diff --git a/src/analysis/forecasted_storm_impacts.py b/src/analysis/forecasted_storm_impacts.py
index 6ce742f..ca7b857 100644
--- a/src/analysis/forecasted_storm_impacts.py
+++ b/src/analysis/forecasted_storm_impacts.py
@@ -87,7 +87,6 @@ def twl_exceedence_time(
     df_profile_features,
     df_forecasted_twl,
     z_twl_col="R_high",
-    z_exceedence_col="dune_toe_z",
 ):
     """
     Returns a dataframe of number of hours the twl exceeded a certain z elevation.
@@ -100,12 +99,13 @@ def twl_exceedence_time(
     """
     logger.info("Getting twl exceedence time")
 
-    # Get a dataframe of prestorm dune toes organised by site_id
-    df_dune_toes = (
-        df_profile_features.query('profile_type=="prestorm"')
-        .reset_index("profile_type")[z_exceedence_col]
-        .to_frame()
-    )
+    # Get the elevation we want to calculate the time TWL exceedes this level.
+    # Note it's usually dune toe, but some profiles don't have a dune toe. In these cases, use dune crest value
+    df_temp = df_profile_features.xs("prestorm", level="profile_type").copy()
+    df_temp.loc[df_temp.dune_toe_z.isnull(), "dune_toe_z"] = df_temp[
+        df_temp.dune_toe_z.isnull()
+    ].dune_crest_z
+    df_dune_toes = df_temp.dune_toe_z.to_frame()
 
     # Merge dune toes into site_id
     df_merged = df_forecasted_twl.merge(
@@ -114,10 +114,10 @@ def twl_exceedence_time(
 
     # Return the sum of hours that twl exceeded the level
     return (
-        (df_merged[z_twl_col] >= df_merged[z_exceedence_col])
+        (df_merged[z_twl_col] >= df_merged["dune_toe_z"])
         .groupby("site_id")
         .sum()
-        .rename("twl_{}_exceedance_hrs".format(z_exceedence_col))
+        .rename("twl_{}_exceedance_hrs".format("dune_toe_z"))
         .to_frame()
     )