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Group | Transformation | Code completed? | Test completed? | Comment | |
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adjust | adjustStage |
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| New feature | |
adjust | adjustQ |
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| New feature | |
adjust |
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| New feature | ||
adjust |
|
| New feature | ||
adjust | adjustTide |
|
| New feature | |
aggregation | instantaneous |
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aggregation | accumulative |
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aggregation | instantaneousToMean |
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aggregation | meanToMean |
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aggregation | seasonal |
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altitude | zero degree altitude |
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altitude | elevation lapse |
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conditional | multiple |
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| This allows definition of multiple rule groups, combined with logical operators (from the current lookup module) | |
conversion | datum |
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| (New feature) This includes an enumeration option called direction local/global | |
disaggregation | accumulative |
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disaggregation | instantaneous |
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disaggregation | meanToInstantaneous |
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disaggregation | meanToMean |
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disaggregation | weights |
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discharge stage | power |
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| Uses the same coefficient sets as stage discharge power. | |
discharge stage | table |
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| Uses the same coefficient sets (for table entries) as stage discharge table. | |
evaporation | penmanNorthEast |
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| should be renamed to the specific type of penman equation | |
filter | moving window |
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| contains options average/maximum/minimum | |
filter | block |
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| contains options average/maximum/minimum | |
interpolation serial | block |
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interpolation serial | default |
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interpolation serial | extrapolate base |
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| Extrapolates by adding future values that start at the last data value and linearly approach a given base value. | |
interpolation serial | extrapolate constant |
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| Extrapolates by filling the gap between the start of the input time series and the first data value or by filling the gap between the last data value and the end of the input time series or by filling both of these gaps. | |
interpolation serial | extrapolate exponential |
|
| New feature: Extrapolates by adding future values that start at the last data value and exponentially approach a given base value. | |
interpolation serial | extrapolate persistence |
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| Extrapolates by adding future values that start with the last moving average value and exponentially approach zero. This can be used together with the filterMoving average and userSimple transformations to reproduce the old originalAndPersistence and movingAverageAndPersistence transformations. | |
interpolation serial | extrapolate trend |
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| Should contain option on how to extrapolate: persistence trend/running mean trend | |
interpolation serial | linear |
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interpolation spatial | average |
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interpolation spatial | bilinear |
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interpolation spatial | closest distance |
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interpolation spatial | kriging |
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interpolation spatial | sum |
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interpolation spatial | inputAverageTimesOutputArea |
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interpolation spatial | inverse distance |
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| (Uses Fortran 90 code) | |
interpolation spatial | sum |
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interpolation spatial | triangulation |
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| (Uses Fortran 90 code) Used to be called Renka & Cline | |
interpolation spatial | weighted |
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| This is the old weighted average approach used for rainfall. | |
lookup | simple |
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| should be called oneDimensional. From the current lookup module | |
lookup | twoDimensionalLookup |
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| should be called twoDimensional. New feature | |
lookup | twoDimensionalTable |
|
| From the current lookup module | |
merge | simple |
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| merge data hierarchy | |
merge | toggle |
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merge | mean |
|
| New feature | |
merge | synoptic |
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| This needs a true false element to indicate if the smaller or the larger quantities prevail (new feature) | |
merge | forecasts |
|
| equivalent to sampleForecasts - this is a new feature. | |
moisture | soil moisture |
|
| unit test not yet available | |
moisture | optical depth |
|
| unit test not yet available | |
precipitation | rainfallEvent |
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| writes median value of event (Enumeration of 2 to indicate where to write the data) | |
precipitation | rainfallEventLength |
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| writes length of event (Enumeration of 2 to indicate where to write the data) | |
precipitation | tipping bucket |
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profile | timeSeries |
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| Converts a profile to a time series. | |
profile | harmonics |
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| Converts an input profile consisting of harmonic components (a Fourier series) to a time series. | |
review | stageReview |
|
| New feature | |
review | tidal balanceReview |
|
| New feature | |
sample | historical |
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sample | forecasts |
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| This samples the first n values from a forecast - somewhat similar to the merge-forecast function | |
sample | equidistant |
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| converts an equidistant series to another equidistant series or to a non-equidistant series | |
sample | non-equidistant |
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| converts a non-equidistant series to another non-equidistant series or to an equidistant series | |
selection | peaks |
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selection | independent peaks |
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| previously called selectWithinHorizontalgaps | |
selection | lows |
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selection | independent lows |
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selection | maximum |
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selection | minimum |
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stage discharge | power |
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| Uses the same coefficient sets as discharge stage power. | |
stage discharge | power backwater |
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| Backwater correction (new feature). | |
stage discharge | power unsteady |
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| Unsteady flow (new feature). | |
stage discharge | parabolic |
|
| New feature | |
stage discharge | table |
|
| Uses the same coefficient sets (for table entries) as discharge stage table. | |
summaryStatistic statisticsSummary | sum, max, etc. |
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| Input is one time series. Output is one value. All values in the input series within the transformation run period are used to get a statistic output value. This is in the old transformations the case for which isBlockFunction is false and no season is specified. | |
cyclicStatistic statisticsCyclic | sum, max, etc. |
|
| These are the seasonal stats - used to define e.g. mean monthly temp. This is e.g. used in climatology to get e.g. the mean temperature in January over the last 100 years. This is in the old transformations the case for which isBlockFunction is false, a season is specified and seasonal is false. | |
ensembleStatistic statisticsEnsemble | sum, max, etc. |
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| Input is an ensemble with multiple time series. Output is one time series. Per time step the ensemble values for that time step are used to get a statistic output value. | |
spatialStatistic statisticsSpatial | sum, max, etc. |
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| New feature. Input is a grid time series. Output is a scalar time series. Per time step all grid cell values for that time step are used to get a statistic output value. | |
locationChildrenStatistic statisticsChildrenLocations | sum, max, etc. |
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| New feature. Input is multiple time series. Output is multiple time series. For each output series (with a parent location) the corresponding child locations are searched in the input series and used to get a statistic output value, per time step. | |
structure | general weir fixed height |
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structure | general weir variable height |
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structure | flatV weir |
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| Enumeration to indicate simple or crest tapping | |
structure | flatV weir backwater |
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| New feature | |
structure | crump weir |
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| Enumeration to indicate simple or crest tapping | |
structure | crump weir backwater |
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| New feature | |
structure |
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structure |
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structure |
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structure |
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time shift | constant |
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time shift | variable |
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time shift | length |
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user |
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| free format expression | ||
user |
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| This can be used for periodic output - the range can be defined, e.g 0-1, 0-360 or 0-100 |
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