After speaking to several of our customers we have identified the top 5 challenges that one may face when collecting water quality data. This post will address challenge number 3. With the expertise of our very own product manager’s and technical support team, we are sharing how to deal with and/or avoid these typical frustrations and how new industry technology can help tackle these big issues.
Anyone dedicated to monitoring natural aquatic environments, such as rivers, lakes, wetlands, oceans, estuaries, and ground water should keep reading.
Uncertainty with future projects, legislation, & technology keep my program in flux. Which instrument can I rely on for the next decade?
- Versatile equipment - customizable sensor configurations, equipment that can be used in an array of applications.
- Multiparameter – one instrument that can do it all.
- Data – make sure it is more accessible with equipment that has built-in Bluetooth technology and/or the ability to easily connect to a computer via a USB connection for cable-free calibrations.
Alright, onto Challenge #3.
Incomplete or Inaccurate Data Wastes My Time. I Need Data Quality Assurances.
Significant resources are wasted when data is missing or instruments are not properly configured. This challenge is nothing new and has been around as long as water quality data has been collected. It is a common frustration because many resources go into collecting field data. Resources such as wasted field trips, data gaps, step changes or bad calibration are some examples. When you’ve wasted a trip to the field because your instrument is not working properly, or you have a data gap because your instrument didn’t start logging, this can cost you money. Technology improvements in the past 20 years have helped to address this challenge.
But, most recently, in the past 5-7 years, there have been improvements that are driven by “smart sensor” technology. Let’s go over a few:
Quality Assurance Programs
Quality assurance can become automated, because smart sensors contain microprocessors. When you plug in the sensor, it starts working and compares its factory calibration with the user calibration to check for compliance. For some, these programs are part of their SOP, and now even easier to adhere to.
Redundant Data Logging
Data is stored both on the instrument and passed through via email or data logger to a web server to give you a back-up data file externally. Powerful microprocessors in the instrument allow for multi-tasking; at the same time, the instrument can be collecting data internally while communicating externally.
Instrument configuration can cause data issues. Old DOS windows with multiple menus were cumbersome. Smart sensors store their own calibration data and automatically configure themselves when plugged into any port on the instrument. The fact that the calibration data is now stored on the sensor itself, as opposed to the individual instrument, allows the sensor to automatically start working right away when installed – saving you time and eliminating the possibility of user input error.
Smart sensors can also send up a flag when a fault condition has occurred: The fault can be communicated in the software or as an LED light on the instrument. It is logged in memory and can be re-checked right before deployment. Now, before you go out for the field trip or deploy your sonde into water, you can have a clear indication if there is a problem with one of the probes, or the calibration, or the battery.
Check out the video for more on the EXO sondes smart sensor technology:
Next, Challenge #4 – Shrinking budgets compromise my program’s goal. How can we be more efficient with what we have?…Coming soon.
Additional Blog Posts of Interest:
Water Quality Monitoring Challenges | 1 of 5
Water Quality Monitoring Challenges | 2 of 5
Rugged, Field-Proven Water Quality Meters | 3 Real Life Examples
A Breakthrough in Multiparameter Water Quality Sampling and Profiling