Lab-0022

Tilt Current Meter Analyses

Model
pandas

Duration
2.0 hrs

Updated
2020-10-27

Download
download

Run online using:

Jupyter

Contributor(s)

Alejandra C. Ortiz at Colby College.

Introduction

We will be analyzing the data from a month long deployment of a Lowell Tilt Current Meter: https://lowellinstruments.com/products/tcm-1-tilt-current-meter/. These meters were deployed at the boat ramp of Bog Stream in North Pond, Maine (44.647773, -69.865923) from Sept. 25th 2020 - Oct. 22, 2020 as part of a final project for GE 254 at Colby College in conjunction with the 7-lakes alliance (https://www.7lakesalliance.org/).

Classroom organization
This was used as a lab to analyze velocity data from a month long deployment in a nearby stream. It was used as part of a final group project students were doing and to further their introduction and comfort with python and pandas dataframes.

Learning objectives
Skills

Importing, analyzing, and visualizing time-series data
Cleaning up raw data
Averaging burst data
Exploring potential drivers of velocity changes at our site (meteorological)

Key concepts

Averaging Time-series data at different frequencies
Importing long-temporal data series
learn how to make more complicated plots in python: 2 y-axes or using color of markers to denote a 3rd variable
learn how to utilize date-time objects in pandas to work FOR you in time-series analyses

Lab notes

Make sure students have some undrestanding of how a TCM (tilt current meter) works - https://www.lowellinstruments.com/download_files/Universal_User_Guide.pdf There is helpful information contained in the dataset.

Requirements
You will need the uploaded TCM output data files and a local weather output (I manually cleaned that file of all header information).

Acknowledgements
CSDMS and Mark Piper helped me create and host these labs on jupyterhub.

References