diff --git a/python/ngen_cal/src/ngen/cal/ngen.py b/python/ngen_cal/src/ngen/cal/ngen.py
index 9d2cd498..ebbe25e9 100644
--- a/python/ngen_cal/src/ngen/cal/ngen.py
+++ b/python/ngen_cal/src/ngen/cal/ngen.py
@@ -46,13 +46,13 @@ def _params_as_df(params: Mapping[str, Parameters], name: str = None):
             df['model'] = k
             df.rename(columns={'name':'param'}, inplace=True)
             dfs.append(df)
-        return pd.concat(dfs)
+        return pd.concat(dfs).set_index('param')
     else:
         p = params.get(name, [])
         df = pd.DataFrame([s.__dict__ for s in p])
         df['model'] = name
         df.rename(columns={'name':'param'}, inplace=True)
-        return df
+        return df.set_index('param')
 
 def _map_params_to_realization(params: Mapping[str, Parameters], realization: Realization):
     # don't even think about calibration multiple formulations at once just yet..
diff --git a/python/ngen_cal/tests/conftest.py b/python/ngen_cal/tests/conftest.py
index 32c06a48..e3af5da5 100644
--- a/python/ngen_cal/tests/conftest.py
+++ b/python/ngen_cal/tests/conftest.py
@@ -1,5 +1,7 @@
+from __future__ import annotations
+
 import pytest
-from typing import Generator, List
+from typing import Generator, List, Mapping
 from pathlib import Path
 from copy import deepcopy
 import json
@@ -11,6 +13,7 @@
 from ngen.cal.calibration_cathment import CalibrationCatchment
 from ngen.cal.model import EvaluationOptions
 from ngen.cal.agent import Agent
+from ngen.cal.parameter import Parameter
 from hypy import Nexus
 
 from .utils import *
@@ -219,3 +222,22 @@ def explicit_catchments(nexus, fabric, workdir) -> Generator[ List[ CalibrationC
         cat = CalibrationCatchment(workdir, id, nexus, start, end, fabric, 'Q_Out', eval_options, data)
         catchments.append(cat)
     yield catchments
+
+@pytest.fixture
+def multi_model_shared_params() -> Mapping[str, list[Parameter]]:
+    p1 = Parameter(name='a', min=0, max=1, init=0)
+    p2 = Parameter(name='d', min=2, max=3, init=0)
+    p3 = Parameter(name='c', min=0, max=1, init=0)
+    p4 = Parameter(name='a', min=0, max=1, init=0)
+    params = {'A':[p1], 'B':[p2, p4], 'C':[p3, p4]}
+
+    return params
+
+@pytest.fixture
+def multi_model_shared_params2() -> Mapping[str, list[Parameter]]:
+    p1 = Parameter(name='a', min=0, max=1, init=0)
+    p2 = Parameter(name='a', min=0, max=1, init=0)
+    p3 = Parameter(name='c', min=0, max=1, init=0)
+    params = {'A':[p1, p3], 'B':[p2]}
+
+    return params
diff --git a/python/ngen_cal/tests/test_params.py b/python/ngen_cal/tests/test_params.py
new file mode 100644
index 00000000..bb483c9d
--- /dev/null
+++ b/python/ngen_cal/tests/test_params.py
@@ -0,0 +1,42 @@
+from __future__ import annotations
+
+from ngen.cal.ngen import _params_as_df
+import pandas as pd
+
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from typing import Mapping
+    from ngen.cal.parameter import Parameter
+
+def test_multi_params(multi_model_shared_params: Mapping[str, list[Parameter]]):
+    # This is essentially the path the params go through from
+    # creation in model.py to update in search.py
+    params = _params_as_df(multi_model_shared_params)
+    params = pd.DataFrame(params).rename(columns={'init':'0'})
+    # create new iteration from old
+    params['1'] = params['0']
+    #update the parameters by index
+    idx1 = 'a'
+    idx2 = 'c'
+    params.loc[idx1, '1'] = 0.5
+    pa = params[ params['model'] == 'A' ].loc[idx1]
+    pb = params[ params['model'] == 'B' ].loc[idx1]
+    pc = params[ params['model'] == 'C' ].loc[idx2]
+
+    assert pa.drop('model').equals( pb.drop('model') )
+    # ensure unique params/alias are not modifed by selection
+    assert pa.loc['1'] != pc.loc['1']
+
+def test_multi_params2(multi_model_shared_params2: Mapping[str, list[Parameter]]):
+    # This is essentially the path the params go through from
+    # creation in model.py to update in search.py
+    params = _params_as_df(multi_model_shared_params2)
+    params = pd.DataFrame(params).rename(columns={'init':'0'})
+    # create new iteration from old
+    params['1'] = params['0']
+    #update the parameters by index
+    params.loc['a', '1'] = 0.5
+    pa = params[ params['model'] == 'A' ].drop('model', axis=1).loc['a']
+    pb = params[ params['model'] == 'B' ].drop('model', axis=1).loc['a']
+    assert pa.equals( pb )