Methods#
A method is a tool inside a workflow, not the workflow itself. If you already know which measurement or which hydrological model you are working with, start from its page below. If you are choosing, start from Workflows instead and let the scientific question pick the method.
Every method page follows the same outline: what you can do, what it needs as input, what it produces, which workflow to open, whether the desktop application supports it, the Python examples, and the optional dependencies it requires.
Electrical resistivity tomography: forward modelling, single-survey and time-lapse inversion, structural constraints, field-data QC.
Travel-time tomography for velocity structure, and the structural information it contributes to a resistivity inversion.
Time- and frequency-domain electromagnetics: layered forward modelling, laterally constrained inversion along a line.
Potential-field anomalies, forward modelling of bodies, and compact 3D inversion.
MT and AMT: instrument time series to impedances by robust processing, phase tensors, Occam 1D with the static shift fixed by TEM, and 2D profiles.
GPR lines from GSSI, pulseEKKO, MALA and SEG-Y: clean-up, migration, velocity from diffraction hyperbolas, and depth sections.
The hydrological end: read model states, predict what a survey would record, and write an interpreted result back as model input.
Brine properties, ionic conductivity, clay surface conduction and seismic grain-contact models with explicit units and uncertainty inputs.
What each geophysical method needs and gives back#
Method |
Property it responds to |
Recovers |
Hydrological use |
|---|---|---|---|
ERT |
Electrical resistivity |
2D or 3D resistivity section |
Water content and saturation through a petrophysical relationship |
Seismic refraction |
P-wave velocity |
2D velocity section |
Weathering and bedrock boundaries, porosity |
TDEM / FDEM |
Electrical conductivity |
Layered conductivity soundings along a line |
Depth to conductive layers over larger areas than ERT covers |
Gravity / magnetics |
Density, magnetic susceptibility |
3D property distribution |
Basin and structural geometry |
Magnetotellurics |
Electrical resistivity, from metres to kilometres deep |
Layered soundings and 2D sections |
Aquifer and basement geometry below the reach of ERT; water content through a petrophysical relationship |
Ground-penetrating radar |
Relative permittivity |
2D reflection section in time or depth |
Layer boundaries and the water table in the top few metres; radar velocity, hence permittivity and water content |
MODFLOW and ParFlow sit on the other side of that table. They supply the water content, saturation and porosity the first column is predicted from, and they are where an interpreted result is written back.
One call across methods#
GeophysicalInversion dispatches to whichever method you name, so a script
can switch method without switching API.
from PyHydroGeophysX.inversion import GeophysicalInversion
inv = GeophysicalInversion("srt", data_file="examples/data/Seismic/srtfieldline2.dat")
result = inv.run()
# Also accepts: "ert", "tdem", "fdem", "joint_ert_srt"
Comparing methods over the same subsurface#
Ex. Hydrology to Multi-Geophysics Responses takes one hydrological profile and predicts what ERT, seismic, EM and gravity would each record over it, which is the fastest way to see what a given method can and cannot resolve for your site.