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: prepare_timeseries basic_model fix_parameters calibration_options adding_rivers adding_wells multiple_wells hantush_response adding_trends changing_responses threshold_non_linear non_linear_recharge recharge_estimation snowmodel comparing_models diagnostic_checking timestep_analysis uncertainty uncertainty_emcee uncertainty_ls_mcmc standardized_groundwater_index signatures ensemble_predictions Basics ------ `Preprocessing user-provided time series`_ `A basic model`_ `Fixing parameters while fitting`_ `Calibration`_ `Modeling with different timesteps`_ .. _Preprocessing user-provided time series: prepare_timeseries.html .. _A basic model: basic_model.html .. _Fixing parameters while fitting: fix_parameters.html .. _Calibration: calibration_options.html .. _Modeling with different timesteps: modeling_timestep.html Stressmodels ------------ `Adding surface water levels`_ `Adding pumping wells`_ `Adding multiple wells`_ `Adding trends`_ `Changing response functions`_ .. _Adding surface water levels: adding_rivers.html .. _Adding pumping wells: adding_wells.html .. _Adding multiple wells: multiple_wells.html .. _Adding trends: adding_trends.html .. _Changing response functions: changing_responses.html Non-linear (Recharge) Models ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ `Threshold non-linearities`_ `Non-linear recharge models`_ `Estimating recharge`_ `Modeling snow`_ .. _Threshold non-linearities: threshold_non_linear.html .. _Non-linear recharge models: non_linear_recharge.html .. _Estimating recharge: recharge_estimation.html .. _Modeling snow: snowmodel.html Model Evaluation ---------------- `Comparing models visually`_ `Diagnostic checking`_ `Reducing autocorrelation`_ `Uncertainty quantification`_ `MCMC uncertainty`_ `MCMC vs. LS`_ .. _Comparing models visually: comparing_models.html .. _Diagnostic checking: diagnostic_checking.html .. _`Reducing autocorrelation`: timestep_analysis.html .. _Uncertainty quantification: uncertainty.html .. _MCMC uncertainty: uncertainty_emcee.html .. _MCMC vs. LS: uncertainty_ls_mcmc.html Applications ------------ `Standardized Groundwater Index`_ `Groundwater signatures`_ `Ensemble predictions`_ .. _Standardized Groundwater Index: standardized_groundwater_index.html .. _Groundwater signatures: signatures.html .. _Ensemble predictions: ensemble_predictions.html Time Series Analysis Manual --------------------------- The `notebooks `_ from the Dutch Manual on Time Series Analysis, which use Pastas, have been translated into English and are available below. The full manual can be found here: Von Asmuth, J., Baggelaar, P., Bakker, M., Brakenhoff, D., Collenteur, R., Ebbens, O., Mondeel, H., Klop, S., & Schaars, F. (2021). Handleiding Tijdreeksanalyse (`STOWA rapport nr. 32 `_). Stichting Toegepast Onderzoek Waterbeheer, Amersfoort. `Preprocessing`_ `Model structure`_ `Model calibration`_ `Model assessment`_ `Case Study 1 Assessing contributions`_ `Case Study 2 Determining characteristics`_ `Case Study 3 System analysis`_ `Case Study 4 Forecasting`_ .. _Preprocessing: stowa_preprocessing.html .. _Model structure: stowa_model_structure.html .. _Model calibration: stowa_calibration.html .. _Model assessment: stowa_assessment.html .. _Case Study 1 Assessing contributions: stowa_cases_contribution_assessment.html .. _Case Study 2 Determining characteristics: stowa_cases_characteristics.html .. _Case Study 3 System analysis: stowa_cases_system_analysis.html .. _Case Study 4 Forecasting: stowa_cases_forecasting.html Pastas Performance ------------------ `Caching for performance`_ .. _Caching for performance: caching_for_performance.html