaster mangers made decisions using information available to them, many time relying on satellite and flood model driven flood maps and anecdotal evidence from contacts in the field. Many maps were available, however, decision-making was hampered by uncertainty in the validity of the flood maps and challenging communication with the most impacted regions.
In partnership with the Malawi Red Cross National Society, we compared ground-truth data (locations of shelter site of internally displaced people (IDPs) and origins of IDPs) with the spatial distribution of remotely sensed and model driven flood products derived from NASA sensors, MODIS, SSM-I and AMSU-A and Landsat data from USGS. Furture, to explore the potential predictive capabilities of geophysical variables, we evaluated the relationship between soil moisture (data from the advanced scatterometer (ASCAT) provided by the European Space Agency and rainfall (data from the Tropical Rainfall Measuring Mission (TRMM) by provided by NASA).
A disaggregation of flood types in the context of monitoring and production of flood maps may aid in the development of a regional flood climatology in southern and eastern Africa, which in turn would contribute to the refinement of triggered actions fixed to levels of geophysical variables. In addition, project outputs suggest further exploration of the relationship of coupled variables, such as forecasted rainfall and antecedent soil moisture status, could be useful in developing thresholds to trigger humanitarian action in Mozambique.
In the same way that the geophysical characteristics of flood vary spatially and temporally by flood type, so too does the linked humanitarian action. The results of this study will increase the ability to forecast and monitor flood events in Mozambique, Malawi and across Africa, benefiting organizations involved with disaster preparedness and relief efforts, with a specific emphasis on providing analysis for the development of forecast based financing mechanisms to release funding before a disaster based on pre determined triggers and actions.