diff --git a/modelskill/matching.py b/modelskill/matching.py
index 5d3a2c000..821c1c628 100644
--- a/modelskill/matching.py
+++ b/modelskill/matching.py
@@ -405,6 +405,14 @@ def match_space_time(
                 observation=observation, mri=mri, spatial_tolerance=spatial_tolerance
             )
 
+        # check that model and observation have non-overlapping variables
+        if overlapping_names := set(mri.data.data_vars).intersection(
+            set(data.data_vars)
+        ):
+            raise ValueError(
+                f"Model: '{mr.name}' and observation have overlapping variables: {overlapping_names}"
+            )
+
         # TODO: is name needed?
         for v in list(mri.data.data_vars):
             data[v] = mri.data[v]
diff --git a/tests/test_match.py b/tests/test_match.py
index 609d9c828..250b564c8 100644
--- a/tests/test_match.py
+++ b/tests/test_match.py
@@ -389,3 +389,52 @@ def test_specifying_mod_item_not_allowed_twice(o1, mr1):
 def test_bad_model_input(o1):
     with pytest.raises(ValueError, match="mod type"):
         ms.match(obs=o1, mod=None)
+
+
+def test_obs_and_mod_can_not_have_same_aux_item_names():
+    obs_df = pd.DataFrame(
+        {"wl": [1.0, 2.0, 3.0], "wind_speed": [1.0, 2.0, 3.0]},
+        index=pd.date_range("2017-01-01", periods=3),
+    )
+
+    mod_df = pd.DataFrame(
+        {"wl": [1.1, 2.0, 3.0], "wind_speed": [0.0, 0.0, 0.0]},
+        index=pd.date_range("2017-01-01", periods=3),
+    )
+
+    obs = ms.PointObservation(obs_df, item="wl", aux_items=["wind_speed"])
+    mod = ms.PointModelResult(mod_df, item="wl", aux_items=["wind_speed"])
+
+    with pytest.raises(ValueError, match="wind_speed"):
+        ms.match(obs=obs, mod=mod)
+
+
+def test_mod_aux_items_must_be_unique():
+    obs_df = pd.DataFrame(
+        {"wl": [1.0, 2.0, 3.0], "wind_speed": [1.0, 2.0, 3.0]},
+        index=pd.date_range("2017-01-01", periods=3),
+    )
+
+    mod_df = pd.DataFrame(
+        {"wl": [1.1, 2.0, 3.0], "wind_speed": [0.0, 0.0, 0.0]},
+        index=pd.date_range("2017-01-01", periods=3),
+    )
+
+    mod2_df = pd.DataFrame(
+        {"wl": [1.2, 2.1, 3.1], "wind_speed": [0.0, 0.0, 0.0]},
+        index=pd.date_range("2017-01-01", periods=3),
+    )
+
+    obs = ms.PointObservation(obs_df, item="wl")
+    mod = ms.PointModelResult(mod_df, item="wl", aux_items=["wind_speed"], name="local")
+
+    # this is ok
+    mod2 = ms.PointModelResult(
+        mod2_df, item="wl", aux_items=["wind_speed"], name="remote"
+    )
+
+    with pytest.raises(ValueError) as e:
+        ms.match(obs=obs, mod=[mod, mod2])
+
+    assert "wind_speed" in str(e.value)
+    assert "remote" in str(e.value)