TY - JOUR
T1 - The regional hydrologic extremes assessment system
T2 - A software framework for hydrologic modeling and data assimilation
AU - Andreadis, Konstantinos M.
AU - Das, Narendra
AU - Stampoulis, Dimitrios
AU - Ines, Amor
AU - Fisher, Joshua B.
AU - Granger, Stephanie
AU - Kawata, Jessie
AU - Han, Eunjin
AU - Behrangi, Ali
N1 - Publisher Copyright:
© 2017 Andreadis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2017/5
Y1 - 2017/5
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85019617408&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019617408&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0176506
DO - 10.1371/journal.pone.0176506
M3 - Article
C2 - 28545077
AN - SCOPUS:85019617408
SN - 1932-6203
VL - 12
JO - PloS one
JF - PloS one
IS - 5
M1 - e0176506
ER -