When copying data using HEC-RTS, either through the Extract or Post functions, it's important to understand how override protections work.
The available options depend on the destination of the data: an HEC-DSS file or an Oracle (CWMS) database.
Destination: HEC-DSS
When writing to an HEC-DSS file (e.g., forecast.dss or a shared HEC-DSS file), you can choose from the following options based on the type of time series data:
Regular Time Series
Option
Description
Replace All
Replaces all existing values with incoming data. Does not create or delete records of missing data.
Replace Missing Values Only
Only fills in missing values in the file with incoming data.
Replace and Create
Replaces all values and creates entire records of missing data if needed.
Replace and Delete
Replaces all values and deletes any records that are entirely missing.
Replace with Non-Missing
Replaces all values, but does not overwrite existing non-missing values with incoming missing ones.
Irregular Time Series
Options
Description
Replace
Deletes all existing values within the incoming time window, then stores the new data.
Merge
Inserts new values and replaces existing ones—even if incoming values are missing.
Destination: Oracle (CWMS Database, CDA)
When posting to an Oracle database (e.g., CWMS Database, CDA), these override options apply to both regular and irregular time series:
Options
Description
Delete Insert
Deletes all existing values in the incoming time window, then inserts new data.
Replace All
Inserts at new times and replaces any values at existing times—even if incoming values are missing.
Do Not Replace
Inserts at new times only; existing values are never overwritten.
Replace Missing Values Only
Replaces existing values only if they are missing. Inserts at new times as usual.
Replace with Non-Missing
Replaces existing values unless the incoming value is missing. Inserts at new times as usual.
Choose your override option carefully based on the data integrity requirements of your workflow. For example, Replace Missing Values Only is a safe choice when preserving existing validated data.