Hydrological modeling and capacity building in the Republic of Namibia

Type Journal Article - Bulletin of the American Meteorological Society
Title Hydrological modeling and capacity building in the Republic of Namibia
Issue 2016
Publication (Day/Month/Year) 2016
URL http://journals.ametsoc.org/doi/full/10.1175/BAMS-D-15-00130.1
The Republic of Namibia, located along the arid and semiarid coast of southwest Africa, is highly dependent on reliable forecasts of surface and groundwater storage and fluxes. Since 2009, the University of Oklahoma (OU) and National Aeronautics and Space Administration (NASA) have engaged in a series of exercises with the Namibian Ministry of Agriculture, Water, and Forestry to build the capacity to improve the water information available to local decision-makers. These activities have included the calibration and implementation of NASA and OU’s jointly developed Coupled Routing and Excess Storage (CREST) hydrological model as well as the Ensemble Framework for Flash Flood Forecasting (EF5). Hydrological model output is used to produce forecasts of river stage height, discharge, and soil moisture.

To enable broad access to this suite of environmental decision support information, a website, the Namibia Flood Dashboard, hosted on the infrastructure of the Open Science Data Cloud, has been developed. This system enables scientists, ministry officials, nongovernmental organizations, and other interested parties to freely access all available water information produced by the project, including comparisons of NASA satellite imagery to model forecasts of flooding or drought. The local expertise needed to generate and enhance these water information products has been grown through a series of training meetings bringing together national government officials, regional stakeholders, and local university students and faculty. Aided by online training materials, these exercises have resulted in additional capacity-building activities with CREST and EF5 beyond Namibia as well as the initial implementation of a global flood monitoring and forecasting system.

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