Final 0.3.0

mississipi.yaml

@@ -0,0 +1,89 @@
+# $ python3 -m nwm_routing -f -V4 ipu08b.yaml # CHANGE THIS
+#--------------------------------------------------------------------------------
+log_parameters:
+    #----------
+    showtiming: True
+    log_level : DEBUG
+    # log_directory: /ngen/t-route-files/ipu_01/logs/
+#--------------------------------------------------------------------------------
+network_topology_parameters:
+    #----------
+    supernetwork_parameters:
+        #----------
+        geo_file_path: /home/quinn/t-route/conus_datastream/RouteLink_CONUS.nc  
+        mask_file_path: /home/quinn/t-route/conus_datastream/ipu_runs/mask_files/reaches08b.txt # CHANGE THIS
+        network_type: 'NHDNetwork'
+        columns: 
+            key: 'link'
+            downstream: 'to'
+            dx : 'Length'
+            n : 'n'
+            ncc : 'nCC'
+            s0 : 'So'
+            bw : 'BtmWdth'
+            waterbody : 'NHDWaterbodyComID'
+            gages : 'gages'
+            tw : 'TopWdth'
+            twcc : 'TopWdthCC'
+            musk : 'MusK'
+            musx : 'MusX'
+            cs : 'ChSlp'
+            alt: 'alt'
+    synthetic_wb_segments:
+        default_factory=lambda: [
+            4800002,
+            4800004,
+            4800006,
+            4800007,
+        ]
+    waterbody_parameters:
+        #----------
+        break_network_at_waterbodies: False 
+#--------------------------------------------------------------------------------
+compute_parameters:
+    #----------
+    parallel_compute_method: by-subnetwork-jit-clustered # CHANGE THIS
+    compute_kernel         : V02-structured
+    assume_short_ts        : False
+    subnetwork_target_size : 1000 # according to t-route this is the most efficient for conus-wide simulations
+    cpu_pool               : 60 #CHANGE THIS
+    restart_parameters:
+        #----------
+        start_datetime: 1979-02-06_18:00 
+        # lite_channel_restart_file: /ngen/t-route-files/warmstate-2002/restart/channel_restart_200204171700
+    forcing_parameters:
+        #----------
+        qts_subdivisions            : 12 # 3600 / 300 = 12 (dt_qlateral / dt = qts_subdivisions)
+        dt                          : 300 # [sec]
+        qlat_input_folder           : /home/quinn/t-route-inputs/
+        qlat_file_pattern_filter    : "*.CHRTOUT_DOMAIN1"
+        nts                         : 2016 # 288 for 1day
+        max_loop_size               : 168  # [hr]  168 hours for one week
+    data_assimilation_parameters:
+        streamflow_da:
+            #----------
+            streamflow_nudging            : False
+            diffusive_streamflow_nudging  : False                  
+        reservoir_da:
+            #----------
+            reservoir_persistence_da:
+                #----------
+                reservoir_persistence_usgs  : False
+                reservoir_persistence_usace : False
+                reservoir_persistence_greatLake : False
+            reservoir_rfc_da:
+                #----------
+                reservoir_rfc_forecasts                 : False
+                reservoir_rfc_forecasts_time_series_path: rfc_TimeSeries/
+                reservoir_rfc_forecasts_lookback_hours  : 48
+
+#--------------------------------------------------------------------------------
+output_parameters:
+#     #----------
+    stream_output: 
+        stream_output_directory: /home/quinn/Contribute_troute/t-route/Not_Fixed # CHANGE THIS
+        stream_output_time: -1 #[hr]
+        stream_output_type: '.nc' #please select only between netcdf '.nc' or '.csv' or '.pkl'
+        stream_output_internal_frequency: 60 #[min] it should be order of 5 minutes. For instance if you want to output every hour put 60
+    lite_restart:
+        lite_restart_output_directory: /home/quinn/Contribute_troute/t-route/Restart/ # CHANGE THIS

src/kernel/diffusive/diffusive.f90

@@ -1446,7 +1446,6 @@ subroutine mesh_diffusive_backward(dtini_given, t0, t, tfin, saveInterval, j) !
                 !'previous z',z(i+1,j), 'dimensionless_D(i,j)', &
                 !dimensionless_D(i,j)
   !      stop
-         pause !test
       end if
       co(i) =q_sk_multi * co(i)
 

src/troute-config/troute/config/compute_parameters.py

@@ -64,8 +64,6 @@ class ComputeParameters(BaseModel):
     If True, Courant metrics are returnd with simulations. This only works for MC simulations
     """
 
-    giuh_node: Optional[bool] = None
-    """If True, flow q from the catchment is assumed to already be delayed using giuh and is added to qdc (flow downstream current timestep) instead of qlat (lateral flow into the reach).  This is only used for MC simulations. """
 
     restart_parameters: "RestartParameters" = Field(default_factory=dict)
     hybrid_parameters: "HybridParameters" = Field(default_factory=dict)

src/troute-config/troute/config/network_topology_parameters.py

@@ -113,22 +113,24 @@ def get_columns(cls, columns: dict, values: Dict[str, Any]) -> dict:
         if columns is None:
             if values['network_type']=="HYFeaturesNetwork":
                 default_columns = {
-                    'key'       : 'id',
-                    'downstream': 'toid',
-                    'dx'        : 'length_m',
-                    'n'         : 'n',
-                    'ncc'       : 'nCC',
-                    's0'        : 'So',
-                    'bw'        : 'BtmWdth',
-                    'waterbody' : 'rl_NHDWaterbodyComID',
-                    'gages'     : 'rl_gages',
-                    'tw'        : 'TopWdth',
-                    'twcc'      : 'TopWdthCC',
-                    'musk'      : 'MusK',
-                    'musx'      : 'MusX',
-                    'cs'        : 'ChSlp',
-                    'alt'       : 'alt',
-                    'mainstem'  : 'mainstem',
+                    'key'           : 'id',
+                    'downstream'    : 'toid',
+                    'dx'            : 'Length_m',
+                    'n'             : 'n',
+                    'ncc'           : 'nCC',
+                    's0'            : 'So',
+                    'bw'            : 'BtmWdth',
+                    'waterbody'     : 'WaterbodyID',
+                    'gages'         : 'rl_gages',
+                    'tw'            : 'TopWdth',
+                    'twcc'          : 'TopWdthCC',
+                    'musk'          : 'MusK',
+                    'musx'          : 'MusX',
+                    'cs'            : 'ChSlp',
+                    'alt'           : 'alt',
+                    'mainstem'      : 'mainstem',
+                    'flowpath_id'   : 'flowpath_id',
+                    'flowpath_toid' : 'flowpath_toid'
                     }
             else:
                 default_columns = {
@@ -218,6 +220,14 @@ class Columns(BaseModel):
     """
     mainstem ID
     """
+    flowpath_id: Optional[str]
+    """
+    flowpath id
+    """
+    flowpath_toid: Optional[str]
+    """
+    flowpathto id
+    """
 
 
 class WaterbodyParameters(BaseModel):
@@ -253,5 +263,4 @@ class LevelPool(BaseModel):
 PreprocessingParameters.update_forward_refs()
 SupernetworkParameters.update_forward_refs()
 WaterbodyParameters.update_forward_refs()
-LevelPool.update_forward_refs()
-
+LevelPool.update_forward_refs()

src/troute-network/troute/AbstractNetwork.py

@@ -35,7 +35,8 @@ class AbstractNetwork(ABC):
                 "supernetwork_parameters", "waterbody_parameters","data_assimilation_parameters",
                 "restart_parameters", "compute_parameters", "forcing_parameters",
                 "hybrid_parameters", "preprocessing_parameters", "output_parameters",
-                "verbose", "showtiming", "break_points", "_routing", "_gl_climatology_df", "_nexus_dict", "_poi_nex_dict"]
+                "verbose", "showtiming", "break_points", "_routing", "_gl_climatology_df", "_nexus_dict", "_poi_nex_dict",
+                "_nexus_to_reach"]
 
 
     def __init__(self, from_files=True, value_dict={}):
@@ -780,9 +781,13 @@ def build_forcing_sets(self,):
 
         if forcing_glob_filter=="nex-*" or forcing_glob_filter == "cat-*":
             all_files = sorted(qlat_input_folder.glob(forcing_glob_filter))
-            final_timestamp = pd.read_csv(all_files[0], header=None, index_col=[0]).tail(1).iloc[0,0]
-            final_timestamp = datetime.strptime(final_timestamp.strip(), "%Y-%m-%d %H:%M:%S")
-
+            #final_timestamp = pd.read_csv(all_files[0], header=None, index_col=[0]).tail(1).iloc[0,0]
+            #final_timestamp = datetime.strptime(final_timestamp.strip(), "%Y-%m-%d %H:%M:%S")
+            # Instead of simply taking the last row of the lateral flow files, compute the actual
+            # simulation end time using the number of time steps and the simulation interval.
+            delt_hours = nts * dt / 3600 # simulation perios in hrs
+            final_timestamp = self.t0 + timedelta(hours = delt_hours)
+
             all_files = [os.path.basename(f) for f in all_files]
 
             run_sets = [