Open xldeltares opened 1 year ago
Also related to the last item in https://github.com/xldeltares/hybridurb/issues/10
Inject delft3dfm model following the example below (ref: neural hydrology)
# --- Data configurations --------------------------------------------------------------------------
# which data set to use [camels_us, camels_gb, global, hourly_camels_us]
dataset: camels_us --> delft3dfm
# Path to data set root
data_dir: ../../data/CAMELS_US --> eindhoven
# Forcing product [daymet, maurer, maurer_extended, nldas, nldas_extended, nldas_hourly]
# can be either a list of forcings or a single forcing product
forcings: --> rainfall and runoff series
- maurer
- daymet
- nldas
dynamic_inputs: --> maybe not needed?
- PRCP(mm/day)_nldas
- PRCP(mm/day)_maurer
- prcp(mm/day)_daymet
- srad(W/m2)_daymet
- tmax(C)_daymet
- tmin(C)_daymet
- vp(Pa)_daymet
# which columns to use as target
target_variables:
- QObs(mm/d) --> mesh1d_water_depth_on_ground?
# clip negative predictions to zero for all variables listed below. Should be a list, even for single variables.
clip_targets_to_zero:
- QObs(mm/d)
For calibration of the regression module, calibration data set including rainfall timeseries at each rain gauges and maximum flood at manholes need to be prepared.