Tracking real-time impacts of climate variability and trade disruptions on water and food security

Food insecurity results from a complex interplay of climate, socio-economic and political drivers, with local food security being frequently influenced by events elsewhere. Recent unprecedented climate events and economic disruptions such as Covid-19 and the resurgence of large intra- and inter-state conflict, show the diverse and unpredictable nature of risk, which can suddenly impacting food production and supply chains.

Here, we present a coupled hydrology-crop production-trade model that is able to simulate, in real time, current and near-future risks to water and food security. The model combines an operational process-based simulation of global crop production and hydrology with an ML-powered trade module, trained on FAOs detailed trade matrix dataset. It is updated monthly with the latest ERA5 climate data from the Copernicus Data Store to assess current risk, and can be forced with seasonal forecasting and long term climate projections up to 2100. The model explains about 50% of yield variability in major growing regions - a critical characteristic for nowcasts or seasonal forecasts – and the majority of food trade and trends therein, but generally still underestimates the variability. As a first step to better reproduce observed crop yield anomalies we improved the simulation of growing seasons in the production model.  

By combining production with trade, we are able to estimate the impact of climate-related yield anomalies elsewhere, and to assess risks for water- and food security at the country, regional or global scale. Derived indicators provide a real-time insight into, for example, food production and storage per capita, crop water productivity, or crop or export specific water stress. Through continued evaluation and learning, we expect to be able to better identify emerging stresses in the food system and its drivers, and support early anticipation of potential future food security risks. This should ultimately lead to a better understanding of the complexity of the global food system and eventually result in a more sustainable food system.