File Formats:Time and Elevation Series Files

Time Series

Time and elevation series can be used in many places in GSSHA to specify time-varying model inputs. For example, stream boundary conditions, overland flow boundary conditions, and well pumping rates. Time series are set up in separate files from the rest of the project. These files may have one or more time series in them, and there may be more than one file. To include a time series in the project, create it in a text file and include it in the project file using this card:

TIME_SERIES_FILE "filename.ts"

This is the only card that may be repeated in the project file so that you can include as many time series files as needed.

Time series are simply listings of date/time and value but there are two types of time series that may be specified -- relative and absolute. These differ in how the date/time is interpreted. For relative time series, the date and time specified is added to the simulation starting time; for absolute the values are simply converted to julien times internally to be compared against the current simulation time. Relative time series work best for short project where you are initializing some feature or testing against a hypothetical set of data. Absolute time series are better for observed data and long run times.

The time series begins with the following card:

GSSHA_TS

next comes the name of the time series. The time series will be referenced by this name throughout the project.

time series name

Then either the card ABSOLUTE or RELATIVE follows to indicate how to treat the date/time formats. (See above.) After the ABSOLUTE or RELATIVE card, the date/time and value lines appear, as many as needed.

year month day hour minute value
year month day hour minute value
year month day hour minute value
...
year month day hour minute value

Finally the card END_TS indicates the end of the date/time and value lines. There may be as many time series in one file as desired; simply place empty lines between the time series.

Here is an example time series