Adapt R doc examples for get_combined_metadata, fix data_type values

Ported three additional examples from R's read_waterdata_combined_meta
that aren't redundant with the ones we already had:

- Groundwater well — surfaces water-level and aquifer columns that the
  surface-water example shows as nulls.
- State + county — common area-of-interest workflow.
- Two-step "inventory then fetch" chain — get_combined_metadata to find
  what's available in a HUC, then get_continuous to pull the actual
  observations at every site found.

Also corrected the data_type description: the live API returns
"Continuous values" and "Daily values" (with the word "values"), not
"Continuous" / "Daily" as the docstring previously claimed. Verified
against api.waterdata.usgs.gov.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: thodson-usgs

dataretrieval/waterdata/api.py

@@ -1042,7 +1042,8 @@ def get_combined_metadata(
         https://help.waterdata.usgs.gov/code/stat_cd_nm_query?stat_nm_cd=%25&fmt=html.
     data_type : string or list of strings, optional
         The type of data the time series represents, e.g.
-        ``"Continuous"``, ``"Daily"``, ``"Field measurements"``.
+        ``"Continuous values"``, ``"Daily values"``,
+        ``"Field measurements"``.
     computation_identifier : string or list of strings, optional
         Indicates whether the data from this time series represent a
         specific statistical computation.
@@ -1106,11 +1107,22 @@ def get_combined_metadata(
     --------
     .. code::
 
-        >>> # All time series and field measurements at a single site
+        >>> # All time series and field measurements at a single surface-water site
         >>> df, md = dataretrieval.waterdata.get_combined_metadata(
         ...     monitoring_location_id="USGS-05407000"
         ... )
 
+        >>> # Same, for a groundwater well — water-level and aquifer columns
+        >>> # are populated where the surface-water example has nulls
+        >>> df, md = dataretrieval.waterdata.get_combined_metadata(
+        ...     monitoring_location_id="USGS-375907091432201"
+        ... )
+
+        >>> # Every series in a single county, useful for area-of-interest workflows
+        >>> df, md = dataretrieval.waterdata.get_combined_metadata(
+        ...     state_name="Wisconsin", county_name="Dane County"
+        ... )
+
         >>> # Inventory across multiple HUCs, restricted to streams and springs
         >>> df, md = dataretrieval.waterdata.get_combined_metadata(
         ...     hydrologic_unit_code=["11010008", "11010009"],
@@ -1129,6 +1141,20 @@ def get_combined_metadata(
         ...     parameter_code="00060",
         ... )
 
+        >>> # Two-step "what's available?" → "fetch it" workflow:
+        >>> # 1. inventory the sites in two HUCs
+        >>> hucs, _ = dataretrieval.waterdata.get_combined_metadata(
+        ...     hydrologic_unit_code=["11010008", "11010009"],
+        ...     site_type="Stream",
+        ... )
+        >>> # 2. pull continuous discharge at every distinct site found
+        >>> sites = hucs["monitoring_location_id"].unique().tolist()
+        >>> df, md = dataretrieval.waterdata.get_continuous(
+        ...     monitoring_location_id=sites,
+        ...     parameter_code="00060",
+        ...     time="P1D",
+        ... )
+
     """
     service = "combined-metadata"
     output_id = "combined_meta_id"