California Climate Variability & Water Resources

Abstract

This project utilizes data from the California Data Exchange Center (CDEC) to create data visualizations examining historical trends and recent weather events. Spanning over 2,000 stations with daily measurements, the dataset is transformed into Tableau dashboards to address the challenge of interpreting the CDEC’s extensive database. The project aims to aid decision-making regarding water resource management by emphasizing the need for adaptation and sustainable water use in the face of climate variability.

Project Overview

This project highlights:

• Objective: Analyze the impact of climate variability on California’s water resources using CDEC data.
• Methods: Data cleaning, transformation, and visualization with Tableau.
• Outcome: Interactive dashboards that enable insights into historical and recent trends, aiding policymakers and stakeholders.

Data Sources

• California Data Exchange Center (CDEC): Primary source of hydrological and climate data.
• Data includes daily measurements from over 2,000 monitoring stations across California.

Tools & Technologies

• Data Cleaning & Transformation: Python (pandas, numpy, matplotlib, etc.)
• Visualization: Tableau for dashboard creation.
• Version Control: GitHub for project management.

Key Features

1. Historical Trend Analysis: Explore long-term trends in precipitation, temperature, and water levels.
2. Impact of Recent Weather Events: Analyze short-term variability and its implications.
3. Interactive Tableau Dashboards: Enable users to filter, zoom, and explore data insights

Project Structure

- data/          # Raw and cleaned datasets
- notebooks/     # Jupyter notebooks for data preprocessing and analysis
- dashboards/    # Tableau files (.twb or .twbx)
- visuals/       # Exported visualizations and graphs
- writeup/       # Final project analysis and writeup
- README.md      # Project documentation

Results

Provided is a link to the cloud-hosted dashboard: Tableau Public

The Tableau dashboards provide actionable insights, including:

• Regional variability in water resources.
• Correlations between climate variables and water availability.
• There is a need for sustainable water resource management.

Future Work

• Incorporate machine learning models to predict future trends.
• Expand analysis to include economic impacts of water variability.
• Enhance dashboards with additional datasets (e.g., agricultural or urban water usage).

Acknowledgments

• California Data Exchange Center (CDEC): For providing the dataset.
• Open-source tools and libraries that supported this project.