diff --git a/src/analysis/forecast_twl.py b/src/analysis/forecast_twl.py
index 70edcab..5298c9c 100644
--- a/src/analysis/forecast_twl.py
+++ b/src/analysis/forecast_twl.py
@@ -316,8 +316,15 @@ def slope_from_profile(
     """
 
     # Need all data to get the slope
-    if any([x is None for x in [profile_x, profile_z, top_elevation, btm_elevation]]):
-        return None
+    # Check validity of profile arrays and return None if data is not good
+    for profile in [profile_x, profile_z]:
+        if all(np.isnan(profile)) or all(x is None for x in profile):
+            return None
+
+    # Check validity of elevation values
+    for ele in [top_elevation, btm_elevation]:
+        if np.isnan(ele) or ele is None:
+            return None
 
     end_points = {"top": {"z": top_elevation}, "btm": {"z": btm_elevation}}
 
@@ -377,6 +384,11 @@ def slope_from_profile(
             True if end_points["top"]["x"] < pts < end_points["btm"]["x"] else False
             for pts in profile_x
         ]
+
+        # Need at least two points to do linear regression
+        if sum(profile_mask) < 2:
+            return None
+
         slope_x = np.array(profile_x)[profile_mask].tolist()
         slope_z = np.array(profile_z)[profile_mask].tolist()
         slope, _, _, _, _ = stats.linregress(slope_x, slope_z)