EO4SD climate cluster's support further improves Africa’s leading drought and food security modelling tool

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The African Risk Capacity's Africa RiskView (ARV) combines Earth Observation (EO) data with population vulnerability data to provide an early-warning model that measures food insecurity and estimates response costs, enabling decision-makers to plan and respond quickly and efficiently to drought stresses. Through an ongoing collaboration with the European Space Agency’s (ESA) Earth Observation for Sustainable Development Climate Resilience (EO4SD CR) cluster, new data is being integrated into ARV allowing it to incorporate previously unavailable essential climate variables.

Rainfall is the main determinant of food security in Africa, as staple crop production is predominantly rainfed. As such, ARV uses a drought index based on a water balance model developed by the Food and Agriculture Organisation (FAO). This index compiles data on rainfall estimates, potential evapotranspiration, water holding capacity in the soil, crop type and their water demands, sowing dates, and length of growing period. These are used to estimate the extent to which the water requirements of the crop have been met, and therefore the food security risk. Predefined benchmarks are used to work out if the drought conditions at the end of a season are an anomaly or not.

Many of these datasets are reliant upon EO data. For instance, NOAA provides estimates of evapotranspiration and rainfall estimates are obtained from different satellite-based sources. To complement this the EO4SD CR have worked with the Africa Risk Capacity to identify other climate variables that could usefully be incorporated into ARV.

After extensive consultation and engagement, the EO4SD CR cluster is now in the process of providing long time series and monitoring on soil moisture, which informs soil water holding capacity estimates, as well as new datasets of precipitation measurements for drought monitoring. The EO4SD and ARC teams are currently working hand-in-hand to allow Africa RiskView ingesting new Copernicus and ESA products.

ARV data can be aggregated to make a particular shape that corresponds to an administrative region, agro-ecological zones, or crop growing regions, making it easier to observe specific areas over time. The frequency and scale of these observations make it possible for the ARV to provide early warnings of drought, as it monitors the growing season from crop sowing time to maturity, indicating which areas in a region, country or province have received minimal rainfall, water deficits, or excess water at the various stages of crop growth, all of which can effect crop yield.

Africa RiskView default My View showing Kenya EAR1 Arid (long rains) season

 

Africa RiskView combines these observations with data on the population to estimate how many people may be directly affected by the observed drought, and how much the response costs may be. The vulnerability profile is based on household survey data from national governments and the World Food Programme’s Comprehensive Food Security and Vulnerability Analysis surveys. This data can be adjusted and input by different users, and matched with the different clusters of observational data to provide a truly tailored description of drought effects to specific populations. By identifying and quantifying risk in this objective way, this early warning tool can also help countries to plan appropriate drought response actions and food security investments.

The information produced by Africa RiskView also has broader applications. The EO time-series data sets can build understanding about the scale of effects associated with different drought impacts, helping to develop early food security assessments in specific geographic areas or contingency planning and emergency preparedness for future shocks in a country. It can also improve understanding of the drivers and causes of food insecurity in areas and identify which investments or risk management strategies are best. The tool could also be helpful in guiding planning and investment decisions aimed at enhancing agricultural productivity or market development and be used to support micro insurance programmes. Currently, the tool focuses on drought, but there is ongoing work to include other risks, including river flooding and tropical cyclones.