hydromt_wflow.workflows.prepare_cold_states

hydromt_wflow.workflows.prepare_cold_states(ds_like: Dataset, config: dict, timestamp: str = None) → Tuple[Dataset, Dict[str, str]]

Prepare cold states for Wflow.

Compute cold states variables: * satwaterdepth: saturated store [mm] * snow: snow storage [mm] * tsoil: top soil temperature [°C] * ustorelayerdepth: amount of water in the unsaturated store, per layer [mm] * snowwater: liquid water content in the snow pack [mm] * canopystorage: canopy storage [mm] * q_river: river discharge [m3/s] * h_river: river water level [m] * h_av_river: river average water level [m] * ssf: subsurface flow [m3/d] * h_land: land water level [m] * h_av_land: land average water level[m] * q_land or qx_land**+**qy_land: overland flow for kinwave [m3/s] or

overland flow in x/y directions for local-inertial [m3/s]

If lakes, also adds: * waterlevel_lake: lake water level [m]

If reservoirs, also adds: * volume_reservoir: reservoir volume [m3]

If glaciers, also adds: * glacierstore: water within the glacier [mm]

Parameters:

• ds_like (xr.Dataset) –

  Dataset containing the staticmaps grid and variables to prepare some of the states.

  • Required variables: wflow_subcatch, wflow_river

  • Other required variables (exact name from the wflow config): c, soilthickness,

    theta_s, theta_r, kv_0, f, slope, ksathorfrac

  • Optional variables (exact name from the wflow config): reservoir.locs,

    glacierstore, reservoir.maxvolume, reservoir.targetfullfrac, lake.waterlevel

• config (dict) – Wflow configuration dictionary.

• timestamp (str, optional) – Timestamp of the cold states. By default uses the starttime from the config.

Returns:

• xr.Dataset – Dataset containing the cold states.

• dict – Config dictionary with the cold states variable names.