How are more frequent droughts in Southern Africa monitored and predicted?

Southern Africa is highly susceptible to droughts, which have devastating impacts on agriculture, water resources, and the livelihoods of millions of people. With the increasing frequency and intensity of these droughts due to climate change, the ability to monitor and predict such events is crucial for effective management and mitigation strategies. This piece explores the advanced methods used to monitor and predict droughts in the region, highlighting the role of space-borne technologies and regional initiatives.

Traditional methods of drought monitoring in Southern Africa have relied heavily on ground-based measurements from meteorological stations. However, these stations often provide limited coverage, especially in remote agricultural areas. To address this, recent advancements in satellite remote sensing have become invaluable. A significant study by Edokossi et al. (2024) highlights the use of space-borne Global Navigation Satellite System Reflectometry (GNSS-R) and Soil Moisture Active and Passive (SMAP) data for monitoring drought conditions in Southern Africa. 

The study found that both GNSS-R and SMAP data are highly effective in measuring soil moisture levels, which are critical for assessing drought severity. The data from these satellites showed strong correlations with traditional models, such as the Global Land Data Assimilation System (GLDAS) NOAH model, with Pearson correlation coefficients close to 0.98 for SMAP and 0.97 for GNSS-R. This indicates that satellite-based monitoring is a reliable and accurate method for detecting early signs of drought.

In addition to monitoring, predicting droughts is essential for proactive disaster management. The study by Manatsa et al. (2017) introduced a novel forecasting approach that integrates the Standardized Precipitation Evapotranspiration Index (SPEI) with El Niño-Southern Oscillation (ENSO) events. The SPEI, which accounts for both precipitation and temperature, has been shown to have a more robust connection to ENSO, making it a valuable tool for predicting drought conditions over Southern Africa.

The ENSO-SPEI prediction scheme developed in this study provides quantitative information on the spatial extent and severity of predicted droughts, offering decision-makers a more accurate assessment of the risks involved. This approach is particularly relevant in the context of global warming, where traditional forecasting methods may fall short in capturing the complexities of climate-driven drought patterns. 

The African Flood and Drought Monitor (AFDM) is another critical tool for monitoring and forecasting droughts across Southern Africa. Developed by a collaboration between Princeton University, UNESCO, and other institutions, the AFDM provides real-time data on meteorological, agricultural, and hydrological droughts. This system also includes a multi-decadal historical reconstruction of the terrestrial water cycle, which helps contextualize current drought conditions against long-term trends.

The AFDM has been instrumental in various applications, from supporting drought resilience programs in countries like Niger and Ethiopia to aiding in the management of water resources downstream of irrigation dams in Nigeria. The tool’s ability to monitor soil moisture and rainfall shortages has also been linked to patterns of human migration, especially in response to prolonged drought conditions in South Africa.

Despite these advancements, significant challenges remain in fully integrating these tools into regional drought management strategies. Issues such as data accessibility, technical capacity, and the need for localized models that account for the unique climatic and geographic conditions of Southern Africa are critical areas that require further development. Moreover, as the region grapples with the impacts of climate change, there is an urgent need for more comprehensive and coordinated approaches to drought monitoring and prediction.