Instruction for water quality data analysis (biodiversity and water quality monitoring report)
I am currently working on the fifth edition of the Biodiversity and Water Quality Monitoring Report for Shuttleworth Conservation Park (SCP) for the year 2024. I have begun drafting the report, and I would like to request your expertise in completing the sections highlighted in yellow in the attached Table of Contents. Specifically, I would appreciate your assistance with the following sections:
1. Biomonitoring, Water Sampling, and Water Analysis Methodologies
2. Results and Discussion
3. Conclusions
The draft I have started writing will serve as a foundation for your work. Additionally, I will be providing the water sampling data collected from May 2023 to April 2024 in an Excel format, which will be crucial for your data analysis.
To support your efforts further, I will also upload the Biodiversity and Water Quality Monitoring Reports from previous years (September 2018 – April 2020, May 2020 – April 2021, May 2021 – April 2022, and May 2022 – April 2023). These documents should provide a valuable context, particularly for the trend analysis in the “Results and Discussion” section, where you will evaluate whether various water quality parameters have increased or decreased during the current reporting period compared to historical datasets.
When discussing the results of the data analysis for the 2024 report, please ensure that references are used to support your findings. You can draw from the references in the fourth edition of the Biodiversity and Water Quality Monitoring Report for SCP (2023) ( uploaded : file name Report – 2022-2023 4th Water Quality Monitoring Technical Report) if they are relevant, or you may include other reputable sources as needed to substantiate the analysis.
For the completion of the report, the following key components should be included:
1. Biomonitoring: A comprehensive inventory of plant and wildlife species throughout SCP, including documentation of algae blooms in the respective ponds.
2. In-situ Water Quality Analysis: Characterization of the physicochemical conditions of all ponds throughout the sampling season by analyzing in-situ water quality parameters.
3. Cascading Pond Performance Analysis: Assessment of the cascading ponds’ performance by examining changes in the physicochemical state of water from the inlet to the outlet of each pond using statistical inference.
4. Trend Analysis: An evaluation of whether various water quality parameters have increased or decreased during the reporting period compared to historical datasets.
5. Exceedance Identification: Identification of any exceedances in water quality parameters relative to provincial guidelines.
6. Water Quantity at Pump Station 2: Measurement and quantification of the water quality at Pump Station 2 fill station to ensure compliance with set standards.
Please refer to the previous year’s report (the 2023 fourth edition is uploaded ) when drafting the “Results and Discussion” section, particularly concerning water quality data analysis techniques. In the fourth edition, various analytical approaches were employed to meet the specific objectives of the study.
The analysis of in-situ water quality parameters involved examining distributions through Box-Whisker plots across all sampling sites, with medians (n = 11) of the parameters used for interpretations. Additionally, line charts were created to track parameter changes over time in select ponds, specifically the four cascading ponds, Pond 3-PS, Pond 5-SW, and Pond 5-NW.
To determine statistical differences in in-situ water quality parameters between the inlet and outlet of each cascading pond, a non-parametric, paired Wilcoxon test was employed. This test was also used to compare differences between the inlet to cascading pond 1 (CP1) and the outlet from cascading pond 4 (CP4) to detect changes in water quality across the entire series of constructed wetland ponds (CP1 to CP4).
Grab samples collected from all sampling sites were analyzed by summarizing each sampling distribution’s median value (a statistical measure of central tendency). For parameters that were below the detection limit (BDL), censored data were included in the analysis at half the detection limit of the respective parameter.
The trend analysis and identification of exceedances were based on grab samples taken at the high-frequency sampling sites: Pond 3-PS, Pond 5-SW, and Pond 5-NW. The trend analysis involved comparing sample distributions from these high-frequency sampling sites (n = 8) with the historical dataset from previous years (n = 8), using the non-paired Wilcoxon statistical test. Box and whisker plots were generated for each parameter to facilitate visual data presentation.
Line charts were also developed to show parameter changes over time for each parameter in the high-frequency ponds. These charts included a precipitation hyetograph from a nearby weather station (NEIR AGDM, Alberta Climate and Information System), located approximately 21 km northwest of SCP, for the sampling period. The inclusion of precipitation data was critical for interpreting results associated with external hydrological influences. To assist with this, I have uploaded the weather data for the area, which should help in creating an accurate precipitation hyetograph.
Lastly, the distributions of grab samples collected before and after the water filter at PS2 were compared using the paired Wilcoxon statistical test. Box and whisker plots were created to visually present the data.
I would like the following visualizations to be included in the report:
• Line charts for temperature and dissolved oxygen across various ponds over the sampling season.
• Hyetographs of precipitation (Neir AGDM) and line charts for salinity measurements in the cascading ponds over the sampling season.
• Line charts showing dissolved oxygen concentrations at the inlet and outlet of each Cascading Pond, with p-values showing differences between distributions using the paired-Wilcoxon test.
• Salinity concentrations at the inlet and outlet of each Cascading Pond, and between CP1 inlet and CP4 outlet, with p-values using the paired-Wilcoxon test.
• Comparisons of magnesium concentration distributions from two sampling periods with Wilcoxon test results.
• Hyetographs of precipitation and line charts for changes in chloride, iron, aluminum, and total alkalinity over the period at high-frequency sampling sites.
• Specific conductivity measurements from grab samples collected before and after the filter at PS2, with paired-Wilcoxon p-value shown.
You can use either R Studio software or Excel for the data analysis, depending on your preference or whichever tool you find most suitable for the tasks.
Please feel free to create additional charts as necessary based on your data analysis.
The uploaded Excel file, titled “2023 May – 2024 April Data HPIP.xlsx,” contains multiple sheets, each representing different aspects of the data collected for the Shuttleworth Conservation Park (SCP) project from May 2023 to April 2024. Here’s an overview of the contents:
1. Template: This serves as a template for data entry, possibly containing predefined formats and guidelines for recording observations and measurements.
2. Clean Data YSI: Contains cleaned data collected using a YSI multiparameter sonde, which likely includes in-situ water quality parameters such as temperature, dissolved oxygen, pH, and more.
3. Site Map: A visual or data-based map of the monitoring sites at SCP, showing the locations of various ponds and sampling points.
4. Monitoring Report: contains detailed entries or summaries related to monitoring activities conducted during the reporting period.
5. WildlifePond: Data specific to wildlife observations in and around the ponds, potentially tracking species presence and activity.
6. Wildlife Tally: A tally or count of wildlife sightings, categorizing the types and numbers of species observed.
7. Algae Observations: Records of algae blooms or other related observations in the ponds, critical for understanding the ecological health of the wetland system.
8. Plant Observations: Data on plant species observed in the area, possibly including growth rates, health assessments, and species diversity.
9. Lab Analysis Water: Results from laboratory analysis of water samples, likely providing detailed chemical and physical water quality data.
10. Lab Analysis Plant: Results from laboratory analysis of plant samples, potentially focusing on the accumulation of nutrients or contaminants in plant tissues.
11. Plant Dry Weight: Data on the dry weight of plants, which can be used to assess biomass and overall plant health.
12. Flow Experiment – Lab Analysis: Lab results related to a flow experiment, possibly testing the effects of water flow on water quality parameters.
13. Flow Times: Data recording the timing of water flow events, which may be critical for understanding the hydrodynamics within the wetland system.
14. Flow Experiment – Clean YSI Data: Cleaned YSI data specifically related to the flow experiment, providing insights into how water flow influences water quality.
15. Data Template: Another template, potentially used for specific experiments or data collection activities.
16. 2023-05-02 to 2024-04-24: These sheets contain data and observations from specific dates, reflecting the ongoing monitoring and data collection efforts throughout the reporting period. Each of these date-named sheets typically has a corresponding “Observations” sheet, which likely includes qualitative notes, contextual information, or additional observations made during field visits.
This comprehensive dataset will support the analysis needed for the Biodiversity and Water Quality Monitoring Report, providing valuable insights into water quality trends, ecological health, and the effectiveness of the stormwater treatment system at SCP.
Comments from Customer
586988608_Report_-_2022-2023_4th_Water_Quality_Monitoring_Technical_Report_5156239942920271.docx – it is like the template to follow (the main one), analyze the same way
586988608_Instructions_-_draft_2024_5th_Water_Quality_Monitoring_Technical_Report_42938347349924.docx – yellow parts should be done.
Previous reports just to show the improvement of the reports (over time) and how to present the information.
Visualization + analysis need to be completed. You can find all the data in Excel sheets.
You will be working on another similar project after that one.
