diff --git a/src/troute-network/troute/DataAssimilation.py b/src/troute-network/troute/DataAssimilation.py
index fd72b0e29..ac0c63d27 100644
--- a/src/troute-network/troute/DataAssimilation.py
+++ b/src/troute-network/troute/DataAssimilation.py
@@ -432,14 +432,15 @@ def __init__(self, network, from_files, value_dict, da_run=[]):
                         reset_index().
                         set_index(['usgs_gage_id']) # <- TODO use input parameter for this
                     )
-                    
+                    gage_lake_df.usgs_lake_id = gage_lake_df.usgs_lake_id.astype(int)
+                    gage_lake_df.index = gage_lake_df.index.astype(str).str.strip()
                     # build dataframe that crosswalks gageIDs to segmentIDs
                     gage_link_df = (
                         network.link_gage_df['gages'].
                         reset_index().
                         set_index(['gages'])
                     )
-                    
+                    gage_link_df.index = gage_link_df.index.astype(str).str.strip()
                     # build dataframe that crosswalks segmentIDs to lakeIDs
                     link_lake_df = (
                         gage_lake_df.
@@ -447,7 +448,7 @@ def __init__(self, network, from_files, value_dict, da_run=[]):
                         reset_index().set_index('link').
                         drop(['index'], axis = 1)
                     )
-
+                    
                     # resample `usgs_df` to 15 minute intervals
                     usgs_df_15min = (
                         self._usgs_df.
@@ -462,18 +463,22 @@ def __init__(self, network, from_files, value_dict, da_run=[]):
                     # containing all of the rows it needs. By using pd.concat here we add in
                     # the missing rows. But this should be fixed earlier, likely in the 
                     # creation of the gages dictionary...
-                    reservoir_usgs_df = pd.concat(
-                        [
-                            usgs_df_15min.join(link_lake_df, how = 'inner').
-                            reset_index().
-                            set_index('usgs_lake_id').
-                            drop(['index'], axis = 1),
-                            usgs_df_15min.join(network.usgs_lake_gage_crosswalk, how='inner').
-                            drop(['usgs_gage_id'], axis = 1).
-                            rename_axis('usgs_lake_id')
-                        ]
-                    )
-                    
+
+                    if not link_lake_df.empty:
+                        reservoir_usgs_df = pd.concat(
+                            [
+                                usgs_df_15min.join(link_lake_df, how = 'inner').
+                                reset_index().
+                                set_index('usgs_lake_id').
+                                drop(['index'], axis = 1),
+                                usgs_df_15min.join(network.usgs_lake_gage_crosswalk, how='inner').
+                                drop(['usgs_gage_id'], axis = 1).
+                                rename_axis('usgs_lake_id')
+                            ]
+                        )
+                    else:
+                        reservoir_usgs_df = pd.DataFrame()
+
                     # create reservoir hybrid DA initial parameters dataframe    
                     if not reservoir_usgs_df.empty:
                         reservoir_usgs_param_df = pd.DataFrame(
@@ -532,7 +537,8 @@ def __init__(self, network, from_files, value_dict, da_run=[]):
         # an error. Need to think through this more. 
         if not self._usgs_df.empty:
             self._usgs_df = self._usgs_df.loc[:,network.t0:]
-    
+            self._usgs_df.index = self._usgs_df.index.astype(str).str.strip()
+
     def update_after_compute(self, run_results,):
         '''
         Function to update data assimilation object after running routing module.
diff --git a/src/troute-network/troute/NHDNetwork.py b/src/troute-network/troute/NHDNetwork.py
index 05738527c..874c5258f 100644
--- a/src/troute-network/troute/NHDNetwork.py
+++ b/src/troute-network/troute/NHDNetwork.py
@@ -269,16 +269,16 @@ def read_geo_file(self,):
             )
             
             if reservoir_da:
-                usgs_hybrid  = reservoir_da.get(
+                usgs_hybrid  = reservoir_da['reservoir_persistence_da'].get(
                     'reservoir_persistence_usgs', 
                     False
                 )
-                usace_hybrid = reservoir_da.get(
+                usace_hybrid = reservoir_da['reservoir_persistence_da'].get(
                     'reservoir_persistence_usace', 
                     False
                 )
                 param_file   = reservoir_da.get(
-                    'gage_lakeID_crosswalk_file',
+                    'reservoir_parameter_file',
                     None
                 )
             else:
@@ -287,18 +287,20 @@ def read_geo_file(self,):
                 usgs_hybrid = False
                 
             # check if RFC-type reservoirs are set to true
-            rfc_params = self.waterbody_parameters.get('rfc')
+               
+            rfc_params = reservoir_da['reservoir_rfc_da'] 
             if rfc_params:
                 rfc_forecast = rfc_params.get(
                     'reservoir_rfc_forecasts',
                     False
                 )
-                param_file = rfc_params.get('reservoir_parameter_file',None)
+                param_file = reservoir_da.get('reservoir_parameter_file',None)
             else:
                 rfc_forecast = False
-
+            
             if (param_file and reservoir_da) or (param_file and rfc_forecast):
                 self._waterbody_type_specified = True
+                
                 (
                     self._waterbody_types_df, 
                     self._usgs_lake_gage_crosswalk, 
@@ -315,6 +317,9 @@ def read_geo_file(self,):
                     reservoir_da.get('crosswalk_usace_lakeID_field', 'usace_lake_id'),
                     self.waterbody_connections.values(),
                 )
+                self._usgs_lake_gage_crosswalk['usgs_gage_id'] = self._usgs_lake_gage_crosswalk['usgs_gage_id'].apply(lambda x: x.decode('utf-8'))
+                self._usgs_lake_gage_crosswalk.index = self._usgs_lake_gage_crosswalk.index.astype(str).str.strip()
+
             else:
                 self._waterbody_type_specified = True
                 self._waterbody_types_df = pd.DataFrame(data = 1, index = self.waterbody_dataframe.index, columns = ['reservoir_type'])