Connecting geophysical data and hydrological models

The central question is what geophysical observations tell us about a hydrological model, and what that model predicts we should measure. Petrophysical relationships and spatial mapping connect the two.

Two directions of information

Direction	Information passed	Start with
Hydrological model → geophysical observations	Map water content, saturation and porosity to physical properties; simulate measurements for a specified survey geometry.	Hydrology to ERT, Hydrology to EM (TDEM and FDEM) and Ex. Hydrology to Multi-Geophysics Responses
Geophysical observations → hydrological interpretation	Recover physical-property models, then estimate water content or porosity using explicit petrophysical assumptions and uncertainty.	Field ERT Data QC and Ex. Monte Carlo Uncertainty Quantification for Hydrologic Properties Estimation
Repeated observations ↔ changing model states	Compare predicted and recovered changes across aligned observation times.	Time-Lapse Monitoring
Complementary surveys → structural information	Use velocity and resistivity information to interpret subsurface boundaries and evaluate structural assumptions relevant to hydrological modeling.	Seismic Structure Constraints and Joint ERT + SRT Inversion

A practical comparison workflow

1. Define the hydrological question. For example: can the proposed change in water content explain a measured change in resistivity?

2. Prepare the model states. Read the relevant MODFLOW / ParFlow outputs, preserve their time ordering and map them onto the geophysical mesh or profile.

3. Specify the petrophysical link. Record porosity, fluid properties and constitutive parameters. Different choices can explain similar measurements.

4. Predict measurements. Use the actual survey geometry and matching units. Compare predicted data with observed data, rather than comparing only images.

5. Interpret the observations. Inspect inversion fit and sensitivity before converting a recovered property model to hydrological quantities.

6. Evaluate the hydrological hypothesis. Compare states at compatible spatial and temporal scales, propagate relevant uncertainty, and decide whether the model assumptions need revisiting.

What the examples demonstrate

The forward examples demonstrate the model-to-measurement connection. The Monte Carlo example demonstrates petrophysical interpretation and parameter uncertainty. Time-lapse and joint examples supply additional observational constraints. These are complementary steps: running a geophysical inversion does not by itself calibrate or update a MODFLOW / ParFlow simulation. An automatic hydrological parameter-update loop requires a separately configured calibration or assimilation workflow; it is not implied by these examples. For the explicit write-back step, see Write updates back to hydrological models: export mapped parameters or initial states to MODFLOW 6 and ParFlow input files, then run and evaluate the hydrological simulation separately.

Recommended reading route

Ex. Loading and Processing Hydrological Model Outputs → Ex. ERT Workflow: From Hydrological Models to ERT responses and Inversion → Ex. Creating Synthetic Time-Lapse ERT Measurements → Ex. Time-Lapse ERT Inversion Techniques → Ex. Monte Carlo Uncertainty Quantification for Hydrologic Properties Estimation.

These examples illustrate successive concepts; check each example’s dataset, mesh and output format before transferring files between them. They are not an automatically connected pipeline.