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The region of southern Africa (SA) has a fragile food economy and is vulnerable to frequent droughts. Interventions to mitigate food insecurity impacts require early warning of droughts – preferably as early as possible before the harvest season (typically starting in April) and lean season (typically starting in November). Hydrologic monitoring and forecasting systems provide a unique opportunity to support early warning efforts, since they can provide regular updates on available root-zone soil moisture (RZSM), a critical variable for crop yield, and provide forecasts of RZSM by combining the estimates of antecedent soil moisture conditions with climate forecasts. For SA, this study documents the predictive capabilities of RZSM products from the recently developed NASA Hydrological Forecasting and Analysis System (NHyFAS). Results show that the NHyFAS products would have identified the regional severe drought event – which peaked during December–February of 2015–2016 – at least as early as 1 November 2015. Next, it is shown that during 1982–2016, February RZSM (Feb-RZSM) forecasts (monitoring product) available in early November (early March) have a correlation of 0.49 (0.79) with the detrended regional crop yield. It is also found that when the February RZSM forecast (monitoring product) available in early November (early March) is indicated to be in the lowest tercile, the detrended regional crop yield is below normal about two-thirds of the time (always), at least over the sample years considered. Additionally, it is shown that the February RZSM forecast (monitoring product) can provide "out-of-sample" crop yield forecasts with comparable (substantially better with 40 % reduction in mean error) skill to December–February ENSO. These results indicate that the NHyFAS products can effectively support food insecurity early warning in the SA region. Finally, since a framework similar to NHyFAS can be used to provide RZSM monitoring and forecasting products over other regions of the globe, this case study also demonstrates potential for supporting food insecurity early warning globally. [ABSTRACT FROM AUTHOR]

The region of southern Africa (SA) has a fragile food economy and is vulnerable to frequent droughts. In 2015–2016, an El Niño-driven drought resulted in major maize production shortfalls, food price increases, and livelihood disruptions that pushed 29 million people into severe food insecurity. Interventions to mitigate food insecurity impacts require early warning of droughts – preferably as early as possible before the harvest season (typically, starting in April) and lean season (typically, starting in November). Hydrologic monitoring and forecasting systems provide a unique opportunity to support early warning efforts, since they can provide regular updates on available rootzone soil moisture (RZSM), a critical variable for crop yield, and provide forecasts of RZSM by combining the estimates of antecedent soil moisture conditions with climate forecasts. For SA, this study documents the predictive capabilities of a recently developed NASA Hydrological Forecasting and Analysis System (NHyFAS). The NHyFAS system's ability to forecast and monitor the 2015/2016 drought event is evaluated. The system's capacity to explain interannual variations in regional crop yield and identify below-normal crop yield events is also evaluated. Results show that the NHyFAS products would have identified the regional severe drought event, which peaked during December–February of 2015/2016, at least as early as 1 November 2015. Next, it is shown that February RZSM forecasts produced as early as 1 November (4–5 months before the start of harvest and about a year before the start of the next lean season) correlate fairly well with regional crop yields (r = 0.49). The February RZSM monitoring product, available in early March, correlates with the regional crop yield with higher skill (r = 0.79). It is also found that when the February RZSM forecast produced on November 1 is indicated to be in the lowest tercile, the detrended regional crop yield is below normal about two-thirds (significance level ~ 86 %) of the time. Furthermore, when the February RZSM monitoring product (available in early March) indicates a lowest tercile value, the crop yield is always below normal, at least over the sample years considered. These results indicate that the NHyFAS products can effectively support food insecurity early warning in the SA region. [ABSTRACT FROM AUTHOR]

A seamless and effective early warning system is critical for mitigating the most adverse impacts of water and food insecurity in Africa. The U.S. Agency for International Development (USAID) supported Famine Early Warning Systems Network (FEWS NET) is tasked with providing early warning and analysis on acute food and water insecurity to help government decision-makers and relief agencies plan for and respond to resulting humanitarian crises. This presentation describes a recently developed multimodel based seasonal scale hydrologic forecasting system, which has been operationally supporting the early warning efforts of FEWS NET since August 2018. Since then, this system has helped identify flood risk potential in parts of Eastern and Western Africa, and development and progression of drought conditions in Southern Africa. Both of these types of extremes contribute to food and water insecurity. At the core of this system is NASA's Land Information System (LIS) (a hydrologic modeling framework), which supports seasonal scale monitoring and forecasts of runoff and soil moisture by combining satellite and reanalysis based atmospheric forcings datasets and dynamical climate forecasts. Specifically, the LIS-based seasonal scale hydrologic forecasting system incorporates NASA/GMAO's Catchment and the Noah Multi-Physics (Noah-MP) land surface models (LSMs). It is driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and the UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) rainfall dataset to provide a long historic record for monitoring (1982-present) of hydrologic variables. Currently, the seasonal scale hydrological forecasts are generated by using NASA's Goddard Earth Observing System Model, version 5 (GEOS-5).Long-term availability of monitoring and forecasts of hydrologic variables allows for historical validation of this dataset against independent hydrologic observations and reported crop yields (up to the extent they are available). Validation results thus far have demonstrated agreement of hydrologic monitoring simulations with independent satellite based observations in Eastern Africa and the value of this system in supporting food insecurity early warning in Southern Africa.This presentation will first describe the development of this system, followed by its validation for drought early warning and subsequently the process of stakeholder engagement and operational application of the products derived from this system by the FEWS NET. [ABSTRACT FROM AUTHOR]