diff --git a/src/analysis/observed_storm_impacts.py b/src/analysis/observed_storm_impacts.py
index 29a5dde..e8537a2 100644
--- a/src/analysis/observed_storm_impacts.py
+++ b/src/analysis/observed_storm_impacts.py
@@ -36,6 +36,8 @@ def volume_change(df_profiles, df_profile_features, zone):
 
     for site_id, df_site in sites:
         logger.debug("Calculating change in beach volume at {} in {} zone".format(site_id, zone))
+
+        # TODO Change this query to an index
         query = "site_id=='{}'&profile_type=='prestorm'".format(site_id)
         prestorm_dune_toe_x = df_profile_features.query(query).dune_toe_x.tolist()
         prestorm_dune_crest_x = df_profile_features.query(query).dune_crest_x.tolist()
@@ -44,7 +46,7 @@ def volume_change(df_profiles, df_profile_features, zone):
         prestorm_dune_crest_x = return_first_or_nan(prestorm_dune_crest_x)
         prestorm_dune_toe_x = return_first_or_nan(prestorm_dune_toe_x)
 
-        # If no dune to has been defined, Dlow = Dhigh. Refer to Sallenger (2000).
+        # If no dune toe has been defined, Dlow = Dhigh. Refer to Sallenger (2000).
         if np.isnan(prestorm_dune_toe_x):
             prestorm_dune_toe_x = prestorm_dune_crest_x
 
@@ -145,6 +147,10 @@ def storm_regime(df_observed_impacts):
 
     df_observed_impacts.loc[swash, "storm_regime"] = "swash"
     df_observed_impacts.loc[collision, "storm_regime"] = "collision"
+
+    # TODO We may be able to identify observed regimes by looking at the change in crest and toe elevation. This would be useful for 
+    # locations where we have overwash and cannot calculate the change in volume correctly. Otherwise, maybe it's better to put it in manually.
+    
     return df_observed_impacts