Option 1: Weather-to-Yield Signal Detection

Given historical yield data (per geography or crop), plus historical weather variables (rainfall, temperature, humidity, wind, soil moisture if available). 

  1. Identify which weather features most strongly correlate with yield variations.
  2. Flag anomalies: counties/fields/seasons where yield is unusually high or low relative to weather conditions.
  3. Build a model that can explain why those anomalies may have occurred.

Bonus:

  1. Visualize the anomalies on a map (e.g., heatmaps by county).
  2. Explain yield deviations during extreme events (2021 drought, flood periods, heat waves, etc.).

Option 2: Predict the Future - 60- and 90- day forcast yield simulation

  1. Build a predictive model that estimates expected yield for the current growing season based on near‑term forecast weather.
  2. Quantify uncertainty (e.g., “yield could drop 10–18% if rainfall is below X”).
  3. Provide early‑warning insights for agronomists or growers.

Bonus

  1. Visualize prediction intervals and uncertainty bands.
  2. Provide a simple natural‑language summary for farmers (“If temperatures exceed 95°F for more than 4 days, expected yield  decreases by 12%.”)
  1. Yields for Corn and Soybean - GitHub Link
  2. Historic Weather Data (Databricks Marketplace - multiple options)

 

 

 

Requirements

Required Submission Materials

Only one team member should complete all submissions.

To be eligible for judging, you MUST:

1. Submit on Devpost
  • Add first and last names of all team members to the Devpost
  • Include a public GitHub repository.
2. Submit a 2-Minute Demo Video
  • Must clearly explain the project and highlight key features.
  • Submit as a publicly accessible YouTube link.
3. Submit a Brief Project Write-Up
  • Outline your ideation and development process.
  • Share how you used Databricks and what was great or frustrating about the platform
  • Credit any public frameworks, APIs, or external tools used.

Hackathon Sponsors

Prizes

3 non-cash prizes
1st Place
1 winner

Databricks Lululemon Everywhere Backpack + Owala Water Bottle

2nd Place
1 winner

Databricks Lululemon Everywhere Backpack

3rd Place
1 winner

Owala Water Bottle

Devpost Achievements

Submitting to this hackathon could earn you:

Judges

Harshit Rai

Ryan Glanzer

Ryan Glanzer

Mehul Bhuva

Mehul Bhuva

Z Sun

Judging Criteria

  • Impact + Relevance
  • Creativity + Originality
  • Technical Depth + Use of Databricks
  • Soundness + Accuracy

Questions? Email the hackathon manager

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