diff --git a/examples/parflow/parflow_streamflow_point_scale_evaluation.ipynb b/examples/parflow/parflow_streamflow_point_scale_evaluation.ipynb
index bd7e8c2..0129456 100644
--- a/examples/parflow/parflow_streamflow_point_scale_evaluation.ipynb
+++ b/examples/parflow/parflow_streamflow_point_scale_evaluation.ipynb
@@ -4,8 +4,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Use HydroData to Retrieve Modeled and Observed Streamflow Data for a Watershed of Interest with ParFlow-CONUS Outputs vs USGS Observed Streamflow - Full Evaluation Workflow\n",
-    "Authors: Irene Garousi-Nejad (igarousi@cuahsi.org), Danielle Tijerina-Kreuzer (dtijerina@cuahsi.org)  \n",
+    "# ParFlow-CONUS1 Streamflow Evaluation  \n",
+    "#### _Use HydroData to Retrieve Modeled and Observed Streamflow Data for a Watershed of Interest with ParFlow-CONUS Outputs vs USGS Observed Streamflow - Full Evaluation Workflow_\n",
+    "Authors: Irene Garousi-Nejad (igarousi@cuahsi.org), Danielle Tijerina-Kreuzer (dtijerina@cuahsi.org), Amy Defnet (amydefnet@princeton.edu)  \n",
     "Last updated: March 2026"
    ]
   },
@@ -144,10 +145,10 @@
     "# ✏️ Specify HUC8 ID and Name for watershed of interest\n",
     "# (The Bayou De Chien HUC '08010201' has only 1 gage, which will run faster than the following Patoka-White HUC '051202')\n",
     "huc_code = '051202'\n",
-    "print(f'HUC-8 ID: {huc_code}')\n",
+    "print(f'HUC ID: {huc_code}')\n",
     "\n",
     "huc_name = 'Patoka-White'\n",
-    "print(f'HUC-8 name: {huc_name}')"
+    "print(f'HUC name: {huc_name}')"
    ]
   },
   {
@@ -165,7 +166,8 @@
    "source": [
     "Here we are providing the code needed to access streamflow observations data from the `hf_hydrodata` Python package for our HUC. If you'd like more detail on this code and the `hf_hydrodata` package, please see the notebook `examples/collect_observations/hydrodata_collect_observations.ipynb`.  \n",
     "\n",
-    "One of the dataframes we collect is the metadata_df. This is an important addition to the observations and it is recommended to always gather and save this for the observations you are using (particularly to support reproducibility within an open-science workflow). The saved file has useful attributes like site names, first and last date of available data, lat/lon, and the query URL.  \n",
+    "##### `metadata_df`\n",
+    "One of the dataframes we collect is the metadata dataframe. This is an important addition to the observations and it is recommended to always gather and save this for the observations you are using (particularly to support reproducibility within an open-science workflow). The saved file has useful attributes like site names, first and last date of available data, lat/lon, and the query URL.  \n",
     "\n",
     "Additionally, the metadata contains **ParFlow-CONUS1 and ParFlow-CONUS2 `i,j` indices, which indicate the exact model domain grid cell the observation aligns with**. This is a useful HydroData feature that removes the need for users to manually match station latitude/longitude coordinates to the appropriate model grid cell, as this spatial mapping is handled directly within HydroData. We will use these indices below to extract PF-CONUS1 modeled streamflow for each USGS gage in the section below. "
    ]
@@ -253,7 +255,8 @@
    "id": "6e2b894b",
    "metadata": {},
    "source": [
-    "##### Request USGS Streamflow data through the HydroData API at each of the gages located in the given HUC and time period using the `hf.get_point_data()` function. This is based on our `point_options` dictionary above. "
+    "##### Request USGS Streamflow data through the HydroData API \n",
+    "Pull streamflow for each of the USGS gages located in the given HUC and time period using the `hf.get_point_data()` function. This is based on our `point_options` dictionary above. "
    ]
   },
   {