diff --git a/autotest/pst_from_tests.py b/autotest/pst_from_tests.py
index 0043456cb..d2d09bfa8 100644
--- a/autotest/pst_from_tests.py
+++ b/autotest/pst_from_tests.py
@@ -554,6 +554,20 @@ def mf6_freyberg_test():
         for line in lines:
             fw.write(line)
 
+    # generate a test with headers and non spatial idex
+    sfr_pkgdf = pd.DataFrame.from_records(m.sfr.packagedata.array)
+    l = sfr_pkgdf.columns.to_list()
+    l = ['#rno', 'k', 'i', 'j'] + l[2:]
+    with open(
+            os.path.join('temp_pst_from',
+                         "freyberg6.sfr_packagedata.txt"), 'r') as fr:
+        lines = [line for line in fr]
+    with open(os.path.join('temp_pst_from',
+                           "freyberg6.sfr_packagedata_test.txt"), 'w') as fw:
+        fw.write(' '.join(l))
+        fw.write('\n')
+        for line in lines:
+            fw.write(line)
 
     template_ws = "new_temp"
     # sr0 = m.sr
@@ -673,7 +687,11 @@ def mf6_freyberg_test():
                           pargp="wel_{0}".format(kper), index_cols=[0, 1, 2], use_cols=[3],
                           upper_bound=1.5, lower_bound=0.5, geostruct=gr_gs)
 
-
+    # test non spatial idx in list like
+    pf.add_parameters(filenames="freyberg6.sfr_packagedata_test.txt", par_name_base="sfr_rhk",
+                      pargp="sfr_rhk", index_cols=['#rno'], use_cols=['rhk'], upper_bound=10.,
+                      lower_bound=0.1,
+                      par_type="grid")
 
     # add model run command
     pf.mod_sys_cmds.append("mf6")
@@ -683,6 +701,35 @@ def mf6_freyberg_test():
     # build pest
     pst = pf.build_pst('freyberg.pst')
 
+    # quick check of write and apply method
+    pars = pst.parameter_data
+    # set reach 1 hk to 100
+    sfr_pars = pars.loc[pars.parnme.str.startswith('sfr')].index
+    pars.loc[sfr_pars, 'parval1'] = np.random.random(len(sfr_pars)) * 10
+
+    sfr_pars = pars.loc[sfr_pars].copy()
+    sfr_pars[['inst', 'col', '#rno']] = sfr_pars.parnme.apply(
+        lambda x: pd.DataFrame([s.split(':') for s in x.split('_')
+                                if ':' in s]).set_index(0)[1])
+    sfr_pars['#rno'] = sfr_pars['#rno'] .astype(int)
+    os.chdir(pf.new_d)
+    pst.write_input_files()
+    try:
+        pyemu.helpers.apply_list_and_array_pars()
+    except Exception as e:
+        os.chdir('..')
+        raise e
+    os.chdir('..')
+    # verify apply
+    df = pd.read_csv(os.path.join(
+        pf.new_d, "freyberg6.sfr_packagedata_test.txt"),
+        delim_whitespace=True, index_col=0)
+    df.index = df.index - 1
+    assert np.isclose(
+        df.rhk, (sfr_pkgdf.set_index('rno').loc[df.index, 'rhk'] *
+                 sfr_pars.set_index('#rno').loc[df.index, 'parval1'])).all()
+    pars.loc[sfr_pars.index, 'parval1'] = 1.0
+
     # add more:
     pf.add_parameters(filenames="freyberg6.sfr_packagedata.txt", par_name_base="sfr_rhk",
                       pargp="sfr_rhk", index_cols={'k': 1, 'i': 2, 'j': 3}, use_cols=[9], upper_bound=10.,
diff --git a/pyemu/prototypes/pst_from.py b/pyemu/prototypes/pst_from.py
index 952b578c5..fcc1333a4 100644
--- a/pyemu/prototypes/pst_from.py
+++ b/pyemu/prototypes/pst_from.py
@@ -462,7 +462,7 @@ def build_pst(self, filename=None, update=False):
                                                       'mult2model_info.csv'))
                 if not any(["apply_list_and_array_pars" in s
                             for s in self.pre_py_cmds]):
-                    self.pre_py_cmds.append(
+                    self.pre_py_cmds.insert(0,
                         "pyemu.helpers.apply_list_and_array_pars("
                         "arr_par_file='mult2model_info.csv')")
             else:
diff --git a/pyemu/utils/helpers.py b/pyemu/utils/helpers.py
index de83532a2..09f9c8165 100644
--- a/pyemu/utils/helpers.py
+++ b/pyemu/utils/helpers.py
@@ -3329,6 +3329,8 @@ def apply_genericlist_pars(df):
             mlts.index = pd.MultiIndex.from_tuples(mlts.sidx.apply(
                 lambda x: tuple(add1+np.array(literal_eval(x)))),
                 names=mlt.index_cols)
+            if mlts.index.nlevels < 2:  # just in case only one index col is used
+                mlts.index = mlts.index.get_level_values(0)
             common_idx = new_df.index.intersection(mlts.index).sort_values()
             mlt_cols = [str(col) for col in mlt.use_cols]
             new_df.loc[common_idx, mlt_cols] = (new_df.loc[common_idx, mlt_cols]