Fig. 3: Map displaying all the points of interest for the day one activites
Berlin 2025 - Aquatic Ecology - Day 1
1 Aim and learning objectives
The aim of this activity is to introduce you to established monitoring methods for assessment of river health. With a particular focus on water quality.
By the end of the practical you will:
Have confidence using environmental sensors and field test kits for measuring water quality and interpreting their output;
Understand the need for measurement replicates and the implications of spatiotemporal variability for water quality monitoring;
Appreciate how urban rivers are modified by humans and the implications this has for water quality and river health.
2 Study sites
Site 1 is close to a major input from land that was formerly used as a large sewage irrigation farm (52.6219° N, 13.4688° E). This section is straitened but has semi-natural banks and continuous riparian vegetation (see Figure 1 & 3).
Site 2 is in Karow, a suburb of Berlin (52.6195°N, 13.4657° E). This section of the river is representative of the river form for the wider suburban area (Figure 2 & 3). Site 3 is directly downstream of a large, treated wastewater effluent input (see Figure 3).
3 Field activities
For this exercise you will work in groups of three or four to assess water quality at three sites on the River Panke. You will measure water quality parameters (water temperature, electrical conductivity, pH, dissolved oxygen and ammonia) at two scales (Figure 4): 1. the point scale (a single representation location at you monitoring site) 2: and across the reach (i.e. multiple points across the reach to capture any spatial variability). Follow the procedures outlined below at each site.
3.1 Sensor calibration
The sensor for measuring EC and pH - Hannah HI 98129 - should be calibrated in a high ionic strength solution. The DO sensor - YSI ProODO – should be calibrated in water saturated air. This process will be demonstrated. Record the un-calibrated (pre-calibrated) readings for both sensors (share your group measurement with others and be sure to make a note of the sensor number). After all the sensors have been calibrated take a final check measurement of the solution and water saturated air, record (post-calibrated) and share.
3.2 Point scale measurement variability
At both sites select a suitable location along the stretch (i.e. with safe access and representative flow characteristics) take five replicate measurements of electrical conductivity (EC), pH and water temperature using the Hannah HI 98129. At the same location take a measurement of dissolved oxygen (DO) using the YSI ProODO. For the ProODO, only the probe should be submerged and may require a stabilisation period of up to 1 minute. Be sure to record all measurements in your field notebook – for DO, both saturation (%) and concentration (mg/L) are required. You should take 5 replicate measurements for pH, EC and DO.
For the ammonia measurement you will use the Hanna HI-700. The sensor enables a rapid colorimetric field measurement of Ammonia concentration using the Nessler method. The process will be demonstrated however you can see the supporting handbook for detailed instructions. For ammonia take 3 measurements per group for the point scale measurements only. The length of time required to a take a measurement means it is not suitable for the transect measurements.
3.3 Reach scale measurement variability
At all sites select 3-5 transects (time permitting) that cover the range of variability in microhabitats at each site (e.g. flow velocity, depth and macrophyte coverage). Also where a major tributary joins the river aim to record cross sections above and below the tributary. Think about the distance downstream and whether you can identify when the two stream are fully mixed.
For each cross section measure the width using the supplied tape measure, and divide into equally spaced measurement intervals (min = 5). Measure the depth at all the measurement locations, then record pH, water temperature and EC (using the Hannah HI 98129) and dissolved oxygen (using the ProODO). Also recorded other features, such as macrophyte coverage, organic accumulation, and flow conditions. See Figure 3 for a schematic representation of the reach scale sampling approach.
3.4 Assessing the impact of wastewater effluent
There is a large input of treated wastewater effluent which enters the Panke ~750m d/s of Site 2 (see Figure 3). Here, collect 5 replicate measurements of water quality using the submersible sensors (pH, EC, DO and water temperature) and 3 replicate measurements of ammonia. If time permits also collect measurements for transects (pH, EC, DO and water temperature) above and below the effluent input (note: this may be easiest from the pedestrian footbridge).
4 Measurement check list
Calibration data for DO and EC (pre and post calibration measurements).
Five replicate spot measurements of EC, DO (saturation and concentration), pH and water temperature for sites 1-3.
Three replicate measurements of ammonia for sites 1-3.
At least three cross sections measured with width, depth, and other conditions (e.g. macrophyte coverage, flow, distance from tributary) recorded for sites 1 & 2.
For all cross-sections record pH, DO, EC and water temperature (minimum 5 points)
Time permitting a cross section as above at site 3.
5 Day one data analysis
5.1 Data processing point scale data
For the pre- and post- calibration data and your point scale water quality variables collected from each site; calculate: 1.mean \(\bar{x}\) (Equation 1), 2. standard deviation (Equation 2) \(\sigma\), and 3.coefficient of variation \(CV\) (Equation 3).
If you have \(n\) measurements and we label each measurement as \(x_i\), the formulas you need are:
\[\bar{x}=\frac{1}n ∑x_i \tag{1}\]
\[\sigma=\sqrt{\frac{1}n ∑(x_i-\bar{x})^2} \tag{2}\]
\[CV=\frac{\sigma}x*100 \tag{3}\]
Create a new table in your notebook with the mean, standard deviation and CV for each water quality variable and site.
Generate a separate table for the pre- and post- sensor calibration measurements.
Tip
Given the large number of values and calculations required you can use spreadsheet software to aid with the process. For example excel or goggle sheets have functions for calculation of mean (AVERAGE()) and standard deviation (STDEVA()) and can be implemented using a smartphone.
Note
If you have time think about ways you could present the data graphically to aid comparison.
Discussion – Write a few sentences on the following in your field notebook:
What do the pre and post calibration σ and CV tell has about instrument drift and precision?
Where there any noticeable differences between the EC and DO sensors?
Why do we need to use the coefficient of variation rather than standard deviation to compare between sensors?
Is measurement variability greater for any of the water quality variables measured? If so why do you think this was the case?
Are there any differences in water quality between Sites 1, 2 and 3? Describe these and hypothesise what might be causing any differences?
Can you think of ways we could improve our monitoring approach?
5.2 Data processing, reach spatial variability
For each site, variable and transect calculate the maximum, minimum, range, mean (Equation 1), standard deviation (Equation 2), and coefficient of variation CV (Equation 3).
Create a new table in your notebook with the maximum, minimum, range, mean, standard deviation and CV for each water quality variable site and transect. Focus on dissolved oxygen saturation and electrical conductivity first. If time permits also generate tables for water temperature and pH.
Discussion – Write a few sentences on the following in your field notebook:
Which variable showed the greatest variability across the transects?
Was variability greater at any of the sites (within and between transects) and was this linked to distance from tributary confluence?
Did any differences in microhabitat conditions appear to explain the patterns?
How do you think time of day might impact your inferences at Site 1? What about Site 2 and 3?
The tables you have generated have lots of numbers and it may be difficult to identify patterns. How could you present the data graphically to aid comparison?
Which summary variables would you prioritize for plotting?
Are your mean point values comparable to the transect mean? Which variables show the greatest/least divergence?
What are the implications of your findings for routine or statutory water quality monitoring?
Based on your findings can you provide any advice for operators or field technicians (i.e. best practice)?