diff --git a/docs/dmg/code.md b/docs/dmg/code.md
index 104870c..a38e7c5 100644
--- a/docs/dmg/code.md
+++ b/docs/dmg/code.md
@@ -9,6 +9,10 @@ For [tutorials](https://github.com/mhpi/generic_deltaModel/tree/master/example)
 - [HydroDL 2.0](https://github.com/mhpi/hydroDL2)
 - [CAMELS Date ](https://mhpi-spatial.s3.us-east-2.amazonaws.com/mhpi-release/camels/camels_data.zip)
 
+We include an optional GUI for constructing/editing 𝛿MG YAML configuration files with a user-friendly interface (instructions below):
+
+- [GUI Config builder (Zip)](https://mhpi-spatial.s3.us-east-2.amazonaws.com/mhpi-release/config_builder_gui/Config+Builder+GUI.zip)
+- ([Source Code](https://github.com/mhpi/GUI-Config-builder))
 
 <br>
 
@@ -102,3 +106,28 @@ For a functioning 𝛿MG + HydroDL2 setup...
 ### 4. Build Models
 
 - That's it. You should now be able to run the tutorials, train/test MHPI benchmarks, and build your own differentiable models.
+
+<br>
+
+# Using the GUI
+
+
+## Setup
+
+To use the HydroDL Config Builder from the GitHub source code, you have two options:
+
+- Run Directly: Execute the tool using main.py.
+- Build a Windows Executable: Use build.py to generate a standalone Windows executable.
+  
+Alternatively, you can skip the build process by downloading the precompiled executable [here](https://mhpi-spatial.s3.us-east-2.amazonaws.com/mhpi-release/config_builder_gui/Config+Builder+GUI.zip). Once downloaded, simply unzip and run the executable  `HydroDL Config Builder.exe` on Windows to start the builder and begin creating/editing your configuration files. 
+
+Two files can potentiallly be created by this process. One contains model and experiment settings, while the other is a data config that specifies dataset specific information like data save paths.
+
+
+## Where do the Config Files go?
+
+Once you have created and saved your YAML config files, they can go one of two places depending on your intentions. 
+- Tutorials: `example/conf`, with data config in `example/conf/observations`.
+- Development with 𝛿MG: `deltaModel/conf` with data config in `deltaModel/conf/observations`
+
+Note. Before running 𝛿MG, ensure that 'observations' in the main config matches the name of the data config you want to use.
diff --git a/docs/dmg/detail.md b/docs/dmg/detail.md
index 93f301d..8ea6485 100644
--- a/docs/dmg/detail.md
+++ b/docs/dmg/detail.md
@@ -13,7 +13,9 @@ For differentiable hydrology models used in MHPI research, 𝛿MG seamlessly int
 
 - **HydroDL2.0 ([`hydroDL2`](https://github.com/mhpi/hydroDL2))**: Home to MHPI's suite of physics-based hydrology models, and differentiable model augmentations (think variational data
       assimilation, model coupling, and additional physics-based hydrology tools).
-- **HydroData ([`hydro_data_dev`](https://github.com/mhpi/hydro_data_dev))**: Data extraction, processing, and management tools optimized for hydrology applications. [*In development*]
+- **HydroData ([`hydro_data_dev`](https://github.com/mhpi/hydro_data_dev))**: Data extraction, processing, and management tools optimized for geospatial datasets.
+- **Config GUI ([`GUI-Config-builder`](https://mhpi-spatial.s3.us-east-2.amazonaws.com/mhpi-release/config_builder_gui/Config+Builder+GUI.zip))([Source](https://github.com/mhpi/GUI-Config-builder))**: An intuitive, user-friendly tool designed to simplify the creation and editing of configuration files for model setup and development.
+- **Concurrent development activities**: We are working on these efforts connected to 𝛿MG: (i) numerical PDE solvers on torch; (ii) [adjoint](https://doi.org/10.5194/hess-28-3051-2024) sensitivity; (iii) extremely efficient and highly accurate surrogate models; (iv) downscaled and bias corrected climate data; (v) mysteriously powerful neural networks.
 
 <br>
 
@@ -81,7 +83,7 @@ According to this schema, we define these core classes, from bottom up:
 ### Quick Start: Building a Differentiable HBV (𝛿HBV) Model
 
 Here’s an example of how you can build a differentiable model, coupling a physics-based model with a neural network to intelligently learn model parameters. In this instance, we use an
-LSTM with the [HBV](https://en.wikipedia.org/wiki/HBV_hydrology_model) hydrology model.
+LSTM with the [HBV](https://en.wikipedia.org/wiki/HBV_hydrology_model) hydrology model. The [Config GUI](https://mhpi-spatial.s3.us-east-2.amazonaws.com/mhpi-release/config_builder_gui/Config+Builder+GUI.zip) can be used to create/edit additional config files for use with these examples. (See [here](https://github.com/mhpi/GUI-Config-builder/blob/main/README.md) for usage instructions.)
 ```python
 CONFIG_PATH = '../example/conf/config_dhbv1_1p.yaml'