geoglows · rhuber6 · Jan 30, 2025 · Jan 31, 2025 · Feb 4, 2025 · Feb 4, 2025
diff --git a/docs/GIS-data.md b/docs/GIS-data.md
@@ -66,8 +66,4 @@ There were some slight modifications made to the TDX-Hydro dataset when creating
 - Streams that had no length and no upstream/downstream segments were removed along with their associated catchments.
 - Streams with no length but with upstream and downstream segments were removed with their associated catchments, and the upstream and/or downstream segments were modified to preserve the connectivity of the network.
 - For many of the regions, headwater streams were dissolved with the downstream segments.
-- Small watersheds that did not represent real flowing streams were often dropped.
-
-## Learn More  
-
-For some more detailed examples of getting and using the GIS data, please look at [GIS Data.pdf](https://drive.google.com/file/d/10NrEV3GAQlI5OypeWn6pCAInDiGBFHLX/view?usp=sharing)
+- Small watersheds that did not represent real flowing streams were often dropped.
diff --git a/docs/api-window-pop-up.png b/docs/api-window-pop-up.png
diff --git a/docs/calendar-forecast.png b/docs/calendar-forecast.png
diff --git a/docs/data-service.md b/docs/data-service.md
@@ -7,12 +7,36 @@ For more information, visit the [GEOGLOWS API Documentation](https://geoglows.ec
 ![image](api.png)
 ---
 
-## Using the API in Applications
+## Using the API
 
-The API can be used in applications requiring streamflow data and can be integrated directly into Python workflows. 
+In order to use the API, most functions require you to know your river ID number. You can find more information about finding your river number here: [Finding River Numbers](https://data.geoglows.org/tutorials/finding-river-numbers). You can download the GIS data by VPU through the data catalog or select a stream on the web application and get a river number that way.
+
+### Using the API Website
+
+To use the API website, follow these steps:
+
+**Step 1:** Click the blue **“Get”** button next to the command you are interested in. This opens a window where you can enter your parameters.  
+
+![API Window Pop-up](api-window-pop-up.png)
+
+**Step 2:** Before entering any numbers, click **“Try it out”** to enable input fields. This allows you to enter numbers and select response formats.
+
+**Step 3:** Enter the required information:  
+- A **9-digit river ID number** (also known as a COMID or Link Number) in the `river_id` field. This is required.  
+- Choose either `csv` or `json` from the dropdown menu under `format`. The default selection is `csv`.  
+- For **forecast data queries**, enter a date in `YYYYMMDD` format. If left blank, it will return the most recent forecast.  
 
-The following resources provide guidance:  
-- [Programmatic_Access Colab.ipynb](https://colab.research.google.com/drive/19PiUTU2noCvNGr6r-1i9cv0YMduTxATs?usp=sharing): A walkthrough example of how to use the GEOGLOWS API.  
-- [Programmatic Access 2.0.pdf](https://drive.google.com/file/d/195LGTwbi4-Ho4JW15qZT-PDgUn10qit1/view?usp=sharing): A presentation with additional details.
+![Execute Button](execute-button.png)
 
-These resources demonstrate how to leverage the API effectively for custom applications and analyses.
+**Step 4:** Click the **blue “Execute”** button at the bottom of the screen. The system will process your request and load for a few seconds. Once finished, you will receive a response code along with an option to download the file.  
+
+![API Response](response-api.png)
+
+### Accessing the API Using Python
+
+One of the easiest ways to access the API is through Python. There is a **GeoGLOWS Python package** (documented here: [GeoGLOWS API Documentation](https://geoglows.readthedocs.io/en/latest/api-documentation.html)) that contains commands for basic analysis and querying specific types of data.
+
+This Python notebook provides examples of using the API in Python, as well as utilizing the Python package: [Programmatic_Access Colab.ipynb](https://colab.research.google.com/drive/19PiUTU2noCvNGr6r-1i9cv0YMduTxATs?usp=sharing)
+
+
+The API can be used in applications requiring streamflow data and can be integrated directly into Python workflows. 
diff --git a/docs/execute-button.png b/docs/execute-button.png
diff --git a/docs/filtered-streams.png b/docs/filtered-streams.png
diff --git a/docs/forecast.md b/docs/forecast.md
@@ -12,11 +12,18 @@ The forecast has a **3-hour time step**, where each flow value represents the av
 ![image](img17.png)
 ---
 
+The streamflow forecast is updated daily using the 24-hour mean value from the ensemble members on the previous day as the initial condition.
+
+The ensemble members have a spatial resolution of 9 kilometers horizontally.
+
+These meteorological forecasts are converted into runoff using the HTESSEL hydrological model. These results are then downscaled using an area-weighted gridding to vector methodology and subsequently routed through the drainage network.
+
+
 ## Ensemble Probabilities and Interpretation
 
 Each ensemble member has an equal probability of occurring. Therefore, forecasts are best understood by looking at summaries of the ensembles rather than individual members.
 
-Forecast plots are designed to help users interpret the range of possible outcomes and uncertainties. The most commonly used forecast plot includes the median, the 20th percentile, and the 80th percentile. These represent 60% of the probability distribution within the ensemble members and provide insight into the potential variability of future streamflows. This approach allows users to see the range of probable scenerios for their streams.
+Forecast plots are designed to help users interpret the range of possible outcomes and uncertainties. The most commonly used forecast plot includes the median, the 20th percentile, and the 80th percentile. These represent 60% of the probability distribution within the ensemble members and provide insight into the potential variability of future streamflows. This approach allows users to see the range of probable scenarios for their streams.
 
 ---
 
@@ -34,5 +41,4 @@ The following graph shows an example of a forecast plot:
 1. The **black line** represents the best estimate of future river flow.  
 2. The **blue shaded region** represents the uncertainty in the prediction. The narrower the blue region, the more confident the model is. The true flow is more likely than not to fall within the blue shaded area.  
 
-For more details, refer to the document: [Forecast_Data.pdf](https://drive.google.com/file/d/1_dDtF3F74Un8PKVkZZdslDjp_MP64-dX/view?usp=sharing).
 
diff --git a/docs/loaded-graph.png b/docs/loaded-graph.png
diff --git a/docs/loaded-graph.png:Zone.Identifier b/docs/loaded-graph.png:Zone.Identifier
@@ -0,0 +1,4 @@
+[ZoneTransfer]
+ZoneId=3
+ReferrerUrl=https://keep.google.com/
+HostUrl=https://lh3.googleusercontent.com/keep-bbsk/AFgXFlKPfOluFsbyU5p3_gkQCor7yMFzv0ln5QMERe2zhL9L0C_1qmCNHMWpKrr-PHFjgyIIWfb8jUejFHL6tM93MYWeUUp8gwE4wOdEbZlvmOLb3-IAbk31pw=s512
diff --git a/docs/response-api.png b/docs/response-api.png
diff --git a/docs/retrospective-variable.png b/docs/retrospective-variable.png
diff --git a/docs/retrospective.md b/docs/retrospective.md
@@ -6,9 +6,14 @@ The retrospective simulation from the River Forecasting System provides a determ
 
 ---
 
-The dataset is deterministic, which means that there is no ensemble, but rather just one best guess of the average flows over the time period. The flow values represent the average flow during the day listed in UTC time. All flow values are in cubic meters per second.
+The dataset is deterministic, which means that there is no ensemble, but rather just one best guess of the average flows over the time period. The start of the time period is given in UTC time. The value given represents the average flow starting at that time until the next timestep. All flow values are in cubic meters per second.  
+
+The inputs to the hydrology model lag from real time by 5 days. Once a week, on Sunday at midnight UTC, the dataset is updated. On that Sunday, GEOGLOWS data will cover up until 5 days ago. On Saturday night, the lag will have accumulated to 12 days.  
+
+The retrospective data is available in several different time increments. The data was calculated at an hourly temporal resolution. Then the hourly timesteps were averaged to provide a daily average, monthly average, and yearly average time series.   
+
+The monthly average data is available in two different formats. One is optimized to read the entire time series for a single river or group of rivers, which is anticipated to be the most common use case. Another is optimized to read a bunch of rivers at a given timestep. 
 
- The inputs to the hydrology model lag from real time by 5 days. Once a week, on Sunday at midnight UTC, the dataset is updated. On that Sunday, GEOGLOWS data will cover up until 5 days ago. On Saturday night, the lag will have accumulated to 12 days.
 
 ---
 
@@ -18,7 +23,9 @@ The runoff data is created by using the runoff data from the **ECMWF ERA5 reanal
 
 The inputs to the model are derived from reanalysis meteorology data, including satellite and gauge-based measurements, which are assimilated to reconstruct the best possible historical precipitation, evaporation, and other hydrological variables. No river gauge data are assimilated during the routing step, ensuring a uniform model-driven approach.
 
-For more details, refer to the document: [ERA5_time period_updates.pdf](https://drive.google.com/file/d/10P53NdkSTfsGsyc-PSE5nVMYAvMCU1Q-/view?usp=sharing).
+## Return Period Calculations
+
+The retrospective simulation is used to define return periods that establish warning levels for each simulated river segment. Streamflow values for return periods of 2, 5, 10, 25, 50 and 100 years are calculated for every stream reach in the model.
 
 
 
diff --git a/docs/web-app.md b/docs/web-app.md
@@ -24,5 +24,47 @@ This allows users to quickly identify rivers experiencing high flows.
 
 Users can download **plots** and **.csv files** for streams of interest.
 
+# Selecting Data
 
-For detailed instructions on how to use the HydroViewer, refer to the presentation: [GEOGLOWS HydroViewer Tutorial.pptx](https://docs.google.com/presentation/d/1-7BOPZjBse7gyzSRfFiBcQx3quHclUGJ/edit?usp=sharing&ouid=118056077920900718177&rtpof=true&sd=true).
+At the global level, only the largest streams are shown. More streams become visible as a user zooms in on the map and their area of interest. If you are not accurate enough in your click, a warning will show asking you to zoom in more and be more precise when clicking the river segment.
+
+Once you have selected the streams, a pop-up window will appear with the river name, ID, and two graphs: the forecasted and retrospective streamflow data.
+
+![loaded-datat](loaded-graph.png)
+
+Plots and `.csv` files can be downloaded for streams of interest by selecting the camera icon in the corner of the plot.
+
+## Previous Forecast Data
+
+By default, when you click on a stream, the 15-day forecast from the current day will be displayed. However, if you would like, you can see a forecast from a previous day by choosing a date from the date dropdown menu.
+
+![calendar](calendar-forecast.png)
+
+## Retrospective Data
+
+By default, you will view 10 years of retrospective data, but this can be adjusted using the grey sliders at the bottom. The entire retrospective dataset, dating back to 1940, can be accessed this way.  
+
+![Retrospective Data](retrospective-variable.png)
+
+## Entering a River ID
+
+If a user already knows the river ID for their stream of interest, they can directly enter the river ID into the application to view the data.
+
+1. Get the chart pop-up window open either by selecting the chart icon in the upper right corner or by it being open from a previous river selection.
+2. Click on **“Enter River ID”** in the top middle of the pop-up window.
+3. Type in any river ID (for example, this reach ID is for the Magdalena River in Colombia: `610363879`) and click **“OK”**.
+4. The forecast and retrospective data will reload and will be displayed for the new river in the pop-up window.
+
+## Filtering Data
+
+Data can also be filtered:
+
+- Click on the **filter** button on the left-hand side to bring up the filtering options.
+- There, you will find options to filter based on:
+  - River country
+  - VPU number
+  - River outlet country
+
+This will only show rivers that meet these criteria on the map.
+
+![filter](filtered-streams.png)
diff --git a/mkdocs.yml b/mkdocs.yml
@@ -24,7 +24,7 @@ theme:
 nav:
   - Home: index.md
   - Overview: overview.md
-  - River Forecasting System:
+  - River Forecast System:
       - Part 1 Available Data:
           - GIS Data: GIS-data.md
           - Retrospective Data: retrospective.md