Digital Tools for Citizen Science
Project description
The objective of this research project is to develop new digital tools to collect and process citizen science observations of water resources. Building on the existing Crowdhydrology project, the research assistant will help design and implement new computer codes to collect observations of water levels and flooding. These data will be used to develop improved models to forecast flooding and quantify stream flow in remote locations across the United State
Project outcome
Digital Tool Development:
- Citizen scientist user response interface to determine why people participate in the CrowdHydrology project (Python computer code linked to Twilio, which interfaces with existing Qualtrics survey)
- Image processing code to collect and catalog images of flooding submitted via text message of flooding (Python computer code, Twilio web scraper, user interface)
Project details
| Length of commitment | About 3-5 months |
| Start time | Anytime |
| In-person, remote, or hybrid? | Hybrid |
| Level of collaboration | Individual Student Project |
| Benefits | Academic credit Work study Stipend |
| Who is eligible | All undergraduate students |
Core partners
Project mentor
Chris Lowry
Associate Professor
Geological Sciences
Start the project
- Email the project mentor using the contact information above to express your interest and get approval to work on the project. (Here are helpful tips on how to contact a project mentor.)
- After you receive approval from the mentor to start this project, click the button to start the digital badge. (Learn more about ELN's digital badge options.)
Preparation activities
Once you begin the digital badge series, you will have access to all the necessary activities and instructions. Your mentor has indicated they would like you to also complete the specific preparation activities below. Please reference this when you get to Step 2 of the Preparation Phase.
Minimum: Coding experience in Python
Preferred: Experience with Twilio APIs, Database management, Image processing
Keywords
Coding, Python, Computer Science, Database, Geology