Delft-FEWS Users Meeting

1. 30 October 2014
Delft-FEWS Edits, Modifiers and What-If’s
Marc van Dijk

2. Why this discussion
Data editor, Modifiers and What-if scenarios are used in FEWS forecasting systems to change the ‘default’ configured behaviour:
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Use of Data Edits for Quality Control (observed time series)
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Use of Modifiers for Quality Control, Model input and Model output (observed and forecast time series)
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Use of What-if scenario’s for Model Input (observed and external forecast time series)

3. Forecasting Process
Import
Processing
Models
Post processing
Dissemination
QC: Time Series Display
QC: Primary Validation
QC: Secondary Validation
Error Correction
Mod: Modifier Display
Mod: Modifier Display
WI: What-If Display Mod: Modifier Display
Mod: Switch / Hierarchy

4. Background Information
NFFS: Example of automated forecasting system
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Primary validation on import of observations
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What-If scenario’s for making an alternative forecast
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PRTF display is an example of on interactive what-if! NWS: Example of manual interactive forecasting system
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Primary validation is done mostly outside of FEWS
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Modifiers are introduced to correct errors in data and tune model input and output HyFS: Example of manual interactive forecasting system
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Quality Control inside of FEWS, using data edits and modifiers
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Introduction of Location Attribute Modifiers to create rainfall scenarios and tune model parameters
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Tendency to use FEWS more and more as interactive forecasting system.
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By using combination of edits. Modifiers and what-if it is easy to loose overview; need for intuitive overview displays.

5. Observations – Data Validation
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Automated data validation is conducted on importing of observed time series
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Validation rules can be location specific (Defined in location meta data)
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Type of validation checks:
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Extreme Values (hard/soft min/max)
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Rate Of Change, Same Reading, Temporary Shift
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Changes quality flag of data value: reliable, doubtful, unreliable
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Unreliable values are interpreted as missing by Delft-FEWS processing modules
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Quality Control is persistent
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Spatial display can be used to get overview of validation flags
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Recent developments on “Custom Flag Source”, Persistent flag, Spatial Homogeneity tests, etc..

6. In the Time Series display it is possible to show graphs with and without void data
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Use the Hide Void menu element from the Chart button of the Plots toolbar to hide void data in the graph (CTRL+Shift+H) In the table of the Time Series display it is possible to see the source of the validation flag
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Select the Validation menu element from the Table button (CTRL+Shift+J)
Primary Data Validation Rules
Flag sources:
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IMP = Imported
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MAN = Manual
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HN = Hard Min (PV)
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HX = Hard Max (PV)
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SN = Soft Min (PV)
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SX = Soft Max (PV) (PV=Primary Validation)

7. Delft-FEWS: QC, Edits, Modifiers en What-If's 17 December 2012
Quality Control examples FEWS Rivieren
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Some examples with data editor and spatial display

8. Persistent Void Data Flag
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The persistent void validation flag is a special flag; it can be copied forward in time.
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Set persistent void flag manually in Plots table (flag source = SFP)
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In processing workflow the persistent void flag is copied to next time steps prior to T0 (flag source = SVP)
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Copy process stops when manual flag is found that makes the data reliable again
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This flag can be used when sensor is not working anymore

9. Use of modifiers in QC and processing
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FEWS can use modifiers to apply changes to time series or model parameters
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A modifier change is made without actually editing the values themselves. The changes are established as a "description of the change“
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A modifier display is used to apply modifiers to the data
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Modifiers can be used in QC and modeling:
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Rating Curve modifier: Change the rating curve table for a selected location
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Sensor Switch modifier: Change the preferred sensor, used in water level and rainfall data hierarchy merging
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Missing modifier: Make a rainfall time series missing for a selected time period
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For all locations with time series modifiers (missing modifier) an overview can be made in Spatial display; like validation flags.

10. Sensor Switch modifier
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The Sensor Switch modifier can be used to switch the sensor preference for a rainfall station gauge or a water level station (change hierarchy)
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Temporarily change the hierarchy of the sensors when merging the observed time series to produce the processed time series

11. Missing Modifier
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The Missing modifier can be used to switch off a gauge for a specified period

12. Modifiers in Forecasts
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Modifiers are mainly used in forecast workflows
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Modifiers can influence transformations, data hierarchy, model states, model parameters, model output time series.
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Modifiers are entered with the Modifier display
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Each modifier has its own frame in the modifier display

13. Forecast Tree (Topology) guides the forecaster through the forecasting process
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Select node from Forecast Tree
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Select Modifier tab to enter and a modifier
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Press Apply button to activate modifier
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Press Run (Local or Server) to run workflow
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Select thumbnail in Plot Overview for correct plot
6.
Open Plot display to see plot with results
IFD in combination with modifiers
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14. Modifier example: Rainfall Scenarios
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In HyFS a Rainfall Scenario is a configured Location Attribute Modifier
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Each catchment or sub-catchment has attributes with preferred scenario
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Modifier is used to change the location attribute values
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The ‘modified’ attribute values will be used in the Forecast Workflows until it is switched off.

15. Example Rainfall Scenarios
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In Transformation module the merge – selectDataSource function is used
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‘Modified’ location attribute values are used to select the correct NWP model or rainfall multiplier

16. Modifiers for models parameters
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Changing model parameters with modifier works the same as any other modifier
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Change the default model parameters
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Can only be used if model adapter supports exchange of model parameters!

17. Example Model parameter
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In General Adapter the export parameter activity is used in combination with Model Parameter File.
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‘Modified’ (model parameter) location attribute values are exported to the model

18. What-if Display
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Several displays in FEWS can be used
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Flexibility is limited to time series and parameterSet and modeldataSet
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Forecasters find the display not very user friendly Time Series
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Transformationsets
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Typical profiles File selection
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Module parameter files
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Module data set files

19. What-if Display
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TaskRun Display can be used:
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More user friendly
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Only limited to time series what-if

20. Should modifiers replace what-if scenarios?
No !
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Currently complete different concept (always applied vs. applied when chosen) Yes !
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GUI is more attractive
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Underlying framework is more powerful
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Working with multiple scenarios in ensemble dimension only appropriate when run times are small For including a modifier in a what-if scenario we miss:
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Ability to connect modifiers to specific runs (workflows)
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Selection of module data set
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GUI design issues:
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Where/how to connect Modifier to scenario
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Where/how to connect scenario to run