SteamWatch Water Quality Monitoring Internship
Lily Raphael, Riley Samples, and Fiona Wolter
About the Watershed Institute
The goal of The Watershed Institute is keeping water clean, safe and healthy is the heart of our mission. We work to protect and restore our water and natural environment in central New Jersey through conservation, advocacy, science and education.
What is a watershed?
A watershed is an area of land where all the water drains into a specific body such as a river, lake, or ocean. It describes the entire land area that contributes water to a particular body of water.
StreamWatch
Biological Team (BAT) | Chemical Team (CAT) | Bacterial Team (BACT) |
| | |
Monitors macroinvertebrate populations and uses pollution tolerance values to quantify water quality | Measures water chemistry
| Measure E. coli levels, indicator for fecal contamination Monitors harmful algal blooms (HABs) |
Lab work
Field work
Fluorometer meter
Hanna Meter (Multiparameter)
Wargo Pond Monitoring
Gather biweekly data using the fieldwork meters in conjunction with taking samples for E.coli, turbidity, and nutrient testing
Purpose
Map of sample locations around Wargo Pond
The Gallery Discrete Analyzer
Photometry: using light absorbance to detect analyte concentration
Process:
Fiona Wolter
Challenges with this Machine
Unclear what to do with a high blank result
Interpreting test results
Frequent Variance in Test Results
Inconsistencies in the same test that is rerun multiple times
Sample Data
Run blank samples in each rack but no standard for what makes a high blank
Blanks
Unclear what distinguishes a low result from a blank
High and low test inconsistencies
Unclear protocol for deciding when to accept vs rerun tests
Addressing these Challenges
Calculate limit of detection (LoD) and limit of quantification (LoQ) using blank sample data and the corresponding calibration curves
Create decision support sheets for accepting vs rerunning test results
Investigate the potential for instrumental drift by charting calibration data from the past five years
Test different preparation methods to evaluate sample non-homogeneity and determine how to minimize this source of error
Calibration Analysis Results
Sample Preparation Data Results
*Run 4 for shake was 356.3261
Making StreamWatch Data Accessible
A goal of The Watershed this year is to make all of their data publicly available. The Watershed has around 40 year of collected data, but none of it is publicly available. The audience for this data consisted of both professional lab group as well as younger educational groups.
To tackle this goal, the first thing I did was create a guide for understanding the data, so that any audience has the opportunity to analyze the data accurately.
This guide covers every column in the master data spreadsheet, and is accessible in both pdf form and directly on the excel sheet.
I sorted the data in to 27 different subsets, as well one sheet that contains all data.
Riley Samples
Making StreamWatch Data Accessible
To further increase the ease of use of The Watershed’s data, I developed a similar guide for data visualization. This guide, provides detailed information on how to clean, subsect, visualize, and analyze the data directly in excel.
Inside the modeling instructions, I created some of my own visualizations to provide inspiration and an expression of the excel modeling capabilities
These instructions, similar to the data dictionary, are available both directly inside the All Streamwatch Data spreadsheet, and also in PDF format.
Making StreamWatch Data Accessible
The last and largest part of making this data accessible was creating a public portal that allows the data to be downloaded. To do this, I utilized a website made by a former intern, originally intended for informing Streamwatch volunteers. This was done through ArcGIS. Here, I developed an additional webpage where the data is publicly accessible, both in browser and downloadable formats.
Also accessible through this dashboard is a document continuing the history of The Watershed’s data collection techniques, which enables users to search for possible explanations to unexpected data shifts.
Benthic Freshwater Macroinvertebrates
Bottom
dwelling
Large enough to be seen with the naked eye
No backbone
Pollution Tolerance of
Macroinvertebrates
Macroinvertebrates and Water Quality
Pollution Sensitive
0-4
Pollution Tolerant
6-10
Pollution “Neutral”
4-6
Crayfish
(5)
Scud
(7)
Stonefly nymph
(1)
Found in lakes, steams, rivers, etc.
Macroinvertebrate Indices
New Jersey Impairment Score (NJIS) |
Coastal Plains Macroinvertebrate Index (CPMI) |
High Gradient Macroinvertebrate Index (HGMI) - Genus |
High Gradient Macroinvertebrate Index (HGMI) - Family |
Map of the index boundaries throughout New Jersey
Indices Calculations
HGMI (genus)
HGMI (family)
CPMI
No further calculations
Raw Data
Select a sample of 100 organisms
Calculate NJIS
Contains Genus Information
Only Contains Family Information
High Gradient Site
Contains Genus Information
Only Contains Family Information
Low Gradient Site
High Gradient
Only Family
Information
Sample Calculation
Learning Takeaways
Water Quality monitoring involves a wide variety of steps and metrics! We were able to see this process through from sample collection and field work to lab work to data analysis, allowing us to better understand the different components of this kind of work.
Our personal projects gave us additional opportunities to explore instrumentation, design experiments, clean and visualize data, and work with software tools such as Excel and ArcGIS.
Acknowledgements and Questions