Abstract:  

Riversearch citizen scientists collected water quality measurements (nitrate and phosphate concentrations and turbidity) from three river catchments in Kent between November 2021 and June 2024. The results of a cumulative link mixed model showed that the Stour had the highest nitrate concentrations and the Medway had the highest phosphate concentrations and turbidity. Samples from grasslands and pastures, parks and gardens, and urban areas had higher nitrate concentrations than samples from woodlands, and nutrient concentrations were lower in streams than rivers and following heavy rain. We detected no change in these measures over time. Many of Kent’s rivers are in poor ecological condition, and so it is vital that collaborative efforts involving farmers, landowners, local authorities, and environmental organizations, successfully implement the strategies available to minimize nutrient runoff and enhance nitrogen retention in the soil in an integrated and holistic approach.  

Introduction 

In 2021 Kent Wildlife Trust sought volunteers to take part in a new citizen science project called Riversearch which aimed to test water quality within the Stour catchment in Kent, as part of the H2O: Source2Sea project. This project worked with the local community, landowners and businesses to restore ecosystem function in the River Stour catchment to reduce some of the impacts of climate change on our community and for wildlife. Volunteers were asked to monitor and collect information about river health by adopting a stretch of river and collecting data on water quality, habitat conditions and pollution sources. In 2023, Riversearch was expanded across the county, with a focus on the Darent Valley and Upper Beult catchments. Rivers are incredibly diverse habitats which support a wide range of wildlife. The data collected by citizen scientists involved in Riversearch allows us to assess the health of the river and identify the best way to manage it for the future. 

Measuring nitrates, phosphates and turbidity can tell us about the health and water quality of an aquatic ecosystem. High nitrate and phosphate levels are commonly caused by agricultural runoff, livestock manure, sewage discharges, urban runoff and atmospheric deposition. Excessive concentrations can lead to nutrient enrichment, algal blooms, and oxygen depletion, adversely affecting aquatic life (Carpenter et al., 1998). In almost all cases, better management of the activities inputting nitrates is the best management action, but creating and restoring wetlands can also help to slow the flow and act as natural filters (Fisher & Acreman, 2004). Phosphate-free alternatives in household products can also contribute to mitigating phosphate pollution in rivers (Comber et al., 2013).  

Methods 

Fieldwork 

Data collection started on the 10th November 2021 and is ongoing. Citizen scientists are given a supply of test kits, enrolled in the mobile mapping application, and provided with health and safety information. Citizen scientists are allowed to choose their own sampling locations but they must be safe to access. Upon arrival, the sampling point is mapped and given a verbatim name, and a new sample is recorded. The start time, end time, waterbody type, dominant land use, dominant bank vegetation, landowner details (where applicable), channel width, channel depth, surveyor’s name, amount of rainfall in previous 24 hours, water level, and notes are recorded. Using a suitable container, such as bucket on a rope, a sample of water is collected from the river and tested for nitrates, phosphates and turbidity using the following methods. The results are recorded in the app and synced to the server.  

Turbidity Test:  

• Fit turbidity tube together and pour water into the container, stopping when the ‘X’ marker is no longer visible when looking from directly above.  

• Ensure, all bubbles have gone.  

• Record the value that the water level is up to on the side of the tube – this is JTU ‘Jackson Turbidity Units’. 

• If the water is clear after completely filling the tube, enter the value at <5. If the value is very turbid and does not reach the values, enter the value as >500.  

Phosphate Test:  

• Have a timer ready before starting this test.  

• Remove the yellow plastic pin from the top of the test tube. Pointing the end the pin was removed from upwards, squeeze the tube with your fingers to remove all the air.  

• Continue squeezing the tube and tip downwards as you enter it into the water sample. 

• Slowly release the pressure and draw up water to fill the tube to halfway.  

• Gently shake the tube to mix the water and reactive agent together. The agent may not completely dissolve, this is not an issue.  

• Place the tube down and set your timer for 5 minutes.  

• Once the time is up, check the colour against the test chart immediately. Using the side of the chart that ranges from 0.02 – 1, compare the colour and record the result.  

Nitrate Test:  

• Have a timer ready before starting this test.  

• Remove the yellow plastic pin from the top of the test tube. Pointing the end the pin was removed from upwards, squeeze the tube with your fingers to remove all the air.  

• Continue squeezing the tube and tip downwards as you enter it into the water sample. 

• Slowly release the pressure and draw up water to fill the tube to halfway.  

• Gently shake the tube to mix the water and reactive agent together. The agent may not completely dissolve, this is not an issue.  

• Place the tube down and set your timer for 3 minutes.  

• Once the time is up, check the colour against the test chart immediately. Using the side of the chart that ranges from 0.2 – 10, compare the colour and record the result. 

Data analysis 

Prior to the analysis the dataset was cleaned. Mobile mapping errors, duplicate samples, the sample from the Rother, and incomplete samples were removed. Following data cleaning, 779 of the 823 samples were retained.  

A cumulative link mixed model (CLMM) was used to compare nitrate, phosphate and turbidity levels between river catchments, and to analyse the trend in nitrate, phosphate and turbidity levels over time. The CLMM is suited to our data which comprises an ordinal response variable (values coded as 1 to 7, e.g. for nitrates <0.02 ppm = 1, 0.02-0.05 = 2, 0.05-0.1 = 3 and so on) with repeated measurements nested within sampling locations and river catchments. The sample date, waterbody type (river, stream or pond), dominant land use (crop, grassland and pasture, park and gardens, urban and woodland), dominant bank vegetation (grass, bare, herbs, shrubs or trees), whether it had rained in the previous 24 hours (none, light or heavy), and water level (average, high or low) were included in the model. Reference factor levels were set to river, crop, grass, none, and average, respectively. The sampling location and catchment were included as nested random effects. The analysis was repeated but with catchment included as a covariate instead of as a random effect. Estimated marginal means were computed for pairwise comparisons.  

Results 

Between 10th November 2021 and 7th June 2024, 823 water quality samples were collected across 123 sampling locations across four river catchments in Kent (only one sample has been collected in the Rother catchment) (Figures 1 and 2). Following data cleaning, the analysis was performed on 779 samples across 123 locations and three catchments.  

Nitrate levels in the Stour (EMM: -0.196, CI [-1.37, 0.98]) were found to be higher than in the Medway (EMM: -1.662, CI [-2.96, 0.36]) and the Darent and Cray (EMM: -1.769, CI [-3.19, 0.35]) (Table 1 and Figure 3).

Table 1. Contrasts from estimated marginal means (EMMs) for nitrates using 0.95 confidence level with tukey adjustment

Phosphate levels in the Medway (EMM: -0.926, CI [-1.97, 0.12]) were found to be higher than in the Stour (EMM: -2.274, CI [-3.23, -1.32]) and the Darent and Cray (EMM: -2.723, CI [-3.88, -1.56]) (Table 2 and Figure 3).

Table 2. Contrasts from estimated marginal means (EMMs) for phosphates using 0.95 confidence level with tukey adjustment

Turbidity levels in the Medway (EMM: -0.042, CI [-1.41, 1.32]) were found to be higher than in the Stour (EMM: -3.325, CI [-4.59, -2.06]) and the Darent and Cray (EMM: -4.755, CI [-6.32, -3.19]) (Table 3 and Figure 3).

Table 3. Contrasts from estimated marginal means (EMMs) for turbidity using 0.95 confidence level with tukey adjustment

Figure 3. Interactive jitter plot showing the spread of the nitrate, phosphate and turbidity data. The horizontal line indicates the mean.

The results of the CLMMs with location and catchment included as nested random effects are presented in forest plots (Figure 4). None of the water quality measures had a statistically significant trend over time. Nitrate levels were found to be much higher in rivers than in streams and ponds. Nitrate levels were found to be higher in grasslands and pastures, parks and gardens, and urban areas, compared to in woodlands. Nitrate levels in croplands were not found to differ significantly compared to other land use types. No relationship was found between the type of bank vegetation and nitrate levels. No relationship was found between the water level and nitrate levels, however nitrate levels were lower following heavy rain.

Figure 4. Forest plot of incidence rate ratios from the CLMM, showing the log-odds (probabilities of moving from a lower concentration to a higher concentration) given a one−unit change in the independent variable, while holding other variables in the model constant. Significant relationships between nutrient concentration and independent variables are shown by asterisks (* p < 0.05, ** p < 0.01, *** p < 0.001).

The only covariate found to influence phosphate levels was the type of bank vegetation, whereby phosphate levels were much higher at sampling locations that had bare river banks. Turbidity was found to be higher in rivers than streams. Turbidity did not vary as a function of surrounding land use. Turbidity was found to be greater when water levels were high and following heavy rain.

Channel width and channel depth measurements were collected at around half of the sampling locations. Therefore, these variables were excluded from the main analysis which requires complete data. When the analyses was repeated for the limited data with channel width and depth measurements, it was found that nitrate levels were higher in wider channels (β = 0.132, SE = 0.063, p = 0.036). Sampling sites in the Stour had greater channel widths and depths (Figure 5).

Discussion

Thanks to a dedicated team of citizen scientists, the RiverSearch Citizen Science project has collected a large and valuable dataset on water quality across several river catchments in Kent. The significantly higher nitrate concentrations observed in the Stour catchment, compared to the other catchments, is likely due to leaching and accumulation of nutrients from a comparably greater coverage of intensive arable farming, pasture, and urban areas with greater human population densities.

The EU Drinking Water Directive states a nitrate concentration of 50 ppm (or mg/l) as an acceptable standard for human consumption, whilst <10 ppm is the Water Framework Directive standard set to prevent eutrophication and minimise deleterious impacts on aquatic environments and biodiversity. Whilst our data shows mean nitrate levels in all three catchments were below 10 ppm, samples over 10 ppm were collected from all three catchments, including two in the Darent and Cray, one in the Medway, and 44 in the Stour. There were a total of 147 records measuring 5-10 ppm across the catchments (Figure 3).

The Water Framework Directive and UK Environment Agency Environmental Quality Standards for phosphate concentrations are <0.025 ppm for high status and <0.1 ppm for good status, to prevent eutrophication and minimise deleterious impacts on aquatic environments and biodiversity. Eight samples in the Darent and Cray, 36 samples in the Medway, and 67 samples in the Stour recorded phosphate concentrations greater than 0.1 ppm (Figure 3).

Low turbidity (0-5 JTU) is generally safe for most aquatic life whilst moderate turbidity (5-25 JTU) can be tolerated by many species. It is promising to see that no turbidity measurements in the Darent and Cray exceeded 4 JTU, whilst only a few in the Stour and Medway exceeded 5 JTU (Figure 3).

Nitrate concentrations and turbidity were lower in streams compared to rivers. Smaller rivers and streams tend to have lower nutrient concentrations than larger rivers because they have a smaller upstream contribution, usually with less human activity. The water travels shorter distances which means there is less opportunity for pollutants to accumulate or be transported downstream. They have faster flow rates compared to larger rivers which help to flush out pollutants and prevent their accumulation, and they have a higher river bank to water volume and so vegetated buffer zones along the banks can act as natural filters, trapping sediments and absorbing nutrients before they enter the water (Burt et al., 2011).

Survey effort has remained consistent throughout time, as indicated by the gradual increase in samples over the course of the project’s lifetime (Figure 1), thus, further increasing the robustness of the dataset for analysis of trends over time. The results showed no statistically significant change in nitrate, phosphate or turbidity levels over the analysis period, based on the sampled catchments.

Nitrate levels were found to be higher in grasslands and pastures, parks and gardens, and urban areas, compared to woodlands. Sources of runoff containing high concentrations of nitrate in these areas include nitrogen-based fertilizers, animal waste, industrial processes, sewage, and fertilizers in gardens or lawns (Burt & Haycock, 1992; Burt et al., 2011). Urban areas tend to reduce water infiltration, leading to increased surface runoff that can carry pollutants and sediments into rivers.

Whilst the RiverSearch dataset has yet to reveal any significant changes in water quality over time (seasonal changes will be treated in a future report) there are clear patterns linked to environmental conditions across Kent. For instance, we have found that shallower streams have lower nutrient concentrations than larger rivers, and that nitrate concentrations are higher around urban and agricultural areas. It is vital that collaborative efforts involving farmers, landowners, local authorities, and environmental organizations, successfully implement the strategies available to minimize nutrient runoff and enhance nitrogen retention in the soil in an integrated and holistic approach. In 2019, 79% of the rivers and lakes in Kent monitored for phosphorus did not meet the required standard for good ecological status as set out under the Water Framework Directive (Tinsley-Marshall et al., 2022).

References

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