Africa RiskView: Methodology

The Africa RiskView model uses the following primary data inputs to compute each of the four major Africa RiskView model components:

Africa RiskView Model Component
Primary Data Input
Drought Index
Modeled Impact
Household surveys
Modeled Costs
ARC Project default settings can be customized by users

All settings in Africa RiskView have been developed so that they can be refined and customized to reflect a country’s drought risk assessment and risk management needs.


Africa RiskView uses several rainfall estimates (RFE) datasets. As a default for rainfall data, Africa RiskView uses RFE 2.0, which is a product of the Climate Prediction Centre (CPC) at the United States National Oceanic and Atmospheric Administration (NOAA) produced every 10 days at a 0.1 degree x 0.1 degree latitude/longitude resolution covering the whole of the African continent. Africa RiskView also uses the newly developed African Rainfall Climatology v2, ARC2, dataset, also produced by CPC-NOAA. With these datasets, users can view actual rainfall estimates, calculate cumulative rainfall and compare rainfall to average at several spatial scales. Historical rainfall datasets are available starting from the year 1983 to the present.

Drought Index

Measuring total rainfall at the end of a season has proven to be too crude of an indicator for estimating the potential impact of rainfall deficits on production and livelihoods. Africa RiskView thus uses the Water Requirement Satisfaction Index, WRSI, as a meaningful indicator of how a shortage of rainfall may impact crop yields and the availability of pasture. The WRSI monitors water deficits throughout the growing season, and captures the impact of timing, amount and distribution of rainfall on staple annual rain-fed crops. Although a simple index, it is used by many national meteorological offices across Africa to monitor rainfall seasons and their impact on agriculture and is the basis on many drought early warning tools for the continent.

The WRSI component of Africa RiskView is based on the work of the United Nations Food and Agriculture Organization (FAO) and the US Geological Survey, which works with and provides data to the Famine Early-Warning Systems Network (USGS/FEWS-NET) of USAID. The RFE data is used as the primary input into the WRSI model and WRSI settings can be customized to reflect local cropping calendars and practices.

Estimated Population Affected

Vulnerable populations in ARC are based on two factors — resiliency, which is a household’s distance from the national poverty line and exposure, which is the percentage of a household income that comes from agricultural activities (production, casual labor and livestock). Using households survey data these two dimensions are used to create a drought vulnerability profile of populations living in each administrative unit of a country. To compute the vulnerability profiles, Comprehensive Food Security and Vulnerability Analysis (CFSVA) surveys are used. In cases where the CFSVA is not available, proxy data from UNICEF‘s Multiple Indicator Cluster Surveys (MICS) or the Demographic and Health Surveys (DHS) are substituted. However, as countries customize the tool at the national level, data collected in other national surveys and assessments can be used to refine the population vulnerability profiles with the most up-to-date information.

Estimated Response Costs

Modeled Costs are currently set at $50 per person affected per season (in bimodal rainfall areas) and $100 per affected person in uni-modal rainfall areas. However, these default numbers should be customized by countries to reflect their response modalities and related budgeted contingency plans.