anaflow.flow.neuman2004
- neuman2004(time, rad, storage, trans_gmean, var, len_scale, rate=-0.0001, r_well=0.0, r_bound=inf, h_bound=0.0, struc_grid=True, parts=30, lap_kwargs=None)[source]
The transient solution for the apparent transmissivity from [Neuman2004].
This solution is build on the apparent transmissivity from Neuman 2004, which represents a mean drawdown in an ensemble of pumping tests in heterogeneous transmissivity fields following an exponential covariance. Presented in [Neuman2004].
- Parameters
time (
numpy.ndarray
) – Array with all time-points where the function should be evaluated.rad (
numpy.ndarray
) – Array with all radii where the function should be evaluated.storage (
float
) – Storage of the aquifer.trans_gmean (
float
) – Geometric-mean transmissivity.var (
float
) – Variance of log-transmissivity.len_scale (
float
) – Correlation-length of log-transmissivity.rate (
float
, optional) – Pumpingrate at the well. Default: -1e-4r_well (
float
, optional) – Radius of the pumping-well. Default:0.0
r_bound (
float
, optional) – Radius of the outer boundary of the aquifer. Default:np.inf
h_bound (
float
, optional) – Reference head at the outer boundary as well as initial condition. Default:0.0
struc_grid (
bool
, optional) – If this is set toFalse
, the rad and time array will be merged and interpreted as single, r-t points. In this case they need to have the same shapes. Otherwise a structured r-t grid is created. Default:True
parts (
int
, optional) – Since the solution is calculated by setting the transmissivity to local constant values, one needs to specify the number of partitions of the transmissivity. Default:30
lap_kwargs (
dict
orNone
optional) – Dictionary forget_lap_inv
containing method and method_dict. The default is equivalent tolap_kwargs = {"method": "stehfest", "method_dict": None}
. Default:None
- Returns
head – Array with all heads at the given radii and time-points.
- Return type
References
- Neuman2004
Neuman, Shlomo P., Alberto Guadagnini, and Monica Riva. ‘’Type-curve estimation of statistical heterogeneity.’’ Water resources research 40.4, 2004