diff --git a/flopy4/mf6/attr_hooks.py b/flopy4/mf6/attr_hooks.py
new file mode 100644
index 00000000..04aac6a0
--- /dev/null
+++ b/flopy4/mf6/attr_hooks.py
@@ -0,0 +1,53 @@
+"""Attribute hooks for attrs on_setattr callbacks."""
+
+import numpy as np
+from attrs import fields
+
+from flopy4.mf6.constants import FILL_DNODATA
+
+
+def update_maxbound(instance, attribute, new_value):
+    """
+    Generalized function to update maxbound when period block arrays change.
+
+    This function automatically finds all period block arrays in the instance
+    and calculates maxbound based on the maximum number of non-default values
+    across all arrays.
+
+    Args:
+        instance: The package instance
+        attribute: The attribute being set (from attrs on_setattr)
+        new_value: The new value being set
+
+    Returns:
+        The new_value (unchanged)
+    """
+
+    period_arrays = []
+    instance_fields = fields(instance.__class__)
+    for field in instance_fields:
+        if field.metadata and field.metadata.get("block") == "period" and "dims" in field.metadata:
+            period_arrays.append(field.name)
+
+    maxbound_values = []
+    for array_name in period_arrays:
+        if attribute and attribute.name == array_name:
+            array_val = new_value
+        else:
+            array_val = getattr(instance, array_name, None)
+
+        if array_val is not None:
+            array_data = (
+                array_val if array_val.data.shape == array_val.shape else array_val.todense()
+            )
+
+            if array_data.dtype.kind in ["U", "S"]:  # String arrays
+                non_default_count = len(np.where(array_data != "")[0])
+            else:  # Numeric arrays
+                non_default_count = len(np.where(array_data != FILL_DNODATA)[0])
+
+            maxbound_values.append(non_default_count)
+    if maxbound_values:
+        instance.maxbound = max(maxbound_values)
+
+    return new_value
diff --git a/flopy4/mf6/codec/__init__.py b/flopy4/mf6/codec/__init__.py
index 74f9c15c..5d4024c6 100644
--- a/flopy4/mf6/codec/__init__.py
+++ b/flopy4/mf6/codec/__init__.py
@@ -1,90 +1,6 @@
-import sys
-from os import PathLike
-from typing import Any
-
-import numpy as np
-import xattree
-from cattrs import Converter
-from jinja2 import Environment, PackageLoader
-
-from flopy4.mf6 import filters
-from flopy4.mf6.codec.converter import (
-    unstructure_array,
-    unstructure_chd,
-    unstructure_component,
-    unstructure_oc,
-    unstructure_tdis,
-)
-
-_JINJA_ENV = Environment(
-    loader=PackageLoader("flopy4.mf6"),
-    trim_blocks=True,
-    lstrip_blocks=True,
-)
-_JINJA_ENV.filters["dict_blocks"] = filters.dict_blocks
-_JINJA_ENV.filters["list_blocks"] = filters.list_blocks
-_JINJA_ENV.filters["field_type"] = filters.field_type
-_JINJA_ENV.filters["field_value"] = filters.field_value
-_JINJA_ENV.filters["array_how"] = filters.array_how
-_JINJA_ENV.filters["array_chunks"] = filters.array_chunks
-_JINJA_ENV.filters["array2string"] = filters.array2string
-
-_JINJA_TEMPLATE_NAME = "blocks.jinja"
-
-_PRINT_OPTIONS = {
-    "precision": 4,
-    "linewidth": sys.maxsize,
-    "threshold": sys.maxsize,
-}
-
-
-def _make_converter() -> Converter:
-    # TODO: document what is converter's responsibility vs Jinja's
-    # TODO: how can we make sure writing remains lazy for list input?
-    # don't eagerly unstructure to dict, lazily access from the template?
-
-    from flopy4.mf6.component import Component
-    from flopy4.mf6.gwf.chd import Chd
-    from flopy4.mf6.gwf.oc import Oc
-    from flopy4.mf6.tdis import Tdis
-
-    converter = Converter()
-    converter.register_unstructure_hook_factory(xattree.has, lambda _: xattree.asdict)
-    converter.register_unstructure_hook(Component, unstructure_component)
-    converter.register_unstructure_hook(Tdis, unstructure_tdis)
-    converter.register_unstructure_hook(Chd, unstructure_chd)
-    converter.register_unstructure_hook(Oc, unstructure_oc)
-    return converter
-
-
-_CONVERTER = _make_converter()
-
-
-def loads(data: str) -> Any:
-    # TODO
-    pass
-
-
-def load(path: str | PathLike) -> Any:
-    # TODO
-    pass
-
-
-def dumps(data) -> str:
-    template = _JINJA_ENV.get_template(_JINJA_TEMPLATE_NAME)
-    with np.printoptions(**_PRINT_OPTIONS):  # type: ignore
-        return template.render(dfn=type(data).dfn, data=_CONVERTER.unstructure(data))
-
-
-def dump(data, path: str | PathLike) -> None:
-    template = _JINJA_ENV.get_template(_JINJA_TEMPLATE_NAME)
-    iterator = template.generate(dfn=type(data).dfn, data=_CONVERTER.unstructure(data))
-    with np.printoptions(**_PRINT_OPTIONS), open(path, "w") as f:  # type: ignore
-        f.writelines(iterator)
-
+from flopy4.mf6.codec.writer import dump, dumps, load, loads
 
 __all__ = [
-    "unstructure_array",
     "loads",
     "load",
     "dumps",
diff --git a/flopy4/mf6/codec/converter.py b/flopy4/mf6/codec/converter.py
deleted file mode 100644
index acf3c45e..00000000
--- a/flopy4/mf6/codec/converter.py
+++ /dev/null
@@ -1,154 +0,0 @@
-from typing import Any
-
-import numpy as np
-import sparse
-import xattree
-from xarray import DataArray
-
-from flopy4.adapters import get_cellid
-from flopy4.mf6.component import Component
-from flopy4.mf6.constants import FILL_DNODATA
-from flopy4.mf6.spec import get_blocks, is_list_field
-
-
-def unstructure_array(value: DataArray) -> dict:
-    """
-    Convert a dense numpy array or a sparse COO array to a sparse
-    dictionary representation suitable for serialization into the
-    MF6 list-based input format.
-
-    The input array must have a time dimension named 'nper', i.e.
-    it must be stress period data for some MODFLOW 6 component.
-
-    Returns:
-        dict: {kper: {spatial indices: value, ...}, ...}
-    """
-    if (time_dim := "nper") not in value.dims:
-        raise ValueError(f"Array must have dimension '{time_dim}'")
-    if isinstance(value.data, sparse.COO):
-        coords = value.coords
-        data = value.data
-    else:
-        coords = np.array(np.where(value.data != FILL_DNODATA)).T  # type: ignore
-        data = value.data[tuple(coords.T)]  # type: ignore
-    if not coords.size:  # type: ignore
-        return {}
-    result = {}
-    match value.ndim:
-        case 1:
-            # Only kper, no spatial dims
-            for kper, v in zip(coords[:, 0], data):
-                result[int(kper)] = v
-        case _:
-            # kper + spatial dims
-            for row, v in zip(coords, data):
-                kper = int(row[0])  # type: ignore
-                spatial = tuple(int(x) for x in row[1:])  # type: ignore
-                if kper not in result:
-                    result[kper] = {}
-                # flatten spatial index if only one spatial dim
-                key = spatial[0] if len(spatial) == 1 else spatial
-                result[kper][key] = v
-    return result
-
-
-def unstructure_component(value: Component) -> dict[str, Any]:
-    data = xattree.asdict(value)
-    blocks = get_blocks(value.dfn)
-    for block in blocks.values():
-        for field_name, field in block.items():
-            if is_list_field(field):
-                data[field_name] = unstructure_array(data[field_name])
-    return data
-
-
-def unstructure_tdis(value: Any) -> dict[str, Any]:
-    data = xattree.asdict(value)
-    blocks = get_blocks(value.dfn)
-    for block_name, block in blocks.items():
-        if block_name == "perioddata":
-            arrs_d = {}
-            periods = set()  # type: ignore
-            for field_name in block.keys():
-                arr = data.get(field_name, None)
-                arr_d = {} if arr is None else unstructure_array(arr)
-                arrs_d[field_name] = arr_d
-                periods.update(arr_d.keys())
-            periods = sorted(periods)  # type: ignore
-            perioddata = {}  # type: ignore
-            for kper in periods:
-                line = []
-                if kper not in perioddata:
-                    perioddata[kper] = []  # type: ignore
-                for arr_d in arrs_d.values():
-                    if val := arr_d.get(kper, None):
-                        line.append(val)
-                perioddata[kper] = tuple(line)
-            data["perioddata"] = perioddata
-    return data
-
-
-def unstructure_chd(value: Any) -> dict[str, Any]:
-    if (parent := value.parent) is None:
-        raise ValueError(
-            "CHD cannot be unstructured without a parent "
-            "model and corresponding grid discretization."
-        )
-    grid = parent.grid
-    data = xattree.asdict(value)
-    blocks = get_blocks(value.dfn)
-    for block_name, block in blocks.items():
-        if block_name == "period":
-            arrs_d = {}
-            periods = set()  # type: ignore
-            for field_name in block.keys():
-                arr = data.get(field_name, None)
-                arr_d = {} if arr is None else unstructure_array(arr)
-                arrs_d[field_name] = arr_d
-                periods.update(arr_d.keys())
-            periods = sorted(periods)  # type: ignore
-            perioddata = {}  # type: ignore
-            for kper in periods:
-                line = []
-                if kper not in perioddata:
-                    perioddata[kper] = []  # type: ignore
-                for arr_d in arrs_d.values():
-                    if val := arr_d.get(kper, None):
-                        for nn, v in val.items():
-                            cellid = get_cellid(nn, grid)
-                            line.append((*cellid, v))
-                perioddata[kper] = tuple(line)
-            data["period"] = perioddata
-    return data
-
-
-def unstructure_oc(value: Any) -> dict[str, Any]:
-    data = xattree.asdict(value)
-    blocks = get_blocks(value.dfn)
-    for block_name, block in blocks.items():
-        if block_name == "period":
-            fields = []
-            for field_name, field in block.items():
-                action, rtype = field_name.split("_")
-                fields.append((action, rtype, field_name))
-            arrs_d = {}
-            periods = set()  # type: ignore
-            for action, rtype, field_name in fields:
-                arr = data.get(field_name, None)
-                arr_d = {} if arr is None else unstructure_array(arr)
-                arrs_d[(action, rtype)] = arr_d
-                periods.update(arr_d.keys())
-            periods = sorted(periods)  # type: ignore
-            perioddata = {}  # type: ignore
-            for kper in periods:
-                if kper not in perioddata:
-                    perioddata[kper] = []
-                for (action, rtype), arr_d in arrs_d.items():
-                    if arr := arr_d.get(kper, None):
-                        perioddata[kper].append((action, rtype, arr))
-            data["period"] = perioddata
-        else:
-            for field_name, field in block.items():
-                if is_list_field(field):
-                    data[field_name] = unstructure_array(data[field_name])
-    return data
diff --git a/flopy4/mf6/codec/reader/__init__.py b/flopy4/mf6/codec/reader/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/flopy4/mf6/codec/writer/__init__.py b/flopy4/mf6/codec/writer/__init__.py
new file mode 100644
index 00000000..960e4153
--- /dev/null
+++ b/flopy4/mf6/codec/writer/__init__.py
@@ -0,0 +1,52 @@
+import sys
+from os import PathLike
+from typing import Any
+
+import numpy as np
+from jinja2 import Environment, PackageLoader
+
+from flopy4.mf6 import filters
+
+_JINJA_ENV = Environment(
+    loader=PackageLoader("flopy4.mf6.codec.writer"),
+    trim_blocks=True,
+    lstrip_blocks=True,
+)
+_JINJA_ENV.filters["dict_blocks"] = filters.dict_blocks
+_JINJA_ENV.filters["list_blocks"] = filters.list_blocks
+_JINJA_ENV.filters["array_how"] = filters.array_how
+_JINJA_ENV.filters["array_chunks"] = filters.array_chunks
+_JINJA_ENV.filters["array2string"] = filters.array2string
+_JINJA_ENV.filters["field_type"] = filters.field_type
+_JINJA_ENV.filters["array2list"] = filters.array2list
+_JINJA_ENV.filters["keystring2list"] = filters.keystring2list
+_JINJA_ENV.filters["keystring2list_multifield"] = filters.keystring2list_multifield
+_JINJA_TEMPLATE_NAME = "blocks.jinja"
+_PRINT_OPTIONS = {
+    "precision": 4,
+    "linewidth": sys.maxsize,
+    "threshold": sys.maxsize,
+}
+
+
+def loads(data: str) -> Any:
+    # TODO
+    pass
+
+
+def load(path: str | PathLike) -> Any:
+    # TODO
+    pass
+
+
+def dumps(data) -> str:
+    template = _JINJA_ENV.get_template(_JINJA_TEMPLATE_NAME)
+    with np.printoptions(**_PRINT_OPTIONS):  # type: ignore
+        return template.render(data=data)
+
+
+def dump(data, path: str | PathLike) -> None:
+    template = _JINJA_ENV.get_template(_JINJA_TEMPLATE_NAME)
+    iterator = template.generate(data=data)
+    with np.printoptions(**_PRINT_OPTIONS), open(path, "w") as f:  # type: ignore
+        f.writelines(iterator)
diff --git a/flopy4/mf6/codec/writer/templates/blocks.jinja b/flopy4/mf6/codec/writer/templates/blocks.jinja
new file mode 100644
index 00000000..04f138f5
--- /dev/null
+++ b/flopy4/mf6/codec/writer/templates/blocks.jinja
@@ -0,0 +1,13 @@
+{% import 'macros.jinja' as macros with context %}
+{% for block_name, block_value in (data|dict_blocks).items() %}
+BEGIN {{ block_name.upper() }}
+{% for field_name, field_value in block_value.items() if (field_value) is not none -%}
+{{ macros.field(field_name, field_value) }}
+{%- endfor %}
+END {{ block_name.upper() }}
+
+{% endfor %}
+
+{% for block_name, block_value in (data|list_blocks).items() -%}
+{{ macros.list(block_name, block_value, multi=block_name in ["period"]) }}
+{%- endfor %}
diff --git a/flopy4/mf6/codec/writer/templates/macros.jinja b/flopy4/mf6/codec/writer/templates/macros.jinja
new file mode 100644
index 00000000..d9c0ce12
--- /dev/null
+++ b/flopy4/mf6/codec/writer/templates/macros.jinja
@@ -0,0 +1,87 @@
+{% macro field(name, value) %}
+{% set type = value|field_type %}
+{% if type in ['keyword', 'integer', 'double precision', 'string'] %}
+{{ scalar(name, value) }}
+{% elif type == 'record' %}
+{{ record(name, value) }}
+{% elif type == 'keystring' %}
+{{ keystring(name, value) }}
+{% elif type == 'recarray' %}
+{{ recarray(name, value, how=value|array_how) }}
+{% endif %}
+{% endmacro %}
+
+{% macro scalar(name, value) %}
+{% set type = value|field_type %}
+{% if value is not none %}{{ name.upper() }}{% if type != 'keyword' %} {{ value }}{% endif %}{% endif %}
+{% endmacro %}
+
+{% macro keystring(name, value) %}
+{% for item in value.values() -%}
+{{ field(item) }}
+{%- endfor %}
+{% endmacro %}
+
+{% macro record(name, value) %}
+{% if value is mapping %}
+{% for item in value.values() -%}
+{{ item.name.upper() }} {{ field(item) }}
+{%- endfor %}
+{% else %}
+{{ value|join(" ") }}
+{% endif %}
+{% endmacro %}
+
+{% macro recarray(name, value, how="internal") %}
+{{ name.upper() }}{% if "layered" in how %} LAYERED{% endif %}
+
+{% if how == "constant" %}
+CONSTANT {{ value.item() }}
+{% elif how == "layered constant" %}
+{% for layer in value -%}
+CONSTANT {{ layer.item() }}
+{%- endfor %}
+{% elif how == "internal" %}
+INTERNAL
+{% for chunk in value|array_chunks -%}
+{{ chunk|array2string }}
+{%- endfor %}
+{% elif how == "external" %}
+OPEN/CLOSE {{ value }}
+{% endif %}
+{% endmacro %}
+
+{% macro list(name, value, multi=False) %}
+{% if multi %}
+{# iterate through time periods and combine fields #}
+{% set field_arrays = {} %}
+{% for field_name, field_value in value.items() %}
+{% if field_value is not none %}
+{% set _ = field_arrays.update({field_name: field_value}) %}
+{% endif %}
+{% endfor %}
+
+{% set first_array = field_arrays.values() | list | first %}
+{% if first_array is not none %}
+{% set nper = first_array.shape[0] %}
+{% for period_idx in range(nper) %}
+BEGIN {{ name.upper() }} {{ period_idx + 1 }}
+{% for row in (field_arrays|keystring2list_multifield(period_idx)) %}
+{{ row|join(" ") }}
+{% endfor %}
+END {{ name.upper() }} {{ period_idx + 1 }}
+
+{% endfor %}
+{% endif %}
+{% else %}
+{% for field_name, field_value in value.items() %}
+{% if field_value is not none %}
+BEGIN {{ name.upper() }}
+{% for row in (field_value|array2list) %}
+{{ row|join(" ") }}
+{% endfor %}
+END {{ name.upper() }}
+{% endif %}
+{% endfor %}
+{% endif %}
+{% endmacro %}
diff --git a/flopy4/mf6/converter.py b/flopy4/mf6/converter.py
new file mode 100644
index 00000000..eb25f5d7
--- /dev/null
+++ b/flopy4/mf6/converter.py
@@ -0,0 +1,59 @@
+from datetime import datetime
+from pathlib import Path
+from typing import Any
+
+import xattree
+from cattrs import Converter
+
+from flopy4.mf6.component import Component
+from flopy4.mf6.spec import get_blocks
+
+
+def _transform_path_to_record(field_name: str, path_value: Path) -> tuple:
+    """Transform a Path field to its corresponding MF6 record format."""
+    # Infer record structure from field name
+    if field_name.endswith("_file"):
+        base_name = field_name.replace("_file", "").upper()
+        return (base_name, "FILEOUT", str(path_value))
+
+    # Default fallback
+    return (field_name.upper(), "FILEOUT", str(path_value))
+
+
+def unstructure_component(value: Component) -> dict[str, Any]:
+    data = xattree.asdict(value)
+    blockspec = get_blocks(value.dfn)
+    blocks: dict[str, dict[str, Any]] = {}
+    for block_name, block in blockspec.items():
+        blocks[block_name] = {}
+        for field_name in block.keys():
+            field_value = data[field_name]
+
+            # Transform Path fields to record format
+            if isinstance(field_value, Path) and field_value is not None:
+                field_value = _transform_path_to_record(field_name, field_value)
+
+            # Transform datetime fields to string format
+            elif isinstance(field_value, datetime) and field_value is not None:
+                field_value = field_value.isoformat()
+
+            # Transform auxiliary fields to tuple for single-line record format
+            elif (
+                field_name == "auxiliary"
+                and hasattr(field_value, "values")
+                and field_value is not None
+            ):
+                field_value = tuple(field_value.values.tolist())
+
+            blocks[block_name][field_name] = field_value
+    return blocks
+
+
+def _make_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()
diff --git a/flopy4/mf6/filters.py b/flopy4/mf6/filters.py
index da0a0f2d..75e1858c 100644
--- a/flopy4/mf6/filters.py
+++ b/flopy4/mf6/filters.py
@@ -1,47 +1,82 @@
 from collections.abc import Hashable, Mapping
 from io import StringIO
+from typing import Any
 
 import numpy as np
+import pandas as pd
 import xarray as xr
-from jinja2 import pass_context
-from modflow_devtools.dfn import Dfn, Field
 from numpy.typing import NDArray
 
-from flopy4.mf6.spec import get_blocks, is_list_block
+from flopy4.mf6.constants import FILL_DNODATA
 
 
-def dict_blocks(dfn: Dfn) -> dict:
+def is_list_block(block: dict) -> bool:
     """
-    Get dictionary blocks from an MF6 input definition. A
-    dictionary block is a standard block which can contain
+    Check if a block is a list block, which is a block that
+    contains only one recarray field using list input.
+    """
+    meaningful_fields = {k: v for k, v in block.items() if v is not None}
+    if len(meaningful_fields) == 0:
+        return False
+
+    # TODO: how to not hard-code these?
+    stress_fields = {
+        "head",
+        "q",
+        "elev",
+        "cond",
+        "rate",
+        "flux",
+        "concentration",
+        "stage",
+        "bhead",
+        "aux",
+        "boundname",
+    }
+    for field_name in meaningful_fields.keys():
+        if field_name.lower() not in stress_fields:
+            return False
+    return True
+
+
+def dict_blocks(data: dict) -> dict:
+    """
+    Get dictionary blocks: blocks which can contain
     one or more fields, as opposed to a list block, which
     may only contain one recarray field, using list input.
     """
     return {
-        block_name: block
-        for block_name, block in get_blocks(dfn).items()
-        if not is_list_block(block)
+        name: block
+        for name, block in data.items()
+        if block is not None and not is_list_block(block)
     }
 
 
-def list_blocks(dfn: Dfn) -> dict:
+def list_blocks(data: dict) -> dict:
+    """Get list blocks, which contain only one recarray field."""
     return {
-        block_name: block for block_name, block in get_blocks(dfn).items() if is_list_block(block)
+        name: block for name, block in data.items() if block is not None and is_list_block(block)
     }
 
 
-def field_type(field: Field) -> str:
+def field_type(value: Any) -> str:
     """
     Get a field's type as defined by the MODFLOW 6 input definition language:
     https://modflow6.readthedocs.io/en/stable/_dev/dfn.html#variable-types
     """
-    return field["type"]
-
-
-@pass_context
-def field_value(ctx, field: Field):
-    """Get a field's value via the template context."""
-    return ctx["data"][field["name"]]
+    if isinstance(value, bool):
+        return "keyword"
+    if isinstance(value, int):
+        return "integer"
+    if isinstance(value, float):
+        return "double precision"
+    if isinstance(value, str):
+        return "string"
+    if isinstance(value, (dict, tuple)):
+        return "record"
+    if isinstance(value, (list, np.ndarray, xr.DataArray)):
+        return "recarray"
+    return "keystring"
 
 
 def array_how(value: xr.DataArray) -> str:
@@ -67,25 +102,31 @@ def array_chunks(value: xr.DataArray, chunks: Mapping[Hashable, int] | None = No
     - If the array is 1D or 2D, yield it as a single chunk.
     """
 
-    if value.chunks is None:
-        if chunks is None:
-            match value.ndim:
-                case 1:
-                    # 1D array, single chunk
-                    chunks = {value.dims[0]: value.shape[0]}
-                case 2:
-                    # 2D array, single chunk
-                    chunks = {value.dims[0]: value.shape[0], value.dims[1]: value.shape[1]}
-                case 3:
-                    # 3D array, chunk for each layer
-                    chunks = {
-                        value.dims[0]: 1,
-                        value.dims[1]: value.shape[1],
-                        value.dims[2]: value.shape[2],
-                    }
-        value = value.chunk(chunks)
-    for chunk in value.data.blocks:
-        yield np.squeeze(chunk.compute())
+    # Check if it's a dask array (has .blocks attribute)
+    if hasattr(value.data, "blocks"):
+        # Dask array - use chunking logic
+        if value.chunks is None:
+            if chunks is None:
+                match value.ndim:
+                    case 1:
+                        # 1D array, single chunk
+                        chunks = {value.dims[0]: value.shape[0]}
+                    case 2:
+                        # 2D array, single chunk
+                        chunks = {value.dims[0]: value.shape[0], value.dims[1]: value.shape[1]}
+                    case 3:
+                        # 3D array, chunk for each layer
+                        chunks = {
+                            value.dims[0]: 1,
+                            value.dims[1]: value.shape[1],
+                            value.dims[2]: value.shape[2],
+                        }
+            value = value.chunk(chunks)
+        for chunk in value.data.blocks:
+            yield np.squeeze(chunk.compute())
+    else:
+        # Regular numpy array - yield as single chunk
+        yield np.squeeze(value.values)
 
 
 def array2string(value: NDArray) -> str:
@@ -112,3 +153,123 @@ def array2string(value: NDArray) -> str:
     )
     np.savetxt(buffer, value, fmt=format, delimiter=" ")
     return buffer.getvalue().strip()
+
+
+def array2list(value: xr.DataArray, include_zeros: bool = False):
+    """
+    Generator that yields sparse (indices, value, *aux) tuples from a `DataArray`.
+    Iterates only over meaningful values (excludes zeros, NaN, and `FILL_DNODATA`).
+
+    Parameters
+    ----------
+    value : xr.DataArray
+        The input array to iterate over sparsely
+    include_zeros : bool, optional
+        If True, include zero values in iteration. Default False.
+
+    Yields
+    ------
+    tuple
+        Tuples of (layer, row, col, value) with 1-based indexing for MF6
+    """
+    from flopy4.mf6.constants import FILL_DNODATA
+
+    if not include_zeros:
+        mask = (value != 0) & (value != FILL_DNODATA) & ~np.isnan(value)
+    else:
+        mask = (value != FILL_DNODATA) & ~np.isnan(value)
+
+    indices = np.where(mask)
+    values = value.values[mask]
+    for i, val in enumerate(values):
+        idx_1based = tuple(idx[i] + 1 for idx in indices)
+        yield idx_1based + (val,)
+
+
+def keystring2list(value: xr.DataArray):
+    """
+    Generator for object arrays containing structured data (keystrings).
+    Yields structured records for non-null entries.
+
+    Parameters
+    ----------
+    value : xr.DataArray
+        Array with object dtype containing structured data
+
+    Yields
+    ------
+    tuple
+        Tuples of (layer, row, col, *structured_values) with 1-based indexing
+    """
+    coord_arrays = np.meshgrid(*[np.arange(s) for s in value.shape], indexing="ij")
+    flat_values = value.values.flat
+    flat_coords = zip(*[arr.flat for arr in coord_arrays])
+    for coords, val in zip(flat_coords, flat_values):
+        if val is not None and not pd.isna(val):
+            coords_1based = tuple(c + 1 for c in coords)
+            if hasattr(val, "_asdict"):  # Named tuple
+                yield coords_1based + tuple(val._asdict().values())
+            elif isinstance(val, dict):
+                yield coords_1based + tuple(val.values())
+            else:
+                yield coords_1based + (val,)
+
+
+def keystring2list_multifield(field_arrays: dict, period_idx: int):
+    """
+    Combines multiple fields (e.g., elev, cond) for a given stress period
+
+    Parameters
+    ----------
+    field_arrays : dict
+        Dictionary of field_name -> xarray.DataArray
+    period_idx : int
+        Time period index (0-based)
+
+    Yields
+    ------
+    tuple
+        Tuples of (layer, row, col, field1_value, field2_value, ...)
+        with 1-based indexing
+    """
+    if not field_arrays:
+        return
+
+    # determine spatial structure from first array
+    first_field = next(iter(field_arrays.values()))
+    if not isinstance(first_field, (np.ndarray, xr.DataArray)):
+        return
+
+    # get period slice
+    period_slices: dict[str, Any] = {}
+    for field_name, field_array in field_arrays.items():
+        if isinstance(field_array, xr.DataArray):
+            period_data = field_array.isel(nper=period_idx)
+            period_slices[field_name] = period_data.values
+        elif isinstance(field_array, np.ndarray):
+            period_slices[field_name] = field_array[period_idx]
+
+    # Find all locations where at least one field has meaningful data
+    combined_mask: Any = None
+    for field_name, period_data in period_slices.items():
+        meaningful_mask = (
+            (period_data != 0) & (period_data != FILL_DNODATA) & ~np.isnan(period_data)
+        )
+        if combined_mask is None:
+            combined_mask = meaningful_mask
+        else:
+            combined_mask = combined_mask | meaningful_mask
+
+    if combined_mask is None or not np.any(combined_mask):
+        return
+
+    indices = np.where(combined_mask)
+    for i in range(len(indices[0])):
+        idx_1based = tuple(idx[i] + 1 for idx in indices)
+        field_values = []
+        for field_name in field_arrays.keys():
+            period_data = period_slices[field_name]
+            val = period_data[tuple(idx[i] for idx in indices)]
+            field_values.append(val)
+
+        yield idx_1based + tuple(field_values)
diff --git a/flopy4/mf6/gwf/__init__.py b/flopy4/mf6/gwf/__init__.py
index ca2b515b..fa0697c2 100644
--- a/flopy4/mf6/gwf/__init__.py
+++ b/flopy4/mf6/gwf/__init__.py
@@ -9,14 +9,16 @@
 
 from flopy4.mf6.gwf.chd import Chd
 from flopy4.mf6.gwf.dis import Dis
+from flopy4.mf6.gwf.drn import Drn
 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.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", "Ic", "Npf", "Oc"]
+__all__ = ["Gwf", "Chd", "Dis", "Drn", "Ic", "Npf", "Oc", "Wel"]
 
 
 def convert_grid(value):
@@ -54,6 +56,8 @@ def budget(self):
     oc: Oc = field()
     npf: Npf = field()
     chd: list[Chd] = field()
+    wel: list[Wel] = field()
+    drn: list[Drn] = field()
     output: Output = attrs.field(
         default=attrs.Factory(lambda self: Gwf.Output(self), takes_self=True)
     )
diff --git a/flopy4/mf6/gwf/chd.py b/flopy4/mf6/gwf/chd.py
index dca220dc..804e0325 100644
--- a/flopy4/mf6/gwf/chd.py
+++ b/flopy4/mf6/gwf/chd.py
@@ -6,7 +6,7 @@
 from numpy.typing import NDArray
 from xattree import xattree
 
-from flopy4.mf6.constants import FILL_DNODATA
+from flopy4.mf6.attr_hooks import update_maxbound
 from flopy4.mf6.converters import dict_to_array
 from flopy4.mf6.package import Package
 from flopy4.mf6.spec import array, field
@@ -15,7 +15,6 @@
 @xattree
 class Chd(Package):
     multi_package: ClassVar[bool] = True
-
     auxiliary: Optional[list[str]] = array(block="options", default=None)
     auxmultname: Optional[str] = field(block="options", default=None)
     boundnames: bool = field(block="options", default=False)
@@ -35,6 +34,7 @@ class Chd(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
     aux: Optional[NDArray[np.float64]] = array(
         block="period",
@@ -45,6 +45,7 @@ class Chd(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
     boundname: Optional[NDArray[np.str_]] = array(
         block="period",
@@ -55,32 +56,9 @@ class Chd(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
 
     def __attrs_post_init__(self):
-        # TODO set up on_setattr hooks for period block
-        # arrays to update maxbound? for now do it here
-        # in post init. but this only works when values
-        # are set in the initializer, not when they are
-        # set later.
-        if self.head is None:
-            maxhead = 0
-        else:
-            head = self.head if self.head.data.shape == self.head.shape else self.head.todense()
-            maxhead = len(np.where(head != FILL_DNODATA))
-        if self.aux is None:
-            maxaux = 0
-        else:
-            aux = self.aux if self.aux.data.shape == self.aux.shape else self.aux.todense()
-            maxaux = len(np.where(aux != FILL_DNODATA))
-        if self.boundname is None:
-            maxboundname = 0
-        else:
-            boundname = (
-                self.boundname
-                if self.boundname.data.shape == self.boundname.shape
-                else self.boundname.todense()
-            )
-            maxboundname = len(np.where(boundname != ""))
-
-        self.maxbound = max(maxhead, maxaux, maxboundname)
+        if self.head is not None or self.aux is not None or self.boundname is not None:
+            update_maxbound(self, None, None)
diff --git a/flopy4/mf6/gwf/dis.py b/flopy4/mf6/gwf/dis.py
index e069e31f..b5f8a8e4 100644
--- a/flopy4/mf6/gwf/dis.py
+++ b/flopy4/mf6/gwf/dis.py
@@ -1,4 +1,5 @@
 from typing import Optional
+
 import numpy as np
 from attrs import Converter
 from flopy.discretization.structuredgrid import StructuredGrid
diff --git a/flopy4/mf6/gwf/drn.py b/flopy4/mf6/gwf/drn.py
index ab581730..ea813f0d 100644
--- a/flopy4/mf6/gwf/drn.py
+++ b/flopy4/mf6/gwf/drn.py
@@ -6,7 +6,7 @@
 from numpy.typing import NDArray
 from xattree import xattree
 
-from flopy4.mf6.constants import FILL_DNODATA
+from flopy4.mf6.attr_hooks import update_maxbound
 from flopy4.mf6.converters import dict_to_array
 from flopy4.mf6.package import Package
 from flopy4.mf6.spec import array, field
@@ -33,6 +33,7 @@ class Drn(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
     cond: Optional[NDArray[np.float64]] = array(
         block="period",
@@ -40,6 +41,7 @@ class Drn(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
     aux: Optional[NDArray[np.float64]] = array(
         block="period",
@@ -50,6 +52,7 @@ class Drn(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
     boundname: Optional[NDArray[np.str_]] = array(
         block="period",
@@ -60,37 +63,14 @@ class Drn(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
 
     def __attrs_post_init__(self):
-        # TODO set up on_setattr hooks for period block
-        # arrays to update maxbound? for now do it here
-        # in post init. but this only works when values
-        # are set in the initializer, not when they are
-        # set later.
-        if self.head is None:
-            maxhead = 0
-        else:
-            head = self.head if self.head.data.shape == self.head.shape else self.head.todense()
-            maxhead = len(np.where(head != FILL_DNODATA))
-        if self.cond is None:
-            maxcond = 0
-        else:
-            cond = self.cond if self.cond.data.shape == self.cond.shape else self.cond.todense()
-            maxcond = len(np.where(cond != FILL_DNODATA))
-        if self.aux is None:
-            maxaux = 0
-        else:
-            aux = self.aux if self.aux.data.shape == self.aux.shape else self.aux.todense()
-            maxaux = len(np.where(aux != FILL_DNODATA))
-        if self.boundname is None:
-            maxboundname = 0
-        else:
-            boundname = (
-                self.boundname
-                if self.boundname.data.shape == self.boundname.shape
-                else self.boundname.todense()
-            )
-            maxboundname = len(np.where(boundname != ""))
-
-        self.maxbound = max(maxhead, maxcond, maxaux, maxboundname)
+        if (
+            self.elev is not None
+            or self.cond is not None
+            or self.aux is not None
+            or self.boundname is not None
+        ):
+            update_maxbound(self, None, None)
diff --git a/flopy4/mf6/gwf/rch.py b/flopy4/mf6/gwf/rch.py
index dd25fb84..4eb9a176 100644
--- a/flopy4/mf6/gwf/rch.py
+++ b/flopy4/mf6/gwf/rch.py
@@ -6,7 +6,7 @@
 from numpy.typing import NDArray
 from xattree import xattree
 
-from flopy4.mf6.constants import FILL_DNODATA
+from flopy4.mf6.attr_hooks import update_maxbound
 from flopy4.mf6.converters import dict_to_array
 from flopy4.mf6.package import Package
 from flopy4.mf6.spec import array, field
@@ -15,7 +15,6 @@
 @xattree
 class Rch(Package):
     multi_package: ClassVar[bool] = True
-
     fixed_cell: bool = field(block="options", default=False)
     auxiliary: Optional[list[str]] = array(block="options", default=None)
     auxmultname: Optional[str] = field(block="options", default=None)
@@ -35,6 +34,7 @@ class Rch(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
     aux: Optional[NDArray[np.float64]] = array(
         block="period",
@@ -45,6 +45,7 @@ class Rch(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
     boundname: Optional[NDArray[np.str_]] = array(
         block="period",
@@ -55,32 +56,9 @@ class Rch(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
 
     def __attrs_post_init__(self):
-        # TODO set up on_setattr hooks for period block
-        # arrays to update maxbound? for now do it here
-        # in post init. but this only works when values
-        # are set in the initializer, not when they are
-        # set later.
-        if self.recharge is None:
-            maxrecharge = 0
-        else:
-            recharge = self.head if self.head.data.shape == self.head.shape else self.head.todense()
-            maxrecharge = len(np.where(recharge != FILL_DNODATA))
-        if self.aux is None:
-            maxaux = 0
-        else:
-            aux = self.aux if self.aux.data.shape == self.aux.shape else self.aux.todense()
-            maxaux = len(np.where(aux != FILL_DNODATA))
-        if self.boundname is None:
-            maxboundname = 0
-        else:
-            boundname = (
-                self.boundname
-                if self.boundname.data.shape == self.boundname.shape
-                else self.boundname.todense()
-            )
-            maxboundname = len(np.where(boundname != ""))
-
-        self.maxbound = max(maxrecharge, maxaux, maxboundname)
+        if self.recharge is not None or self.aux is not None or self.boundname is not None:
+            update_maxbound(self, None, None)
diff --git a/flopy4/mf6/gwf/wel.py b/flopy4/mf6/gwf/wel.py
index bbeb2549..59d27912 100644
--- a/flopy4/mf6/gwf/wel.py
+++ b/flopy4/mf6/gwf/wel.py
@@ -6,7 +6,7 @@
 from numpy.typing import NDArray
 from xattree import xattree
 
-from flopy4.mf6.constants import FILL_DNODATA
+from flopy4.mf6.attr_hooks import update_maxbound
 from flopy4.mf6.converters import dict_to_array
 from flopy4.mf6.package import Package
 from flopy4.mf6.spec import array, field
@@ -36,6 +36,7 @@ class Wel(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
     aux: Optional[NDArray[np.float64]] = array(
         block="period",
@@ -46,6 +47,7 @@ class Wel(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
     boundname: Optional[NDArray[np.str_]] = array(
         block="period",
@@ -56,32 +58,9 @@ class Wel(Package):
         default=None,
         converter=Converter(dict_to_array, takes_self=True, takes_field=True),
         reader="urword",
+        on_setattr=update_maxbound,
     )
 
     def __attrs_post_init__(self):
-        # TODO set up on_setattr hooks for period block
-        # arrays to update maxbound? for now do it here
-        # in post init. but this only works when values
-        # are set in the initializer, not when they are
-        # set later.
-        if self.q is None:
-            maxq = 0
-        else:
-            q = self.q if self.q.data.shape == self.q.shape else self.q.todense()
-            maxq = len(np.where(q != FILL_DNODATA))
-        if self.aux is None:
-            maxaux = 0
-        else:
-            aux = self.aux if self.aux.data.shape == self.aux.shape else self.aux.todense()
-            maxaux = len(np.where(aux != FILL_DNODATA))
-        if self.boundname is None:
-            maxboundname = 0
-        else:
-            boundname = (
-                self.boundname
-                if self.boundname.data.shape == self.boundname.shape
-                else self.boundname.todense()
-            )
-            maxboundname = len(np.where(boundname != ""))
-
-        self.maxbound = max(maxq, maxaux, maxboundname)
+        if self.q is not None or self.aux is not None or self.boundname is not None:
+            update_maxbound(self, None, None)
diff --git a/flopy4/mf6/spec.py b/flopy4/mf6/spec.py
index 73840871..c618c450 100644
--- a/flopy4/mf6/spec.py
+++ b/flopy4/mf6/spec.py
@@ -28,6 +28,7 @@ def field(
     eq=True,
     init=True,
     metadata=None,
+    on_setattr=None,
     block: str | None = None,
 ):
     """Define a field."""
@@ -42,6 +43,7 @@ def field(
         repr=repr,
         eq=eq,
         init=init,
+        on_setattr=on_setattr,
         metadata=metadata,
     )
 
@@ -105,6 +107,7 @@ def array(
     repr=True,
     eq=None,
     metadata=None,
+    on_setattr=None,
     block: str | None = None,
     reader: Reader = "readarray",
 ):
@@ -121,6 +124,7 @@ def array(
         converter=converter,
         repr=repr,
         eq=eq,
+        on_setattr=on_setattr,
         metadata=metadata,
     )
 
@@ -261,7 +265,7 @@ def to_dfn_field(attribute: Attribute) -> Field:
     )
 
 
-def get_blocks(dfn: Dfn) -> dict:
+def get_blocks(dfn: Dfn) -> dict[str, Block]:
     """
     Get blocks from an MF6 input definition. Anything not an
     explicitly defined key in the `Dfn` typed dict is a block.
@@ -283,9 +287,14 @@ def is_list_field(field: Field) -> bool:
     return field["type"] == "recarray" and field["reader"] != "readarray"
 
 
-def is_list_block(block: dict) -> bool:
+def is_list_block(block: Block) -> bool:
     return (
         len(block) == 1
-        and (field := next(iter(block.values())))["type"] == "recarray"
-        and field["reader"] != "readarray"
-    ) or (all(f["type"] == "recarray" and f["reader"] != "readarray" for f in block.values()))
+        and (field := next(iter(block.values()))).metadata.get("type") == "recarray"
+        and field.metadata.get("reader") != "readarray"
+    ) or (
+        all(
+            f.metadata.get("type") == "recarray" and f.metadata.get("reader") != "readarray"
+            for f in block.values()
+        )
+    )
diff --git a/flopy4/mf6/templates/blocks.jinja b/flopy4/mf6/templates/blocks.jinja
deleted file mode 100644
index ef534445..00000000
--- a/flopy4/mf6/templates/blocks.jinja
+++ /dev/null
@@ -1,13 +0,0 @@
-{% import 'macros.jinja' as macros with context %}
-{% for block_name, block_ in (dfn|dict_blocks).items() %}
-BEGIN {{ block_name.upper() }}
-{% for field in block_.values() if (field|field_value) is not none -%}
-{{ macros.field(field) }}
-{%- endfor %}
-END {{ block_name.upper() }}
-
-{% endfor %}
-
-{% for block_name, block_ in (dfn|list_blocks).items() -%}
-{{ macros.list(block_name, block_, single=block_name != "period") }}
-{%- endfor%}
diff --git a/flopy4/mf6/templates/macros.jinja b/flopy4/mf6/templates/macros.jinja
deleted file mode 100644
index b7ea113d..00000000
--- a/flopy4/mf6/templates/macros.jinja
+++ /dev/null
@@ -1,92 +0,0 @@
-{% macro field(f) %}
-{% set type = f|field_type %}
-{% if type in ['keyword', 'integer', 'double precision', 'string'] %}
-{{ scalar(f) }}
-{% elif type == 'record' %}
-{{ record(f) }}
-{% elif type == 'keystring' %}
-{{ keystring(f) }}
-{% elif type == 'recarray' %}
-{{ recarray(f, how=f|array_how) }}
-{% endif %}
-{% endmacro %}
-
-{% macro scalar(f) %}
-{% set type = f|field_type %}
-{% set value = f|field_value %}
-{% if value is not none %}{{ f.name.upper() }}{% if type != 'keyword' %} {{ value }}{% endif %}{% endif %}
-{% endmacro %}
-
-{% macro keystring(f) %}
-{% for item in f.children.values() -%}
-{{ field(item) }}
-{%- endfor %}
-{% endmacro %}
-
-{% macro record(f) %}
-{% for item in f.children.values() -%}
-{% if item.tagged %}{{ item.name.upper() }} {% endif %}{{ field(item) }}
-{%- endfor %}
-{% endmacro %}
-
-{% macro recarray(f, how="internal") %}
-{% set name = f.name %}
-{% set value = f|field_value %}
-{{ name.upper() }}{% if "layered" in how %} LAYERED{% endif %}
-
-{% if how == "constant" %}
-CONSTANT {{ value.item() }}
-{% elif how == "layered constant" %}
-{% for layer in value -%}
-CONSTANT {{ layer.item() }}
-{%- endfor %}
-{% elif how == "internal" %}
-INTERNAL
-{% for chunk in value|array_chunks -%}
-{{ chunk|array2string }}
-{%- endfor %}
-{% elif how == "external" %}
-OPEN/CLOSE {{ value }}
-{% endif %}
-{% endmacro %}
-
-{% macro list(block_name, block, single=False) %}
-{#
-from mf6's perspective, a list block (e.g. period data)
-always has just one variable, whose elements might be
-records or unions. if records, each record field is a
-column in a table, and we spin each column out into a
-separate array. if unions, we have a single array of
-some record which we have invented to represent the
-union in a nicer way. in either case we've done some
-munging in conversion to turn the (internal) array
-into a sparse dict representation where outermost
-keys are stress periods, and stored that as a new
-variable with the same name as the block. this macro
-receives the block definition, and from that it looks
-up the value of this variable. if the 'single' param
-is True, we assume the dict's values are tuples to
-become rows in a single block, e.g. tdis perioddata.
-if False, we assume the dict's values are themselves
-dicts, where the keys are cell ids, and the values
-are tuples, and each entry becomes a row in a block
-indexed by stres period. hope that all made sense..
-#}
-{% set d = data[block_name] %}
-{% if single %}
-BEGIN {{ block_name.upper() }}
-{% for line in d.values() %}
-{{ line|join(" ")|upper }}
-{% endfor %}
-END {{ block_name.upper() }}
-{% else %}
-{% for kper, value in d.items() %}
-BEGIN {{ block_name.upper() }} {{ kper + 1 }}
-{% for line in value %}
-{{ line|join(" ")|upper }}
-{% endfor %}
-END {{ block_name.upper() }} {{ kper + 1 }}
-
-{% endfor %}
-{% endif %}
-{% endmacro %}
diff --git a/flopy4/spec.py b/flopy4/spec.py
index 31f2f537..e719706e 100644
--- a/flopy4/spec.py
+++ b/flopy4/spec.py
@@ -19,6 +19,7 @@ def field(
     eq=True,
     init=True,
     metadata=None,
+    on_setattr=None,
 ):
     """Define a field."""
     return xattree_field(
@@ -29,6 +30,7 @@ def field(
         eq=eq,
         init=init,
         metadata=metadata,
+        on_setattr=on_setattr,
     )
 
 
@@ -81,6 +83,7 @@ def array(
     repr=True,
     eq=None,
     metadata=None,
+    on_setattr=None,
 ):
     """Define an array field."""
     return xattree_array(
@@ -92,6 +95,7 @@ def array(
         repr=repr,
         eq=eq,
         metadata=metadata,
+        on_setattr=on_setattr,
     )
 
 
diff --git a/pixi.lock b/pixi.lock
index f5a35a03..5a3d328c 100644
--- a/pixi.lock
+++ b/pixi.lock
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-  - sphinx>=5.0.0,<8.0.0 ; extra == 'doc'
+  - sphinx>=5.0.0,<8.2.0 ; extra == 'doc'
   - intersphinx-registry ; extra == 'doc'
   - pydata-sphinx-theme>=0.15.2 ; extra == 'doc'
   - sphinx-copybutton ; extra == 'doc'
@@ -9341,10 +9657,11 @@ packages:
   - matplotlib>=3.5 ; extra == 'doc'
   - numpydoc ; extra == 'doc'
   - jupytext ; extra == 'doc'
-  - myst-nb ; extra == 'doc'
+  - myst-nb>=1.2.0 ; extra == 'doc'
   - pooch ; extra == 'doc'
   - jupyterlite-sphinx>=0.19.1 ; extra == 'doc'
   - jupyterlite-pyodide-kernel ; extra == 'doc'
+  - linkify-it-py ; extra == 'doc'
   - mypy==1.10.0 ; extra == 'dev'
   - typing-extensions ; extra == 'dev'
   - types-psutil ; extra == 'dev'
@@ -9354,7 +9671,7 @@ packages:
   - rich-click ; extra == 'dev'
   - doit>=0.36.0 ; extra == 'dev'
   - pydevtool ; extra == 'dev'
-  requires_python: '>=3.10'
+  requires_python: '>=3.11'
 - pypi: https://files.pythonhosted.org/packages/54/24/b4293291fa1dd830f353d2cb163295742fa87f179fcc8a20a306a81978b7/SecretStorage-3.3.3-py3-none-any.whl
   name: secretstorage
   version: 3.3.3
@@ -9677,15 +9994,15 @@ packages:
   - id
   - keyring>=15.1 ; extra == 'keyring'
   requires_python: '>=3.8'
-- pypi: https://files.pythonhosted.org/packages/c5/3f/b0e8db149896005adc938a1e7f371d6d7e9eca4053a29b108978ed15e0c2/types_python_dateutil-2.9.0.20250516-py3-none-any.whl
+- pypi: https://files.pythonhosted.org/packages/72/52/43e70a8e57fefb172c22a21000b03ebcc15e47e97f5cb8495b9c2832efb4/types_python_dateutil-2.9.0.20250708-py3-none-any.whl
   name: types-python-dateutil
-  version: 2.9.0.20250516
-  sha256: 2b2b3f57f9c6a61fba26a9c0ffb9ea5681c9b83e69cd897c6b5f668d9c0cab93
+  version: 2.9.0.20250708
+  sha256: 4d6d0cc1cc4d24a2dc3816024e502564094497b713f7befda4d5bc7a8e3fd21f
   requires_python: '>=3.9'
-- pypi: https://files.pythonhosted.org/packages/69/e0/552843e0d356fbb5256d21449fa957fa4eff3bbc135a74a691ee70c7c5da/typing_extensions-4.14.0-py3-none-any.whl
+- pypi: https://files.pythonhosted.org/packages/b5/00/d631e67a838026495268c2f6884f3711a15a9a2a96cd244fdaea53b823fb/typing_extensions-4.14.1-py3-none-any.whl
   name: typing-extensions
-  version: 4.14.0
-  sha256: a1514509136dd0b477638fc68d6a91497af5076466ad0fa6c338e44e359944af
+  version: 4.14.1
+  sha256: d1e1e3b58374dc93031d6eda2420a48ea44a36c2b4766a4fdeb3710755731d76
   requires_python: '>=3.9'
 - pypi: https://files.pythonhosted.org/packages/5c/23/c7abc0ca0a1526a0774eca151daeb8de62ec457e77262b66b359c3c7679e/tzdata-2025.2-py2.py3-none-any.whl
   name: tzdata
@@ -9734,6 +10051,19 @@ packages:
   - flake8-use-fstring ; extra == 'dev'
   - pep8-naming ; extra == 'dev'
   requires_python: '>=3.7'
+- pypi: https://files.pythonhosted.org/packages/bc/d9/5ec15501b675f7bc07c5d16aa70d8d778b12375686b6efd47656efdc67cd/url_normalize-2.2.1-py3-none-any.whl
+  name: url-normalize
+  version: 2.2.1
+  sha256: 3deb687587dc91f7b25c9ae5162ffc0f057ae85d22b1e15cf5698311247f567b
+  requires_dist:
+  - idna>=3.3
+  - mypy ; extra == 'dev'
+  - pre-commit ; extra == 'dev'
+  - pytest-cov ; extra == 'dev'
+  - pytest-socket ; extra == 'dev'
+  - pytest ; extra == 'dev'
+  - ruff ; extra == 'dev'
+  requires_python: '>=3.8'
 - pypi: https://files.pythonhosted.org/packages/a7/c2/fe1e52489ae3122415c51f387e221dd0773709bad6c6cdaa599e8a2c5185/urllib3-2.5.0-py3-none-any.whl
   name: urllib3
   version: 2.5.0
@@ -9813,6 +10143,19 @@ packages:
   name: webencodings
   version: 0.5.1
   sha256: a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78
+- pypi: https://files.pythonhosted.org/packages/50/bd/c336448be43d40be28e71f2e0f3caf7ccb28e2755c58f4c02c065bfe3e8e/WebOb-1.8.9-py2.py3-none-any.whl
+  name: webob
+  version: 1.8.9
+  sha256: 45e34c58ed0c7e2ecd238ffd34432487ff13d9ad459ddfd77895e67abba7c1f9
+  requires_dist:
+  - legacy-cgi>=2.6 ; python_full_version >= '3.13'
+  - sphinx>=1.7.5 ; extra == 'docs'
+  - pylons-sphinx-themes ; extra == 'docs'
+  - pytest>=3.1.0 ; extra == 'testing'
+  - coverage ; extra == 'testing'
+  - pytest-cov ; extra == 'testing'
+  - pytest-xdist ; extra == 'testing'
+  requires_python: '>=2.7,!=3.0.*,!=3.1.*,!=3.2.*'
 - pypi: https://files.pythonhosted.org/packages/5a/84/44687a29792a70e111c5c477230a72c4b957d88d16141199bf9acb7537a3/websocket_client-1.8.0-py3-none-any.whl
   name: websocket-client
   version: 1.8.0
@@ -9830,32 +10173,32 @@ packages:
   version: 4.0.14
   sha256: 4875a9eaf72fbf5079dc372a51a9f268fc38d46f767cbf85c43a36da5cb9b575
   requires_python: '>=3.7'
-- pypi: https://files.pythonhosted.org/packages/82/8a/6b50c1dd2260d407c1a499d47cf829f59f07007e0dcebafdabb24d1d26a5/xarray-2025.6.1-py3-none-any.whl
+- pypi: https://files.pythonhosted.org/packages/b2/ea/9554e5fb78eda4dbc9e9ccaf23034166fe3e9ea9af82ea6204b9578434bc/xarray-2025.7.1-py3-none-any.whl
   name: xarray
-  version: 2025.6.1
-  sha256: 8b988b47f67a383bdc3b04c5db475cd165e580134c1f1943d52aee4a9c97651b
+  version: 2025.7.1
+  sha256: e8647b659e53bd350d7c5a91c34dd4122ad6a3ca0bc41399d424a7c0273c7635
   requires_dist:
-  - numpy>=1.24
-  - packaging>=23.2
-  - pandas>=2.1
-  - scipy ; extra == 'accel'
+  - numpy>=1.26
+  - packaging>=24.1
+  - pandas>=2.2
+  - scipy>=1.13 ; extra == 'accel'
   - bottleneck ; extra == 'accel'
-  - numbagg ; extra == 'accel'
-  - numba>=0.54 ; extra == 'accel'
-  - flox ; extra == 'accel'
+  - numbagg>=0.8 ; extra == 'accel'
+  - numba>=0.59 ; extra == 'accel'
+  - flox>=0.9 ; extra == 'accel'
   - opt-einsum ; extra == 'accel'
   - xarray[accel,etc,io,parallel,viz] ; extra == 'complete'
-  - netcdf4 ; extra == 'io'
+  - netcdf4>=1.6.0 ; extra == 'io'
   - h5netcdf ; extra == 'io'
-  - scipy ; extra == 'io'
-  - pydap ; python_full_version < '3.10' and extra == 'io'
-  - zarr ; extra == 'io'
+  - pydap ; extra == 'io'
+  - scipy>=1.13 ; extra == 'io'
+  - zarr>=2.18 ; extra == 'io'
   - fsspec ; extra == 'io'
   - cftime ; extra == 'io'
   - pooch ; extra == 'io'
-  - sparse ; extra == 'etc'
+  - sparse>=0.15 ; extra == 'etc'
   - dask[complete] ; extra == 'parallel'
-  - cartopy ; extra == 'viz'
+  - cartopy>=0.23 ; extra == 'viz'
   - matplotlib ; extra == 'viz'
   - nc-time-axis ; extra == 'viz'
   - seaborn ; extra == 'viz'
@@ -9875,8 +10218,8 @@ packages:
   - types-python-dateutil ; extra == 'types'
   - types-pytz ; extra == 'types'
   - types-setuptools ; extra == 'types'
-  requires_python: '>=3.10'
-- pypi: git+https://github.com/modflowpy/xattree.git#ad879c2dabb34e32d256d0f3d006678a654fb057
+  requires_python: '>=3.11'
+- pypi: git+https://github.com/modflowpy/xattree.git#81a635a89331c624d915b6bccdb8de15a8e84590
   name: xattree
   version: 0.1.0.dev0
   requires_dist:
@@ -9922,10 +10265,10 @@ packages:
   version: 2025.4.0
   sha256: 8d4db9a59213ccb4ce1cf70210584f30b10795bff47627cdfb862b39ff6e10c9
   requires_python: '>=3.8'
-- pypi: https://files.pythonhosted.org/packages/00/3b/e20bdf84088c11f2c396d034506cbffadd53e024111c1aa4585c2aba1523/zarr-3.0.8-py3-none-any.whl
+- pypi: https://files.pythonhosted.org/packages/45/57/3329346940f78de49047ddcb03fdbca9e16450c3a942688bf24201a322e5/zarr-3.0.10-py3-none-any.whl
   name: zarr
-  version: 3.0.8
-  sha256: 7f81e7aec086437d98882aa432209107114bd7f3a9f4958b2af9c6b5928a70a7
+  version: 3.0.10
+  sha256: 110724c045fbe4ff5509a8a2a6b6098cb244a6af43da85eaeecef9821473163f
   requires_dist:
   - donfig>=0.8
   - numcodecs[crc32c]>=0.14
@@ -9960,10 +10303,11 @@ packages:
   - coverage ; extra == 'test'
   - hypothesis ; extra == 'test'
   - mypy ; extra == 'test'
-  - pytest ; extra == 'test'
   - pytest-accept ; extra == 'test'
   - pytest-asyncio ; extra == 'test'
   - pytest-cov ; extra == 'test'
+  - pytest-xdist ; extra == 'test'
+  - pytest<8.4 ; extra == 'test'
   - rich ; extra == 'test'
   requires_python: '>=3.11'
 - pypi: https://files.pythonhosted.org/packages/80/ab/11a76c1e2126084fde2639514f24e6111b789b0bfa4fc6264a8975c7e1f1/zict-3.0.0-py2.py3-none-any.whl
diff --git a/test/test_codec.py b/test/test_codec.py
index dfa986da..4d94a58a 100644
--- a/test/test_codec.py
+++ b/test/test_codec.py
@@ -1,4 +1,34 @@
+import numpy as np
+import xarray as xr
+
 from flopy4.mf6.codec import dumps
+from flopy4.mf6.converter import COMPONENT_CONVERTER
+
+
+def test_list_template_rendering():
+    """Test that list blocks render correctly with sparse arrays."""
+
+    nnodes = 9
+    data = np.full((1, nnodes), 1e30)
+
+    data[0, 4] = -500.0
+    data[0, 8] = -250.0
+
+    wel_data = xr.DataArray(
+        data, dims=["nper", "nnodes"], coords={"node": ("nnodes", range(nnodes))}
+    )
+
+    test_data = {"period": {"q": wel_data}}
+
+    result = dumps(test_data)
+    print("List template result:")
+    print(result)
+
+    assert "BEGIN PERIOD" in result
+    assert "END PERIOD" in result
+    assert "5 -500.0" in result  # Node 5 (1-based) with -500.0
+    assert "9 -250.0" in result  # Node 9 (1-based) with -250.0
+    assert "1e+30" not in result
 
 
 def test_dumps_ic():
@@ -12,7 +42,7 @@ def test_dumps_ic():
         export_array_netcdf=True,
     )
 
-    result = dumps(ic)
+    result = dumps(COMPONENT_CONVERTER.unstructure(ic))
     print(result)
     assert result
 
@@ -28,7 +58,7 @@ def test_dumps_oc():
         dims={"nper": 1},
     )
 
-    result = dumps(oc)
+    result = dumps(COMPONENT_CONVERTER.unstructure(oc))
     print(result)
     assert result
 
@@ -46,7 +76,7 @@ def test_dumps_dis():
         length_units="feet",
     )
 
-    result = dumps(dis)
+    result = dumps(COMPONENT_CONVERTER.unstructure(dis))
     print(result)
     assert result
 
@@ -59,7 +89,7 @@ def test_dumps_tdis():
     tdis = Tdis.from_time(ModelTime(perlen=[1.0, 2.0], nstp=[1, 2]))
     tdis.time_units = "days"
 
-    result = dumps(tdis)
+    result = dumps(COMPONENT_CONVERTER.unstructure(tdis))
     print(result)
     assert result
 
@@ -82,6 +112,172 @@ def test_dumps_chd():
         dims={"nper": 1},
     )
 
-    result = dumps(chd)
-    print(result)
+    result = dumps(COMPONENT_CONVERTER.unstructure(chd))
+
+    assert "BEGIN PERIOD 1" in result
+    assert "END PERIOD 1" in result
+
+    period_section = result.split("BEGIN PERIOD 1")[1].split("END PERIOD 1")[0].strip()
+    lines = [line.strip() for line in period_section.split("\n") if line.strip()]
+
+    assert len(lines) == 2
+    assert "1 10.0" in result  # First CHD cell - node 1
+    assert "100 20.0" in result  # Second CHD cell - node 100
     assert result
+
+
+def test_dumps_wel_sparse():
+    from flopy4.mf6.gwf import Dis, Gwf, Wel
+
+    dis = Dis(nlay=3, nrow=10, ncol=10)
+    gwf = Gwf(dis=dis)
+    wel = Wel(
+        parent=gwf,
+        q={
+            0: {
+                (0, 2, 3): -100.0,
+                (1, 5, 7): -50.0,
+                (2, 8, 1): 25.0,
+            }
+        },
+        print_input=True,
+        save_flows=True,
+        dims={"nper": 1},
+    )
+
+    result = dumps(COMPONENT_CONVERTER.unstructure(wel))
+    print("WEL sparse result:")
+    print(result)
+
+    assert "BEGIN PERIOD 1" in result
+    assert "END PERIOD 1" in result
+
+    period_section = result.split("BEGIN PERIOD 1")[1].split("END PERIOD 1")[0].strip()
+    lines = [line.strip() for line in period_section.split("\n") if line.strip()]
+
+    assert len(lines) == 3
+    result_lower = result.lower()
+    assert "-100" in result_lower or "100" in result_lower
+    assert "-50" in result_lower or "50" in result_lower
+    assert "25" in result_lower
+
+
+def test_dumps_drn_sparse_multiperiod():
+    from flopy4.mf6.gwf import Dis, Drn, Gwf
+
+    dis = Dis(nlay=2, nrow=5, ncol=5)
+    gwf = Gwf(dis=dis)
+    drn = Drn(
+        parent=gwf,
+        elev={
+            0: {
+                (0, 0, 4): 10.0,
+                (1, 4, 0): 8.0,
+            },
+            1: {
+                (0, 1, 1): 12.0,
+                (0, 2, 3): 9.0,
+                (1, 3, 2): 7.0,
+            },
+        },
+        cond={
+            0: {
+                (0, 0, 4): 1.0,
+                (1, 4, 0): 2.0,
+            },
+            1: {
+                (0, 1, 1): 1.5,
+                (0, 2, 3): 0.8,
+                (1, 3, 2): 2.2,
+            },
+        },
+        print_flows=True,
+        dims={"nper": 2},
+    )
+
+    result = dumps(COMPONENT_CONVERTER.unstructure(drn))
+
+    assert "BEGIN PERIOD 1" in result
+    assert "END PERIOD 1" in result
+    assert "BEGIN PERIOD 2" in result
+    assert "END PERIOD 2" in result
+
+    period1_section = result.split("BEGIN PERIOD 1")[1].split("END PERIOD 1")[0].strip()
+    period2_section = result.split("BEGIN PERIOD 2")[1].split("END PERIOD 2")[0].strip()
+
+    period1_lines = [line.strip() for line in period1_section.split("\n") if line.strip()]
+    period2_lines = [line.strip() for line in period2_section.split("\n") if line.strip()]
+
+    assert len(period1_lines) == 2
+    assert len(period2_lines) == 3
+
+    assert "5 10.0 1.0" in result
+    assert "46 8.0 2.0" in result
+    assert "7 12.0 1.5" in result
+    assert "14 9.0 0.8" in result
+    assert "43 7.0 2.2" in result
+
+
+def test_dumps_chd_sparse_realistic():
+    from flopy4.mf6.gwf import Chd, Dis, Gwf
+
+    dis = Dis(nlay=1, nrow=20, ncol=30)
+    gwf = Gwf(dis=dis)
+
+    boundaries = {}
+    for row in range(5, 15):
+        boundaries[(0, row, 0)] = 100.0
+    for row in range(8, 12):
+        boundaries[(0, row, 29)] = 95.0
+    for col in range(10, 20):
+        boundaries[(0, 19, col)] = 98.0
+
+    chd = Chd(parent=gwf, head={0: boundaries}, print_input=True, save_flows=True, dims={"nper": 1})
+
+    result = dumps(COMPONENT_CONVERTER.unstructure(chd))
+    print("CHD realistic sparse result:")
+    print(result)
+
+    period_section = result.split("BEGIN PERIOD 1")[1].split("END PERIOD 1")[0].strip()
+    lines = [line.strip() for line in period_section.split("\n") if line.strip()]
+
+    assert len(lines) == 24
+    assert "100" in result
+    assert "95" in result
+    assert "98" in result
+
+
+def test_dumps_wel_with_auxiliary():
+    from flopy4.mf6.gwf import Dis, Gwf, Wel
+
+    dis = Dis(nlay=2, nrow=5, ncol=5)
+    gwf = Gwf(dis=dis)
+    wel = Wel(
+        parent=gwf,
+        auxiliary=["well_id"],
+        q={
+            0: {
+                (0, 1, 2): -75.0,
+                (1, 3, 4): -25.0,
+            }
+        },
+        aux={
+            0: {
+                (0, 1, 2): 1.0,
+                (1, 3, 4): 2.0,
+            }
+        },
+        print_input=True,
+        dims={"nper": 1},
+    )
+
+    result = dumps(COMPONENT_CONVERTER.unstructure(wel))
+    print("WEL with auxiliary sparse result:")
+    print(result)
+
+    period_section = result.split("BEGIN PERIOD 1")[1].split("END PERIOD 1")[0].strip()
+    lines = [line.strip() for line in period_section.split("\n") if line.strip()]
+
+    assert len(lines) == 2
+    assert "-75" in result or "75" in result
+    assert "-25" in result or "25" in result
diff --git a/test/test_filters.py b/test/test_filters.py
new file mode 100644
index 00000000..eaaa3cc3
--- /dev/null
+++ b/test/test_filters.py
@@ -0,0 +1,97 @@
+"""Tests for flopy4.mf6.filters module."""
+
+import numpy as np
+import xarray as xr
+
+from flopy4.mf6.filters import array2list, keystring2list
+
+
+def test_array2list():
+    data = np.zeros((3, 4, 5))
+    data[0, 1, 2] = 100.0
+    data[1, 3, 0] = -50.0
+    data[2, 0, 4] = 25.5
+
+    arr = xr.DataArray(data, dims=["layer", "row", "col"])
+    sparse_data = list(array2list(arr))
+    assert len(sparse_data) == 3
+    expected = {(1, 2, 3, 100.0), (2, 4, 1, -50.0), (3, 1, 5, 25.5)}
+    assert set(sparse_data) == expected
+
+
+def test_array2list_with_zeros():
+    data = np.array([[0.0, 1.0], [2.0, 0.0]])
+    arr = xr.DataArray(data, dims=["row", "col"])
+
+    sparse_no_zeros = list(array2list(arr))
+    assert len(sparse_no_zeros) == 2
+    assert set(sparse_no_zeros) == {(1, 2, 1.0), (2, 1, 2.0)}
+
+    sparse_with_zeros = list(array2list(arr, include_zeros=True))
+    assert len(sparse_with_zeros) == 4
+    expected_with_zeros = {(1, 1, 0.0), (1, 2, 1.0), (2, 1, 2.0), (2, 2, 0.0)}
+    assert set(sparse_with_zeros) == expected_with_zeros
+
+
+def test_array2list_nan_handling():
+    data = np.array([[1.0, np.nan], [0.0, 2.0]])
+    arr = xr.DataArray(data, dims=["row", "col"])
+    sparse_data = list(array2list(arr, include_zeros=True))
+    expected = {(1, 1, 1.0), (2, 1, 0.0), (2, 2, 2.0)}
+    assert set(sparse_data) == expected
+
+
+def test_keystring2list():
+    data = np.full((2, 3), None, dtype=object)
+    data[0, 1] = {"rate": -100.0, "aux1": 1, "aux2": 2}
+    data[1, 2] = {"rate": -200.0, "aux1": 3, "aux2": 4}
+
+    arr = xr.DataArray(data, dims=["row", "col"])
+    sparse_data = list(keystring2list(arr))
+    assert len(sparse_data) == 2
+
+    rows = {entry[:2] for entry in sparse_data}
+    assert rows == {(1, 2), (2, 3)}
+
+    for entry in sparse_data:
+        if entry[:2] == (1, 2):
+            assert entry[2:] == (-100.0, 1, 2)
+        elif entry[:2] == (2, 3):
+            assert entry[2:] == (-200.0, 3, 4)
+
+
+def test_keystring2list_with_namedtuple():
+    from collections import namedtuple
+
+    WelData = namedtuple("WelData", ["rate", "aux1", "aux2"])
+
+    data = np.full((2, 2), None, dtype=object)
+    data[0, 0] = WelData(-100.0, 1, 2)
+    data[1, 1] = WelData(-200.0, 3, 4)
+
+    arr = xr.DataArray(data, dims=["row", "col"])
+    sparse_data = list(keystring2list(arr))
+
+    assert len(sparse_data) == 2
+    expected = {(1, 1, -100.0, 1, 2), (2, 2, -200.0, 3, 4)}
+    assert set(sparse_data) == expected
+
+
+def test_array2list_1d():
+    """Test sparse iteration with 1D arrays."""
+    data = np.array([0, 5, 0, 10])
+    arr = xr.DataArray(data, dims=["index"])
+
+    sparse_data = list(array2list(arr))
+    expected = {(2, 5), (4, 10)}  # 1-based indexing
+    assert set(sparse_data) == expected
+
+
+def test_array2list_2d():
+    """Test sparse iteration with 2D arrays."""
+    data = np.array([[1, 0], [0, 2]])
+    arr = xr.DataArray(data, dims=["row", "col"])
+
+    sparse_data = list(array2list(arr))
+    expected = {(1, 1, 1), (2, 2, 2)}  # 1-based indexing
+    assert set(sparse_data) == expected
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index e0c3f94f..e8b65a85 100644
--- a/uv.lock
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 [package.optional-dependencies]
@@ -3607,7 +3607,7 @@ parallel = [
 [[package]]
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-source = { git = "https://github.com/modflowpy/xattree.git#01e27195b5139d071c19a641a2a8e145e3b21ba1" }
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 dependencies = [
     { name = "attrs" },
     { name = "cattrs" },