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Practice note: Naming and storing time-series data
This practice note is one of a set developed to provide consistency and transparency of river system models being used within the Murray-Darling Basin. The notes cover modelling practices, such as naming conventions for folder structures, to model methods, such as for flow routing and residual inflow estimation, and have been developed through a collaboration between the MDBA, Basin States and CSIRO.
Produced in collaboration with:
This practice note, Naming and storing time-series data, describes the recommended conventions for naming and storing of time series input data sets in eWater Source river system models that underpin water resource plans; and provides examples of implementing the conventions.
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Background
Large amounts of time-series data (e.g. daily rainfall) are required to be stored within river system models. Within eWater Source, time-series data are stored within the Data Sources Explorer ({+}https://wiki.ewater.org.au/display/SD41/Specifying + data +inputs#Specifyingdatainputs-+ DataSourcesExplorerinputs#DataSourcesExplorer).
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General principles
- An appropriate folder structure should be used for storing time series data within the Data Sources Explorer
- Folder names should allow users to easily identify the contents of the folder.
- Clearly named csv files should be created for each data type.
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Conventions
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for
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naming
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and
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storing
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time series data
- The following minimum set of folders should be created within the Data Sources Explorer:
- ClimateData
- DiversionsData
- FlowData
- GaugeData
- Miscellaneous
- SalinityData
- A single csv file should be created for each data type and the file name should clearly identify the data type (e.g. PatchedPointRainfall)
- All csv files should cover the same temporal period
- Where necessary, gauged inflows should be extended with -9999 to cover the period of the model run (as Source will only run over the period of the shorted time series file used as input).
- All columns in a csv file should have the same units.
- Each column within the csv file should have a sensible heading. For climate or flow data, this should be either the gauge name or the gauge number, or both.
Table 1: Recommended conventions for naming and storing time series data, with examples. (These examples are from the Murray and Lower Darling Source model)
Folder | Contents (csv files) | Units | Examples |
ClimateData | PatchedPointRainfall_csv | mm | Patched Point Rainfall data from Silo ( |
) |
MortonLakeEvaporation_csv | mm | Patched Point Morton Lake evapotranspiration from |
FAO56Evaporation_csv | mm | Patched Point FAO56 evapotranspiration from Silo ( |
Folder
Contents (csv files)
Units
Examples
SourceCalibrationStorageRel
eases
) | |||
DiversionsData | SourceIrrigationDiversions | ML/day | Observed diversion data |
FlowData | SourceInflows | ML/day | Flow data for inflows |
26/10/2017 | D18/5953 | 1 |
| SourceCalibrationStorageReleases | ML/day | Infilled flow data for setting storage |
| releases during calibration period | |||
| GaugeData | GaugedFlows | ML/day | Observed flow data |
| GaugedLevels | m | Observed reservoir levels for storages | |
| Miscellaneous | Regulators SourceAllocation_csv |
| SalinityData | SourceCalibrationGaugedSal inity_csv |
ty
| SourceCalibrationInflowSalinity_csv | EC |
26/10/2017 | D18/5953 | 2 |