diff --git a/.vscode/settings.json b/.vscode/settings.json
index 9910f3a3..19282e7c 100644
--- a/.vscode/settings.json
+++ b/.vscode/settings.json
@@ -13,6 +13,7 @@
         }
     },
     "mypy-type-checker.importStrategy": "fromEnvironment",
+    "python.analysis.typeCheckingMode": "off",
     "files.exclude": {
         "**/.git": true,
         "**/.svn": true,
diff --git a/flopy4/mf6/adapters.py b/flopy4/mf6/adapters.py
index 452fd530..dc39255a 100644
--- a/flopy4/mf6/adapters.py
+++ b/flopy4/mf6/adapters.py
@@ -264,7 +264,6 @@ def plottable(self):
 
     @property
     def has_stress_period_data(self):
-        # TODO oc returns true? is stress package?
         return "nper" in self._data.dims
 
     def check(self, f=None, verbose=True, level=1, checktype=None):
diff --git a/flopy4/mf6/binding.py b/flopy4/mf6/binding.py
new file mode 100644
index 00000000..a3c05fa9
--- /dev/null
+++ b/flopy4/mf6/binding.py
@@ -0,0 +1,51 @@
+from attrs import define
+
+from flopy4.mf6.component import Component
+from flopy4.mf6.exchange import Exchange
+from flopy4.mf6.model import Model
+from flopy4.mf6.package import Package
+from flopy4.mf6.solution import Solution
+
+
+@define
+class Binding:
+    """
+    An MF6 component binding: a record representation of the
+    component for writing to a parent component's name file.
+    """
+
+    type: str
+    fname: str
+    terms: tuple[str, ...] | None = None
+
+    def to_tuple(self) -> tuple[str, ...]:
+        if self.terms and any(self.terms):
+            return (self.type, self.fname, *self.terms)
+        else:
+            return (self.type, self.fname)
+
+    @classmethod
+    def from_component(cls, component: Component) -> "Binding":
+        def _get_binding_type(component: Component) -> str:
+            cls_name = component.__class__.__name__
+            if isinstance(component, Exchange):
+                return f"{'-'.join([cls_name[:2], cls_name[3:]]).upper()}6"
+            elif isinstance(component, Solution):
+                return f"{component.slntype}6"
+            else:
+                return f"{cls_name.upper()}6"
+
+        def _get_binding_terms(component: Component) -> tuple[str, ...] | None:
+            if isinstance(component, Exchange):
+                return (component.exgmnamea, component.exgmnameb)  # type: ignore
+            elif isinstance(component, Solution):
+                return tuple(component.models)
+            elif isinstance(component, (Model, Package)):
+                return (component.name,)  # type: ignore
+            return None
+
+        return cls(
+            type=_get_binding_type(component),
+            fname=component.filename or component.default_filename(),
+            terms=_get_binding_terms(component),
+        )
diff --git a/flopy4/mf6/codec/writer/__init__.py b/flopy4/mf6/codec/writer/__init__.py
index 811db456..78d08c0b 100644
--- a/flopy4/mf6/codec/writer/__init__.py
+++ b/flopy4/mf6/codec/writer/__init__.py
@@ -13,8 +13,9 @@
 )
 _JINJA_ENV.filters["field_type"] = filters.field_type
 _JINJA_ENV.filters["array_how"] = filters.array_how
-_JINJA_ENV.filters["array_chunks"] = filters.array_chunks
+_JINJA_ENV.filters["array2chunks"] = filters.array2chunks
 _JINJA_ENV.filters["array2string"] = filters.array2string
+_JINJA_ENV.filters["array2const"] = filters.array2const
 _JINJA_ENV.filters["data2list"] = filters.data2list
 _JINJA_TEMPLATE_NAME = "blocks.jinja"
 _PRINT_OPTIONS = {
diff --git a/flopy4/mf6/codec/writer/filters.py b/flopy4/mf6/codec/writer/filters.py
index 2e3c4815..d0eecb29 100644
--- a/flopy4/mf6/codec/writer/filters.py
+++ b/flopy4/mf6/codec/writer/filters.py
@@ -6,6 +6,7 @@
 import xarray as xr
 from modflow_devtools.dfn.schema.v2 import FieldType
 from numpy.typing import NDArray
+from xattree import Scalar
 
 from flopy4.mf6.constants import FILL_DNODATA
 
@@ -33,13 +34,13 @@ def field_type(value: Any) -> FieldType:
 
 
 def array_how(value: xr.DataArray) -> str:
-    # TODO
-    # - detect constant arrays?
-    # - above certain size, use external?
+    # TODO above certain size, use external?
+    if value.max() == value.min():
+        return "constant"
     return "internal"
 
 
-def array_chunks(value: xr.DataArray, chunks: Mapping[Hashable, int] | None = None):
+def array2chunks(value: xr.DataArray, chunks: Mapping[Hashable, int] | None = None):
     """
     Yield chunks from a dask-backed array of up to 3 dimensions.
     If it's not already chunked, split it into chunks of the
@@ -128,18 +129,28 @@ def nonempty(value: NDArray | xr.DataArray) -> NDArray:
     return mask
 
 
-def data2list(value: list | tuple | dict | xr.Dataset | xr.DataArray):
+def array2const(value: xr.DataArray) -> Scalar:
+    if np.issubdtype(value.dtype, np.integer):
+        return value.max().item()
+    if np.issubdtype(value.dtype, np.floating):
+        return f"{value.max().item():.8f}"
+    return value.ravel()[0]
+
+
+def data2list(value: list | dict | xr.Dataset | xr.DataArray):
     """
     Yield records (tuples) from data in a `list`, `dict`, `DataArray` or `Dataset`.
     """
 
-    if isinstance(value, (list, tuple)):
+    if isinstance(value, list):
         for rec in value:
+            if not isinstance(rec, tuple):
+                raise ValueError(f"Unsupported record type: {type(rec)}")
             yield rec
         return
 
     if isinstance(value, dict):
-        for name, val in value.values():
+        for name, val in value.items():
             yield (name, val)
         return
 
diff --git a/flopy4/mf6/codec/writer/templates/macros.jinja b/flopy4/mf6/codec/writer/templates/macros.jinja
index f235620f..4e802d36 100644
--- a/flopy4/mf6/codec/writer/templates/macros.jinja
+++ b/flopy4/mf6/codec/writer/templates/macros.jinja
@@ -32,14 +32,14 @@
 {{ inset ~ name.upper() }}{% if "layered" in how %} LAYERED{% endif %}
 
 {% if how == "constant" %}
-CONSTANT {{ value.item() }}
+{{ inset }}CONSTANT {{ value|array2const -}}
 {% elif how == "layered constant" %}
 {% for layer in value -%}
-CONSTANT {{ layer.item() }}
+{{ inset }}CONSTANT {{ layer|array2const -}}
 {%- endfor %}
 {% elif how == "internal" %}
 INTERNAL
-{% for chunk in value|array_chunks -%}
+{% for chunk in value|array2chunks -%}
 {{ (2 * inset) ~ chunk|array2string }}
 {%- endfor %}
 {% elif how == "external" %}
diff --git a/flopy4/mf6/component.py b/flopy4/mf6/component.py
index 93951569..be0219f9 100644
--- a/flopy4/mf6/component.py
+++ b/flopy4/mf6/component.py
@@ -1,12 +1,13 @@
 from abc import ABC
 from collections.abc import MutableMapping
 from pathlib import Path
-from typing import ClassVar
+from typing import Any, ClassVar
 
 import numpy as np
 from attrs import fields
 from modflow_devtools.dfn import Dfn, Field
 from packaging.version import Version
+from xattree import asdict as xattree_asdict
 from xattree import xattree
 
 from flopy4.mf6.constants import FILL_DNODATA, MF6
@@ -197,3 +198,19 @@ def write(self, format: str = MF6) -> None:
         self._write(format=format)
         for child in self.children.values():  # type: ignore
             child.write(format=format)
+
+    def to_dict(self, blocks: bool = False) -> dict[str, Any]:
+        """Convert the component to a dictionary representation."""
+        data = xattree_asdict(self)
+        data.pop("filename")
+        data.pop("workspace", None)
+        data.pop("nodes", None)  # TODO: find a better way to omit
+        if blocks:
+            blocks_ = {}  # type: ignore
+            for field_name, field_value in data.items():
+                block_name = self.dfn.fields[field_name].block
+                if block_name not in blocks_:
+                    blocks_[block_name] = {}
+                blocks_[block_name][field_name] = field_value
+            return blocks_
+        return data
diff --git a/flopy4/mf6/config.py b/flopy4/mf6/config.py
index 58fd9b6b..14da6705 100644
--- a/flopy4/mf6/config.py
+++ b/flopy4/mf6/config.py
@@ -1,3 +1,3 @@
 # TODO use https://environ-config.readthedocs.io/en/stable/?
 
-SPARSE_THRESHOLD = 1000
+SPARSE_THRESHOLD = 100000
diff --git a/flopy4/mf6/constants.py b/flopy4/mf6/constants.py
index bcd2aaaf..6d0089eb 100644
--- a/flopy4/mf6/constants.py
+++ b/flopy4/mf6/constants.py
@@ -1,5 +1,6 @@
 import numpy as np
 
 MF6 = "mf6"
+PERIOD = "period"
 FILL_DEFAULT = np.nan
 FILL_DNODATA = 1e30
diff --git a/flopy4/mf6/converter.py b/flopy4/mf6/converter.py
index 82956469..2f0617f5 100644
--- a/flopy4/mf6/converter.py
+++ b/flopy4/mf6/converter.py
@@ -1,4 +1,4 @@
-from collections.abc import Iterable, MutableMapping
+from collections.abc import Iterable, Mapping
 from datetime import datetime
 from pathlib import Path
 from typing import Any
@@ -7,70 +7,199 @@
 import sparse
 import xarray as xr
 import xattree
-from attrs import define
 from cattrs import Converter
-from modflow_devtools.dfn.schema.block import block_sort_key
+from modflow_devtools.dfn import block_sort_key
 from numpy.typing import NDArray
 from xattree import get_xatspec
 
 from flopy4.adapters import get_nn
+from flopy4.mf6.binding import Binding
 from flopy4.mf6.component import Component
 from flopy4.mf6.config import SPARSE_THRESHOLD
-from flopy4.mf6.constants import FILL_DNODATA
+from flopy4.mf6.constants import FILL_DNODATA, PERIOD
 from flopy4.mf6.context import Context
-from flopy4.mf6.exchange import Exchange
-from flopy4.mf6.model import Model
-from flopy4.mf6.package import Package
-from flopy4.mf6.solution import Solution
 from flopy4.mf6.spec import fields_dict
 
 
-@define
-class _Binding:
+def path_to_tuple(name: str, value: Path) -> tuple[str, str, str]:
+    if name.endswith("_file"):
+        base_name = name.replace("_file", "").upper()
+        return (base_name, "FILEOUT", str(value))
+    return (name.upper(), "FILEOUT", str(value))
+
+
+def get_binding_blocks(value: Component) -> dict[str, dict[str, list[tuple[str, ...]]]]:
+    if not isinstance(value, Context):
+        return {}
+
+    blocks = {}  # type: ignore
+    xatspec = xattree.get_xatspec(type(value))
+
+    for child_name, child_spec in xatspec.children.items():
+        if (child := getattr(value, child_name, None)) is None:
+            continue
+        if (block_name := child_spec.metadata["block"]) not in blocks:  # type: ignore
+            blocks[block_name] = {}
+        match child:
+            case Component():
+                blocks[block_name][child_name] = [Binding.from_component(child).to_tuple()]
+            case Mapping():
+                blocks[block_name][child_name] = [
+                    Binding.from_component(comp).to_tuple()
+                    for comp in child.values()
+                    if comp is not None
+                ]
+            case Iterable():
+                blocks[block_name][child_name] = [
+                    Binding.from_component(comp).to_tuple() for comp in child if comp is not None
+                ]
+            case _:
+                raise ValueError(f"Unexpected child type: {type(child)}")
+
+    return blocks
+
+
+def has_structured_grid_dims(value: xr.DataArray) -> bool:
+    """
+    Check if the DataArray has structured grid dimensions: 'nlay', 'nrow', and 'ncol'.
+    """
+    return all(dim in value.dims for dim in ["nlay", "nrow", "ncol"])
+
+
+def has_grid_dims(value: xr.DataArray) -> bool:
+    """
+    Check if the DataArray has spatial dimensions: 'nodes' and/or 'nlay', 'nrow', and 'ncol'.
+    """
+    return "nodes" in value.dims or has_structured_grid_dims(value)
+
+
+def has_tdis_dims(value: xr.DataArray) -> bool:
+    """
+    Check if the DataArray has a time dimensions 'nper'.
+    """
+    return "nper" in value.dims
+
+
+def _hack_structured_grid_dims(value: xr.DataArray, structured_grid_dims: Mapping):
     """
-    An MF6 component binding: a record representation of the
-    component for writing to a parent component's name file.
+    Temporary hack to convert flat nodes dimension to 3d structured dims.
+    long term solution for this is to use a custom xarray index. filters
+    should then have access to all dimensions needed.
     """
 
-    type: str
-    fname: str
-    terms: tuple[str, ...] | None = None
-
-    def to_tuple(self):
-        if self.terms and any(self.terms):
-            return (self.type, self.fname, *self.terms)
-        else:
-            return (self.type, self.fname)
-
-    @classmethod
-    def from_component(cls, component: Component) -> "_Binding":
-        def _get_binding_type(component: Component) -> str:
-            cls_name = component.__class__.__name__
-            if isinstance(component, Exchange):
-                return f"{'-'.join([cls_name[:2], cls_name[3:]]).upper()}6"
-            elif isinstance(component, Solution):
-                return f"{component.slntype}6"
-            else:
-                return f"{cls_name.upper()}6"
-
-        def _get_binding_terms(component: Component) -> tuple[str, ...] | None:
-            if isinstance(component, Exchange):
-                return (component.exgmnamea, component.exgmnameb)  # type: ignore
-            elif isinstance(component, Solution):
-                return tuple(component.models)
-            elif isinstance(component, (Model, Package)):
-                return (component.name,)  # type: ignore
-            return None
-
-        return cls(
-            type=_get_binding_type(component),
-            fname=component.filename or component.default_filename(),
-            terms=_get_binding_terms(component),
+    if "nper" in (old_dims := set(value.dims).copy()):
+        old_dims.remove("nper")
+        shape: tuple[int, ...] = (
+            value.sizes["nper"],
+            structured_grid_dims["nlay"],
+            structured_grid_dims["nrow"],
+            structured_grid_dims["ncol"],
         )
+        dims: tuple[str, ...] = ("nper", "nlay", "nrow", "ncol")
+        coords = {
+            "nper": value.coords["nper"],
+            "nlay": range(structured_grid_dims["nlay"]),
+            "nrow": range(structured_grid_dims["nrow"]),
+            "ncol": range(structured_grid_dims["ncol"]),
+        }
+    else:
+        shape = (
+            structured_grid_dims["nlay"],
+            structured_grid_dims["nrow"],
+            structured_grid_dims["ncol"],
+        )
+        dims = ("nlay", "nrow", "ncol")
+        coords = {
+            "nlay": range(structured_grid_dims["nlay"]),
+            "nrow": range(structured_grid_dims["nrow"]),
+            "ncol": range(structured_grid_dims["ncol"]),
+        }
+
+    if old_dims == {"nodes"}:
+        value = xr.DataArray(
+            value.data.reshape(shape),
+            dims=dims,
+            coords=coords,
+        )
+
+    return value
+
+
+def unstructure_field(
+    name: str,
+    value: Any,
+    # TODO: temporary, remove not needed
+    structured_grid_dims: Mapping | None,
+) -> tuple[str, Any]:
+    """
+    Convert:
+
+      - bools to keywords (since they should only be written if true)
+      - paths to records with 'FILEIN/OUT' keywords etc
+      - datetimes to ISO format
+      - 'auxiliary' arrays to tuples since they are written inline
+      - period block arrays to dictionaries of kper-sliced arrays
+
+    All other values are left as is.
+
+    Parameters
+    ----------
+    name : str
+        The name of the field
+    value : Any
+        The value of the field
+
+    Returns
+    -------
+        A tuple of (name, value) since the name might be
+        modified (e.g. '_file' suffix removed for paths)
+    """
+
+    match value:
+        case None:
+            return name, None
+        case bool():
+            return name, (value if value else None)
+        case Path():
+            rec = path_to_tuple(name, value)
+            name = rec[0]  # '_file' suffix may have been dropped
+            return name, rec
+        case datetime():
+            return name, value.isoformat()
+        case xr.DataArray():
+            if name == "auxiliary":
+                return name, tuple(value.values.tolist())
+            if has_grid_dims(value):
+                if structured_grid_dims is None:
+                    raise ValueError("Need structured grid dimension sizes")
+                value = _hack_structured_grid_dims(value, structured_grid_dims=structured_grid_dims)
+            if has_tdis_dims(value):
+                value = {kper: value.isel(nper=kper) for kper in range(value.sizes["nper"])}
+            return name, value
+        case _:
+            return name, value
+
+
+def unstructure_block(
+    block: dict[str, Any],
+    # TODO: temporary, remove not needed
+    structured_grid_dims: Mapping | None,
+) -> dict[str, Any]:
+    """Unstructure a block of data, converting fields to a suitable format."""
+    return dict(
+        [
+            unstructure_field(
+                name=field_name,
+                value=block.get(field_name, None),
+                structured_grid_dims=structured_grid_dims,
+            )
+            for field_name in block.keys()
+        ]
+    )
 
 
-def _attach_field_metadata(
-    dataset: xr.Dataset, component_type: type, field_names: list[str]
+def _hack_field_metadata(
+    dataset: xr.Dataset, component_type: type, field_names: Iterable[str]
 ) -> None:
     # TODO: attach metadata to array attrs instead of dataset attrs
     field_metadata = {}
@@ -81,175 +210,73 @@ def _attach_field_metadata(
     dataset.attrs["field_metadata"] = field_metadata
 
 
-def _path_to_tuple(field_name: str, path_value: Path) -> tuple:
-    if field_name.endswith("_file"):
-        base_name = field_name.replace("_file", "").upper()
-        return (base_name, "FILEOUT", str(path_value))
-    return (field_name.upper(), "FILEOUT", str(path_value))
+def segment_period_data(block: dict[str, Any], cls: type[Component]) -> dict[str, dict[str, Any]]:
+    """Partition period data by stress period"""
+    arrays = {}  # type: ignore
+    blocks = {}  # type: ignore
+    period = PERIOD.upper()
+
+    for arr_name, periods in block.items():
+        for kper, arr in periods.items():
+            if kper not in arrays:
+                arrays[kper] = {}
+            arrays[kper][arr_name] = arr
+
+    for kper, arrs in arrays.items():
+        dataset = xr.Dataset(arrs)
+        _hack_field_metadata(dataset, cls, arrs.keys())
+        blocks[f"{period} {kper + 1}"] = {period: dataset}
+
+    return blocks
 
 
 def unstructure_component(value: Component) -> dict[str, Any]:
-    blockspec = dict(sorted(value.dfn.blocks.items(), key=block_sort_key))  # type: ignore
+    """Unstructure a Component."""
+    dfn = value.dfn
+    cls = type(value)
+    data = value.to_dict(blocks=True)
     blocks: dict[str, dict[str, Any]] = {}
-    xatspec = xattree.get_xatspec(type(value))
+    blocks.update(binding_blocks := get_binding_blocks(value))
 
-    # Handle child component bindings before converting to dict
-    if isinstance(value, Context):
-        for field_name, child_spec in xatspec.children.items():
-            if hasattr(child_spec, "metadata") and "block" in child_spec.metadata:  # type: ignore
-                block_name = child_spec.metadata["block"]  # type: ignore
-                field_value = getattr(value, field_name, None)
-
-                if block_name not in blocks:
-                    blocks[block_name] = {}
-
-                if isinstance(field_value, Component):
-                    components = [_Binding.from_component(field_value).to_tuple()]
-                elif isinstance(field_value, MutableMapping):
-                    components = [
-                        _Binding.from_component(comp).to_tuple()
-                        for comp in field_value.values()
-                        if comp is not None
-                    ]
-                elif isinstance(field_value, Iterable):
-                    components = [
-                        _Binding.from_component(comp).to_tuple()
-                        for comp in field_value
-                        if comp is not None
-                    ]
-                else:
-                    continue
-
-                if components:
-                    blocks[block_name][field_name] = components
-
-    data = xattree.asdict(value)
-
-    for block_name, block in blockspec.items():
-        if block_name not in blocks:
-            blocks[block_name] = {}
-        period_data = {}
-        period_blocks = {}  # type: ignore
-
-        for field_name in block.keys():
-            # Skip child components that have been processed as bindings
-            if isinstance(value, Context) and field_name in xatspec.children:
-                child_spec = xatspec.children[field_name]
-                if hasattr(child_spec, "metadata") and "block" in child_spec.metadata:  # type: ignore
-                    if child_spec.metadata["block"] == block_name:  # type: ignore
-                        continue
-
-            field_value = data[field_name]
-            # convert:
-            #   - paths to records
-            #   - datetime to ISO format
-            #   - auxiliary fields to tuples
-            #   - xarray DataArrays with 'nper' dimension to kper-sliced datasets
-            #     (and split the period data into separate kper-indexed blocks)
-            #   - other values to their original form
-            if isinstance(field_value, Path):
-                rec = _path_to_tuple(field_name, field_value)
-                # name may have changed e.g dropping '_file' suffix
-                blocks[block_name][rec[0]] = rec
-            elif isinstance(field_value, datetime):
-                blocks[block_name][field_name] = field_value.isoformat()
-            elif (
-                field_name == "auxiliary"
-                and hasattr(field_value, "values")
-                and field_value is not None
-            ):
-                blocks[block_name][field_name] = tuple(field_value.values.tolist())
-            elif isinstance(field_value, xr.DataArray) and "nper" in field_value.dims:
-                has_spatial_dims = any(
-                    dim in field_value.dims for dim in ["nlay", "nrow", "ncol", "nodes"]
-                )
-                if has_spatial_dims:
-                    # terrible hack to convert flat nodes dimension to 3d structured dims.
-                    # long term solution for this is to use a custom xarray index. filters
-                    # should then have access to all dimensions needed.
-                    dims_ = set(field_value.dims).copy()
-                    dims_.remove("nper")
-                    if dims_ == {"nodes"}:
-                        parent = value.parent  # type: ignore
-                        field_value = xr.DataArray(
-                            field_value.data.reshape(
-                                (
-                                    field_value.sizes["nper"],
-                                    parent.dims["nlay"],
-                                    parent.dims["nrow"],
-                                    parent.dims["ncol"],
-                                )
-                            ),
-                            dims=("nper", "nlay", "nrow", "ncol"),
-                            coords={
-                                "nper": field_value.coords["nper"],
-                                "nlay": range(parent.dims["nlay"]),
-                                "nrow": range(parent.dims["nrow"]),
-                                "ncol": range(parent.dims["ncol"]),
-                            },
-                            name=field_value.name,
-                        )
-
-                    period_data[field_name] = {
-                        kper: field_value.isel(nper=kper)
-                        for kper in range(field_value.sizes["nper"])
-                    }
-                else:
-                    if np.issubdtype(field_value.dtype, np.str_):
-                        period_data[field_name] = {
-                            kper: field_value[kper] for kper in range(field_value.sizes["nper"])
-                        }
-                    else:
-                        if block_name not in period_data:
-                            period_data[block_name] = {}
-                        period_data[block_name][field_name] = field_value  # type: ignore
-            else:
-                if field_value is not None:
-                    if isinstance(field_value, bool):
-                        if field_value:
-                            blocks[block_name][field_name] = field_value
-                    else:
-                        blocks[block_name][field_name] = field_value
-
-        if block_name in period_data and isinstance(period_data[block_name], dict):
-            dataset = xr.Dataset(period_data[block_name])
-            _attach_field_metadata(dataset, type(value), list(period_data[block_name].keys()))  # type: ignore
-            blocks[block_name] = {block_name: dataset}
-            del period_data[block_name]
-
-        for arr_name, periods in period_data.items():
-            for kper, arr in periods.items():
-                if kper not in period_blocks:
-                    period_blocks[kper] = {}
-                period_blocks[kper][arr_name] = arr
-
-        for kper, block in period_blocks.items():
-            dataset = xr.Dataset(block)
-            _attach_field_metadata(dataset, type(value), list(block.keys()))
-            blocks[f"{block_name} {kper + 1}"] = {block_name: dataset}
-
-    # make sure options block always comes first
-    if "options" in blocks:
-        options_block = blocks.pop("options")
-        blocks = {"options": options_block, **blocks}
-
-    # total temporary hack! manually set solutiongroup 1. still need to support multiple..
+    # temporary hack! TODO remove once we have a structured grid index
+    if "nlay" in value.data.dims:  # type: ignore
+        structured_grid_dims = value.data.dims  # type: ignore
+    elif value.data.parent is not None and "nlay" in value.data.parent.dims:  # type: ignore
+        structured_grid_dims = value.data.parent.dims  # type: ignore
+    else:
+        structured_grid_dims = None
+
+    blocks.update(
+        {
+            block_name: unstructure_block(
+                data[block_name], structured_grid_dims=structured_grid_dims
+            )
+            for block_name in dfn.blocks.keys()
+            if block_name not in binding_blocks
+        }
+    )
+    if period_block := blocks.pop(PERIOD, None):
+        period_block = {k: v for k, v in period_block.items() if v is not None}
+        blocks.update(segment_period_data(period_block, cls))
+
+    # total temporary hack! manually set solutiongroup 1.
+    # TODO support multiple solution groups
     if "solutiongroup" in blocks:
         sg = blocks["solutiongroup"]
         blocks["solutiongroup 1"] = sg
         del blocks["solutiongroup"]
 
-    return {name: block for name, block in blocks.items() if name != "period"}
+    return dict(sorted(blocks.items(), key=block_sort_key))
 
 
-def _make_converter() -> Converter:
+def make_component_converter() -> Converter:
     converter = Converter()
     converter.register_unstructure_hook_factory(xattree.has, lambda _: xattree.asdict)
     converter.register_unstructure_hook(Component, unstructure_component)
     return converter
 
 
-COMPONENT_CONVERTER = _make_converter()
+COMPONENT_CONVERTER = make_component_converter()
 
 
 def dict_to_array(value, self_, field) -> NDArray:
diff --git a/flopy4/mf6/gwf/__init__.py b/flopy4/mf6/gwf/__init__.py
index 70a64443..ab22979e 100644
--- a/flopy4/mf6/gwf/__init__.py
+++ b/flopy4/mf6/gwf/__init__.py
@@ -13,12 +13,13 @@
 from flopy4.mf6.gwf.ic import Ic
 from flopy4.mf6.gwf.npf import Npf
 from flopy4.mf6.gwf.oc import Oc
+from flopy4.mf6.gwf.sto import Sto
 from flopy4.mf6.gwf.wel import Wel
 from flopy4.mf6.model import Model
 from flopy4.mf6.spec import field
 from flopy4.mf6.utils import open_cbc, open_hds
 
-__all__ = ["Gwf", "Chd", "Dis", "Drn", "Ic", "Npf", "Oc", "Wel"]
+__all__ = ["Gwf", "Chd", "Dis", "Drn", "Ic", "Npf", "Oc", "Sto", "Wel"]
 
 
 def convert_grid(value):
@@ -66,11 +67,12 @@ def budget(self):
     nc_filerecord: Optional[Path] = field(block="options", default=None)
     dis: Dis = field(converter=convert_grid, block="packages")
     ic: Ic = field(block="packages")
-    oc: Oc = field(block="packages")
+    oc: Oc = field(block="packages", default=None)
     npf: Npf = field(block="packages")
+    sto: Sto = field(block="packages", default=None)
     chd: list[Chd] = field(block="packages")
-    wel: list[Wel] = field(block="packages")
     drn: list[Drn] = field(block="packages")
+    wel: list[Wel] = field(block="packages")
     output: Output = attrs.field(
         default=attrs.Factory(lambda self: Gwf.Output(self), takes_self=True)
     )
diff --git a/flopy4/mf6/gwf/oc.py b/flopy4/mf6/gwf/oc.py
index 00a5e8d5..4d3ee592 100644
--- a/flopy4/mf6/gwf/oc.py
+++ b/flopy4/mf6/gwf/oc.py
@@ -55,28 +55,28 @@ class Period:
     save_head: Optional[NDArray[np.object_]] = array(
         object,
         block="period",
-        default="all",
+        default=None,
         dims=("nper",),
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
     )
     save_budget: Optional[NDArray[np.object_]] = array(
         object,
         block="period",
-        default="all",
+        default=None,
         dims=("nper",),
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
     )
     print_head: Optional[NDArray[np.object_]] = array(
         object,
         block="period",
-        default="all",
+        default=None,
         dims=("nper",),
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
     )
     print_budget: Optional[NDArray[np.object_]] = array(
         object,
         block="period",
-        default="all",
+        default=None,
         dims=("nper",),
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
     )
diff --git a/flopy4/mf6/gwf/sto.py b/flopy4/mf6/gwf/sto.py
index ac1e20c7..9dea32c2 100644
--- a/flopy4/mf6/gwf/sto.py
+++ b/flopy4/mf6/gwf/sto.py
@@ -39,13 +39,7 @@ class Sto(Package):
         default=0.15,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
     )
-    steady_state: Optional[NDArray[np.bool_]] = array(
-        block="period",
-        dims=("nper",),
-        default=None,
-        converter=Converter(dict_to_array, takes_self=True, takes_field=True),
-    )
-    transient: Optional[NDArray[np.bool_]] = array(
+    storage: Optional[NDArray[np.str_]] = array(
         block="period",
         dims=("nper",),
         default=None,
diff --git a/flopy4/mf6/solution.py b/flopy4/mf6/solution.py
index ba444e24..c41fc44e 100644
--- a/flopy4/mf6/solution.py
+++ b/flopy4/mf6/solution.py
@@ -1,9 +1,8 @@
 from abc import ABC
-from pathlib import Path
-from typing import ClassVar, Optional
+from typing import ClassVar
 
 import attrs
-from xattree import field, xattree
+from xattree import xattree
 
 from flopy4.mf6.package import Package
 
@@ -12,8 +11,7 @@
 class Solution(Package, ABC):
     slntype: ClassVar[str] = "sln"
 
-    slnfname: Optional[Path] = field(default=None)  # type: ignore
     models: list[str] = attrs.field(default=attrs.Factory(list))
 
     def default_filename(self) -> str:
-        return str(self.slnfname) if self.slnfname else f"solution.{self.slntype.lower()}"
+        return f"solution.{self.slntype.lower()}"
diff --git a/flopy4/spec.py b/flopy4/spec.py
index 3d9b5ddb..0721fdca 100644
--- a/flopy4/spec.py
+++ b/flopy4/spec.py
@@ -1,6 +1,8 @@
 """
 Wrap `xattree` and `attrs` specification utilities.
 These include field decorators and introspection functions.
+TODO: add `derived` option to dims? or more generic option
+to any field indicating it is not part of the formal spec?
 """
 
 from attrs import NOTHING, Attribute
diff --git a/pixi.lock b/pixi.lock
index d821b698..703dbaef 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -14,8 +14,8 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.44-ha97dd6f_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.7.1-hecca717_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.6-h2dba641_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-h767d61c_6.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-h767d61c_6.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-h767d61c_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-h767d61c_7.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.1-hb9d3cd8_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.50.4-h0c1763c_0.conda
@@ -23,7 +23,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.1-hb9d3cd8_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.5-h2d0b736_3.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.5.4-h26f9b46_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.8-h2b335a9_101_cp313.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.9-h2b335a9_100_cp313.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.13-8_cp313.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.2-h8c095d6_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_hd72426e_102.conda
@@ -34,12 +34,12 @@ environments:
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       - pypi: https://files.pythonhosted.org/packages/d8/2b/a40e1488fdfa02d3f9a653a61a5935ea08b3c2225ee818db6a76c7ba9695/cattrs-25.3.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/e4/37/af0d2ef3967ac0d6113837b44a4f0bfe1328c2b9763bd5b1744520e5cfed/certifi-2025.10.5-py3-none-any.whl
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-      - pypi: https://files.pythonhosted.org/packages/7e/95/42aa2156235cbc8fa61208aded06ef46111c4d3f0de233107b3f38631803/charset_normalizer-3.4.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
+      - pypi: https://files.pythonhosted.org/packages/ba/08/52f06ff2f04d376f9cd2c211aefcf2b37f1978e43289341f362fc99f6a0e/cftime-1.6.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
+      - pypi: https://files.pythonhosted.org/packages/f5/83/6ab5883f57c9c801ce5e5677242328aa45592be8a00644310a008d04f922/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
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+      - pypi: https://files.pythonhosted.org/packages/1c/48/01d8d3dbeafddd4df305a4a9fc0375389a017721b83b6ef0dd76c268ae0b/crc32c-2.7.1.post0-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl
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+      - pypi: https://files.pythonhosted.org/packages/f3/92/a2fa0fcb7909a781470272b91860521fbefc36b696ab4fa42ead4953eef2/h5netcdf-1.7.0-py3-none-any.whl
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-      - pypi: git+https://github.com/MODFLOW-USGS/modflow-devtools.git#cc9dff57283b92b3f2bc06034bce378e981e9282
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+      - pypi: git+https://github.com/MODFLOW-USGS/modflow-devtools.git#2aa99d53133debb21fd681f56684f3183f6ed949
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diff --git a/test/data/npf01_75x75.k33 b/test/data/npf01_75x75.k33
new file mode 100644
index 00000000..33788c07
--- /dev/null
+++ b/test/data/npf01_75x75.k33
@@ -0,0 +1,75 @@
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+       375.43210298     111.93193435     164.54122101    3177.29827764      55.68301423      62.90612217     433.28313076      69.81058826     122.13154711     924.53207252     100.36081350      95.12000268     427.11172447     163.21747874     263.86299714    2002.46237320     379.63127609     218.35838019     139.23154384     199.76945139     114.76800057     423.77583859     466.09777869     113.35714614     119.70426370      39.30377516     546.39437201      32.45182405     148.91379126     209.07771688     148.20874085      32.96593245     563.56410911    1200.11846399    1923.27474581     246.30835001     166.70503878     270.24419506      55.19212329      30.22681126     169.43856034      50.68655132     117.28578125      81.50420506     291.00230032      69.97523972      76.40877871     117.85172015    1513.55510061     745.45535509      55.77849357     250.17593672      39.00441024     225.82448882    1371.13706604     142.01695407      16.18919144     228.21754719    1263.14413824     239.69412623     211.24960887    1465.05169308     368.29084413     787.75783740      72.36465729     234.34583897      94.15769011    7665.49853465    1189.44429855      81.12554413      69.52433795     284.29375239     169.11565399    2314.97107757    1480.61580336
+        39.84693191     121.95044020     255.53631596     210.00660714     412.52309132     351.30774748      23.03683719    3893.25040421     169.98572427      83.82636662     139.74843358     112.88100168     556.54140800     152.77919121     105.92368128     301.45417712     187.74877156     142.82232029     319.22366740     756.84641162      83.08130506     119.85260896     104.40239760      66.31023782      20.02280939     293.83512988     162.26223026     151.49257442     315.01610985     231.03188461      26.09632301      19.44832126     115.06958277     492.74329161     156.66073198     348.54744641      36.76461861     201.65685571     352.28411764     313.91479877      72.76922989     117.03221453     351.99519501     210.77818996     625.52718747      38.47445232    1349.04966954     465.65418907     129.98783342     234.18673137     133.72663692      73.25970678      23.09943674      20.15973867       2.72240647     159.16259119      36.81336649      57.68201528      94.76776245     137.43310585      79.20878345     131.30730506      73.60012077     145.04739099     800.12338200      61.75460976      44.49822513      71.41963934      38.81505095    1045.21649897      31.99530478      54.40044166      15.20076022       9.98357115     198.21361818
+       144.49644082     915.99877620     522.38248868     188.20143075     164.50973662     155.41049437     607.12881170      64.54117396      21.83417937     565.70100384     342.75406456     337.24939556     290.87693663      75.38096067      80.92287107      71.26456962     260.13884447      70.26761101      62.54760691      13.33339220     209.75225869      98.19452287      71.77204859     356.35597621     447.85590200     164.42095348      55.28848456     133.63691112      44.42043945      21.87396112      12.89069102     198.65426697      96.96217485     206.63758911     366.51569699      39.94775772      48.83264703      66.85220365     261.84903092    1916.78517904     609.40823984     146.32050150    1964.15094205     128.24460326     319.15698862      27.16659692      34.04299903     419.07429354      26.17174445     525.81393057      82.46434188     238.37960465     823.49847143     206.03883722      47.80486577      21.85584096     568.21524762      31.29693536      20.93637719      77.82156255     147.47636616      23.32037951     165.38454347     759.54442865      46.10720931      14.10151942      79.18208424    1039.81051386     220.71054474     239.78749681     333.76557358    1576.39778579      84.30062779     196.03071726     243.61086598
+       563.00950616      83.23003984      19.23538118      17.85078441     105.32863954      27.82493196      39.15787649     345.77415517     263.50766108    1494.47615383     285.42560958      61.80923372      82.81890159      80.51385599      60.32002619   10760.08493283      25.28924597     106.31455588     430.67806670      31.23960518     232.72584654      67.66331977     174.73907241     407.87437868      79.59126830     118.87059966     248.17896891     131.26933938      49.26052439      24.64822938     201.65139038     521.10390303      40.92980323      16.94436064     366.72377044     107.85813201      47.58641362      61.04088031      34.43131036      91.42431867     557.83209952    1894.25604116      71.96729506     581.73419921     112.06546231     312.30469452     256.79704946    1175.81278863      12.00191157     209.41386117      78.52014579     585.56772811     148.82442194     245.60393443      23.59426435     627.02975564     708.58396477     176.97964269      66.78405201     257.92696424      67.90045888     259.70541398    3565.84356096     171.05041602      27.86603979      51.25475731     370.05629618    2510.88980841     217.23508743      45.24342434     339.78586707      53.73641755     205.13686524     557.96593445      21.36040523
+       382.19692336     484.49684825     378.74291249      69.71907715    1381.90713333      81.28996215     224.00065372     609.06124272       9.84875650     107.87938291     242.32736705     979.32712529    1616.01129493     131.70769230      42.69289828     182.32668288     227.33328322     205.05139703      97.51972053    1156.10750860      82.95079617      39.76006630     467.59833758    1893.28452458      84.15448338     559.44448201     986.28764504      86.65799936      60.86353352      53.03683396      99.36982072     989.61972653      79.60418364     264.92469081     195.01803924      32.19324471     233.37386634     239.00456343      12.00388884      61.34347338      16.36658236     163.48323643     152.90123712     387.81163338     202.29069584     228.61133952     919.86058209     104.91889326    1070.72963196     301.16313998     143.77274148     261.16582334      88.78837097      73.88273973     561.93069570     249.33240149     111.42660128      18.53222803     380.77952072     118.81276569     436.35934456     136.69628232    1176.17619648     163.68109290     110.89888512    4102.00432369      98.75950968     235.91612642     163.16134096     135.27343448      43.58096361      74.76521192    3232.50774440     288.01576551      94.52173272
+        85.11723181      43.05153255     275.64389160     708.19893211    1059.02342250     388.78454062     137.18956423      95.53443071    2772.37996168    1196.07183116     257.52659673     258.70874636     107.63347544       7.11106106     226.68963331     120.04903608     484.59620754     433.81835122    1208.72712168     250.21207740     346.40403367      56.22568780      19.49425355     135.27217017     159.63557238     193.51291027      71.79302006     103.80525316     888.37523305     233.85249984     174.47700737     139.06008908      34.77947497      66.99811159     206.20640952     465.44275549     413.41721960     184.88796214      33.77074946     775.04751540     393.81989005      36.38820735     231.38609215     333.02924901      39.59517810     955.75993026     222.71558867     136.76475755      68.37835699     111.80889499     319.00259059      32.26097021      57.44349650      20.53188323     627.97883315     418.73194925      17.64774247     458.75780913     362.80934528      39.76051130     187.34084026      70.63187920      66.61372522     120.47462695     215.83313588     166.26559521      50.35792059     160.80660849     147.24186593     105.93676518     476.94880247      22.59770804     610.34989063      17.06247163     111.79155552
+       198.12227709     172.95656018     173.59069743     269.40636403     343.67277468      36.02756108      13.03501359     115.39168655     168.49527489     390.97409822      21.05243760     286.27416038     318.18472461     310.03498774      58.60078204     104.35203099     126.25420268     116.24496796      68.15176344     543.50152480      25.11356565     113.70153027    1587.10610308      78.27099257     128.65119515     147.80342249     147.45421960     250.06595224      73.84931124     186.87442101      50.44274020     434.60429878     566.10978394     117.96306569       8.63535383     318.24205620    1913.29368179      17.59374079     101.14885036     431.55178589     471.06053346      49.91736665     321.72707470      68.68051440      35.99112613     255.75758219     233.49849845      94.45659825      25.37941040      72.06165271     200.11725287      10.55474112     191.11578999     825.15705058     147.21128566     190.02248903      50.61859969      59.67626054      62.32685507     453.86918682     161.58728950    1094.19378368     120.41061925     217.01758369      98.10784528     412.82004900     298.13759769     123.50976934      33.23822127      32.20998333     995.88418045     191.52702403     161.58754567     823.82169659     164.68763049
+       196.75020225      67.13312027      59.21351773      54.02875664     145.44551478      12.23517115     942.43360359     211.45803175      51.67552910     225.77825588      92.20469329     219.29082789     219.20964932      50.42046131      59.16863700     161.96936594    1501.61892531      86.60748147     164.81264055      83.92133151      58.61049309     290.07634682     236.75634803      13.32939317      89.69135674      14.30429130      82.81845415      61.75357059     342.71372750     350.32061870     179.16951992     188.32621346    1220.91744487     170.30532698     124.52233282     417.37758957     663.44677579      91.89776561      64.06306575     101.00158512     240.21016213     872.81382013      36.36919975      78.04857270     310.15359084      20.83133428     268.29364957      77.21209998     453.16600929     524.62199123     140.93967842     302.02284984     102.24056511       9.37282023      46.09928831     870.96734696    2012.27423352     199.12591317      23.13233843      95.72244225      16.71836671       6.60384644     153.48908685     260.95753999      60.72152465     213.24537237     717.42794435     424.10102793     155.34409798    7352.21305213     357.88017717    1194.16611266     310.55403983     216.73368392     646.87805406
+        69.25890327      20.10898723    1522.08812657     156.58688942     476.39357235     124.26778797      55.77061355      89.43930333      71.25830746      74.49747335     204.20748499      28.13736678      72.74362124      53.89036028     197.72410700    1138.92911444     146.07643583      33.08159848     221.38096367     383.96256798      36.55157192      42.18928966     357.70775047     330.46905161     163.77317647      69.78350675     110.16930278      38.30926549     385.83036252      80.91462661     648.25984337      15.36835755      67.21399029     120.66712174      90.03714039     115.09516875     206.96563202     398.66532758     548.10211124     390.84873303     527.88335501      87.92496131      34.44827160      75.11898708      48.44843086      12.50561096      12.24682746      50.79467490      12.35164167      55.90307049     275.28279452     148.18222970     150.35923190     239.54173960      92.25780865     295.83725962     617.38529444     136.59751135     402.40337553     187.36275685     161.56686067      38.20525222     742.44177085     210.47805343     270.35989947     322.18378657    2067.94107298     154.16707158      51.16033382     189.07784712     357.84550772      63.40200438     242.46352385     112.49951375     225.32779796
+       767.14680065     115.00270501       8.50672864     423.65523359     156.17310085      17.26784112     657.16781642     220.15159777     112.11852518      55.50996015      79.94496953     365.91672218      94.82776987      33.14848560      25.01238084      36.86531075     296.00825813      43.82413549      67.28833541     285.18059183      29.96918856     348.31615502     104.39223277     512.29154429     143.99468705      10.32061088     235.96254336     715.80896799     191.06193425     141.74061159     406.63133227     247.86876690      82.86521966      32.30856267      67.63294158     394.48349028     732.42809300     150.16859754     119.56845952     437.72903805     661.52891340      47.90274689     173.02948565     198.96382754     350.58682512     385.85110149     348.86145056      70.32406617     810.42999554     344.64515980      50.29143542     131.82851372     129.35225508     228.53250426      11.31590385      82.10094398     141.45551101      56.93906298     339.36573517     155.28499164      13.08082431    3317.71830189     747.99669797     113.31418947     339.82390001      10.22989042     154.83825915     805.81302660      52.06865067     293.18474826      47.38153082      86.69421323      45.96857321     272.71734021      97.62015018
diff --git a/test/test_component.py b/test/test_component.py
index a62c94c1..1a6215bb 100644
--- a/test/test_component.py
+++ b/test/test_component.py
@@ -205,7 +205,7 @@ def test_init_sim_explicit_dims():
 def test_init_big_sim():
     # if size over threshold, arrays should be sparse
     time = ModelTime(perlen=[1.0], nstp=[1], tsmult=[1.0])
-    grid = StructuredGrid(nlay=1, nrow=100, ncol=100)
+    grid = StructuredGrid(nlay=1, nrow=1000, ncol=1000)
     sim = Simulation(tdis=time)
     gwf = Gwf(parent=sim, dis=grid)
     ic = Ic(parent=gwf)
@@ -220,11 +220,11 @@ def test_init_big_sim():
     assert gwf.oc is oc
     assert gwf.npf is npf
     assert gwf.chd[0] is chd
-    assert np.array_equal(sim.models["gwf"].npf.k, np.ones(10000))
-    assert np.array_equal(sim.models["gwf"].npf.data.k, np.ones(10000))
+    assert np.array_equal(sim.models["gwf"].npf.k, np.ones(1000000))
+    assert np.array_equal(sim.models["gwf"].npf.data.k, np.ones(1000000))
     assert chd.head[0, 0].item() == 1.0
-    assert chd.head[0, 9999].item() == 0.0
-    assert np.array_equal(chd.head[0, 1:9999].data.todense(), np.full((9998,), FILL_DNODATA))
+    assert chd.head[0, 99099].item() == 0.0
+    assert np.array_equal(chd.head[0, 1:99099].data.todense(), np.full((99098,), FILL_DNODATA))
     assert np.array_equal(chd.head.data.todense(), chd.data.head.data.todense())
     assert np.array_equal(
         chd.head.data.todense(),
@@ -270,80 +270,6 @@ def test_ims_dfn():
     assert "inner_maximum" in set(dfn.blocks["linear"].keys())
 
 
-def test_gwf_chd01(function_tmpdir):
-    sim_name = "chd01"
-    gwf_name = "gwf_chd01"
-    time = ModelTime(perlen=[5.0], nstp=[1], tsmult=[1.0], time_units="days")
-
-    ims = Ims(
-        slnfname="sln1.ims",
-        models=[gwf_name],
-        print_option="summary",
-        outer_dvclose=1.00000000e-06,
-        outer_maximum=100,
-        under_relaxation="none",
-        inner_maximum=300,
-        inner_dvclose=1.00000000e-06,
-        inner_rclose=1.00000000e-06,
-        linear_acceleration="cg",
-        relaxation_factor=1.0,
-        scaling_method="none",
-        reordering_method="none",
-    )
-
-    sim = Simulation(
-        tdis=time,
-        workspace=function_tmpdir,
-        name=sim_name,
-        solutions={"ims": ims},
-    )
-
-    dis = Dis(
-        nlay=1,
-        nrow=1,
-        ncol=100,
-        delr=1.0,
-        delc=1.0,
-        top=1.0,
-        botm=0.0,
-        idomain=1,
-    )
-
-    gwf = Gwf(parent=sim, save_flows=True, dis=dis, name=gwf_name)
-
-    ic = Ic(parent=gwf, strt=1.0)
-
-    oc = Oc(
-        parent=gwf,
-        budget_file=f"{gwf_name}.cbc",
-        head_file=f"{gwf_name}.hds",
-        head="PRINT_FORMAT COLUMNS  10  WIDTH  15  DIGITS  6  GENERAL",
-        save_head=["last"],
-        # save_head={0: "last"},
-        save_budget=["last"],
-        print_head=["last"],
-        print_budget=["last"],
-    )
-
-    npf = Npf(
-        parent=gwf,
-        save_specific_discharge=True,
-        k=1.0,
-        k33=1.0,
-        icelltype=0,
-    )
-
-    chd = Chd(
-        parent=gwf,
-        print_flows=True,
-        head={0: {(0, 0, 0): 1.0, (0, 0, 99): 0.0}},
-        name="chd-1",
-    )
-
-    sim.write()
-    sim.run()
-
-
 def test_quickstart(function_tmpdir):
     sim_name = "quickstart"
     gwf_name = "mymodel"
diff --git a/test/test_interface.py b/test/test_interface.py
index 75d4e697..c6601a22 100644
--- a/test/test_interface.py
+++ b/test/test_interface.py
@@ -97,8 +97,7 @@ def test_flopy3_model(tmp_path):
         assert p.name == pnames[i]
         assert p.package_type == ptypes[i]
         assert p.parent is gwf3
-        # TODO oc?
-        if p.name == "chd0" or p.name == "oc":
+        if p.name == "chd0":
             assert p.has_stress_period_data
         else:
             assert not p.has_stress_period_data
diff --git a/test/test_mf6.py b/test/test_mf6.py
new file mode 100644
index 00000000..eb35a717
--- /dev/null
+++ b/test/test_mf6.py
@@ -0,0 +1,191 @@
+import numpy as np
+from flopy.discretization.modeltime import ModelTime
+
+from flopy4.mf6.gwf import Chd, Dis, Gwf, Ic, Npf, Oc, Sto, Wel
+from flopy4.mf6.ims import Ims
+from flopy4.mf6.simulation import Simulation
+
+
+def test_gwf_chd01(function_tmpdir):
+    # mf6 test_gwf_chd01
+    sim_name = "chd01"
+    gwf_name = "gwf_chd01"
+    time = ModelTime(perlen=[5.0], nstp=[1], tsmult=[1.0], time_units="days")
+
+    ims = Ims(
+        filename="sln1.ims",
+        models=[gwf_name],
+        print_option="summary",
+        outer_dvclose=1.00000000e-06,
+        outer_maximum=100,
+        under_relaxation="none",
+        inner_maximum=300,
+        inner_dvclose=1.00000000e-06,
+        inner_rclose=1.00000000e-06,
+        linear_acceleration="cg",
+        relaxation_factor=1.0,
+        scaling_method="none",
+        reordering_method="none",
+    )
+
+    sim = Simulation(
+        tdis=time,
+        workspace=function_tmpdir,
+        name=sim_name,
+        solutions={"ims": ims},
+    )
+
+    dis = Dis(
+        nlay=1,
+        nrow=1,
+        ncol=100,
+        delr=1.0,
+        delc=1.0,
+        top=1.0,
+        botm=0.0,
+        idomain=1,
+    )
+
+    gwf = Gwf(parent=sim, save_flows=True, dis=dis, name=gwf_name)
+
+    ic = Ic(parent=gwf, strt=1.0)
+
+    oc = Oc(
+        parent=gwf,
+        budget_file=f"{gwf_name}.cbc",
+        head_file=f"{gwf_name}.hds",
+        head="PRINT_FORMAT COLUMNS  10  WIDTH  15  DIGITS  6  GENERAL",
+        save_head=["last"],
+        # save_head={0: "last"},
+        save_budget=["last"],
+        print_head=["last"],
+        print_budget=["last"],
+    )
+
+    npf = Npf(
+        parent=gwf,
+        save_specific_discharge=True,
+        k=1.0,
+        k33=1.0,
+        icelltype=0,
+    )
+
+    chd = Chd(
+        parent=gwf,
+        print_flows=True,
+        head={0: {(0, 0, 0): 1.0, (0, 0, 99): 0.0}},
+        name="chd-1",
+    )
+
+    sim.write()
+    sim.run()
+
+
+def test_gwf_npf01(function_tmpdir):
+    # mf6 test_gwf_npf01_75X75
+    sim_name = "npf01"
+    gwf_name = "npf01_75x75"
+
+    time = ModelTime(
+        perlen=[1.0, 1000.0, 1.0], nstp=[1, 10, 1], tsmult=[1.0, 1.5, 1.0], time_units="days"
+    )
+
+    ims = Ims(
+        filename="sln1.ims",
+        models=[gwf_name],
+        print_option="summary",
+        outer_dvclose=1.00000000e-06,
+        outer_maximum=100,
+        under_relaxation="none",
+        inner_maximum=300,
+        inner_dvclose=1.00000000e-06,
+        inner_rclose=0.01000000,
+        linear_acceleration="cg",
+        relaxation_factor=1.0,
+        scaling_method="none",
+        reordering_method="none",
+    )
+
+    sim = Simulation(
+        tdis=time,
+        workspace=function_tmpdir,
+        name=sim_name,
+        solutions={"ims": ims},
+    )
+
+    dis = Dis(
+        nlay=1,
+        nrow=75,
+        ncol=75,
+        delr=266.66666667,
+        delc=266.66666667,
+        top=100.00000000,
+        botm=-100.00000000,
+        idomain=1,
+    )
+
+    gwf = Gwf(parent=sim, save_flows=True, dis=dis, name=gwf_name)
+
+    ic = Ic(parent=gwf, strt=40.0)
+
+    oc = Oc(
+        parent=gwf,
+        budget_file=f"{gwf_name}.cbc",
+        head_file=f"{gwf_name}.hds",
+        head="PRINT_FORMAT COLUMNS  10  WIDTH  15  DIGITS  6  GENERAL",
+        # save_head=[None, None, "last"],
+        # print_head=[None, None, "last"],
+        save_head=["last", None, None],
+        print_head=["last", None, None],
+        print_budget=["last", None, None],
+    )
+
+    k = np.loadtxt("data/npf01_75x75.k").flatten()
+    k33 = np.loadtxt("data/npf01_75x75.k33").flatten()
+    # k = np.loadtxt("data/npf01_75x75.k")
+    # k33 = np.loadtxt("data/npf01_75x75.k33")
+
+    npf = Npf(
+        parent=gwf,
+        k=k,
+        k33=k33,
+        icelltype=1,
+    )
+
+    sto = Sto(
+        parent=gwf,
+        iconvert=1,
+        ss=0.0,
+        sy=0.1,
+        storage=np.array(["steady-state", "transient", "steady-state"]),
+    )
+
+    import json
+
+    chd_data = {}
+    chd_data[0] = {}
+    with open("data/npf01_75x75.head", "r") as f:
+        chddata = json.load(f)
+        keys = list(chddata["0"])
+        for k in keys:
+            kup = k.replace("(", "").replace(")", "")
+            tokens = kup.split(",")
+            l = list(int(x) for x in tokens)
+            lx = tuple(l)
+            chd_data[0][lx] = float(chddata["0"][k])
+
+    chd = Chd(
+        parent=gwf,
+        print_flows=True,
+        head=chd_data,
+    )
+
+    wel = Wel(
+        parent=gwf,
+        print_input=True,
+        print_flows=True,
+        q={1: {(0, 38, 38): -1.00000000e03}},
+    )
+
+    sim.write()
+    sim.run()