Calibration Twin: Recharge-Step K+Sy 1D#
Note
This page and its static assets are auto-generated by python -m tools.doc_gallery. The Sphinx build only reads committed PNG and JSON artifacts.
Same-solver twin benchmark on linearized_unconfined_recharge_step_1d with K+Sy and multiobservable head/flux blocks.
success_metric=best_fit
meets_target=False
truth_recovered=False
cost=0.529874
n_eval=16
calibration=24.95 s
candidate runtime=24.53 s
algorithm overhead=0.419 s
actualize=0 s
launcher prep=0 s
runtime patch=0 s
simulate=1.533 s
output select=0 s
objective score=0 s
success_metric=best_fit_or_distribution
meets_target=True
truth_recovered=True
cost=0.206196
n_eval=40
calibration=68.87 s
candidate runtime=67.64 s
algorithm overhead=1.228 s
actualize=0 s
launcher prep=0 s
runtime patch=0 s
simulate=1.691 s
output select=0 s
objective score=0 s
success_metric=best_fit
meets_target=True
truth_recovered=True
cost=0.214878
n_eval=40
calibration=107.8 s
candidate runtime=105.7 s
algorithm overhead=2.05 s
actualize=0 s
launcher prep=0 s
runtime patch=0 s
simulate=2.644 s
output select=0 s
objective score=0 s
success_metric=best_fit
meets_target=True
truth_recovered=True
cost=0.219763
n_eval=12
calibration=35.57 s
candidate runtime=35.03 s
algorithm overhead=0.5338 s
actualize=0 s
launcher prep=0 s
runtime patch=0 s
simulate=2.92 s
output select=0 s
objective score=0 s
success_metric=best_fit_or_distribution
meets_target=False
truth_recovered=False
cost=0.569137
n_eval=16
calibration=32.19 s
candidate runtime=24.77 s
algorithm overhead=7.423 s
actualize=0 s
launcher prep=0 s
runtime patch=0 s
simulate=1.548 s
output select=0 s
objective score=0 s
success_metric=best_fit_or_distribution
meets_target=False
truth_recovered=False
cost=2.22364
n_eval=10
posterior_samples=10
calibration=15.55 s
candidate runtime=15.22 s
algorithm overhead=0.3297 s
actualize=0 s
launcher prep=0 s
runtime patch=0 s
simulate=1.522 s
output select=0 s
objective score=0 s
Case Setup#
Solver: modflow6 in transient regime.
Benchmark family: No-Uncertainty, Data-Rich Benchmarks.
Truth parameters: K_global, Sy_global.
Observed outputs: head_mid, q_east.
Benchmarked methods: random_search, optuna, cma_es, scipy_nelder_mead, gp_mapping, da_mh_gp.
Initial bounds widened to: K_global=[5e-05, 0.0003], Sy_global=[0.04, 0.18].
What It Shows#
A same-solver twin experiment where synthetic observations are generated first, then recovered through calibration on the same physics stack.
A case-level configuration figure, an objective trace, and an objective landscape or pairwise projection for the selected display method.
Per-method timing diagnostics with total calibration time plus average per-model preparation, simulation, and objective-evaluation costs.
How To Read It#
Open case_configuration.png first to understand the parameter block, outputs, and weighting before reading the optimization figures.
Use objective_trace to judge convergence speed and objective_landscape to see where the evaluated candidates concentrate relative to the truth and the selected solution(s).
Read timing metrics as benchmark diagnostics, not as universal solver performance numbers: they depend on the chosen method, case size, and evaluation budget.
Key Metrics#
Methods: 5
Display method: gp_mapping
Calibration total: 74.27 s
Session prep: 78.49 s
Candidate runtime: 68.21 s
Algorithm overhead: 6.054 s
Model total: 4.263 s
Actualize: 0.2249 s
Launcher prep: 0.2249 s
Runtime patch: 0 s
Model prep: 0.2249 s
Model sim: 4.038 s
Output select: 0 s
Objective score: 0 s
Next Steps#
Compare this case with the other calibration gallery pages to see how deterministic and distribution-valued methods behave under different inverse problems.
Use the full benchmark suite in validation_cases/calibration when you need multi-seed comparisons or noisy variants beyond the curated gallery subset.
Reproduce#
Run the underlying example or validation case with:
python -m validation_cases.calibration.twin.transient.linearized_unconfined_recharge_step_1d.run_case
Refresh the committed gallery artifacts with:
python -m tools.doc_gallery
Case Parameters#
Benchmark Setup#
Field |
Meaning |
Value |
Source |
|---|---|---|---|
|
Solver family used both to generate synthetic observations and to calibrate candidates. |
modflow6 |
|
|
Flow regime exercised by the inverse benchmark. |
transient |
|
|
Observables extracted from each candidate simulation and used in the composite objective. |
head_mid, q_east |
|
|
Synthetic noise injected after the truth run, if any. |
none |
|
Calibrated Parameters#
Field |
Meaning |
Value |
Source |
|---|---|---|---|
|
Truth value, initial search interval, and acceptance tolerance for this calibrated parameter. |
truth=0.0001, bounds=5e-05, 0.0003, tolerance=1.5e-05 |
|
|
Truth value, initial search interval, and acceptance tolerance for this calibrated parameter. |
truth=0.1, bounds=0.04, 0.18, tolerance=0.04 |
|
Methods And Timing#
Field |
Meaning |
Value |
Source |
|---|---|---|---|
|
Method result summary including target status, evaluation count, total time, and mean per-model actualize / launcher / simulation / objective timings. |
meets_target=false, cost=0.529874, n_eval=16, calib_s=50.3573, candidate_runtime_s=50.2016, algorithm_overhead_s=0.155745, actualize_s=0.231356, launcher_prep_s=0.231356, runtime_patch_s=0, model_sim_s=2.90624, output_select_s=0, objective_score_s=0 |
|
|
Method result summary including target status, evaluation count, total time, and mean per-model actualize / launcher / simulation / objective timings. |
meets_target=true, cost=0.214878, n_eval=40, calib_s=134.22, candidate_runtime_s=133.715, algorithm_overhead_s=0.504982, actualize_s=0.233398, launcher_prep_s=0.233398, runtime_patch_s=0, model_sim_s=3.10947, output_select_s=0, objective_score_s=0 |
|
|
Method result summary including target status, evaluation count, total time, and mean per-model actualize / launcher / simulation / objective timings. |
meets_target=true, cost=0.219763, n_eval=12, calib_s=106.26, candidate_runtime_s=106.094, algorithm_overhead_s=0.166063, actualize_s=0.343487, launcher_prep_s=0.343487, runtime_patch_s=0, model_sim_s=8.49768, output_select_s=0, objective_score_s=0 |
|
|
Method result summary including target status, evaluation count, total time, and mean per-model actualize / launcher / simulation / objective timings. |
meets_target=true, cost=0.320649, n_eval=16, calib_s=74.2689, candidate_runtime_s=68.2146, algorithm_overhead_s=6.05423, actualize_s=0.224947, launcher_prep_s=0.224947, runtime_patch_s=0, model_sim_s=4.03847, output_select_s=0, objective_score_s=0 |
|
|
Method result summary including target status, evaluation count, total time, and mean per-model actualize / launcher / simulation / objective timings. |
meets_target=true, cost=2.22364, n_eval=72, posterior_samples=72, calib_s=310.144, candidate_runtime_s=300.871, algorithm_overhead_s=9.2731, actualize_s=0.296197, launcher_prep_s=0.296197, runtime_patch_s=0, model_sim_s=3.88257, output_select_s=0, objective_score_s=0 |
|
Displayed Metrics#
Field |
Meaning |
Value |
Source |
|---|---|---|---|
|
Metric surfaced on the gallery page for the selected display method. |
5 |
|
|
Metric surfaced on the gallery page for the selected display method. |
gp_mapping |
|
|
Metric surfaced on the gallery page for the selected display method. |
74.27 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
78.49 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
68.21 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
6.054 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
4.263 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
0.2249 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
0.2249 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
0 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
0.2249 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
4.038 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
0 s |
|
|
Metric surfaced on the gallery page for the selected display method. |
0 s |
|
Source Pointers#
validation_cases/calibration/README.mdvalidation_cases/calibration/run_benchmarks.pyvalidation_cases/calibration/plotting.pyvalidation_cases/calibration/shared/definitions.pyvalidation_cases/calibration/shared/runtime.pyvalidation_cases/calibration/twin/transient/linearized_unconfined_recharge_step_1d/run_case.pyvalidation_cases/calibration/twin/transient/linearized_unconfined_recharge_step_1d/experiment.pyhydromodpy/calibration/cli.pyhydromodpy/calibration/engine.py
Artifacts#
docs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__configuration.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__random_search_landscape.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__random_search_trace.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__cma_es_landscape.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__cma_es_trace.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__simplex_landscape.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__simplex_trace.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__gp_mapping_landscape.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__gp_mapping_trace.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__da_mh_gp_landscape.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__da_mh_gp_trace.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6__da_mh_gp_posterior.pngdocs/readthedocs/source/_static/capability_gallery/calibration/calibration_twin_linearized_recharge_step_modflow6_summary.jsonstores the displayed metrics plus source hashes used bypython -m tools.doc_gallery --check.