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1. Firstly you need to generate the long profile using a transformation module instance (converting from point data to long profile) or import the long profile from an external model (see example of how to generate a long profile in Sobek). When using a transformation (see code example below) the input variable should contain all the point data and the output is reference by a single point. The location of the input data locations is matched via the x, y coordinates in the branches file (see below). This means that the input variable can also be a grid.
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<variable> <variableId>Model_Output</variableId> <timeSeriesSet> <moduleInstanceId>Your_Module</moduleInstanceId> <valueType>scalar</valueType> <parameterId>Q.simulated.forecast</parameterId> <locationSetId>River1_Outputs</locationSetId> <timeSeriesType>simulated forecasting</timeSeriesType> <timeStep unit="minute" multiplier="15"/> <relativeViewPeriod unit="day" start="-10" end="24"/> <readWriteMode>add originals</readWriteMode> <synchLevel>1</synchLevel> </timeSeriesSet> </variable> <variable> <variableId>Profile</variableId> <timeSeriesSet> <moduleInstanceId>CreateLongProfile</moduleInstanceId> <valueType>longitudinalprofile</valueType> <parameterId>Long.profile</parameterId> <locationId>River1</locationId> <timeSeriesType>simulated forecasting</timeSeriesType> <timeStep unit="minute" multiplier="15"/> <relativeViewPeriod unit="day" start="-10" end="24"/> <readWriteMode>read only</readWriteMode> </timeSeriesSet> </variable> <transformation id="InterpolationSpatialClosestDistanceTest"> <interpolationSpatial> <closestDistance> <inputVariable> <variableId>Model_Output</variableId> </inputVariable> <searchRadius>0</searchRadius> <outputVariable> <variableId>Profile</variableId> </outputVariable> </closestDistance> </interpolationSpatial> </transformation> |
2. Secondly you need a branch file which describes this river or long-sectional branch. The branch is linked to the long profile via the location.
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