Abstract
The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geographic Information System (GIS) applications. The datasets ingested are obtained from numerous space-borne sensors and represent multiple components of the water cycle. The object-oriented design of the software allows for modularity and extensibility, showcased here with the coupling of the core hydrologic model with a crop growth model. RHEAS can exploit multi-threading to scale with increasing number of processors, while the database allows delivery of data products and associated uncertainty through a variety of GIS platforms. A set of three example implementations of RHEAS in the United States and Kenya are described to demonstrate the different features of the system in real-world applications.
Highlights
Water resources management is a major challenge globally, involving tradeoffs between multiple objectives and coordination with a heterogeneous set of stakeholders
We present a prototype software framework that automates the ingestion of diverse datasets, and the deployment of a hydrologic model incorporating data assimilation and facilitating the coupling with other earth science models
The datasets that are not produced by the Regional Hydrologic Extremes Assessment System (RHEAS) models, including satellite observations and model data that are used to generate inputs or constraints for the models, are automatically fetched from various sources and ingested into the PostGIS database
Summary
Water resources management is a major challenge globally, involving tradeoffs between multiple objectives (e.g., water supply, agriculture, hydropower, ecology) and coordination with a heterogeneous set of stakeholders. The datasets that are not produced by the RHEAS models, including satellite observations and model data that are used to generate inputs or constraints for the models, are automatically fetched from various sources and ingested into the PostGIS database.
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