Quick Scenario Builder - Industrial Demands
This "Quick Scenario Builder" gives you a complete overview of total industrial water demands as well as a single user interface to quickly build scenarios 2 and 3 out of data previously entered under scenario 1.
When the form opens, it shows data for the first balancing year and the dry year type.
A different balancing year is selected by year-selector on top of the form ,
The data table in the form shows the spatial selection (the descriptive name entered in the log table) and the total annual demand as saved in the STP file STP_INDUSTRY as monthly volumes of each demand center.
The annual growth rate shown on the right side are not a data table but rather a list box permitting the selection of records for updating.
Data manipulation is possible in 3 different ways:
- Fill data: For scenario 2 or 3 selected by the fill-button located under the column, data from scenario one are copied. This does not only include STP data, but log-table data as well. Afterwards, the display of demand volumes and annual growth rate is refreshed.
- Empty data: For scenario 2 or 3 selected by the delete-button located under the column, STP data are set to zero and log data are removed. Afterwards, the display of demand volumes and irrigated areas is refreshed.
- Recalculate data: The 3rd option is more complex. It makes only sense after the scenario has already been populated with data. You have to select one or more records in the list box (showing the annual growth rate) and have to enter a multiplication factor, with which these growth rates are to be reduced. Select the option if only the year currently shown should be updated (this is the default), the year shown and the following years or even all years. After records have been selected and the multiplication factor has been set to a value <1, the hammer-button becomes enabled and can be pressed . This will recalculate growth rate and industrial demands in a simple way, by just reducing growth-percentage data stored in the respective log table by the entered factor and then recalculating the demand data for the STP-table.