Seasonal-Scale Water Deficit Forecasting in Africa and the Middle East Using NASA’s Land Information System (LIS)

A seamless and effective water deficit monitoring and early warning system is critical for assessing food security in Africa and the Middle East. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA’s Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of drought and water availability monitoring products in the region. Next, it will focus on evaluating drought and water availability forecasts. Finally, we highlight our ongoing collaboration with end-user partners in the region (e.g., USAID’s Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the products through NASA’s web-services.

The water deficit forecasting system thus far incorporates NASA GMAO’s Catchment and the Noah Multi-Physics (MP) LSMs. In addition, the LSMs’ surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics.

To establish a climatology from 1981-2015, the two LSMs are driven by NASA/GMAO’s Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) rainfall dataset. Comparison of the models’ energy and hydrological budgets with independent observations suggests that major droughts are well-reflected in the climatology.

The system uses seasonal climate forecasts from NASA’s GEOS-5 (the Goddard Earth Observing System Model-5) and NCEP’s Climate Forecast System (CFSv2), and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region. Current work suggests that for the Blue Nile basin, (1) the combination of GEOS-5 and CFSv2 is equivalent in skill to the full North American Multimodel Ensemble (NMME); and (2) the seasonal water deficit forecasting system skill for both soil moisture and streamflow anomalies is greater than the standard Ensemble Streamflow Prediction (ESP) benchmark approach.