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They are then interpolated to model grid points as the input to drive the model, ROMS.
To drive the model, hydrometeorological, soil, and remotely sensed physiological data are utilized.
The simulation needs are transformed into requirements that drive the model development.
Meteorological fields used to drive the model were from the fifth generation Mesoscale Model (MM5).
The measured daily flow rate data were used as time series boundary conditions to drive the model.
Nonetheless, for the reader we provide here a brief overview of the key aspects and interactions which drive the model.
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The focus should be on teaching the underlying ideas and mechanisms which drive the models, rather than the ability to derive all the results mathematically.
Such converters present nonlinear characteristics and approximations of them are used to drive the models.
We believe the inadequacy of data to drive the models is typical of the majority of catchment scale setting.
Reliability and availability models are as good as the parameters used to drive the models, such as failure rates, recovery success rate, and recovery and maintenance time.
For example, open questions include: For System-Dynamics and Bayesian Network models, we can transfer predefined player actions as "evidence" to populate and drive the models.
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