From Global to Local: Providing Actionable Flood Forecast Information in a Cloud‐Based Computing Environment1. (11th February 2016)

• Record Type: Journal Article
• Authors: Perez, J. Fidel; Swain, Nathan R.; Dolder, Herman G.; Christensen, Scott D.; Snow, Alan D.; Nelson, E. James; Jones, Norman L.
• Is Part Of: Journal of the American Water Resources Association. Volume 52:Number 4(2016:Aug.)
• Page Start: 965
• Page End: 978
• Publication Date: 2016-02-11
• Subjects: flood forecast -- flood warning -- web apps -- emergency response -- Tethys Platform; Water-supply -- Periodicals; Hydrology -- Periodicals; Water resources development -- Periodicals; Water resources development -- Environmental aspects -- Periodicals; 333.9100973
• DOI: 10.1111/1752-1688.12392
• Languages: English
• ISSNs: 1093-474X

Abstract

Abstract: Global and continental scale flood forecast provide coarse resolution flood forecast, but from the perspective of emergency management, flood warnings should be detailed and specific to local conditions. The desired refinement can be provided by the use of downscaling global scale models and through the use of distributed hydrologic models to produce a high‐resolution flood forecast. Three major challenges associated with transforming global flood forecasting to a local scale are addressed in this work. The first is using open‐source software tools to provide access to multiple data sources and lowering the barriers for users in management agencies at local level. This can be done through the Tethys Platform that enables web water resources modeling applications. The second is finding a practical solution for the computational requirements associated with running complex models and performing multiple simulations. This is done using Tethys Cluster that manages distributed and cloud computing resources as a companion to the Tethys Platform for web app development. The third challenge is discovering ways to downscale the forecasts from the global extent to the local context. Three modeling strategies have been tested to address this, including downscaling of coarse resolution global runoff models to high‐resolution stream networks and routing with Routing Application for Parallel computatIon of Discharge (RAPID), the use of hierarchical Gridded Surface and Subsurface Hydrologic Analysis (GSSHA) distributed models, and pre‐computed distributed GSSHA models.