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MeanToInstantaneous
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disaggregates data |
MeanToInstantaneous
Input
- inputVariable
Output
- outputVariable
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If this is not the case, the procedure checks if there is a continous continuous rise or fall or if the mean values are in a peak or valley.
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After this procedure the estimated instantanaeous instantaneous values are corrected by using the AdjustQMeanDailyDischarge-transformation described below(a volume correction). This transformation will ensure that the mean values of the estimated instantaneous time series are equal to the orignal mean values.
Adjustment Procedure Using Mean Daily Discharge
from 533adjustq.pdf?
Configuration example
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Configuration example
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<transformation id="disaggregation imeanToInstantaneous">
<disaggregation>
<meanToInstantaneous>
<inputVariable>
<timeSeriesSet>
<moduleInstanceId>ImportTelemetry</moduleInstanceId>
<valueType>scalar</valueType>
<parameterId>Q.obs</parameterId>
<locationSetId>hydgauges</locationSetId>
<timeSeriesType>external historical</timeSeriesType>
<timeStep unit="minute" multiplier="15"/>
<relativeViewPeriod unit="day" startOverrulable="true" start="-7" end="0"/>
<readWriteMode>read only</readWriteMode>
</timeSeriesSet>
</inputVariable>
<outputVariable>
<timeSeriesSet>
<moduleInstanceId>Aggregate_Historic</moduleInstanceId>
<valueType>scalar</valueType>
<parameterId>Q.obs_disaggregated</parameterId>
<locationSetId>hydgauges</locationSetId>
<timeSeriesType>external historical</timeSeriesType>
<timeStep unit="minute" multiplier="5"/>
<relativeViewPeriod unit="day" startOverrulable="true" start="-7" end="0"/>
<readWriteMode>add originals</readWriteMode>
</timeSeriesSet>
</outputVariable>
</meanToInstantaneous>
</disaggregation>
</transformation>
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