Model
Digital Document
Publisher
Florida Atlantic University
Description
This research proposes an Infrastructure to model complex systems for hydrological modeling.
Currently, the three main hydrological packages are: i) SEAWAT (modeling groundwater flow); ii) HECRAS
(modeling surface water flow); iii) HEC-HMS (modeling atmospheric water flow). Each of these models is self-contained and has a different timescale and simulation speed. Consequently, any integrated model will only run as fast as the slowest of the models. This makes it difficult to provide reliable and dynamic information on water levels and water availability for a given geographical region in a timely manner. The goal of this research is to facilitate the integration of multiple hydrological models from different hydrological packages by applying Electronic Design Automation (EDA) methodologies, including System Level Design (SLD) methodology, SystemC-AMS language, Python language and libraries (numpy, Statsmodels, and ctypes). The EDA methodology brings in the additional advantage of significantly improved simulation speed. The Infrastructure to Model Complex Systems applications is
demonstrated using the following SEAWAT benchmark problems: i) Case 1; ii) Henry; iii) Elder problem.
Simulation results from the aforementioned benchmarks are analyzed and discussed. Lastly, future research
work is presented.
Currently, the three main hydrological packages are: i) SEAWAT (modeling groundwater flow); ii) HECRAS
(modeling surface water flow); iii) HEC-HMS (modeling atmospheric water flow). Each of these models is self-contained and has a different timescale and simulation speed. Consequently, any integrated model will only run as fast as the slowest of the models. This makes it difficult to provide reliable and dynamic information on water levels and water availability for a given geographical region in a timely manner. The goal of this research is to facilitate the integration of multiple hydrological models from different hydrological packages by applying Electronic Design Automation (EDA) methodologies, including System Level Design (SLD) methodology, SystemC-AMS language, Python language and libraries (numpy, Statsmodels, and ctypes). The EDA methodology brings in the additional advantage of significantly improved simulation speed. The Infrastructure to Model Complex Systems applications is
demonstrated using the following SEAWAT benchmark problems: i) Case 1; ii) Henry; iii) Elder problem.
Simulation results from the aforementioned benchmarks are analyzed and discussed. Lastly, future research
work is presented.
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