Property:Describe numerical limitations
From CSDMS
This is a property of type Text.
B
Model is solved implicitly, but can become inaccurate at very large (~1000 year) timesteps. When baselevel forcing is mild and block effects are significant, slope-inversion instabilities can develop. The model catches these and will not continue running. +
E
Model limitations are related to the use of the goal seek function in excel to find the solution. +
P
Model should never be numerically unstable but its behavior depends on ratios of various parameters. If the model seems to not be "doing anything", look at the parameter initialization functions in deltaRCM_tools.py +
M
Model slows down as layers are added making long runs (>2000 years) impractical. +
H
Model works well for resistant layer dips between 10 and 80 degrees. End members will work, but domain setup must be altered. +
D
Most Dakota analysis techniques require multiple iterations of a model to explore a requested parameter space, so an experiment created with Dakotathon can take a long time to run and produce a lot of model output. +
C
Most of the heavy lifting algorithms are implicit, thus numerically stable +
H
N
S
R
G
Numerical instabilities occur if the time step is too large. +
C
Numerical limitations and issues:
# Currently the model runs with a constant timestep, which is limited by the maximum inflow. Future versions may include adaptive time-stepping.
# As mentioned above, the model channels tend to be one or two cells wide. Future versions may address this issue with some combination of diffusive regularization or multi-scale modeling. +
A
Overall, the model is very computationally intensive. It is usually ran on a grid or a cluster. +
T
Overland flow is currently modeled in a nonstandard way. Diffusive wave and dynamic wave routing routines need more testing. The linkage between the unsaturated zone (infiltration component) and saturated zone (subsurface flow component and water table) is not robust. +
I
Poor scaling for ice-flow models with direct solvers (improves upon use of iterative solvers, but convergence is not systematic). +
T
C
Probably more than we know but none come to mind. +
M
R
