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Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy.

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The methods behind the predefined impulse response function in continuous time (PIRFICT) time series model are extended to cover more complex situations where multiple stresses influence ground water head fluctuations simultaneously. In comparison to autoregressive moving average (ARMA) time series models, the PIRFICT model is optimized for use on hydrologic problems. The objective of the paper is twofold. First, an approach is presented for handling multiple stresses in the model. Each stress has a specific parametric impulse response function. Appropriate impulse response functions for other stresses than precipitation are derived from analytical solutions of elementary hydrogeological problems. Furthermore, different stresses do not need to be connected in parallel in the model, as is the standard procedure in ARMA models. Second, general procedures are presented for modeling and interpretation of the results. The multiple-input PIRFICT model is applied to two real cases. In the first one, it is shown that this model can effectively decompose series of ground water head fluctuations into partial series, each representing the influence of an individual stress. The second application handles multiple observation wells. It is shown that elementary physical knowledge and the spatial coherence in the results of multiple wells in an area may be used to interpret and check the plausibility of the results. The methods presented can be used regardless of the hydrogeological setting. They are implemented in a computer package named Menyanthes (www.menyanthes.nl).

Sinusoidal fluctuations of the flux at the soil surface dampen with depth in the vadose zone such that beyond a certain depth, flow may be approximated as steady. To investigate the damping with depth, we developed a new analytic solution for vertical periodic flow in the vadose zone, with a sinusoidal flux specified at the soil surface. The solution is based on the use of the Gardner–Kozeny model for hydraulic conductivity and soil moisture and on a linearization of the diffusive and advective terms in the governing differential equation. A characteristic length is presented for the damping of the flux with depth. At a depth of three times the characteristic length, the amplitude of the flux had reduced to 5% of the value at the surface. We compared the analytic solution to finite‐element solutions of the original, nonlinear differential equation for 16 soils based on four reference soils, using a daily sinusoidal cycling of evaporation and infiltration at the soil surface. For the soils and circumstances investigated, the analytic solution produced reasonable values of the damping factor at any depth in the soil profile compared with the finite‐element solutions. The solution is more accurate when the fluctuations (both amplitude and period) are smaller. The presented solution may be used for general cases of one‐dimensional infiltration when the surface flux is written as a Fourier series.