Given limited financial resources, extensive reconstruction needs, and high vulnerability to frequent hazard events, how does a country identify and prioritize investments to most effectively reduce disaster risk?  Tackling this question is especially important in a diverse country such as Bolivia, where national and municipal agencies struggle with this dilemma on a daily basis.  Extreme climate events, such as El Niño or La Niña, cause severe flooding and drought that impair crop yields and livelihoods, and spur outbreaks in diseases such as malaria, dengue, and cholera.  In 2005, 2006, and 2007, climate events affected approximately 45 of Bolivia’s 339 municipalities, and between 2007 and 2008 alone La Niña’s damages were valued at US$757 million—over 5.7% of GDP.

To determine the most effective solutions to reduce risk across different sectors in Bolivia, six national ministries teamed up with the Global Facility for Disaster Reduction and Recovery (GFDRR) and World Bank’s disaster risk management (DRM) team to develop a national DRM program for the country. This involved collecting and sharing required risk information by strengthening geospatial information systems in the agriculture, public works, health, planning, environment and water sectors, culminating in the establishment of a virtual data-sharing platform called GeoSINAGER.

GeoSINAGER facilitates the flow of geospatial, hazard and socio-economic data among agencies at both the national and municipal levels. The platform also enables practitioners to create digitized geographic maps by layering geospatial data with socio-economic information in order to visualize municipalities that are most vulnerable to the four main hazards (flood, drought, frost, forest fires). The team also collaborated to develop a new methodology, the Municipality Risk Indicator (MRI), to improve investment decisions for public infrastructure and land planning to reduce sectoral vulnerabilities and improve resilience to natural hazards.

The MRI is a database and visualization tool that enables government officials to examine sectoral relationships at both the national and municipal level. The MRI methodology assigns high, medium or low risk levels to key sectors in each municipality under various climate scenarios and hazards, allowing decision-makers to quickly grasp and understand levels of risk and identify strategic infrastructures (hospitals, schools, roads, airports) exposed to specific hazards. With this snapshot, authorities can identify and target vulnerable municipalities and individual sectors to reduce disaster risk.

Often, impacts to these sectors are inter-related, and risk reduction efforts can be leveraged in a multi-sectoral approach. Since 2002, for example, agricultural production in the country has dropped considerably, affecting over half the population. Recurrent climate impacts are further impeding food security and compelling decision makers to prioritize agricultural risk in the country. Utilizing geospatial data tools like GeoSINAGER and the new MRI methodology, national authorities were able to determine that interruptions in the transportation network and connectivity to markets were driving agricultural losses.

With this connection between infrastructure and agriculture clearly visible, the Government agreed to prioritize more resilient road infrastructure and improve transport lines, especially for major agricultural areas, resulting in a $220 million national road infrastructure project. “The Municipal Risk Indicator (MRI) allowed us to establish a new approach to municipal-level planning,” Mr. Lucio Tito, Manager of the Agricultural Risk and Climate Change Unit in Bolivia. “We believe that this approach will impact our work through more effective disaster risk management. The MRI provides indicators for different levels and types of risk across all 339 municipalities that can be applied to mitigate impacts to the agricultural sector in high-risk areas.”

The MRI methodology and other strategic initiatives funded by GFDRR—such as strengthening national agencies and developing collaborative information-sharing platforms—have helped to form a comprehensive disaster risk management strategy at the national level. This will enable Bolivia to better target financial resources for maximizing risk reduction activities across key sectors in the future.

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