Your search found 2 records
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]
Hydrology ; Forecasting ; Early warning systems ; Food security ; Water security ; Drought ; Flooding ; Precipitation ; Groundwater ; Water storage ; Soil water content ; Stream flow ; Monitoring ; Land area ; Meteorological factors ; Satellite observation ; Modelling / Africa / Middle East
(Location: IWMI HQ Call no: e-copy only Record No: H049803)
https://journals.ametsoc.org/bams/article-pdf/101/7/E1007/4981535/bamsd180264.pdf
https://vlibrary.iwmi.org/pdf/H049803.pdf
https://vlibrary.iwmi.org/pdf/H049803.pdf
(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 Mugiyo, H.; Magadzire, T.; Choruma, D. J.; Chimonyo, V. G. P.; Manzou, R.; Jiri, O.; Mabhaudhi, Tafadzwanashe. 2023. El Niño’s effects on southern African agriculture in 2023/24 and anticipatory action strategies to reduce the impacts in Zimbabwe. Atmosphere, 14(11):1692. (Special issue: Joint Disasters of High Temperature and Drought) [doi: https://doi.org/10.3390/atmos14111692]
El Nino ; Early warning systems ; Strategies ; Disaster risk reduction ; Climate services ; Weather ; Rainfall ; Drought ; Heat stress ; Mitigation ; Crop production ; Crop yield ; Agricultural sector ; Farmers / Southern Africa / Zimbabwe
(Location: IWMI HQ Call no: e-copy only Record No: H052405)
https://www.mdpi.com/2073-4433/14/11/1692/pdf?version=1700139089
https://vlibrary.iwmi.org/pdf/H052405.pdf
https://vlibrary.iwmi.org/pdf/H052405.pdf
(1.79 MB) (1.79 MB)
The frequency of El Niño occurrences in southern Africa surpasses the norm, resulting in erratic weather patterns that significantly impact food security, particularly in Zimbabwe. The effects of these weather patterns posit that El Niño occurrences have contributed to the diminished maize yields. The objective is to give guidelines to policymakers, researchers, and agricultural stakeholders for taking proactive actions to address the immediate and lasting impacts of El Niño and enhance the resilience of the agricultural industry. This brief paper provides prospective strategies for farmers to anticipate and counteract the El Niño-influenced dry season projected for 2023/24 and beyond. The coefficient of determination R2 between yield and ENSO was low; 11 of the 13 El Niño seasons had a negative detrended yield anomaly, indicating the strong association between El Nino’s effects and the reduced maize yields in Zimbabwe. The R2 between the Oceanic Nino Index (ONI) and rainfall (43%) and between rainfall and yield (39%) indirectly affects the association between ONI and yield. To safeguard farmers’ livelihoods and improve their preparedness for droughts in future agricultural seasons, this paper proposes a set of strategic, tactical, and operational decision-making guidelines that the agriculture industry should follow. The importance of equipping farmers with weather and climate information and guidance on drought and heat stress was underscored, encompassing strategies such as planting resilient crop varieties, choosing resilient livestock, and implementing adequate fire safety measures.
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