This function estimates lake water levels using a hydrological model with nudging to observed water levels. It optimizes parameters to minimize the error between simulated and observed levels, applying nudging to guide the simulation towards observed values.
Usage
estimate_lake_wlev(
data,
hyps_df,
model,
init_elev,
params = NULL,
initial_guess = NULL,
verbose = FALSE
)Arguments
- data
data frame with columns:
Date: Date of observation
HYD_flow: Inflow to the lake (m3/day)
MET_pprain: Precipitation on the lake surface (m/day)
evap_m3: Evaporation from the lake surface (m3/day)
lvl_obs: Observed lake water level (m)
is_obs_lvl: Logical indicating if lvl_obs is an observation (TRUE/FALSE)
- hyps_df
data frame with hypsograph data containing columns:
elev: Elevation (m)
area: Surface area at that elevation (m2)
volume: Volume at that elevation (m3)
- model
Character string indicating the evaporation model to use:
"dy_cd": DYRESM-CAEDYM dynamic evaporation
"glm_aed": GLM-AED dynamic evaporation
"gotm_wet": GOTM-WET dynamic evaporation
- init_elev
Numeric; initial lake elevation (m) to start the simulation. This should be a reasonable estimate based on the observed levels to ensure the optimization converges.
- initial_guess
Optional initial guess for optimization parameters:
C: Outflow coefficient
h_inv: Inversion height for outflow calculation
- verbose
Logical indicating whether to print optimization details