Open TBovenschen opened 1 year ago
Good suggestions! I would also be in favor of being able to still use the 'old' setup_riverwidth method.
For river depth, another suggestion could be to use directly discharge from wflow outputs based on kinematic wave approach (under the Lin database a return period of 2 years is used). Note that for the kinematic wave, a default bankfull_width of 1 meter an be used and has almost no impact on the results for water level and very little to no impact on the discharge.
Suggestion: split setup_rivers
into setup_rivers
(mask only and dem adjust) and setup_river_cross_sections
(width, depth, roughness)
setup_rivers
: derive mask and data from high res dem and width if available in this dataset
setup_river_cross_sections_from_vector
and setup_river_cross_sections(_from_raster)
should allow to update only width or only depth or only roughness. (later like d3d setup_river_cross_sections_from_point
xy crosssection)
roughness methods:
setup_rivers
maybe improve with table per resolution or upstream areawidth methods:
setup_rivers
setup_riverwidth
method - discharge is best - uparea can be okay locallydepth methods:
setup_rivers
setup_rivers
Also possible: create new river database merging lins and merit hydro data Add new river dataset GRIT: https://zenodo.org/records/7629908 Interesting abstract (data not yet available?): https://meetingorganizer.copernicus.org/EGU24/EGU24-19997.html
When no river geometry data is available (hydroAtlas or Lin 2019 do not have small rivers included) HydroMT does not create the riverwidth and -depth layers and the wflow model can not be run. Maybe the old deprecated method of setup_riverwidth could be used as backup to the new methods, to estimate the riverwidth based on discharge/precip/upstream area when no data is available. I think it would be most logical if this would be included as an option in the setup_river method. Another option would be to estimate the river width based on a raster (like merit_hydro). Merit_hydro has the river width data included, and it covers some area that are not covered by for example Lin 2019, so might be useful sometimes. I am however not sure whether this is possible and would give reliable results.