Examples ======== Below you can find examples of how Pastas models are used for the analysis of groundwater levels. Examples in the form of Python scripts can also be found on the `examples directory on GitHub `_. .. toctree:: :maxdepth: 4 :hidden: :glob: ./* Basics ------ `Preprocessing user-provided time series`_ `A basic model`_ `Fixating parameters while fitting`_ `Calibration`_ .. _Preprocessing user-provided time series: 00_prepare_timeseries.ipynb .. _A basic model: 01_basic_model.ipynb .. _Fixating parameters while fitting: 02_fix_parameters.ipynb .. _Calibration: 03_calibration_options.ipynb Stressmodels ------------ `Adding surface water levels`_ `Adding pumping wells`_ `Adding multiple wells`_ `Adding trends`_ `Changing response functions`_ .. _Adding surface water levels: 04_adding_rivers.ipynb .. _Adding pumping wells: 05_adding_wells.ipynb .. _Adding multiple wells: 06_multiple_wells.ipynb .. _Adding trends: 07_adding_trends.ipynb .. _Changing response functions: 08_changing_responses.ipynb Non-linear (Recharge) Models ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ `Threshold non-linearities`_ `Non-linear recharge models`_ `Estimating recharge`_ `Modeling snow`_ .. _Threshold non-linearities: 09_threshold_non_linear.ipynb .. _Non-linear recharge models: 10_non_linear.ipynb .. _Estimating recharge: 11_recharge_estimation.ipynb .. _Modeling snow: 12_snowmodel.ipynb Model Evaluation ---------------- `Comparing models visually`_ `Diagnostics checking`_ `Reducing autocorrelation`_ `Uncertainty quantification`_ `MCMC uncertainty`_ .. _Comparing models visually: 13_comparing_models.ipynb .. _Diagnostics checking: 14_diagnostics_checking.ipynb .. _`Reducing autocorrelation`: 15_timestep_analysis.ipynb .. _Uncertainty quantification: 16_uncertainty.ipynb .. _MCMC uncertainty: 17_emcee_uncertainty.ipynb Applications ------------ `Standardized Groundwater Index`_ `Groundwater signatures`_ .. _Standardized Groundwater Index: 18_sgi_example.ipynb .. _Groundwater signatures: 19_signatures.ipynb