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1 Arsenault, K. R.; Shukla, S.; Hazra, A.; Getirana, A.; McNally, A.; Kumar, S. V.; Koster, R. D.; Peters-Lidard, C. D.; Zaitchik, B. F.; Badr, H.; Jung, H. C.; Narapusetty, B.; Navari, M.; Wang, S.; Mocko, D. M.; Funk, C.; Harrison, L.; Husak, G. J.; Adoum, A.; Galu, G.; Magadzire, T.; Roningen, J.; Shaw, M.; Eylander, J.; Bergaoui, K.; McDonnell, Rachael A.; Verdin, J. P. 2020. The NASA hydrological forecast system for food and water security applications. Bulletin of the American Meteorological Society (BAMS), 101(7):E1007-E1025. [doi: https://doi.org/10.1175/BAMS-D-18-0264.1]
(Location: IWMI HQ Call no: e-copy only Record No: H049803)
(8.47 MB) (8.47 MB)
Many regions in Africa and the Middle East are vulnerable to drought and to water and food insecurity, motivating agency efforts such as the U.S. Agency for International Development’s (USAID) Famine Early Warning Systems Network (FEWS NET) to provide early warning of drought events in the region. Each year these warnings guide life-saving assistance that reaches millions of people. A new NASA multimodel, remote sensing–based hydrological forecasting and analysis system, NHyFAS, has been developed to support such efforts by improving the FEWS NET’s current early warning capabilities. NHyFAS derives its skill from two sources: (i) accurate initial conditions, as produced by an offline land modeling system through the application and/or assimilation of various satellite data (precipitation, soil moisture, and terrestrial water storage), and (ii) meteorological forcing data during the forecast period as produced by a state-of-the-art ocean–land–atmosphere forecast system. The land modeling framework used is the Land Information System (LIS), which employs a suite of land surface models, allowing multimodel ensembles and multiple data assimilation strategies to better estimate land surface conditions. An evaluation of NHyFAS shows that its 1–5-month hindcasts successfully capture known historic drought events, and it has improved skill over benchmark-type hindcasts. The system also benefits from strong collaboration with end-user partners in Africa and the Middle East, who provide insights on strategies to formulate and communicate early warning indicators to water and food security communities. The additional lead time provided by this system will increase the speed, accuracy, and efficacy of humanitarian disaster relief, helping to save lives and livelihoods.
2 Bergaoui, Karim; Belhaj Fraj, Makram; Fragaszy, Stephen; Ghanim, A.; Hamadin, O.; Al-Karablieh, E.; Fakih, M.; Salama, S.; Fayad, A.; Yessef, M.; Belghrissi, H.; Hassels, T.; Ali, Marwa; Badr, H.; Hazra, A.; Nie, W.; Arsenault, K.; Hayes, M.; Svoboda, M.; McDonnell, Rachael. 2022. MENAdrought synthesis of drought monitoring, early warning, and seasonal forecasting tools and capability development: final report. Project report prepared by the International Water Management Institute (IWMI) for the Bureau for the Middle East of the United States Agency for International Development (USAID). Washington, DC, USA: USAID; Colombo, Sri Lanka: International Water Management Institute (IWMI). 74p. [doi: https://doi.org/10.5337/2023.202]
(Location: IWMI HQ Call no: e-copy only Record No: H052340)
(1.48 MB)
3 Bergaoui, Karim; Belhaj Fraj, Makram; Fragaszy, Stephen; Ghanim, A.; Hamadin, O.; Al-Karablieh, E.; Al-Bakri, J.; Fakih, M.; Fayad, A.; Comair, F.; Yessef, M.; Mansour, H. B.; Belgrissi, H.; Arsenault, K.; Peters-Lidard, C.; Kumar, S.; Hazra, A.; Nie, W.; Hayes, M.; Svoboda, M.; McDonnell, Rachael. 2024. Development of a composite drought indicator for operational drought monitoring in the MENA Region. Scientific Reports, 14:5414. [doi: https://doi.org/10.1038/s41598-024-55626-0]
(Location: IWMI HQ Call no: e-copy only Record No: H052703)
(2.06 MB) (2.06 MB)
This paper presents the composite drought indicator (CDI) that Jordanian, Lebanese, Moroccan, and Tunisian government agencies now produce monthly to support operational drought management decision making, and it describes their iterative co-development processes. The CDI is primarily intended to monitor agricultural and ecological drought on a seasonal time scale. It uses remote sensing and modelled data inputs, and it reflects anomalies in precipitation, vegetation, soil moisture, and evapotranspiration. Following quantitative and qualitative validation assessments, engagements with policymakers, and consideration of agencies’ technical and institutional capabilities and constraints, we made changes to CDI input data, modelling procedures, and integration to tailor the system for each national context. We summarize validation results, drought modelling challenges and how we overcame them through CDI improvements, and we describe the monthly CDI production process and outputs. Finally, we synthesize procedural and technical aspects of CDI development and reflect on the constraints we faced as well as trade-offs made to optimize the CDI for operational monitoring to support policy decision-making—including aspects of salience, credibility, and legitimacy—within each national context.
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