For everyone who worked with Menyanthes From Menyanthes to Phrea
Modelling on your own measurements
Dawaco Phrea™ gives Pastas a complete graphical workspace for modelling. Explain groundwater levels from precipitation, evaporation and abstraction, look ahead with an uncertainty band and set a scenario next to the baseline: on the measurements you already manage, with the map alongside and no programming.
Pastas, without scripts
Pastas, with a graphical workspace
Worked with Menyanthes? In Phrea you build Pastas models with the mouse, on your own measurements, with the map alongside.
No scripts. Choose a well; KNMI precipitation and evaporation are found for you, and you calibrate in one click.
The map belongs to it. Model and well are linked to the map both ways: from model to well, and from well to model.
What moves the groundwater level?
A time-series model splits the measured level into the contribution of each cause. You see which part of the pattern comes from the weather and which part from an abstraction.
Phrea calculates with Pastas, the open-source engine for groundwater time-series analysis. You see how strongly the groundwater responds to a wet or dry season, and which part of the pattern an abstraction explains.
The model takes the level from the same system in which you measure, validate and deliver. The result comes back next to the measurements, not in a loose file on someone's drive.
Every result shows how well the model fits, so you judge it before you act on it. A model value is not a measurement, and you can always tell.
What a time-series model needs is already there
Your measurements, the weather, the abstraction and the map: in the same product, with no exports between packages.
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On your own measurements
The model reads the groundwater level from your own network: the same series you manage and validate. No second version of the truth.
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The weather is already there
The weather is already there: nothing to fetch yourself.
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Abstraction as a cause
Separate the effect of an abstraction from the effect of the weather, and back up your conversation about a permit or a measure.
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The map belongs to it
From model to well on the map, and from a well on the map to its model. The spatial picture stays with the series.
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Look ahead and ask what-if
Forecasts with an uncertainty band, and a scenario next to the baseline to see what a measure does.
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Open and reproducible
Every result can be retrieved, and every model exports to Pastas' own file format, so you can always continue in Python.
Some features are available as an add-on module. Time-series modelling is available as a module.
Looking ahead
Look ahead, and ask what if
Run ahead with an uncertainty band, so you see how certain an expectation is. Or set a scenario next to the baseline: what does the level do if the abstraction is halved? The difference is shown, with the assumptions.
That turns a model into something to discuss: for a permit application, a measure or a question from the neighbourhood.
From one well to a whole area
Build models for many wells at once, and keep them current. The picture of a whole area stays up to date, even when nobody thinks of it.
So you no longer update every model one by one, and a new year of measurements does not pass your models by unnoticed.
Honest about what a model is
A model value is not a measurement. You always see that.
From a forecast, Phrea calculates the GHG, GLG and GVG. Those values never appear on their own: they always carry the label ‘projected from a model simulation, not measured’, with the uncertainty band. So a model number never slips into a report or a permit file as a measured value.
And every result can be retrieved. Whoever asks next year where a number came from gets an answer. Because every model also exports to Pastas' own file format, you are never locked in.
What modelling in one product changes
Three places where models in the same product deliver something different from a modelling package on the side.
FAQ
Frequently asked questions about modelling
Is Dawaco Phrea™ an alternative to Menyanthes?
Yes, for time-series analysis of groundwater levels. Phrea uses Pastas as its calculation engine and gives it a complete graphical workspace for modelling (build, calibrate, assess, forecast), with the map alongside. It is not a new version of Menyanthes, and not a copy: you work in one product that also covers your monitoring network, validation and BRO delivery. From Menyanthes to Phrea
Is Menyanthes still supported?
According to its own download page, the freely downloadable version of Menyanthes is no longer supported. For the status of other versions, please ask its makers.
Do I need to program?
No. You build, calibrate, assess, forecast and run a scenario in Phrea with the mouse. If you do want to continue in Python, export the model to Pastas' own file format.
What is Pastas?
Pastas is open-source software (MIT licence) for groundwater time-series analysis, scientifically published in 2019. It continues the method that Menyanthes was also based on. Pastas is driven by Python scripts; Phrea adds the graphical workspace, on the same data you manage.
Which series can the model use?
KNMI precipitation and evaporation, and abstraction as an explanatory series. With these the model explains the groundwater level from the weather and from the influence of a well field.
Can I retrieve an earlier model result?
Yes. Every model result can be retrieved and accounted for later.
Are the projected GHG, GLG and GVG measurements?
No. They come from a model simulation and are therefore always shown with the label ‘projected from a model simulation, not measured’.
Can Phrea also do spatial modelling?
Not yet: Phrea models time series per observation well. Spatial groundwater modelling and 3D visualisation are on the roadmap.
Is modelling included in Phrea as standard?
Time-series modelling is available as a module.
When is Phrea available?
Dawaco Phrea™ is available from October 2026.
Menyanthes and Pastas are named here descriptively. Dawaco is not affiliated with the makers or rights holders of Menyanthes, nor with the Pastas project.
See your own wells in a time-series model
In a demo we show on example wells how Phrea explains levels and looks ahead, also if you come from Menyanthes. Available from October 2026.