Decision Calendar

A Python-based tool for creating Decision Calendar Plots for Hydrological Forecasting.

Overview

This repository contains tools to generate decision calendar visualizations for hydrological forecasting. Decision calendars help river forecast centers, water resource managers and stakeholders understand the timing of key decisions and their relationship to hydrological forecasts.

Repository Structure

• notebooks/ - Jupyter Notebook for creating decision calendars -config/ - Configuration files in YAML format
  • chena.yaml - Configuration for Chena River analysis
  • ross.yaml - Configuration for Ross River analysis
• scripts/ - Python scripts for generating decision calendars
  • decision_calendars.py - Main script for creating decision calendar plots
• data/ - Data files for streamflow and snow data
• output/ - Output files for decision calendars
• images/ - Images used in the decision calendars

Example Output

Getting Started

Prerequisites

• Python 3.x
• Required Python packages (recommend creating a virtual environment):

  pip install jupyter numpy pandas matplotlib pyyaml pycirclize

Usage

1. Clone the repository:

   git clone https://github.com/DaveCasson/decision_calendar.git
   cd decision_calendar

2. Launch Jupyter Notebook:

   jupyter notebook

3. Run the notebook notebooks/decision_calendars.ipynb to create decision calendars.

4. Configure your analysis (and colour schemes) by modifying the YAML files in the config/ directory to match your specific river system and decision points.

Updating the config files

The YAML configuration files in the config/ directory define the parameters for each river system's decision calendar. You can use the existing templates (chena.yaml and ross.yaml) as examples for creating configurations for other river systems.

Configuration Update Instructions

Colors and Styles

To update colors or styles:

1. Modify the hex codes under each relevant section.
   • Example: Change annual_activities.critical_period from "#896279" to "#123456".
2. Update styles (e.g., line types, markers) in the styles section:
   • linestyle: Options include "-" (solid), "--" (dashed), ":" (dotted), or "-." (dashdot).
   • linewidth: Adjust thickness (e.g., 3 for thicker lines).
   • marker: Update to other symbols like "o", "P", or "v".
   • markerfacecolor: Use colors defined in visualization or input custom hex codes.

Track Configurations

Track configurations define visualization details like colors, line types, and ranges.

• To update specific tracks:
  1. Change type (e.g., "line", "infill", "marker").
  2. Update color using the keys in the colors section or custom hex codes.
  3. Modify linestyle, linewidth, and alpha (transparency).
  4. Adjust r_start, r_end, and months to change placement and duration.
  • Example:

    hydrological_critical_period:
      type: "infill"
      color: "hydrological_forecasting.critical_period"
      alpha: 0.7
      r_start: 65
      r_end: 86
      months: ["Apr", "May", "Jun", "Jul", "Aug", "Sep"]

---

Legend Groups

Legend groups control the labels and descriptions for different elements.

• To update:
  1. Modify description for the group title.
  2. Adjust the color and linestyle for clarity.
  3. Add or remove elements as needed:
     • Use type options like "line", "marker", or "space".
     • Example:

       - type: line
         color: "hydrological_forecasting.forecast"
         linestyle: "dotted"
         linewidth: 3
         label: "HEFS Forecasts"

---

Plot Settings

To update plot configurations:

1. Modify figure size:
   • Example: Change figsize: [30, 16] to adjust width and height.
2. Update title text under titles.
3. Adjust the legend position (loc) and style attributes like fontsize and edgecolor.

Contributions are welcome! Please feel free to submit a Pull Request.

MIT License