Property:Describe numerical limitations
From CSDMS
This is a property of type Text.
C
ROMS has a predictior-corrector algorithm that is efficient and accuarate. This class of model (terrain-following) exhibits stronger sensitivity to topography which results in pressure gradient errors. ROMS has several pressure gradient algorithms that minimize this problem. +
U
ROMS has a predictior-corrector algorithm that is efficient and accuarate. This class of model (terrain-following) exhibits stronger sensitivity to topography which results in pressure gradient errors. ROMS has several pressure gradient algorithms that minimize this problem. +
C
ROMS has a predictior-corrector algorithm that is efficient and accuarate. This class of model (terrain-following) exhibits stronger sensitivity to topography which results in pressure gradient errors. ROMS has several pressure gradient algorithms that minimize this problem. +
Run times can be long (60 +days for large areas over many 100's of years).
Flow model is steady state +
L
Runs slowly - iterates implicit scheme. Some sort of matrix algebra might improve speed. +
M
Runs with grid sizes greater than about 600x600 may require many days on a PC.
Model assumes fluvial streams have gradients determined by steady-state transport.
Depositional stratigraphy not modeled. +
S
SBEACH is an empirically based model that was developed for sandy beaches with uniform representative grain sized in the range of 0.2 to 0.42 mm. SBEACH should be tested or calibrated using data from beach profile surveyed before and after storms on the project coast. +
P
See 'Description of Input and Examples for PHREEQC Version 3 - A computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations'. +
W
See WRF-Hydro Technical Description https://ral.ucar.edu/projects/wrf_hydro/technical-description-user-guide +
E
See article: https://doi.org/10.3390/rs10121915 +
C
See documentation. The major limitation is computational time. This can be alleviated with sensible selection of module parameters. See documentation for guidance. +
T
See https://tribshms.readthedocs.io/en/latest/ +
S
N
See related publication by J. A. Czuba. +
R
See related publications by J. A. Czuba. +
F
See:
Version 2.0: Cohen et al. (2019), The Floodwater Depth Estimation Tool (FwDET v2.0) for Improved Remote Sensing Analysis of Coastal Flooding. Natural Hazards and Earth System Sciences (NHESS)
Version 1.0: Cohen, S., G. R. Brakenridge, A. Kettner, B. Bates, J. Nelson, R. McDonald, Y. Huang, D. Munasinghe, and J. Zhang (2017), Estimating Floodwater Depths from Flood Inundation Maps and Topography. Journal of the American Water Resources Association (JAWRA):1–12. +
D
G
Semi-implicit solution can decrease in accuracy for extremely long (hundreds of millions of years for typical input parameters) time steps +
P
F
