diff --git a/docs/api/changelog.rst b/docs/api/changelog.rst
index 5a46fabc6..2fc2228bf 100644
--- a/docs/api/changelog.rst
+++ b/docs/api/changelog.rst
@@ -44,6 +44,8 @@ Fixed
 - Fixed bug where :func:`imod.evaluate.convert_pointwaterhead_freshwaterhead`
   produced incorrect results when point water heads were below elevation levels
   for unstructured grids.
+- Support pandas 3.0.
+
 
 Changed
 ~~~~~~~
diff --git a/examples/imod-wq/Henry-wq.py b/examples/imod-wq/Henry-wq.py
index f3751e129..38b5b0b9b 100644
--- a/examples/imod-wq/Henry-wq.py
+++ b/examples/imod-wq/Henry-wq.py
@@ -102,7 +102,7 @@
 )
 m["oc"] = imod.wq.OutputControl(save_head_idf=True, save_concentration_idf=True)
 m.create_time_discretization(
-    additional_times=pd.date_range("2000-01-01", "2001-01-01", freq="M")
+    additional_times=pd.date_range("2000-01-01", "2001-01-01", freq="ME")
 )
 
 # %%
diff --git a/examples/mf6/circle_transport.py b/examples/mf6/circle_transport.py
index b802e939e..7c0f8aeda 100644
--- a/examples/mf6/circle_transport.py
+++ b/examples/mf6/circle_transport.py
@@ -194,7 +194,7 @@
 # stress period is a year long. We can then use the "last" keyword in the output
 # control to save the output.
 
-simtimes = pd.date_range(start="2000-01-01", end="2030-01-01", freq="As")
+simtimes = pd.date_range(start="2000-01-01", end="2030-01-01", freq="YS")
 simulation.create_time_discretization(additional_times=simtimes)
 
 # %%
diff --git a/examples/mf6/hondsrug.py b/examples/mf6/hondsrug.py
index b855c4e04..806e3fcda 100644
--- a/examples/mf6/hondsrug.py
+++ b/examples/mf6/hondsrug.py
@@ -336,7 +336,7 @@ def outer_edge(da):
 # resampled to a yearly step by using the xarray function
 # `Dataset.resample <http://xarray.pydata.org/en/stable/generated/xarray.Dataset.resample.html#xarray.Dataset.resample>`_.
 
-rch_trans_yr = rch_trans.resample(time="A", label="left").mean()
+rch_trans_yr = rch_trans.resample(time="YS", label="left").mean()
 rch_trans_yr
 
 # %%
diff --git a/imod/evaluate/constraints.py b/imod/evaluate/constraints.py
index ad13c4367..2b9573370 100644
--- a/imod/evaluate/constraints.py
+++ b/imod/evaluate/constraints.py
@@ -126,7 +126,8 @@ def stability_constraint_advection(front, lower, right, top_bot, porosity=0.3, R
     dt = 1.0 / (1.0 / dt_x + 1.0 / dt_y + 1.0 / dt_z)
 
     dt_xyz = xr.concat(
-        (dt_x, dt_y, dt_z), dim=pd.Index(["x", "y", "z"], name="direction")
+        (dt_x, dt_y, dt_z),
+        dim=pd.Index(["x", "y", "z"], name="direction", dtype="object"),
     )
     return dt, dt_xyz
 
@@ -254,9 +255,11 @@ def _get_stage_name(sid):
                 if not drop_allnan or not dt.isnull().all():
                     results.append(dt)
                     resultids.append(comb)
-    dt_all = xr.concat(
-        results, pd.Index(resultids, name="combination"), coords="minimal"
-    )
+    # Set index to object dtype to work around xarray concat issue where
+    # StringDtype could not be interpreted as a data type with pandas 3.0 (as
+    # np.dtype is called.)
+    id_index = pd.Index(resultids, name="combination", dtype="object")
+    dt_all = xr.concat(results, id_index, coords="minimal")
 
     # overall dt
     dt_min = dt_all.min(dim="combination")
diff --git a/imod/formats/gen/gen.py b/imod/formats/gen/gen.py
index d1006cf34..ce2ffde30 100644
--- a/imod/formats/gen/gen.py
+++ b/imod/formats/gen/gen.py
@@ -267,7 +267,7 @@ def read_binary(path: Union[str, Path]) -> "geopandas.GeoDataFrame":  # type: ig
     else:
         df = pd.DataFrame()
     df["feature_type"] = feature_type
-    df["feature_type"] = df["feature_type"].replace(GENTYPE_TO_NAME)
+    df["feature_type"] = df["feature_type"].replace(GENTYPE_TO_NAME).astype(str)
 
     geometry = []
     for ftype, geom in zip(feature_type, xy):
diff --git a/imod/formats/ipf.py b/imod/formats/ipf.py
index 0d6ff861e..e5c8d7cb9 100644
--- a/imod/formats/ipf.py
+++ b/imod/formats/ipf.py
@@ -458,7 +458,8 @@ def write_assoc(path, df, itype=1, nodata=1.0e20, assoc_columns=None):
     # The reason is that datetime columns are converted to string as well
     # and then quoted. This causes trouble with some iMOD(batch) functions.
     for column in df.columns:
-        if df.loc[:, column].dtype == np.dtype("O"):
+        # Test for strings compatible with pandas 2 and 3
+        if pd.api.types.is_string_dtype(df[column].dtype):
             df.loc[:, column] = df.loc[:, column].astype(str)
             df.loc[:, column] = '"' + df.loc[:, column] + '"'
 
@@ -509,7 +510,8 @@ def write(path, df, indexcolumn=0, assoc_ext="txt", nodata=1.0e20):
     # The reason is that datetime columns are converted to string as well
     # and then quoted. This causes trouble with some iMOD(batch) functions.
     for column in df.columns:
-        if df.loc[:, column].dtype == np.dtype("O"):
+        # Test for strings compatible with pandas 2 and 3
+        if pd.api.types.is_string_dtype(df[column].dtype):
             df.loc[:, column] = df.loc[:, column].astype(str)
             df.loc[:, column] = '"' + df.loc[:, column] + '"'
 
diff --git a/imod/mf6/multimodel/exchange_creator.py b/imod/mf6/multimodel/exchange_creator.py
index 31a55e6a8..f10548f5b 100644
--- a/imod/mf6/multimodel/exchange_creator.py
+++ b/imod/mf6/multimodel/exchange_creator.py
@@ -290,10 +290,12 @@ def rearrange_connected_cells(self):
 
         label_decreasing = df["cell_label1"] > df["cell_label2"]
 
-        colnames = ["cell_idx1", "cell_idx2", "cell_label1", "cell_label2"]
-        colnames_reversed = ["cell_idx2", "cell_idx1", "cell_label2", "cell_label1"]
+        if label_decreasing.any():
+            colnames = ["cell_idx1", "cell_idx2", "cell_label1", "cell_label2"]
+            colnames_reversed = ["cell_idx2", "cell_idx1", "cell_label2", "cell_label1"]
 
-        decreasing_connections = df.loc[label_decreasing, colnames].values
-        df.loc[label_decreasing, colnames_reversed] = decreasing_connections
+            df_decreasing = df.loc[label_decreasing, colnames]
+            df_decreasing.columns = colnames_reversed
+            df.loc[label_decreasing, colnames_reversed] = df_decreasing
 
         self._connected_cells = df
diff --git a/imod/testing.py b/imod/testing.py
index 890468b9c..970603e61 100644
--- a/imod/testing.py
+++ b/imod/testing.py
@@ -16,7 +16,7 @@ def assert_frame_equal(left: pd.DataFrame, right: pd.DataFrame, **kwargs):
     def always_int64(df):
         df = df.copy()
         for column, dtype in df.dtypes.items():
-            if np.issubdtype(dtype, np.integer):
+            if pd.api.types.is_integer_dtype(dtype):
                 df[column] = df[column].astype(np.int64)
         return df
 
diff --git a/imod/tests/test_evaluate/test_constraints.py b/imod/tests/test_evaluate/test_constraints.py
index 2948d56d8..d28909296 100644
--- a/imod/tests/test_evaluate/test_constraints.py
+++ b/imod/tests/test_evaluate/test_constraints.py
@@ -94,13 +94,13 @@ def test_intra_cell_boundary_conditions(test_da1):
     riv1drn = test_da1 * (0.3 * 1.0) / min(100.0, 150) * (1.0 - 0.0)
     dt_min_ref = np.minimum(ghbdrn, riv1drn)
 
-    assert dt_min_ref.equals(dt_min)
-    assert dt_all.equals(
-        xr.concat(
-            (ghbdrn, riv1drn), pd.Index(["ghb-drn", "riv_0-drn"], name="combination")
-        )
+    expected_index = pd.Index(
+        ["ghb-drn", "riv_0-drn"], name="combination", dtype="object"
     )
 
+    assert dt_min_ref.equals(dt_min)
+    assert dt_all.equals(xr.concat((ghbdrn, riv1drn), expected_index))
+
 
 def test_intra_cell_boundary_conditions_thickness_zero(test_da1):
     top_bot = xr.Dataset({"top": test_da1 * -1.0, "bot": test_da1 * -1.0})
diff --git a/imod/tests/test_formats/test_gen.py b/imod/tests/test_formats/test_gen.py
index 566cd1acc..7b4483266 100644
--- a/imod/tests/test_formats/test_gen.py
+++ b/imod/tests/test_formats/test_gen.py
@@ -160,16 +160,17 @@ def test_gen_single_feature(tmp_path, ftype):
     imod.gen.write(path, gdf, feature_type="feature_type")
     back = imod.gen.read(path)
     assert (back["feature_type"] == ftype).all()
+    geom_actual = back["geometry"]
+    geom_expected = gdf["geometry"]
+    expected = gdf.drop(columns="geometry").sort_index(axis=1)
+    actual = back.drop(columns="geometry").sort_index(axis=1)
+    # TODO: account for the fact that geopandas string type is ArrowStringArray, whereas iMOD GEN reader returns object dtype.
+    assert expected.equals(actual)
     if ftype in ("circle", "rectangle"):
         # Gotta do a different check, geometries won't be exactly the same
-        geom_actual = back["geometry"].iloc[0]
-        geom_expected = gdf["geometry"].iloc[0]
-        expected = gdf.drop(columns="geometry").sort_index(axis=1)
-        actual = back.drop(columns="geometry").sort_index(axis=1)
-        assert expected.equals(actual)
-        assert approximately_equal(geom_actual, geom_expected)
+        assert approximately_equal(geom_actual.iloc[0], geom_expected.iloc[0])
     else:
-        assert gdf.sort_index(axis=1).equals(back.sort_index(axis=1))
+        assert geom_actual.geom_equals(geom_expected).all()
 
 
 def test_gen_multi_feature(tmp_path):
diff --git a/imod/tests/test_formats/test_prj_wel.py b/imod/tests/test_formats/test_prj_wel.py
index a071f3e78..e5e535743 100644
--- a/imod/tests/test_formats/test_prj_wel.py
+++ b/imod/tests/test_formats/test_prj_wel.py
@@ -798,8 +798,8 @@ def test_open_projectfile_data_out_of_bounds_wells(
             assert actual[field] == wel_expected[field]
         if actual["has_associated"]:
             timeseries = data["wel-associated"]["dataframe"][0]["time"]
-            # Test if last element NaT
-            assert timeseries.iloc[-1] is pd.NaT
+            # Test if last element not NaT (since pandas 3, before it was NaT)
+            assert timeseries.iloc[-1] == pd.Timestamp("2999-11-12 00:00:00")
 
 
 @pytest.mark.unittest_jit
diff --git a/imod/tests/test_mf6/test_ex01_twri.py b/imod/tests/test_mf6/test_ex01_twri.py
index 17a6d38da..5709b8df5 100644
--- a/imod/tests/test_mf6/test_ex01_twri.py
+++ b/imod/tests/test_mf6/test_ex01_twri.py
@@ -432,7 +432,7 @@ def test_simulation_write_and_run(twri_model, tmp_path):
     assert head.shape == (1, 3, 15, 15)
     assert np.all(
         head["time"].values
-        == np.array("1999-01-02T00:00:00.000000000", dtype="datetime64[ns]")
+        == np.array("1999-01-02T00:00:00.000000", dtype="datetime64[ns]")
     )
     meanhead_layer = head.groupby("layer").mean(dim=xr.ALL_DIMS)
     mean_answer = np.array([59.79181509, 30.44132373, 24.88576811])
diff --git a/imod/tests/test_mf6/test_mf6_drn.py b/imod/tests/test_mf6/test_mf6_drn.py
index a2bba1158..62d2138aa 100644
--- a/imod/tests/test_mf6/test_mf6_drn.py
+++ b/imod/tests/test_mf6/test_mf6_drn.py
@@ -418,10 +418,10 @@ def test_clip_box_transient(transient_drainage):
     selection = drn.clip_box(time_min="2001-01-01", time_max="2004-01-01")
     expected = np.array(
         [
-            "2001-01-01T00:00:00.000000000",
-            "2002-01-01T00:00:00.000000000",
-            "2003-01-01T00:00:00.000000000",
-            "2004-01-01T00:00:00.000000000",
+            "2001-01-01T00:00:00.000000",
+            "2002-01-01T00:00:00.000000",
+            "2003-01-01T00:00:00.000000",
+            "2004-01-01T00:00:00.000000",
         ],
         dtype="datetime64[ns]",
     )
@@ -434,9 +434,9 @@ def test_clip_box_transient(transient_drainage):
     selection = drn.clip_box(time_min="2000-06-01", time_max="2002-06-01")
     expected = np.array(
         [
-            "2000-06-01T00:00:00.000000000",
-            "2001-01-01T00:00:00.000000000",
-            "2002-01-01T00:00:00.000000000",
+            "2000-06-01T00:00:00.000000",
+            "2001-01-01T00:00:00.000000",
+            "2002-01-01T00:00:00.000000",
         ],
         dtype="datetime64[ns]",
     )
@@ -447,10 +447,10 @@ def test_clip_box_transient(transient_drainage):
     selection = drn.clip_box(time_min="1990-06-01", time_max="2002-06-01")
     expected = np.array(
         [
-            "1990-06-01T00:00:00.000000000",
-            "2000-01-01T00:00:00.000000000",
-            "2001-01-01T00:00:00.000000000",
-            "2002-01-01T00:00:00.000000000",
+            "1990-06-01T00:00:00.000000",
+            "2000-01-01T00:00:00.000000",
+            "2001-01-01T00:00:00.000000",
+            "2002-01-01T00:00:00.000000",
         ],
         dtype="datetime64[ns]",
     )
diff --git a/imod/tests/test_mf6/test_mf6_npf.py b/imod/tests/test_mf6/test_mf6_npf.py
index 75f094743..c97c4188a 100644
--- a/imod/tests/test_mf6/test_mf6_npf.py
+++ b/imod/tests/test_mf6/test_mf6_npf.py
@@ -303,10 +303,8 @@ def test_npf_from_imod5_settings(imod5_dataset, tmp_path):
     # move the coordinates a bit so that it doesn't match the grid of k (and the regridding settings will matter)
     target_grid = data["khv"]["kh"]
     x = target_grid["x"].values
-    x += 50
     y = target_grid["y"].values
-    y += 50
-    target_grid = target_grid.assign_coords({"x": x, "y": y})
+    target_grid = target_grid.assign_coords({"x": x + 50, "y": y + 50})
 
     settings = imod.mf6.NodePropertyFlow.get_regrid_methods()
     settings_1 = deepcopy(settings)
diff --git a/imod/tests/test_mf6/test_mf6_out.py b/imod/tests/test_mf6/test_mf6_out.py
index a0867985d..e3b412b10 100644
--- a/imod/tests/test_mf6/test_mf6_out.py
+++ b/imod/tests/test_mf6/test_mf6_out.py
@@ -434,7 +434,7 @@ def test_open_cbc__dis_datetime(transient_twri_result):
         )
 
     for array in cbc.values():
-        assert array.coords["time"].dtype == np.dtype("datetime64[ns]")
+        assert array.coords["time"].dtype == np.dtype("datetime64[us]")
 
 
 def test_open_cbc__dis_transient_unconfined(transient_unconfined_twri_result):
@@ -535,7 +535,7 @@ def test_open_cbc__disv_datetime(circle_result):
         )
 
     for array in cbc.values():
-        assert array.coords["time"].dtype == np.dtype("datetime64[ns]")
+        assert array.coords["time"].dtype == np.dtype("datetime64[us]")
 
 
 def test_open_cbc__disv_sto(circle_result_sto):
diff --git a/imod/tests/test_mf6/test_mf6_rch.py b/imod/tests/test_mf6/test_mf6_rch.py
index ae8c8037f..16fef6bb9 100644
--- a/imod/tests/test_mf6/test_mf6_rch.py
+++ b/imod/tests/test_mf6/test_mf6_rch.py
@@ -409,7 +409,8 @@ def test_planar_rch_from_imod5_constant(imod5_dataset, tmp_path):
     target_discretization = StructuredDiscretization.from_imod5_data(data)
 
     # create a planar grid with time-independent recharge
-    data["rch"]["rate"]["layer"].values[0] = -1
+    data["rch"]["rate"] = data["rch"]["rate"].assign_coords(layer=[-1])
+
     assert not is_transient_data_grid(data["rch"]["rate"])
     assert is_planar_grid(data["rch"]["rate"])
 
@@ -432,7 +433,7 @@ def test_planar_rch_from_imod5_constant(imod5_dataset, tmp_path):
     assert "maxbound 33856" in rendered_rch
     assert rendered_rch.count("begin period") == 1
     # teardown
-    data["rch"]["rate"]["layer"].values[0] = 1
+    data["rch"]["rate"] = data["rch"]["rate"].assign_coords(layer=[1])
 
 
 @pytest.mark.unittest_jit
diff --git a/imod/tests/test_mf6/test_mf6_simulation.py b/imod/tests/test_mf6/test_mf6_simulation.py
index 06a9be30c..945fe1871 100644
--- a/imod/tests/test_mf6/test_mf6_simulation.py
+++ b/imod/tests/test_mf6/test_mf6_simulation.py
@@ -211,7 +211,7 @@ def test_simulation_open_head(circle_model, tmp_path):
     )
     assert head.dims == ("time", "layer", "mesh2d_nFaces")
     assert head.shape == (52, 2, 216)
-    assert str(head.coords["time"].values[()][0]) == "2013-04-29T22:00:00.000000000"
+    assert str(head.coords["time"].values[()][0]) == "2013-04-29T22:00:00.000000"
 
 
 class PathCases:
diff --git a/imod/tests/test_mf6/test_mf6_timedis.py b/imod/tests/test_mf6/test_mf6_timedis.py
index 20c1ecda6..baf01670d 100644
--- a/imod/tests/test_mf6/test_mf6_timedis.py
+++ b/imod/tests/test_mf6/test_mf6_timedis.py
@@ -22,7 +22,7 @@ def test_render():
         """\
         begin options
           time_units days
-          start_date_time 2000-01-01T00:00:00.000000000
+          start_date_time 2000-01-01T00:00:00.000000
         end options
 
         begin dimensions
diff --git a/imod/tests/test_mf6/test_mf6_transport_model.py b/imod/tests/test_mf6/test_mf6_transport_model.py
index c95f048ac..50600b8ae 100644
--- a/imod/tests/test_mf6/test_mf6_transport_model.py
+++ b/imod/tests/test_mf6/test_mf6_transport_model.py
@@ -153,7 +153,7 @@ def test_transport_concentration_loading(tmp_path, flow_transport_simulation):
         simulation_start_time="2000-01-31",
         time_unit="s",
     )
-    assert conc_time.coords["time"].dtype == np.dtype("datetime64[ns]")
+    assert conc_time.coords["time"].dtype == np.dtype("datetime64[us]")
 
 
 def test_transport_balance_loading(tmp_path, flow_transport_simulation):
@@ -170,7 +170,7 @@ def test_transport_balance_loading(tmp_path, flow_transport_simulation):
         simulation_start_time="2000-01-31",
         time_unit="s",
     )
-    assert balance_time.coords["time"].dtype == np.dtype("datetime64[ns]")
+    assert balance_time.coords["time"].dtype == np.dtype("datetime64[us]")
 
     np.testing.assert_allclose(
         balance_notime.sel(species="a")["source-sink mix_ssm"].values,
diff --git a/imod/tests/test_mf6/test_mf6_wel.py b/imod/tests/test_mf6/test_mf6_wel.py
index 22d06307f..c37f71e7d 100644
--- a/imod/tests/test_mf6/test_mf6_wel.py
+++ b/imod/tests/test_mf6/test_mf6_wel.py
@@ -883,7 +883,9 @@ def test_import_and_convert_to_mf6(imod5_dataset, tmp_path, wel_class):
     wel = wel_class.from_imod5_data("wel-WELLS_L3", data, times, minimum_thickness=1.0)
     assert wel.dataset["x"].values[0] == 197910.0
     assert wel.dataset["y"].values[0] == 362860.0
-    assert np.mean(wel.dataset["rate"].values) == -317.2059091946156
+    np.testing.assert_almost_equal(
+        np.mean(wel.dataset["rate"].values), -317.2059091946156
+    )
     # convert to a gridded well
     top = target_dis.dataset["top"]
     bottom = target_dis.dataset["bottom"]
@@ -895,7 +897,9 @@ def test_import_and_convert_to_mf6(imod5_dataset, tmp_path, wel_class):
     assert len(mf6_well.dataset["x"].values) == 1
     assert mf6_well.dataset["x"].values[0] == 197910.0
     assert mf6_well.dataset["y"].values[0] == 362860.0
-    assert np.mean(mf6_well.dataset["rate"].values) == -317.2059091946156
+    np.testing.assert_almost_equal(
+        np.mean(mf6_well.dataset["rate"].values), -317.2059091946156
+    )
 
     # write the package for validation
     write_context = WriteContext(simulation_directory=tmp_path)
diff --git a/imod/tests/test_typing/test_typing_grid.py b/imod/tests/test_typing/test_typing_grid.py
index 449af956f..de122616b 100644
--- a/imod/tests/test_typing/test_typing_grid.py
+++ b/imod/tests/test_typing/test_typing_grid.py
@@ -95,11 +95,11 @@ def test_is_planar_grid(basic_dis, basic_unstructured_dis):
         assert not is_planar_grid(bottom_layer)
 
         # set layer coordinates as present and 0
-        bottom_layer.coords["layer"].values[0] = 0
+        bottom_layer = bottom_layer.assign_coords(layer=[0])
         assert is_planar_grid(bottom_layer)
 
         # set layer coordinates as present and -1
-        bottom_layer.coords["layer"].values[0] = -1
+        bottom_layer = bottom_layer.assign_coords(layer=[-1])
         assert is_planar_grid(bottom_layer)
 
 
@@ -120,7 +120,7 @@ def test_has_negative_layer(basic_dis, basic_unstructured_dis):
         assert not has_negative_layer(bottom_layer)
 
         # set layer coordinates as present and -1
-        bottom_layer.coords["layer"].values[0] = -1
+        bottom_layer = bottom_layer.assign_coords(layer=[-1])
         assert has_negative_layer(bottom_layer)
 
 
diff --git a/imod/tests/test_util/test_util_time.py b/imod/tests/test_util/test_util_time.py
index 81d3e62c5..90014b242 100644
--- a/imod/tests/test_util/test_util_time.py
+++ b/imod/tests/test_util/test_util_time.py
@@ -4,6 +4,7 @@
 import numpy as np
 import pandas as pd
 import pytest
+from pytest_cases import parametrize_with_cases
 
 import imod
 from imod.util.time import _check_year, forcing_starts_ends, to_datetime_internal
@@ -138,3 +139,35 @@ def test_forcing__irregular_day():
         package_times=package_times, globaltimes=globaltimes
     )
     assert starts_ends == ["1", "2:4", "5", "6"]
+
+
+class DateTimeCases:
+    def case_Y(self):
+        return ["2000", "2001", "9999"]
+
+    def case_Ymd(self):
+        return ["20000101", "20000102", "99990101"]
+
+    def case_YmdH(self):
+        return ["2000010100", "2000010200", "9999010100"]
+
+    def case_YmdHM(self):
+        return ["200001010000", "200001020000", "999901010000"]
+
+    def case_YmdHMS(self):
+        return ["20000101000000", "20000102000000", "99990101000000"]
+
+
+@parametrize_with_cases("datestr", cases=DateTimeCases)
+def test_to_pandas_datetime_series(datestr):
+    """
+    Test whether behavior of pandas stays similar to the past, since pandas 2
+    and 3 have different base time units (ns vs us). The function should be able to handle
+    both cases, but the test is to check if the behavior of pandas has changed
+    in a way that affects the function.
+    """
+    series = pd.Series(datestr)
+    datetime_series = imod.util.time.to_pandas_datetime_series(series)
+    assert datetime_series.dtype == np.dtype("datetime64[us]")
+    assert datetime_series.iloc[0] == np.datetime64("2000-01-01", "us")
+    assert datetime_series.iloc[-1] == np.datetime64("9999-01-01", "us")
diff --git a/imod/tests/test_wq/test_wq_drn.py b/imod/tests/test_wq/test_wq_drn.py
index 217d54521..c2e2fa874 100644
--- a/imod/tests/test_wq/test_wq_drn.py
+++ b/imod/tests/test_wq/test_wq_drn.py
@@ -88,10 +88,7 @@ def test_render_with_stress_repeats__elevation(drainage):
 
 def test_compress_discontinuous_layers(drainage):
     drn = drainage
-    layer = drn["layer"].values
-    layer[1] += 1
-    layer[2] += 2
-    drn["layer"] = drn["layer"].copy(data=layer)
+    drn.dataset = drn.dataset.assign_coords(layer=[1, 3, 5])
     directory = pathlib.Path(".")
 
     compare = """
diff --git a/imod/util/expand_repetitions.py b/imod/util/expand_repetitions.py
index 869e8e0a4..981b85073 100644
--- a/imod/util/expand_repetitions.py
+++ b/imod/util/expand_repetitions.py
@@ -141,8 +141,9 @@ def resample_timeseries(
         drop=True
     )
     # If last value is nan (fell outside range), pad with last well rate.
-    if np.isnan(output_frame["rate"].values[-1]):
-        output_frame["rate"].values[-1] = well_rate["rate"].values[-1]
+    last_index = output_frame.index[-1]
+    if output_frame.isna().loc[last_index, "rate"]:
+        output_frame.loc[last_index, "rate"] = well_rate["rate"].iloc[-1]
 
     if is_steady_state:
         # Take first element, the slice is to force pandas to return it as
diff --git a/imod/util/time.py b/imod/util/time.py
index 75186b517..8525fcb6c 100644
--- a/imod/util/time.py
+++ b/imod/util/time.py
@@ -18,9 +18,10 @@
 def to_pandas_datetime_series(series: pd.Series):
     """
     Convert series to pandas datetime, uses length of first string to find the
-    appropriate format. This takes nanosecond as base. This only supports going
-    up to the year 2261; the function sets dates beyond this year silently to
-    pd.NaT.
+    appropriate format. This takes nanosecond as base in pandas 2, which only
+    supports going up to the year 2261; the function sets dates beyond this year
+    silently to pd.NaT. Pandas 3 takes microsecond as base, which supports going
+    beyond the year 9999.
     """
     len_date = len(series.iloc[0])
     dt_format = DATETIME_FORMATS[len_date]
diff --git a/pixi.lock b/pixi.lock
index ef8160db4..861b8a952 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -339,7 +339,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/orc-2.1.2-h17f744e_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-2.3.3-py312hf79963d_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-3.0.0-py312h8ecdadd_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pango-1.56.3-h9ac818e_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/partd-1.4.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pathspec-0.12.1-pyhd8ed1ab_1.conda
@@ -390,7 +390,6 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-gmsh-4.15.0-pyh57928b3_3.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-graphviz-0.21-pyhbacfb6d_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/python-librt-0.7.8-py312h5253ce2_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/python-tzdata-2025.3-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.12-8_cp312.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytokens-0.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytz-2025.2-pyhd8ed1ab_0.conda
@@ -811,7 +810,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/osx-64/orc-2.2.1-hd1b02dc_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-64/pandas-2.3.3-py312h86abcb1_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-64/pandas-3.0.0-py312hc7bc305_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-64/pango-1.56.3-hae8941d_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/partd-1.4.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pathspec-0.12.1-pyhd8ed1ab_1.conda
@@ -860,7 +859,6 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-gmsh-4.15.0-pyh57928b3_3.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-graphviz-0.21-pyhbacfb6d_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-64/python-librt-0.7.8-py312hf7082af_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/python-tzdata-2025.3-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.12-8_cp312.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytokens-0.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytz-2025.2-pyhd8ed1ab_0.conda
@@ -1258,7 +1256,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/orc-2.2.1-h4fd0076_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pandas-2.3.3-py312h5978115_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pandas-3.0.0-py312hae6be28_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pango-1.56.3-h5fd7515_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/partd-1.4.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pathspec-0.12.1-pyhd8ed1ab_1.conda
@@ -1307,7 +1305,6 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-gmsh-4.15.0-pyh57928b3_3.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-graphviz-0.21-pyhbacfb6d_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/python-librt-0.7.8-py312hb3ab3e3_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/python-tzdata-2025.3-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.12-8_cp312.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytokens-0.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytz-2025.2-pyhd8ed1ab_0.conda
@@ -1664,7 +1661,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/win-64/orc-2.2.1-h7414dfc_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/win-64/pandas-2.3.3-py312hc128f0a_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/pandas-3.0.0-py312h95189c4_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/pango-1.56.3-h0c53d3b_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/partd-1.4.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pathspec-0.12.1-pyhd8ed1ab_1.conda
@@ -2216,7 +2213,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/overrides-7.7.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-2.3.3-py312hf79963d_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-3.0.0-py312h8ecdadd_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandocfilters-1.5.0-pyhd8ed1ab_0.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pango-1.56.3-h9ac818e_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/parso-0.8.5-pyhcf101f3_0.conda
@@ -2766,7 +2763,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/overrides-7.7.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-64/pandas-2.3.3-py312h86abcb1_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-64/pandas-3.0.0-py312hc7bc305_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandocfilters-1.5.0-pyhd8ed1ab_0.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/osx-64/pango-1.56.3-hae8941d_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/parso-0.8.5-pyhcf101f3_0.conda
@@ -3293,7 +3290,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/overrides-7.7.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pandas-2.3.3-py312h5978115_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pandas-3.0.0-py312hae6be28_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandocfilters-1.5.0-pyhd8ed1ab_0.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pango-1.56.3-h5fd7515_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/parso-0.8.5-pyhcf101f3_0.conda
@@ -3778,7 +3775,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/overrides-7.7.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/win-64/pandas-2.3.3-py312hc128f0a_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/pandas-3.0.0-py312h95189c4_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandocfilters-1.5.0-pyhd8ed1ab_0.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/win-64/pango-1.56.3-h0c53d3b_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/parso-0.8.5-pyhcf101f3_0.conda
@@ -4793,7 +4790,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/orjson-3.11.5-py312h94568fe_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-2.3.3-py312hf79963d_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-3.0.0-py312h8ecdadd_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pango-1.56.3-h9ac818e_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/partd-1.4.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pathlib2-2.3.7.post1-py312h7900ff3_5.conda
@@ -5341,7 +5338,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/osx-64/orjson-3.11.5-py312hf2aa680_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-64/pandas-2.3.3-py312h86abcb1_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-64/pandas-3.0.0-py312hc7bc305_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-64/pango-1.56.3-hae8941d_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/partd-1.4.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-64/pathlib2-2.3.7.post1-py312hb401068_5.conda
@@ -5864,7 +5861,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/orjson-3.11.5-py312h6f167cc_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pandas-2.3.3-py312h5978115_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pandas-3.0.0-py312hae6be28_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pango-1.56.3-h5fd7515_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/partd-1.4.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pathlib2-2.3.7.post1-py312h81bd7bf_5.conda
@@ -6346,7 +6343,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/win-64/orjson-3.11.5-py312hfb36fc7_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-25.0-pyh29332c3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pandamesh-0.2.3-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/win-64/pandas-2.3.3-py312hc128f0a_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/pandas-3.0.0-py312h95189c4_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/pango-1.56.3-h0c53d3b_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/partd-1.4.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/pathlib2-2.3.7.post1-py312h2e8e312_5.conda
@@ -21667,213 +21664,234 @@ packages:
   - pkg:pypi/pandamesh?source=hash-mapping
   size: 38710
   timestamp: 1738918268750
-- conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-2.3.3-py312hf79963d_1.conda
-  sha256: f633d5f9b28e4a8f66a6ec9c89ef1b6743b880b0511330184b4ab9b7e2dda247
-  md5: e597b3e812d9613f659b7d87ad252d18
+- conda: https://conda.anaconda.org/conda-forge/linux-64/pandas-3.0.0-py312h8ecdadd_0.conda
+  sha256: 729c74e74703ab8686ee3915fd3023b6c454d0d97c60ec2e5f5c537cdab5277a
+  md5: 2db19c9eb81049acf8108ccfbe5cc2ed
   depends:
+  - python
+  - numpy >=1.26.0
+  - python-dateutil >=2.8.2
   - __glibc >=2.17,<3.0.a0
   - libgcc >=14
   - libstdcxx >=14
-  - numpy >=1.22.4
   - numpy >=1.23,<3
-  - python >=3.12,<3.13.0a0
-  - python-dateutil >=2.8.2
-  - python-tzdata >=2022.7
   - python_abi 3.12.* *_cp312
-  - pytz >=2020.1
   constrains:
-  - xarray >=2022.12.0
-  - qtpy >=2.3.0
+  - adbc-driver-postgresql >=1.2.0
+  - adbc-driver-sqlite >=1.2.0
+  - beautifulsoup4 >=4.12.3
+  - blosc >=1.21.3
+  - bottleneck >=1.4.2
+  - fastparquet >=2024.11.0
+  - fsspec >=2024.10.0
+  - gcsfs >=2024.10.0
   - html5lib >=1.1
-  - pandas-gbq >=0.19.0
-  - tzdata >=2022.7
-  - fsspec >=2022.11.0
-  - fastparquet >=2022.12.0
+  - hypothesis >=6.116.0
+  - jinja2 >=3.1.5
+  - lxml >=5.3.0
+  - matplotlib >=3.9.3
+  - numba >=0.60.0
+  - numexpr >=2.10.2
   - odfpy >=1.4.1
-  - pyxlsb >=1.0.10
-  - scipy >=1.10.0
-  - sqlalchemy >=2.0.0
-  - pytables >=3.8.0
-  - bottleneck >=1.3.6
-  - pyarrow >=10.0.1
-  - numexpr >=2.8.4
+  - openpyxl >=3.1.5
+  - psycopg2 >=2.9.10
+  - pyarrow >=13.0.0
+  - pyiceberg >=0.8.1
+  - pymysql >=1.1.1
   - pyqt5 >=5.15.9
-  - xlsxwriter >=3.0.5
-  - openpyxl >=3.1.0
-  - blosc >=1.21.3
-  - matplotlib >=3.6.3
-  - lxml >=4.9.2
-  - numba >=0.56.4
-  - s3fs >=2022.11.0
+  - pyreadstat >=1.2.8
+  - pytables >=3.10.1
+  - pytest >=8.3.4
+  - pytest-xdist >=3.6.1
+  - python-calamine >=0.3.0
+  - pytz >=2024.2
+  - pyxlsb >=1.0.10
+  - qtpy >=2.4.2
+  - scipy >=1.14.1
+  - s3fs >=2024.10.0
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   - tabulate >=0.9.0
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   - xlrd >=2.0.1
-  - gcsfs >=2022.11.0
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-  - python-calamine >=0.1.7
-  - zstandard >=0.19.0
-  - psycopg2 >=2.9.6
-  - beautifulsoup4 >=4.11.2
+  - xlsxwriter >=3.2.0
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   license: BSD-3-Clause
   license_family: BSD
   purls:
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-  size: 15099922
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-- conda: https://conda.anaconda.org/conda-forge/osx-64/pandas-2.3.3-py312h86abcb1_2.conda
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   depends:
+  - python
+  - numpy >=1.26.0
+  - python-dateutil >=2.8.2
   - __osx >=10.13
   - libcxx >=19
-  - numpy >=1.22.4
   - numpy >=1.23,<3
-  - python >=3.12,<3.13.0a0
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   - python_abi 3.12.* *_cp312
-  - pytz >=2020.1
   constrains:
-  - pyarrow >=10.0.1
-  - tabulate >=0.9.0
+  - adbc-driver-postgresql >=1.2.0
+  - adbc-driver-sqlite >=1.2.0
+  - beautifulsoup4 >=4.12.3
+  - blosc >=1.21.3
+  - bottleneck >=1.4.2
+  - fastparquet >=2024.11.0
+  - fsspec >=2024.10.0
+  - gcsfs >=2024.10.0
   - html5lib >=1.1
-  - s3fs >=2022.11.0
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-  - fsspec >=2022.11.0
-  - python-calamine >=0.1.7
-  - xarray >=2022.12.0
-  - numba >=0.56.4
+  - hypothesis >=6.116.0
+  - jinja2 >=3.1.5
+  - lxml >=5.3.0
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+  - numba >=0.60.0
+  - numexpr >=2.10.2
+  - odfpy >=1.4.1
+  - openpyxl >=3.1.5
+  - psycopg2 >=2.9.10
+  - pyarrow >=13.0.0
+  - pyiceberg >=0.8.1
+  - pymysql >=1.1.1
   - pyqt5 >=5.15.9
+  - pyreadstat >=1.2.8
+  - pytables >=3.10.1
+  - pytest >=8.3.4
+  - pytest-xdist >=3.6.1
+  - python-calamine >=0.3.0
+  - pytz >=2024.2
+  - pyxlsb >=1.0.10
+  - qtpy >=2.4.2
+  - scipy >=1.14.1
+  - s3fs >=2024.10.0
+  - sqlalchemy >=2.0.36
+  - tabulate >=0.9.0
+  - xarray >=2024.10.0
   - xlrd >=2.0.1
-  - blosc >=1.21.3
-  - odfpy >=1.4.1
-  - openpyxl >=3.1.0
-  - fastparquet >=2022.12.0
-  - xlsxwriter >=3.0.5
-  - pyreadstat >=1.2.0
-  - sqlalchemy >=2.0.0
-  - gcsfs >=2022.11.0
-  - beautifulsoup4 >=4.11.2
-  - lxml >=4.9.2
+  - xlsxwriter >=3.2.0
+  - zstandard >=0.23.0
   license: BSD-3-Clause
   license_family: BSD
   purls:
   - pkg:pypi/pandas?source=hash-mapping
-  size: 14008759
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/pandas-2.3.3-py312h5978115_2.conda
-  sha256: 93aa5b02e2394080a32fee9fb151da3384d317a42472586850abb37b28f314db
-  md5: fcbba82205afa4956c39136c68929385
+  size: 14115594
+  timestamp: 1769076448005
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/pandas-3.0.0-py312hae6be28_0.conda
+  sha256: e77a102f752d66a4afbda7ba4746689ec3083723d5d6fc7d5af8ddef25ff5655
+  md5: 2b38a1d070dff7f0f92641a5fa130e23
   depends:
+  - python
+  - numpy >=1.26.0
+  - python-dateutil >=2.8.2
   - __osx >=11.0
+  - python 3.12.* *_cpython
   - libcxx >=19
-  - numpy >=1.22.4
   - numpy >=1.23,<3
-  - python >=3.12,<3.13.0a0
-  - python >=3.12,<3.13.0a0 *_cpython
-  - python-dateutil >=2.8.2
-  - python-tzdata >=2022.7
   - python_abi 3.12.* *_cp312
-  - pytz >=2020.1
   constrains:
-  - xarray >=2022.12.0
-  - scipy >=1.10.0
-  - tabulate >=0.9.0
-  - pytables >=3.8.0
-  - xlsxwriter >=3.0.5
-  - pyxlsb >=1.0.10
-  - odfpy >=1.4.1
-  - zstandard >=0.19.0
-  - fastparquet >=2022.12.0
-  - gcsfs >=2022.11.0
-  - beautifulsoup4 >=4.11.2
-  - qtpy >=2.3.0
-  - xlrd >=2.0.1
-  - pandas-gbq >=0.19.0
-  - s3fs >=2022.11.0
-  - pyreadstat >=1.2.0
-  - tzdata >=2022.7
-  - html5lib >=1.1
-  - fsspec >=2022.11.0
-  - lxml >=4.9.2
-  - numexpr >=2.8.4
+  - adbc-driver-postgresql >=1.2.0
+  - adbc-driver-sqlite >=1.2.0
+  - beautifulsoup4 >=4.12.3
   - blosc >=1.21.3
-  - openpyxl >=3.1.0
-  - pyarrow >=10.0.1
-  - python-calamine >=0.1.7
-  - numba >=0.56.4
-  - sqlalchemy >=2.0.0
+  - bottleneck >=1.4.2
+  - fastparquet >=2024.11.0
+  - fsspec >=2024.10.0
+  - gcsfs >=2024.10.0
+  - html5lib >=1.1
+  - hypothesis >=6.116.0
+  - jinja2 >=3.1.5
+  - lxml >=5.3.0
+  - matplotlib >=3.9.3
+  - numba >=0.60.0
+  - numexpr >=2.10.2
+  - odfpy >=1.4.1
+  - openpyxl >=3.1.5
+  - psycopg2 >=2.9.10
+  - pyarrow >=13.0.0
+  - pyiceberg >=0.8.1
+  - pymysql >=1.1.1
   - pyqt5 >=5.15.9
-  - psycopg2 >=2.9.6
-  - bottleneck >=1.3.6
-  - matplotlib >=3.6.3
+  - pyreadstat >=1.2.8
+  - pytables >=3.10.1
+  - pytest >=8.3.4
+  - pytest-xdist >=3.6.1
+  - python-calamine >=0.3.0
+  - pytz >=2024.2
+  - pyxlsb >=1.0.10
+  - qtpy >=2.4.2
+  - scipy >=1.14.1
+  - s3fs >=2024.10.0
+  - sqlalchemy >=2.0.36
+  - tabulate >=0.9.0
+  - xarray >=2024.10.0
+  - xlrd >=2.0.1
+  - xlsxwriter >=3.2.0
+  - zstandard >=0.23.0
   license: BSD-3-Clause
   license_family: BSD
   purls:
   - pkg:pypi/pandas?source=hash-mapping
-  size: 13893993
-  timestamp: 1764615503244
-- conda: https://conda.anaconda.org/conda-forge/win-64/pandas-2.3.3-py312hc128f0a_2.conda
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+  size: 13876050
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+- conda: https://conda.anaconda.org/conda-forge/win-64/pandas-3.0.0-py312h95189c4_0.conda
+  sha256: cf9409d6f3b82a966d62c6d25dac02cf7277887591ff98d5f80f44815acef084
+  md5: 471867d1335d19294ff2b3391c4c7122
   depends:
-  - numpy >=1.22.4
-  - numpy >=1.23,<3
-  - python >=3.12,<3.13.0a0
+  - python
+  - numpy >=1.26.0
   - python-dateutil >=2.8.2
-  - python-tzdata >=2022.7
-  - python_abi 3.12.* *_cp312
-  - pytz >=2020.1
-  - ucrt >=10.0.20348.0
+  - python-tzdata
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
+  - ucrt >=10.0.20348.0
+  - numpy >=1.23,<3
+  - python_abi 3.12.* *_cp312
   constrains:
+  - adbc-driver-postgresql >=1.2.0
+  - adbc-driver-sqlite >=1.2.0
+  - beautifulsoup4 >=4.12.3
   - blosc >=1.21.3
-  - qtpy >=2.3.0
-  - pandas-gbq >=0.19.0
-  - lxml >=4.9.2
-  - fsspec >=2022.11.0
-  - xarray >=2022.12.0
-  - gcsfs >=2022.11.0
-  - tabulate >=0.9.0
-  - numba >=0.56.4
-  - xlrd >=2.0.1
+  - bottleneck >=1.4.2
+  - fastparquet >=2024.11.0
+  - fsspec >=2024.10.0
+  - gcsfs >=2024.10.0
   - html5lib >=1.1
-  - beautifulsoup4 >=4.11.2
+  - hypothesis >=6.116.0
+  - jinja2 >=3.1.5
+  - lxml >=5.3.0
+  - matplotlib >=3.9.3
+  - numba >=0.60.0
+  - numexpr >=2.10.2
+  - odfpy >=1.4.1
+  - openpyxl >=3.1.5
+  - psycopg2 >=2.9.10
+  - pyarrow >=13.0.0
+  - pyiceberg >=0.8.1
+  - pymysql >=1.1.1
   - pyqt5 >=5.15.9
-  - openpyxl >=3.1.0
-  - zstandard >=0.19.0
-  - psycopg2 >=2.9.6
-  - bottleneck >=1.3.6
-  - pytables >=3.8.0
-  - pyreadstat >=1.2.0
-  - python-calamine >=0.1.7
-  - pyarrow >=10.0.1
-  - s3fs >=2022.11.0
-  - matplotlib >=3.6.3
+  - pyreadstat >=1.2.8
+  - pytables >=3.10.1
+  - pytest >=8.3.4
+  - pytest-xdist >=3.6.1
+  - python-calamine >=0.3.0
+  - pytz >=2024.2
   - pyxlsb >=1.0.10
-  - tzdata >=2022.7
-  - odfpy >=1.4.1
-  - sqlalchemy >=2.0.0
-  - scipy >=1.10.0
-  - xlsxwriter >=3.0.5
-  - fastparquet >=2022.12.0
-  - numexpr >=2.8.4
+  - qtpy >=2.4.2
+  - scipy >=1.14.1
+  - s3fs >=2024.10.0
+  - sqlalchemy >=2.0.36
+  - tabulate >=0.9.0
+  - xarray >=2024.10.0
+  - xlrd >=2.0.1
+  - xlsxwriter >=3.2.0
+  - zstandard >=0.23.0
   license: BSD-3-Clause
   license_family: BSD
   purls:
   - pkg:pypi/pandas?source=hash-mapping
-  size: 13779090
-  timestamp: 1764615170494
+  size: 13593024
+  timestamp: 1769076331133
 - conda: https://conda.anaconda.org/conda-forge/noarch/pandocfilters-1.5.0-pyhd8ed1ab_0.tar.bz2
   sha256: 2bb9ba9857f4774b85900c2562f7e711d08dd48e2add9bee4e1612fbee27e16f
   md5: 457c2c8c08e54905d6954e79cb5b5db9
diff --git a/pixi.toml b/pixi.toml
index c9cb3acf4..6121d63b1 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -88,7 +88,7 @@ netcdf4 = "*"
 numba = ">=0.50"
 numpy = "*"
 pandamesh = "*"
-pandas = "*"
+pandas = ">=3"
 pip = "*"
 plum-dispatch = "*"
 pooch = "*"