30 October 2014

Delft-FEWS Edits, Modifiers and What-If’s

Marc van Dijk

Why this discussion

Data editor, Modifiers and What-if scenarios are used in FEWS forecasting systems to change the ‘default’ configured behaviour:

• Use of Data Edits for Quality Control (observed time series)

• Use of Modifiers for Quality Control, Model input and Model output

(observed and forecast time series)

• Use of What-if scenario’s for Model Input (observed and external forecast time series)

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

Background Information

NFFS: Example of automated forecasting system • Primary validation on import of observations • What-If scenario’s for making an alternative forecast • PRTF display is an example of on interactive what-if!

NWS: Example of manual interactive forecasting system

• Primary validation is done mostly outside of FEWS • Modifiers are introduced to correct errors in data and tune model input

and output

HyFS: Example of manual interactive forecasting system • Quality Control inside of FEWS, using data edits and modifiers • Introduction of Location Attribute Modifiers to create rainfall scenarios

and tune model parameters

• Tendency to use FEWS more and more as interactive forecasting system. • By using combination of edits. Modifiers and what-if it is easy to loose

overview; need for intuitive overview displays.

Observations – Data Validation

• Automated data validation is conducted on importing of observed time series • Validation rules can be location specific (Defined in location meta data) • Type of validation checks:

• Extreme Values (hard/soft min/max) • Rate Of Change, Same Reading, Temporary Shift

• Changes quality flag of data value: reliable, doubtful, unreliable • Unreliable values are interpreted as missing by Delft-FEWS processing modules

• Quality Control is persistent • Spatial display can be used to get overview of validation flags

• Recent developments on “Custom Flag Source”, Persistent flag, Spatial Homogeneity

tests, etc..

In the Time Series display it is possible to show graphs with and without void data • 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 • Select the Validation menu element from the Table button (CTRL+Shift+J)

Primary Data Validation Rules

Flag sources: •IMP = Imported •MAN = Manual •HN = Hard Min (PV) •HX = Hard Max (PV) •SN = Soft Min (PV) •SX = Soft Max (PV)

(PV=Primary Validation)

17 December 2012 Delft-FEWS: QC, Edits, Modifiers en What-If's

Quality Control examples FEWS Rivieren

• Some examples with data editor and spatial display

Persistent Void Data Flag

• The persistent void validation flag is a special flag; it can be copied forward in time. • Set persistent void flag manually in Plots table (flag source

= SFP)

• In processing workflow the persistent void flag is copied to next time steps prior to T0 (flag source = SVP)

• Copy process stops when manual flag is found that makes the data reliable again

• This flag can be used when sensor is not working anymore

Use of modifiers in QC and processing

• FEWS can use modifiers to apply changes to time series or model parameters

• A modifier change is made without actually editing the values themselves. The changes are established as a "description of the change“

• A modifier display is used to apply modifiers to the data

• Modifiers can be used in QC and modeling:

• Rating Curve modifier: Change the rating curve table for a selected location • Sensor Switch modifier: Change the preferred sensor, used in water level and

rainfall data hierarchy merging • Missing modifier: Make a rainfall time series missing for a selected time period

• For all locations with time series modifiers (missing modifier) an overview can be

made in Spatial display; like validation flags.

Sensor Switch modifier

• The Sensor Switch modifier can be used to switch the sensor preference for a rainfall station gauge or a water level station (change hierarchy)

• Temporarily change the hierarchy of the sensors when merging the observed time series to produce the processed time series

Missing Modifier

• The Missing modifier can be used to switch off a gauge for a specified period

Modifiers in Forecasts

• Modifiers are mainly used in forecast workflows • Modifiers can influence transformations, data hierarchy, model states, model

parameters, model output time series. • Modifiers are entered with the Modifier display • Each modifier has its own frame in the modifier display

Forecast Tree (Topology) guides the forecaster through the forecasting process 1. Select node from Forecast Tree 2. Select Modifier tab to enter and a modifier 3. Press Apply button to activate modifier 4. Press Run (Local or Server) to run workflow 5. 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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Modifier example: Rainfall Scenarios

• In HyFS a Rainfall Scenario is a configured Location Attribute Modifier • Each catchment or sub-catchment has attributes with preferred scenario

• Modifier is used to change the location attribute values • The ‘modified’ attribute values will be used in the Forecast Workflows until it is switched

off.

Example Rainfall Scenarios

• In Transformation module the merge – selectDataSource function is used

• ‘Modified’ location attribute values are used to select the correct NWP model or rainfall multiplier

Modifiers for models parameters

• Changing model parameters with modifier works the same as any other modifier • Change the default model parameters • Can only be used if model adapter supports exchange of model parameters!

Example Model parameter

• In General Adapter the export parameter activity is used in combination with Model Parameter File.

• ‘Modified’ (model parameter) location attribute values are exported to the model

What-if Display

• Several displays in FEWS can be used • Flexibility is limited to time series and parameterSet and modeldataSet • Forecasters find the display not very user friendly

Time Series • Transformationsets • Typical profiles File selection • Module parameter files • Module data set files

What-if Display

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

Should modifiers replace what-if scenarios?

No ! • Currently complete different concept (always applied vs. applied when chosen)

Yes ! • GUI is more attractive • Underlying framework is more powerful • 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: • Ability to connect modifiers to specific runs (workflows) • Selection of module data set • GUI design issues:

> Where/how to connect Modifier to scenario > Where/how to connect scenario to run