- ext_thiem_tpl(rad, r_ref, cond_gmean, len_scale, hurst, var=None, c=1.0, dim=2.0, lat_ext=1.0, rate=-0.0001, h_ref=0.0, K_well='KH', prop=1.6)[source]
The extended Thiem solution for truncated power-law fields.
The extended Theis solution for steady flow under a pumping condition in a confined aquifer. The type curve is describing the effective drawdown in a d-dimensional statistical framework, where the conductivity distribution is following a log-normal distribution with a truncated power-law correlation function build on superposition of gaussian modes.
numpy.ndarray) – Array with all radii where the function should be evaluated
float) – Reference radius with known head (see h_ref)
float) – Geometric-mean conductivity. You can also treat this as transmissivity by leaving ‘lat_ext=1’.
float) – Corralation-length of log-conductivity.
float) – Hurst coefficient of the TPL model. Should be in (0, 1).
float) – Variance of the log-conductivity. If var is given, c will be calculated accordingly. Default:
float, optional) – Intensity of variation in the TPL model. Is overwritten if var is given. Default:
float, optional) – Dimension of space. Default:
float, optional) –
Lateral extend of the aquifer:
sqare-root of cross-section in 1D
thickness in 2D
meaningless in 3D
float, optional) – Pumpingrate at the well. Default: -1e-4
float, optional) – Reference head at the reference-radius r_ref. Default:
float, optional) – Explicit conductivity value at the well. One can choose between the harmonic mean (
"KH"), the arithmetic mean (
"KA") or an arbitrary float value. Default:
float, optional) – Proportionality factor used within the upscaling procedure. Default:
head – Array with all heads at the given radii and time-points.
- Return type
If you want to use cartesian coordiantes, just use the formula
r = sqrt(x**2 + y**2)