RASOR project support to flood risk analysis in Malawi: Workshop Debrief

The Government of Malawi requested that the World Bank Group and the Global Facility for Disaster Reduction and Recovery (GFDRR) provide support to improve flood modeling in regions along the western shore of Lake Malawi. In order to do so the institutions have been working together, alongside the Rapid Analysis and Spatialization of Risk (RASOR) team, over the past year with overall objective of developing multi-hazard risk assessments for the lakeshore region. RASOR is a platform that performs multi-hazard risk analysis for the full the cycle of disaster management.

Outcomes of the project have been the production of flood hazard profile layers for major flood hotspots calculated over various return periods and exposure data. The former are available in raster (GeoTiff) formats and the latter as vector datasets. The hazards layers have been developed from a 12m resolution TanDEM-X Digital Elevation Model (DEM) which has much more accuracy than any existing surface data and has been adopted by RASOR for risk management applications. For the flood risk profiles, RASOR used these as well as archived and near-real time, very-high resolution optical and radar satellite data combined with in-situ data. The layers have the capacity to improve the accuracy of flood risk scenario modelling work in InaSAFE . These new datasets build on the philosophies and practices of Open Data for Resilience Initiative’s global open data movement to tackle the challenges of reducing vulnerability and building resilience to natural hazards and the impacts of climate change across the globe.

These free datasets can be downloaded from the Malawi Spatial Data Portal by using “rasor” as a search keyword. The same datasets are also available via a RASOR QGIS plugin. One will however need a username and a password from RASOR if they would like to explore this option. Along with downloading flood hazard profile layers from RASOR, users can create personal profiles at http://www.rasor-project.eu/rasor-platform/ and upload their own data to the platform and, in a matter of minutes, generate results for their own local application.

In the month of July 2016, a workshop was held in Salima from July 19th to 23rd. It was the final part of a series of activities, following two missions with the same participants, with the objective of delivering consolidated results of the flood risk analyses conducted over the past year and outlining the RASOR platform process and procedure. The audience at the workshop was mainly made up of technical experts drawn from the Department of Disaster Management Affairs, the Surveys Department, and Water and Hydrometeorology Department.

The first day of the workshop revolved around a coordination meeting where the RASOR and GFDRR team members met with the audience to provide an overview of the training activities and objectives. With these fundamentals established, the second day of the workshop was dedicated to an overview of flood modelling methodologies and a discussion about and demonstration of the RASOR risk management platform. Both pluvial and fluvial flooding were addressed along with a presentation about Malawi’s vulnerability curves. Particular focus was put on flood modelling work in northern Malawi for 2015-2016, risk characterization data, and a summary of risk indicators. The workshop concluded on the third day after sessions about disaster risk assessment training the introduction of a RASOR mobile application for exposure mapping and data collection, made by Roberto Rudari from RASOR. The RASOR app, called RASOR-layers, runs on the Android platform and is currently available in Google Play. The last day also saw the workshop attendees use the app during a field visit to one of the flood prone areas along the Linthipe River for field data collection.

RASOR-app-field-mapping

Participants using RASOR layers app for exposure data collection in Salima on 21st July 2016.
Photo by GFDRR

For more information on RASOR please see http://www.rasor-project.eu/.