Quantifying The Drivers and Impacts of Natural Disturbance Events – The 2013 Colorado Floods
This lesson demonstrates ways that society and scientists identify and use data to understand disturbance events by focusing on the 2013 Boulder County, Colorado flooding events. Further, it encourages students to think about why we need to quantify change and the different types of data needed to quantify landscape change after a disturbance event.
This lesson focuses on flooding as a natural disturbance event with impacts on humans. While the drivers and impacts of flooding extend beyond the metrics used in this lesson, we use subsets of these datasets to elicit discussion surrounding how we can study flooding and how the event impacts humans:
- Palmer Drought Index: NOAA's Climate Divisional Database (nCLIMDIV)
- Precipitation: National Climatic Data Center-NOAA
- Stream Discharge: USGS stream gauges
- Before/After Terrain Data: NEON AOP LiDAR-derived Elevation Models
- Before/After Imagery: various sources, each image has source information
The teaching data subsets can be found on and downloaded from the NEON Data Skills account on FigShare.
Estimated Duration: 75 minutes (with suggestions for shorter or longer duration)
Themes: Ecological Disturbance
Audience: Undergraduate courses
Class size: Any (adapt the Q&A/Discussion questions to small group discussions or instructor-led introductions as needed)
- Internet access: if presenting, live from the website or accessing videos.
- Computer & projector
- Optional: audio capabilities for videos
- Optional: Computer/device with internet access
Materials Needed: None
This lesson focuses on how data can be used to quantify the drivers and impacts of natural disturbance events and why the quantification is important to for society’s understanding of, forecasting of, and recovery from disturbance events.
After the lesson, students will be able to:
- Explain how and why data are needed to support scientific inquiry.
- Summarize how data can be collected and used to quantify a flood event, including precipitation and stream gauges and lidar .
- Organize the various drivers and impacts of disturbance events to show causation.
- Diagram relationships between different variables (drivers and impacts) and how they influence disturbance events.
- Describe how disturbance events can impact society.
- Contrast how different types of data can be used to quantify changes in terrain.
- Summarize what lidar data are and several ways the data can be used.
- Explain the concept of a “100-year event” and why we might have two 100-year floods five years apart.
- Define: disturbance event, LiDAR, stream discharge (including CFS – cubic feet per second), and floodplain.
Data Skills Objectives
See optional R based Data Activities for individual data skills objectives.
Data & Coding Extensions
All data used in this activity are freely available ( NEON Data Skills account on FigShare).
The code for data manipulation and creation of the visuals is available at the end of each lesson. Throughout each lesson these activities are listed as Optional Data Activity. This could be used in the classroom, in a lab, or an out-of-classroom setting for students already familiar with basic coding and working with data (e.g. graduate students in a cross-listed course).
Suggestions for Presenting Lesson
The detailed lesson page can be used directly to teach from, for students to follow along with the instructor, or to serve as a reference for students before or after the class.
Instructors may also choose to download text, figures, graphics or video from this site and present the lesson in the medium of their choice.
Teaching Modules Collection
This lesson page is part of larger collection of lessons utilizing data collected during the 2013 Colorado Floods that are designed for undergraduate and graduate students. All lessons and related materials can be found on the NEON Data Skills portal.
Use of NEON Teaching Modules
All lessons developed by the National Ecological Observatory Network are open-access (CC-BY) and designed as a resource for the greater community. General feedback on the lesson is welcomed in the comments section for each lesson page. If you develop additional materials related to or supporting this lesson, and are willing to share them, we provide the opportunity for you to share them with other instructors. Please contact NEON Data Skills or, if familiar with GitHub, submit a pull request with the materials to the lesson’s repo (available from the lesson’s webpage). All materials will be reviewed by NEON staff prior to inclusion or linking to from the NEON Data Skills portal.