diff --git a/Core/LAMBDA/viz_functions/image_based/viz_hand_fim_processing/lambda_function.py b/Core/LAMBDA/viz_functions/image_based/viz_hand_fim_processing/lambda_function.py
index 783a726d..ff1c17da 100644
--- a/Core/LAMBDA/viz_functions/image_based/viz_hand_fim_processing/lambda_function.py
+++ b/Core/LAMBDA/viz_functions/image_based/viz_hand_fim_processing/lambda_function.py
@@ -107,7 +107,6 @@ def lambda_handler(event, context):
     s3_path_piece = ''
     
     # Get db table names and setup db connection
-    print(f"Adding data to {db_fim_table}")# Only process inundation configuration if available data
     db_schema = db_fim_table.split(".")[0]
     db_table = db_fim_table.split(".")[-1]
     if any(x in db_schema for x in ["aep", "fim_catchments", "catfim"]):
@@ -121,7 +120,7 @@ def lambda_handler(event, context):
     if "catchments" in db_fim_table:
         df_inundation = create_inundation_catchment_boundary(huc8, branch)
 
-        print(f"Adding data to {db_fim_table}")# Only process inundation configuration if available data
+        # print(f"Adding data to {db_fim_table}")# Only process inundation configuration if available data
         try:
             df_inundation.to_postgis(f"{db_table}", con=process_db.engine, schema=db_schema, if_exists='append')
         except Exception as e:
@@ -130,13 +129,11 @@ def lambda_handler(event, context):
         process_db.engine.dispose()
 
     else:
-        print(f"Processing FIM for huc {huc8} and branch {branch}")
+        print(f"Processing HUC-branch {huc8_branch} for {fim_config_name} for {date}T{hour}:00:00Z")
 
         s3_path_piece = '/'.join([run_values[by] for by in process_by])
         subsetted_data = f"{data_prefix}/{product}/{fim_config_name}/workspace/{date}/{hour}/data/{s3_path_piece}_data.csv"
 
-        print(f"Processing HUC {huc8} for {fim_config_name} for {date}T{hour}:00:00Z")
-
         if input_variable == 'stage':
             stage_lookup = s3_csv_to_df(data_bucket, subsetted_data)
             stage_lookup = stage_lookup.set_index('hydro_id')
@@ -154,14 +151,14 @@ def lambda_handler(event, context):
             stage_lookup = pd.DataFrame()
             df_zero_stage_records = pd.DataFrame()
             if catch_exists and hand_exists and rating_curve_exists:
-                print("->Calculating flood depth")
+                # print("->Calculating flood depth")
                 stage_lookup, df_zero_stage_records = calculate_stage_values(rating_curve_key, data_bucket, subsetted_data, huc8_branch)  # get stages
             else:
                 print(f"catchment, hand, or rating curve are missing for huc {huc8} and branch {branch}:\nCatchment exists: {catch_exists} ({catchment_key})\nHand exists: {hand_exists} ({hand_key})\nRating curve exists: {rating_curve_exists} ({rating_curve_key})")
  
         # If not a reference/egis fim run, Upload zero_stage reaches for tracking / FIM cache
         if fim_run_type != 'reference' and not df_zero_stage_records.empty:
-            print(f"Adding zero stage data to {db_table}_zero_stage")# Only process inundation configuration if available data
+            # print(f"Adding zero stage data to {db_table}_zero_stage")# Only process inundation configuration if available data
             df_zero_stage_records = df_zero_stage_records.reset_index()
             df_zero_stage_records.drop(columns=['hydro_id','feature_id'], inplace=True)
             df_zero_stage_records.to_sql(f"{db_table}_zero_stage", con=process_db.engine, schema=db_schema, if_exists='append', index=False)
@@ -184,7 +181,7 @@ def lambda_handler(event, context):
             df_no_inundation = stage_lookup.merge(df_inundation.drop_duplicates(), on=['hand_id'],how='left',indicator=True)
             df_no_inundation = df_no_inundation.loc[df_no_inundation['_merge'] == 'left_only']
             if df_no_inundation.empty == False:
-                print(f"Adding {len(df_no_inundation)} reaches with NaN inundation to zero_stage table")
+                # print(f"Adding {len(df_no_inundation)} reaches with NaN inundation to zero_stage table")
                 df_no_inundation.drop(df_no_inundation.columns.difference(['hand_id','rc_discharge_cms','note']), axis=1,  inplace=True)
                 df_no_inundation['note'] = "Error - No inundation returned from hand processing."
                 df_no_inundation.to_sql(f"{db_table}_zero_stage", con=process_db.engine, schema=db_schema, if_exists='append', index=False)
@@ -193,7 +190,7 @@ def lambda_handler(event, context):
             if df_inundation.empty:
                 return
         
-            print(f"Adding data to {db_fim_table}")# Only process inundation configuration if available data
+            # print(f"Adding data to {db_fim_table}")# Only process inundation configuration if available data
             try:
                 df_inundation.drop(columns=['hydro_id', 'feature_id'], inplace=True)
                 df_inundation.to_sql(db_table, con=process_db.engine, schema=db_schema, if_exists='append', index=False)
@@ -218,7 +215,7 @@ def lambda_handler(event, context):
             df_inundation['branch'] = branch
             df_inundation = df_inundation.rename(columns={"index": "oid"})
             
-            print(f"Adding data to {db_fim_table}")# Only process inundation configuration if available data
+            # print(f"Adding data to {db_fim_table}")# Only process inundation configuration if available data
             try:
                 df_inundation.to_postgis(f"{db_table}", con=process_db.engine, schema=db_schema, if_exists='append')
             except Exception as e:
@@ -228,8 +225,6 @@ def lambda_handler(event, context):
 
     print(f"Successfully processed tif for HUC {huc8} and branch {branch} for {product} for {reference_time}")
 
-    return
-
 def create_inundation_catchment_boundary(huc8, branch):
     """
         Creates the catchment boundary polygons
@@ -238,7 +233,7 @@ def create_inundation_catchment_boundary(huc8, branch):
     
     catchment_dataset = None
     try:
-        print("--> Connecting to S3 datasets")
+        # print("--> Connecting to S3 datasets")
         tries = 0
         raster_open_success = False
         while tries < 3:
@@ -249,12 +244,12 @@ def create_inundation_catchment_boundary(huc8, branch):
             except Exception as e:
                 tries += 1
                 time.sleep(30)
-                print(f"Failed to open datasets. Trying again in 30 seconds - ({e})")
+                # print(f"Failed to open datasets. Trying again in 30 seconds - ({e})")
 
         if not raster_open_success:
             raise HANDDatasetReadError("Failed to open HAND and Catchment datasets")
             
-        print("--> Setting up mapping array")
+        # print("--> Setting up mapping array")
         profile = catchment_dataset.profile  # get the rasterio profile so the output can use the profile and match the input  # noqa
 
         # set the output nodata to 0
@@ -262,7 +257,7 @@ def create_inundation_catchment_boundary(huc8, branch):
         profile['dtype'] = "int32"
 
         # Open the output raster using rasterio. This will allow the inner function to be parallel and write to it
-        print("--> Setting up windows")
+        # print("--> Setting up windows")
 
         # Get the list of windows according to the raster metadata so they can be looped through
         windows = subdivide(riowindows.Window(0, 0, width=catchment_dataset.width, height=catchment_dataset.height), 1024, 1024)
@@ -297,7 +292,7 @@ def process(window):
                 except Exception as e:
                     tries += 1
                     time.sleep(10)
-                    print(f"Failed to open catchment. Trying again in 10 seconds - ({e})")
+                    # print(f"Failed to open catchment. Trying again in 10 seconds - ({e})")
 
             if not catchment_open_success:
                 raise HANDDatasetReadError("Failed to open Catchment dataset window")
@@ -320,7 +315,7 @@ def process(window):
         if catchment_dataset is not None:
             catchment_dataset.close()
 
-    print("Generating polygons")
+    # print("Generating polygons")
     crs = 'EPSG:3338' if str(huc8).startswith('19') else 'EPSG:5070'
     df_final = gpd.GeoDataFrame(geoms, columns=['hydro_id', 'geom'], crs=crs, geometry="geom")
     df_final = df_final.dissolve(by="hydro_id")
@@ -328,10 +323,10 @@ def process(window):
     df_final = df_final.set_crs('epsg:3857')
     
     if df_final.index.has_duplicates:
-        print("dropping duplicates")
+        # print("dropping duplicates")
         df_final = df_final.drop_duplicates()
     
-    print("Adding additional metadata columns")
+    # print("Adding additional metadata columns")
     df_final = df_final.reset_index()
     df_final = df_final.rename(columns={"index": "hydro_id"})
     df_final['fim_version'] = FIM_VERSION
@@ -357,7 +352,7 @@ def create_inundation_output(huc8, branch, stage_lookup, reference_time, input_v
         if not os.path.exists('/tmp/raw_rasters/'):
             os.mkdir('/tmp/raw_rasters/')
         
-        print("--> Connecting to S3 datasets")
+        # print("--> Connecting to S3 datasets")
         tries = 0
         raster_open_success = False
         while tries < 3:
@@ -374,7 +369,7 @@ def create_inundation_output(huc8, branch, stage_lookup, reference_time, input_v
         if not raster_open_success:
             raise HANDDatasetReadError("Failed to open HAND and Catchment datasets")
             
-        print("--> Setting up mapping array")
+        # print("--> Setting up mapping array")
         catchment_nodata = int(catchment_dataset.nodata)  # get no_data value for catchment raster
         valid_catchments = stage_lookup.index.tolist() # parse lookup to get features with >0 stages  # noqa
         hydroids = stage_lookup.index.tolist()  # parse lookup to get all features
@@ -399,7 +394,7 @@ def create_inundation_output(huc8, branch, stage_lookup, reference_time, input_v
         profile['dtype'] = "int32"
 
         # Open the output raster using rasterio. This will allow the inner function to be parallel and write to it
-        print("--> Setting up windows")
+        # print("--> Setting up windows")
 
         # Get the list of windows according to the raster metadata so they can be looped through
         windows = subdivide(riowindows.Window(0, 0, width=hand_dataset.width, height=hand_dataset.height), 1024, 1024)
@@ -510,7 +505,7 @@ def process(window):
         if catchment_dataset is not None:
             catchment_dataset.close()
 
-    print("Generating polygons")
+    # print("Generating polygons")
     crs = 'EPSG:3338' if str(huc8).startswith('19') else 'EPSG:5070'
     df_final = gpd.GeoDataFrame(geoms, columns=['hydro_id', 'geom'], crs=crs, geometry="geom")
     df_final = df_final.dissolve(by="hydro_id")
@@ -521,17 +516,17 @@ def process(window):
     df_final = df_final.join(stage_lookup).dropna()
     
     if df_final.index.has_duplicates:
-        print("dropping duplicates")
+        # print("dropping duplicates")
         df_final = df_final.drop_duplicates()
     
-    print("Converting m columns to ft")
+    # print("Converting m columns to ft")
     df_final['rc_stage_ft'] = (df_final['rc_stage_m'] * 3.28084).astype(int)
     df_final['rc_previous_stage_ft'] = round(df_final['rc_previous_stage_m'] * 3.28084, 2)
     df_final['rc_discharge_cfs'] = round(df_final['rc_discharge_cms'] * 35.315, 2)
     df_final['rc_previous_discharge_cfs'] = round(df_final['rc_previous_discharge_cms'] * 35.315, 2)
     df_final = df_final.drop(columns=["rc_stage_m", "rc_previous_stage_m", "rc_discharge_cms", "rc_previous_discharge_cms"])
     
-    print("Adding additional metadata columns")
+    # print("Adding additional metadata columns")
     df_final = df_final.reset_index()
     df_final = df_final.rename(columns={"index": "hydro_id"})
     df_final['fim_version'] = FIM_VERSION
@@ -562,9 +557,9 @@ def s3_csv_to_df(bucket, key, columns=None):
     for i in range(5):
         try:
             # Read S3 csv file into Pandas DataFrame
-            print(f"Reading {key} from {bucket} into DataFrame")
+            # print(f"Reading {key} from {bucket} into DataFrame")
             df = pd.read_csv(f"s3://{bucket}/{key}", **extra_pd_args)
-            print("DataFrame creation Successful")
+            # print("DataFrame creation Successful")
         except Exception as e:
             if i == 4: print(f"Failed to read from S3:\n{e}")
             continue
@@ -599,13 +594,13 @@ def calculate_stage_values(hydrotable_key, subsetted_streams_bucket, subsetted_s
     df_forecast = df_forecast.drop(columns=['huc8_branch', 'huc'])
     df_forecast = df_forecast.set_index('hydro_id')
     
-    print(f"Removing {len(df_forecast[df_forecast['stage_m'].isna()])} reaches with a NaN interpolated stage")
+    # print(f"Removing {len(df_forecast[df_forecast['stage_m'].isna()])} reaches with a NaN interpolated stage")
     df_zero_stage = df_forecast[df_forecast['stage_m'].isna()].copy()
     df_zero_stage['note'] = "NaN Stage After Hydrotable Lookup"
     df_forecast = df_forecast[~df_forecast['stage_m'].isna()]
 
     stage0 = df_forecast['stage_m'] == 0
-    print(f"Removing {len(df_forecast[stage0])} reaches with a 0 interpolated stage")
+    # print(f"Removing {len(df_forecast[stage0])} reaches with a 0 interpolated stage")
     df_zero_stage = pd.concat([df_zero_stage, df_forecast[stage0]], axis=0)
     df_zero_stage['note'] = np.where(df_zero_stage.note.isnull(), "0 Stage After Hydrotable Lookup", "NaN")
     df_forecast = df_forecast[~stage0]
@@ -613,7 +608,7 @@ def calculate_stage_values(hydrotable_key, subsetted_streams_bucket, subsetted_s
     df_zero_stage.drop(columns=['discharge_cms', 'stage_m', 'rc_stage_m', 'rc_previous_stage_m', 'rc_previous_discharge_cms'], inplace=True)
     
     df_forecast = df_forecast.join(df_hydro_max)
-    print(f"{len(df_forecast)} reaches will be processed")
+    # print(f"{len(df_forecast)} reaches will be processed")
      
     return df_forecast, df_zero_stage
 
@@ -663,14 +658,18 @@ def interpolate_stage(df_row, df_hydro):
     if hydrotable_index >= len(stages):
         exceeds_max = True
         hydrotable_index = hydrotable_index - 1
-        
+
     hydrotable_previous_index = hydrotable_index-1
     if CACHE_FIM_RESOLUTION_FT == 1 or exceeds_max:
+        # This is a simpler case because this is the resoluation at which the hydrotable is provided
         rounded_stage = stages[hydrotable_index]
+        rc_discharge = discharges[hydrotable_index]
+        rc_previous_stage = stages[hydrotable_previous_index]
+        rc_previous_discharge = discharges[hydrotable_previous_index]
     else:
         rounded_stage = round_m_to_nearest_ft_resolution(interpolated_stage, CACHE_FIM_RESOLUTION_FT, CACHE_FIM_RESOLUTION_ROUNDING)
-    rc_previous_stage = stages[hydrotable_previous_index]
-    rc_discharge = discharges[hydrotable_index]
-    rc_previous_discharge = discharges[hydrotable_previous_index]
-    
+        rc_discharge = round(np.interp(rounded_stage, stages, discharges), 2)
+        rc_previous_stage = max(rounded_stage - CACHE_FIM_RESOLUTION_FT, 0)
+        rc_previous_discharge = round(np.interp(rc_previous_stage, stages, discharges), 2)
+
     return interpolated_stage, rounded_stage, rc_previous_stage, rc_discharge, rc_previous_discharge
\ No newline at end of file
diff --git a/Core/LAMBDA/viz_functions/viz_db_postprocess_sql/fim_caching_templates/0_create_or_truncate_tables.sql b/Core/LAMBDA/viz_functions/viz_db_postprocess_sql/fim_caching_templates/0_create_or_truncate_tables.sql
index b4104d5f..897bd15a 100644
--- a/Core/LAMBDA/viz_functions/viz_db_postprocess_sql/fim_caching_templates/0_create_or_truncate_tables.sql
+++ b/Core/LAMBDA/viz_functions/viz_db_postprocess_sql/fim_caching_templates/0_create_or_truncate_tables.sql
@@ -23,7 +23,7 @@ CREATE TABLE {db_fim_table}
 	forecast_stage_ft double precision,
     rc_discharge_cfs double precision,
     rc_previous_discharge_cfs double precision,
-    rc_stage_ft integer,
+    rc_stage_ft double precision,
     rc_previous_stage_ft integer,
     max_rc_stage_ft double precision,
     max_rc_discharge_cfs double precision,
@@ -37,7 +37,7 @@ DROP TABLE IF EXISTS {db_fim_table}_geo;
 
 CREATE TABLE {db_fim_table}_geo (
     hand_id integer,
-    rc_stage_ft integer,
+    rc_stage_ft double precision,
     geom geometry(geometry, 3857)
 );