geoglows · rhuber6 · Jan 30, 2025 · Jan 31, 2025 · Feb 4, 2025 · Feb 4, 2025
diff --git a/docs/accessing-data.md b/docs/accessing-data.md
diff --git a/docs/data-service.md b/docs/data-service.md
diff --git a/docs/index.md b/docs/index.md
@@ -1,30 +1,6 @@
 # Welcome to the GEOGLOWS Model Training Hub!
-![image](image3.png)
+![image](static/images/image3.png)
 
 [Watch this video to learn about GEOGLOWS!](https://youtu.be/v8FhgV4cBnI)
 
-![image](img10.png)
-
-
-## Navigating the Website
-
-The first page on this site gives a brief overview of GEOGLOWS and its history. After that, the bulk of the training section begins. This training is broken down into 3 main sections, each having different sub sections within them. We recommend you start with the first section (Available Data) before progressing to the second section (Accessing Data). The third section (Skills and Examples) is a more advanced section designed for people looking to complete specific tasks using the GEOGLOWS data who already have a good understanding of the first two sections. As you are learning about the data, there is also a website available with more information on how to download and use the GEOGLOWS data: https://data.geoglows.org/. This is a great resource once you have a basic understanding of the data. Here is a brief overview of what you can expect to learn: 
-
-1. **Available Data** - This section details the available datasets through GEOGLOWS. It is divided into 3 sections:  
-    - **a. GIS Data** - Learn about the hydrography data used in the GEOGLOWS model, including stream centerlines, catchment boundaries, and their unique identifiers, derived from high-resolution elevation products.  
-    - **b. Retrospective River Discharge** - Explore over 85 years of daily average streamflow data, derived from meteorological reanalysis and updated weekly, offering insights into historical river discharge.  
-    - **c. Forecast River Discharge** - Understand daily river flow forecasts with a 51-member ensemble providing detailed predictions at 3-hour intervals, including uncertainty ranges for better planning.  
-
-2. **Accessing Data** - This section explains how the previously described data can be accessed and downloaded using 4 different techniques. Each section will detail a different technique:  
-    - **a. A Data Catalog** - This section explains the data catalog available through AWS buckets.  
-    - **b. A Data Service** - This section describes how to use our REST API to access GEOGLOWS data.  
-    - **c. A Web Map** - This section explains the Esri Living Atlas map layer that can be loaded into any GIS software (ArcGIS or QGIS).  
-    - **d. A Web App** - This section introduces you to the HydroViewer, which is our web application that allows for easy visualization and download of data globally.  
-
-3. **Skills and Examples** - This section explains more advanced techniques that can be used when using the data for specific purposes.  
-    - **a. Accessing and Interpreting Data** - This section includes Google Colab notebooks that show you how to use the GEOGLOWS Python package to make and customize your streamflow plots.  
-    - **b. Bias Correction and SABER Overview** - This section gives a brief overview of bias correction and a technique called SABER that applies bias correction to other areas.  
-    - **c. Bias Correction for Forecast Data** - This section provides a notebook that goes through examples of bias-correcting the forecast data.  
-
-
-
+![image](static/images/img10.png)
diff --git a/docs/old_pages/overview.md b/docs/old_pages/overview.md
@@ -0,0 +1,149 @@
+# What is GEOGLOWS? 
+
+![image](../static/images/image3.png)
+
+## Overview
+The GEOGLOWS (Global Earth Observations Global Water Sustainability) 
+initiative is a collaborative effort aimed at improving global 
+water sustainability through advanced hydrological forecasting 
+and data analysis. Leveraging the power of Earth observations, 
+numerical weather predictions, and supercomputing, GEOGLOWS 
+provides actionable information on streamflow status and 
+outlook for every river worldwide. By making decades of 
+historical climatological flow data and future forecasts 
+easily accessible, GEOGLOWS supports informed decision-making
+in water resource management, disaster risk reduction, and 
+climate adaptation. This global service enables countries 
+and organizations to enhance their understanding of 
+water-related challenges and implement effective solutions, 
+ultimately contributing to a more sustainable and 
+resilient future.
+
+The presentation linked below provides deeper insights 
+into the scope and impact of GEOGLOWS.
+
+[GEOGLOWS V2 Overview](https://drive.google.com/file/d/1h9skkuJQ-LR301nXSHjYRNHnso07gtac/view?usp=sharing)
+
+## History
+The GEOGLOWS initiative, established under the framework
+of the Group on Earth Observations (GEO), has its roots 
+in a commitment to integrate Earth observation data to 
+enhance global water sustainability. The journey began 
+in 2014 at the GEO Plenary in Geneva, where the need for 
+coordinated water data management became evident. With 
+support from partners such as NASA, ECMWF, and regional 
+organizations, GEOGLOWS evolved from early efforts in the 
+Dominican Republic to a broader application of global 
+hydrological modeling. By leveraging advanced technologies, 
+including the ECMWF’s global weather forecasts and cutting-edge
+cloud computing, GEOGLOWS pioneered global streamflow 
+forecasting services. These services provide critical 
+information to support decision-making in water management,
+helping to mitigate the impacts of floods, droughts, and
+other water-related challenges. Over time, the initiative
+has expanded its reach, integrating local and regional 
+hydrological insights, and fostering collaborations 
+across continents to address the complex issues of 
+water scarcity and disaster preparedness.
+
+The presentation below offers a deeper insight into 
+the history and impact of GEOGLOWS.
+
+[GEOGLOWS History](https://drive.google.com/file/d/1dICEwFCFEIWnYgVAUNlrqsUMj487yp4o/view?usp=sharing)
+
+## Model Formulation
+The GEOGLOWS model leverages the Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (HTESSEL) alongside the ECMWF Integrated Forecast System (IFS) to conduct detailed calculations of water and energy balances within grid cells. HTESSEL simulates how land surfaces respond to atmospheric conditions, estimating critical variables such as surface and sub-surface runoff for both operational ensemble forecasts and retrospective simulations. The model employs varying spatial resolutions for its runoff files, including approximately 25 km for historical ERA-5 data, 16 km for low-resolution ensemble members, and 8 km for high-resolution forecasts. By intersecting grid lines with specific basins and applying runoff depth values, the model calculates water volumes over different time periods, which are then routed through the stream network using the Muskingum method with the RAPID algorithm. This approach provides valuable discharge data for hydrological analysis and decision-making.
+
+The presentation below offers a deeper insight into the model formulation of the GEOGLOWS Model.
+
+[Model Formulation](https://drive.google.com/file/d/1thabA0RBfSVYAIcKkgMOBFSZwhtmxvv2/view?usp=sharing)
+
+## Understanding GEOGLOWS Data
+[Understanding GEOGLOWS Data Presentation](https://drive.google.com/file/d/1-4MQ1ge4J9I5iQGHYlY3f0VR724S_eXp/view?usp=sharing)
+
+### Hydrofabric
+  * The GEOGLOWS ECMWF Streamflow Service leverages a Hydrologic 
+  Modeling as a Service (HMaaS) approach, centralizing 
+  cyberinfrastructure, expertise, and state-of-the-art 
+  forecasting capabilities to provide reliable streamflow 
+  data. Instead of requiring local agencies to manage and 
+  compute vast amounts of data independently, GEOGLOWS 
+  streamlines the process by using ensemble meteorological 
+  forecasts from ECMWF, processed through the HTESSEL 
+  land surface model. This generates global runoff data, 
+  which is mapped to GEOGLOWS watersheds and routed through 
+  river networks using the RAPID model to produce 15-day 
+  forecasts. Additionally, the ERA-5 retrospective 
+  historical data spanning over 80 years is used to 
+  derive return periods, placing current forecasts 
+  in a meaningful historical context. These streamflow 
+  forecasts are accessible via web mapping services and APIs, 
+  facilitating the development of customized applications 
+  tailored to address local water management challenges 
+  such as flooding, drought, and water security.
+
+### Map
+  * The GEOGLOWS ECMWF Streamflow Model can be easily explored 
+  using a mapping service developed in collaboration with 
+  Esri (see: [https://hydroviewer.geoglows.org/](https://hydroviewer.geoglows.org/)). 
+  The web map 
+  allows users to visualize current streamflow conditions worldwide,
+  with line thickness indicating discharge magnitude and 
+  line color showing if and when a river's discharge exceeds
+  the threshold for a specific return period. The app also 
+  lets you select a specific stream to view both the forecast 
+  and historical simulation data for that river.
+
+![image](../static/images/hydroviewer.png)
+
+### Retrospective Data
+  * The retrospective (or historical) simulation is a deterministic
+  model with a daily resolution, covering the period from 1940 to the 
+  present (over 80 years). This simulation helps calculate return 
+  periods for maximum discharge values using the Gumbel Distribution, 
+  providing essential context for interpreting hydrological forecasts.
+![image](../static/images/img9.png)
+
+### Forecasts
+  * The forecast simulation has a 15-day horizon and includes 
+  52 ensemble members: 51 low-resolution members and 1 high-resolution
+  member with a 10-day horizon. The time resolution is 3-hour 
+  intervals for low-resolution ensembles and 1-hour intervals for 
+  the high-resolution member. The preferred forecast plot features
+  the median, 20th percentile, and 80th percentile (Uncertainty Bounds),
+  representing 60% of the probability distribution within the 
+  ensemble members.
+![image](../static/images/img8.png)
+
+## Stories of Application
+
+GEOGLOWS has been instrumental in transforming water management 
+and disaster response across the globe. From helping predict 
+floods and droughts in Nepal, to improving transboundary flow 
+forecasts in Bangladesh, GEOGLOWS empowers local agencies with 
+the tools to make life-saving decisions. In the Dominican Republic, 
+GEOGLOWS enhances capacity for hydrological challenges, including 
+flood risk and irrigation management. The service has extended 
+early warning lead times in Malawi and has been crucial in 
+managing reservoir releases during hurricanes in Honduras. 
+These real-world applications demonstrate the global impact 
+of GEOGLOWS in addressing critical water-related challenges. 
+For more in-depth stories of how GEOGLOWS is making a difference 
+worldwide, visit [GEOGLOWS Stories](https://stories.geoglows.org/home).
+
+
+[Stories Presentation](https://drive.google.com/file/d/1-CbslVlrtOyobNkR18uusWVdjqp0OsuW/view?usp=sharing) 
+
+
+## Joining GEOGLOWS
+Are you interested in being part of the global GEOGLOWS community? 
+By joining, you can stay updated with the latest developments, collaborate 
+with experts, and access valuable resources related to hydrological forecasting 
+and water sustainability.
+
+To join the GEOGLOWS network, simply sign up for our Google Group:
+[Join the group!](https://groups.google.com/g/geoglows)
+
+By becoming a member, you will be part of a growing community 
+focused on advancing global water sustainability and streamflow forecasting.
+