PREFACE

From sewage water surveillance in Rotterdam-Rijnmond to quality monitoring of UF membrane systems

This is the fifteenth edition of Water Matters, the knowledge magazine of H₂O. This edition consists five articles on a variety of topics, written by water professionals based on solid research.
When assessing the articles, the editorial board consisting of experts from the Dutch watersector, made a selection, looking for a clear relationship with daily practice, which is the purpose of Water Matters. Research, results and findings form the basis for articles that describe new knowledge, insights and technologies with a view to practical application.
In this edition, researchers from Partners4UrbanWater, KWR Water Research Institute, Erasmus University Medical Center, Rotterdam, GGD Rotterdam-Rijnmond kick off with a study on sewage water monitoring in the Rotterdam-Rijnmond region.
Furthermore, you will find articles on a new measurement method for quality monitoring of UF membrane systems, a study on fish migration (opportunities and bottlenecks for river lamprey in the Grift), provenance and microbial safety of drinking water extraction using DNA fingerprints and a study with the research question: how should Waternet's drinking water distribution network grow with the city of Amsterdam?
Water Matters is, just like the magazine H₂O, an initiative of the Royal Dutch Water Network (KNW), the independent knowledge network for and by Dutch water professionals.
The publication of Water Matters is made possible by leading players in the Dutch water sector. These Founding Partners are Deltares, KWR Watercycle Research Institute, Royal HaskoningDHV and Stichting Toegepast Onderzoek Waterbeheer (STOWA). With the publication of Water Matters the participating institutions want to make new, applicable water knowledge accessible.

You can also read the Dutch version of Water Matters digitally on H₂O-online (https://www.h2owaternetwerk.nl/water-matters)

Would you like to respond? Please let us know: redactie@h2o-media.nl.

Monique Bekkenutte
Publisher (H₂O Foundation)
Huib de Vriend
Chairman editorial board of Water Matters

Sewage surveillance in Rotterdam-Rijnmond 2020-2022

During the first wave of COVID-19 in the spring of 2020 it proved to be possible to monitor the presence of virus particles of the new pathogen in sewage. That led to a project plan to develop sewage surveillance as a way of monitoring SARS-CoV-2 at village or neighbourhood level. That project has proven ground-breaking for the analysis of virus variants in sewage and for the analysis of the relationship between ‘sewage data’ and data on positive tests, visits to doctors and hospital admittances.

Purpose of the study: to capture the infection pyramid

The basic idea behind the study was the so-called ‘surveillance pyramid’ (see illustration 1). The top of the pyramid represents patients who have died, the second layer patients in hospital, and the third concerns patients diagnosed by a GP. The fourth layer represents infected persons who have been registered via testing centres or other health systems. The fifth layer are people with symptoms and the sixth layers are carriers, including people with no symptoms.
The top three layers are monitored using registrations by the Public Health Authority, GPs and hospitals, referred to collectively in this project as ‘above ground’, while the bottom layer, the carriers, are monitored by means of sewage surveillance, referred to in this project as the ‘underground’. At an early stage of the pandemic, it became clear that the above ground surveillance was missing much of the transmission of SARS-CoV-2.
In this project, we investigated how data from different sources and layers of the pyramid support each other. In selecting the locations for the study we endeavoured as far as possible to link layers in the pyramid by looking for sewer districts with the best possible overlap with the territory covered by a GP-practice. Data from the GGD testing centres are also associated with sewer districts through ZIP codes. Because of privacy legislation, the research team could work only with anonymised data. For data from testing centres, for example, for each test result that includes only the date and the result per sewer district, emphatically no names and addresses.

Figure 1. Infection pyramid with the data used per layer (Nieuwenhuijse and Koopmans, 2017).

When the study was set up in the spring of 2020, mass testing in testing centres was not possible yet. Therefore in selecting the locations for the study, the emphasis was on finding matches between GPs’ territories and the sewer system. Both are different from the districts and neighbourhoods used by the Dutch Central Statistics Bureau (CBS), making the choice of locations somewhat laborious. In the end, three areas in Rotterdam-Rijnmond were selected, namely Rozenburg, Ommoord and Katendrecht. In order to obtain insight into the effect of scale on the results of the study, we also selected larger areas. At the beginning of 2021, Bergschenhoek was added in view of large-scale investigation of the emergence of the Alpha variant in this location (van Beek et.al., 2022).

Figure 2. Sampling cabinet at the Katendrecht underground sewer pumping station. The equipment regularly adds a bit of sewage to a sampling vessel to get a representative 24-hour sample.

Quality assurance and normalisation

For reliable results, the sewage surveillance must meet the following conditions:
1. The sewage at the sampling location is representative for the excretion of the virus throughout the population. The most important requirement in this regard is that faeces end up in the sewage. This is usually the case, although there are exceptions in the case of incontinence or when the call of nature is answered elsewhere.
2. The population is more or less constant. This is not the case for tourist areas, for example. In Rotterdam, the opposite applies: in the 2021 summer vacation period, the number of people fell by between 10 and 15 percent.
3. The sample is representative for the sewage at the sampling location. During transport through the sewers, the virus load is exposed to all kinds of influences, such as discharge via a combined sewer overflow. Defective pumps or sewer pipes with long residence times can also lead to the sample on day X not being representative for the excretion on that day.
4. Discharge measurement is sufficiently reliable. This can be achieved by means of good control of the measuring arrangements and ongoing data validation.
5. The laboratory analysis is sufficiently reliable. Strict quality controls and double checking make this condition readily attainable too.

In the ‘Rotterdam-Rijnmond sewage surveillance’ research project, much attention was given to sampling, laboratory analysis and normalisation routines for keeping watch on the representativeness of the population’s faeces and of the results of the analysis. Normalisation involves defining the degree of dilution of household wastewater with other sorts of wastewater such as rainwater, non-sanitary wastewater and industrial wastewater. The use of different methods of normalisation alongside each other is important in this context. A difference in methods can point to a non-representative or less representative sample as a result of technical problems with pumps, combined sewer overflows or incorrect assumptions about the number of people ‘taking part’ in the virus excretion.

The normalisation methods researched and applied weekly are:
• Normalisation on the basis of discharge: throughput measurements can determine the share of household wastewater in the sample and so take account of its dilution with industrial wastewater, non-sanitary wastewater and rainfall run-off.
• Normalisation on the basis of conductivity: electrical conductivity is a good measure of the dilution of a sewage sample with rainfall run-off.
• Normalisation on the basis of crAssphage: crAssphage is a virus that infects bacteria in the human gut, and that therefore follows the same route through sewage as SARS-CoV-2 virus particles. Providing the population’s excretion is stable, this makes crAssphage theoretically very suitable as a normaliser for the number of ‘excretors’ from whom faeces have arrived in the sewage system on the day of sampling.

Figure 3 shows an example of the effect of normalisation. Particularly on rainy days, a sharp correction needs to be made for the share of household wastewater in the sample. By maintaining the three normalisation methods in parallel, it proved possible to rectify non-representative samples due to prolonged pump malfunction, or mistakes in sample taking or inadequate specimens in the laboratory method due to inhibitions, for example.

Figure 3. Normalisation of SARS-CoV-2 measurements in sewage of area INF3, see figure 4 for the period September-December 2020 (Langeveld et al., 2021)

Trend analysis

Comparing the trends in the various layers of the surveillance pyramid provides an insight into the development of the pandemic. Figure 4 gives an example of this comparison. The trend in the number of positive tests is broadly in line with the trend in the normalised measurements of sewage. At several moments, it can be seen that the sewage signal is more objective, because it is independent of test behaviour.
From mid-December 2020 anyone who so wished could be tested, and many people made use of this in order to be sure of being safe for the upcoming holiday period. This gave the impression of a new surge in the circulation of the virus, whereas the sewage data showed that there was no increase at all.
In mid-February, snowfall brought slippery conditions underfoot. This was one possible reason why the number of positive tests decreased, which again was not visible in the sewage data.
The third interesting moment was the ‘dansen met Jansen’ spike: young people were given access to nightlife after one vaccination with no waiting period, coupled with 'testing before access'. This led to a huge spike in the number of positive tests among young people who, until then, had generally not had themselves tested in large numbers, while the spike as seen in the sewage was much lower.
The conclusion is that differences between numbers of positive tests and sewage data are caused by changes in testing behaviour. To verify this, we made a statistical calculation model with which the number of positive tests is calculated as a function of the concentration of virus particles in the sewage and testing behaviour. This calculation model is very capable of calculating the number of positive tests during the whole period including the new variants such as the Alpha and Delta variants. The Omicron variant, which is associated with reduced excretion, made it necessary to correct for this reduced output in the model.
The trend analysis of the sewage data and particularly the statistical modelling have proved to be powerful tools helping to monitor the pandemic and signal changes in testing and their behaviour of the population and the virus itself.

Figure 4. Comparison of trends in positive tests (absolute and modelled amounts) and SARS-CoV 2 in sewage. Interesting moments are December 2020, when the number of positive tests increased but SARS-CoV-2 in sewage did not, and the ‘dansen met Jansen’ spike in early July 2021, when the number of positive tests rose sharply but SARS-CoV-2 in sewage much less so.

Conclusion

This large-scale and long-lasting study has shown that sewage surveillance is a mature method enabling the health authorities to monitor disease that circulate in society and end up in sewage via excretion. For COVID-19 the added value has been proven and recently there have also been positive experiences with the monkey pox virus.

Jeroen Langeveld
(Partners4UrbanWater)
Remy Schilperoort
(Partners4UrbanWater)
Gertjan Medema
(KWR Water Research Institute)
Miranda de Graaf
(Erasmus University Medical Centre, Rotterdam)
Paul Bijkerk
(GGD (Public Health Service) Rotterdam-Rijnmond)

Background picture:
Bijschrift

Summary

Sewage has proven to be an important and reliable source of information on public health in the past few years. A large-scale and long-term study in Rotterdam-Rijnmond has shown that sewage surveillance is a mature method enabling the authorities to monitor the spread of diseases that end up in the sewage via excretion. It was evident from the sewage data that in the case of a number of spikes in positive tests in testing centres, it was not that the number of infected people had suddenly shot up but rather that many people had gone to the testing centre.

References

Nieuwenhuijse, D.F. & Koopmans, M.P. (2017) Metagenomic sequencing for surveillance of food-and waterborne viral diseases. Frontiers in Microbiology, 8, 230.

Miranda de Graaf et al. (2002) Capturing the SARS-CoV-2 infection pyramid within the municipality of Rotterdam using longitudinal sewage surveillance. medRxiv 2022.06.27.22276938

Janko van Beek et al. (2022) Population-based screening in a municipality after a primary school outbreak of the SARS-CoV-2 Alpha variant, the Netherlands, December 2020 – February 2021. Plos-one 17 (10)

Jeroen Langeveld et al. (2021). Normalisation of SARS-CoV-2 concentrations in wastewater: the use of flow, conductivity and CrAssphage. medRxiv 2021.11.30.21266889

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New measuring method for quality assurance of UF membrane systems

Membranes are being applied with increasing frequency and on an ever greater scale in the preparation of drinking water. Ultrafiltration (UF) removes harmful micro-organisms such as bacteria and viruses for example. When a membrane is damaged it can be penetrated, particularly by viruses. This is obviously undesirable. How can you show in practice that the membrane installation is actually effective in keeping out viruses? And how can you monitor this?

One way of determining the efficiency with which UF membranes remove unwanted elements is to measure the turbidity of the water before and after it passes through the membrane. However, this method is not sufficiently sensitive to monitor the effectiveness of virus removal in the drinking water preparation and thus the reliability (integrity) of the UF membranes. The concentration of viruses in surface water is between 10 and 100 times greater than that of bacteria. So the efficiency of removal also needs to be higher. Therefore in order to establish whether UF membranes meet the requirements laid down for virus removal, a sensitive measuring method is needed. For this purpose so-called surrogate viruses such as the bacteriophage MS2 can be added for the measurements. This is viable for laboratory or pilot scheme testing, but is undesirable on a practical scale in view of the costs and the possible negative effect on drinking water quality.

Natural viruses

KWR has developed a patented sensitive method for identifying natural viruses from surface water. This natural virus (NV) method [1, 2] uses natural viruses as indicators of reliability (integrity) of the UF membrane, by estimating virus removal performance.

The degree of removal of micro-organisms, including viruses, is expressed by the term log reduction value (LRV). It is a logarithmic scale: 6 LRV means that one in every million viruses survives; 5 LRV means one in 100,000 survives.

Depending on the virus concentration in the water analysed, the NV method gives an LRV of 7 or more [2] with small sample volumes and without the addition of surrogates. The method has been tested at the laboratory and pilot scheme scale for suitability for systematically monitoring the integrity of UF membranes. The practical applicability of the method at full scale was then tested. Based on earlier research [2] the virus markers NV2247, NV2310 and NV2314, commonly found in surface water, were chosen. Of these three, NV2310 consistently had the highest concentration in incoming water (1 x 10⁸ V/L). For that reason, the results of this virus marker are compared with state-of-the-art turbidity measurements.

Laboratory testing of the effect of fibre damage

In order to determine the effect of fibre breakage on the integrity of UF membranes, KWR and membrane producer Pentair X-Flow carried out tests with small UF modules (one with 120 fibres, one of 0.08 m²) the fibres of which were deliberately and systematically damaged. The effect of the fibre breakage was calculated with a simple Excel model, based on existing knowledge. This included, among other things, the effect of fibre breakage on the permeability of the fibre. It was assumed that the LRV for viruses of a broken fibre was 0 and for an intact fibre 5. The model calculated that with one damaged fibre out of 120 the LRV declines sharply, from 5 to 1.3. The same calculations were also carried out for greater numbers of damaged fibres.

Then intact modules and modules with one or three damaged fibres were double-tested in the laboratory. Two different types of damaged fibres were studied: leaky fibres (0.5 mm hole) and shorter fibres (as simulation for complete fibre breakage). The incoming water was from the Lekkanaal (NV2310 1 × 10⁸ V/L). The natural virus concentrations and the turbidity were determined before and after the UF module. The intact modules gave an LRV of between 5 and 6 for NV2310 (illustration 1, top), while the turbidity test resulted in an LRV of just 2.2. Damaging just one fibre by making a hole in it led to a decline in LRV to 1 for NV2310. Further damage led to further decreases in LRV. The LRV values are in line with the decline calculated by the Excel model, although the model predicted a slightly (0.4) higher LRV over the whole range, so in other words the model systematically overestimates the LRV.

Illustration 1. LRV of intact and damaged UF module, determined with NV2310, turbidity and model calculation. Top for small module (120 fibres), bottom for 8-inch UF module (64 m²).

Also, shortening (‘breaking’) a fibre leads to a bigger decline in LRV than making a hole. However, a hole in just one fibre is enough to cause a significant decline in LRV as shown with the help of the NV method. The turbidity measurement shows comparable LRVs for the different types and degrees of damage: a value of around 1 for damage to a single fibre with a single hole. An intact fibre however gives an LRV of 2.2, as a result of which the turbidity measurement seems to show a much smaller decline than the NV method.

Pilot testing of the effect of fibre breaks

The effect of a broken fibre on LRV was also determined for an 8-inch UF module (18,600 fibres, 64 m²), based on the model calculations and the results of the laboratory tests (illustration 1, bottom graph). With one damaged fibre we saw a sharp decline in LRV to 2.5.
We then hot tapped into epoxy or outer layer of the membrane and systematically cut through the fibres in the UF module. After each such intervention the pipe was sealed and a test was carried out on three filtration cycles, each of 20 minutes filtering and half a minute rinsing (back) to remove any contamination. Sampling of the natural viruses took place half-way through the second and third filtration cycles. Tests were carried out with the intact module and with 1, 3, 5, 10 and 50 severed fibres. The incoming water was once again from a canal, the Twentekanaal, with 3 × 10⁷ NV2314 V/L. As well as the NV analysis the turbidity was also measured before and after the UF module.
Just as in the laboratory, 5 LRV can be demonstrated for an intact module (illustration 1, bottom graph). As more and more fibres are severed, LRV declines to 2; this is in line with the model calculations. Just as in the laboratory, here too the model predicts a sharp fall (to 1.2 LRV). The turbidity measurements also show declining LRV – from 1.5 to 0.9 – but the differences are significantly smaller than with the NV method.

The model calculations agree with the test results and can be used to predict trends in fibre breaks. However the calculations are based on only a small number of measurements. It would be advisable to further optimise the model with more pilot tests, to determine the effect of a damaged fibre on permeability, for example, or test various types of UF membrane with different types of water.

And then in practice

Practice measurements were taken over the course of a year and a half using the NV method at the De Gavers water production centre (WPC) (De Watergroep, Belgium). At the beginning and the end of the test period, measurements were taken in three UF blocks, each of 40 membranes (100 m³/hr, Pentair X-Flow membranes). During the test period the membranes of two of the three blocks which had been in use for twelve years were replaced with new Pentair X-Flow membranes.

Following replacement of the membranes the LRV rose to 5 (illustration 2), having previously declined to 3 (in block 2). Block 3, which was not replaced, registered an LRV of 4 at the start and end of the measuring period. The real LRV at the beginning may be higher – the method of measuring is limiting in view of the small volumes of natural viruses in the incoming water at the time of sampling. The virus concentration in the incoming water can vary depending on the location and seasonal influences, for example, as a result of which the maximum demonstrable LRV fluctuates. An LRV of between 3 and 4 at the start of the measuring period for UF blocks 1 and 2 suggests between one and three broken fibres or expanded pores per membrane module (judging by the previous pilot scheme tests). However at the pilot scale different membranes were used, so further research is needed to confirm this conclusion.

Illustration 2. LRV NV2310 of three blocks of the UF practice installation at the De Gavers WPC. In blocks 1 and 2 the membranes have meanwhile been replaced. Shaded column: the maximum demonstrable LRV (in reality possibly higher).

The supplier attributes an LRV of 4 to the UF membranes at the De Gavers WPC. The measured LRVs comply with these specifications. We wish to stress here that the NV method tells us nothing about the quality of the drinking water, not even if there are suspected broken fibres, since the UF membranes are only part of the purification system. The NV method can however provide support for operational decisions, for example on whether or not to replace membrane modules.

Conclusions and practical significance

With the new NV method, the efficiency with which intact UF membranes remove viruses can be determined without using surrogates, with a range of 5 LRV at both laboratory and pilot and actual scale. With turbidity measurements in the laboratory and in pilot tests, an LRV of only about 2 could be demonstrated.
The NV method shows that both in the laboratory (120 fibres) and at pilot scheme scale (8-inch UF module, 18,600 fibres), even with just one broken fibre, there is already a significant reduction in LRV. This tallies with the model’s predictions. Further optimisation of this model will lead to better predictions. The NV method shows the influence of broken fibres more clearly than do turbidity measurements. Users, such as drinking water companies, can use this new method to monitor the performance of the UF membranes precisely and to determine when the performance deteriorates and it becomes advisable to replace the membranes or take other measures.

Danny Harmsen
(KWR)
Emile Cornelissen
(KWR and Ghent University)
Han Vervaeren
(De Watergroep)
Stefan Koel
(Pentair X-Flow)

Background picture:
UF membrane system, De Gavers drinking water production centre

Summary

Much use is made of membranes in the preparation of drinking water. When membranes are damaged the efficiency of virus removal (log reduction value, LRV) declines as viruses pass through the membrane. In this article, the LRV of ultrafiltration (UF) membranes is described with a new method of measurement for natural viruses (NV method) in surface water (without applying surrogates). With this method the influence of broken fibres on the integrity of UF membranes was determined at laboratory and pilot scheme scale and compared with model calculations. The tests show that for an intact UF module, an LRV of 5 can be demonstrated. A damaged module leads to a reduction in LRV to between LRV 3 and LRV 1 depending on the degree and nature of the damage. The model proves well able to predict this. Measuring the integrity of a UF installation at full scale using the NV method results in an LRV of between 4 and 5. With this new method, users can accurately monitor the performance of UF membranes.

Sources

[1] European Patent Office (EPO), Method for determining the effectiveness of removal of viruses in a purification process, EP 3 486 650 A1

[2] Hornstra, L.M, Rodrigues da Silva, T., Blankert, B., Heijnen, L., Beerendonk, E.F., Cornelissen, E.R. & Medema, G.J. 2019 Monitoring the Integrity of Reverse Osmosis Membranes Using Novel Indigenous Freshwater Viruses and Bacteriophages . ES&T 5 (9), 1535-1544.

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Migration pathways and bottlenecks for river lamprey in the Grift - a study on fish migration

The river lamprey (Lampetra fluviatilis) is a fish in the lamprey family (Petromyzontidae) with a circular suction disc instead of jaws and a snake-like body. The river lamprey is an endangered migratory fish, with just a handful of spawning grounds in the Netherlands. The species is protected: it is designated as ‘sensitive’ on the Red List and is a Habitats Directive species for various Natura 2000 sites including the ‘Rijntakken’ (Rhine distributaries). From 2019 to 2022, on behalf of the Province of Gelderland and the Water Board ‘Vallei en Veluwe’, we studied migration pathways and bottlenecks to migration within the Grift drainage basin for river lamprey.

Adult river lampreys live in the sea. They are ectoparasites: with their characteristic oral disc they cling to bigger fish by suction and absorb blood and tissue. They swim to the sea from freshwater in the spring as young adults. After about a year and a half they migrate upriver to spawn. Then their entire digestive system is replaced by bigger reproductive organs to make spawning as effective as possible. River lampreys are therefore semelparous: they die after their ascent of the freshwater, regardless of whether or not they have successfully spawned. Conservation of the species is therefore heavily dependent on the accessibility of suitable spawning and nursery habitats.
After spawning, the larvae are briefly carried downstream by the flow, after which they dig themselves into soft brook and river sediments. There they feed by filtering organic waste and micro-organisms from the water (filter feeding). After five or six years they head off downstream to the sea, thereby completing the circle.

Illustration 1. Adult river lamprey are 40 to 45 centimetres long. With their characteristic oral disc they cling fast to the host. With their concentric rows of teeth they tear open the skin and feed on blood and tissue. Photograph: Jesper Berndsen, RAVON.

Impassable man-made barriers

On the way to their spawning grounds, river lamprey and other migratory fish are hindered by many man-made obstacles. Not reaching the spawning grounds or reaching them late has serious consequences, since spawning often takes place in a short time window with much competition for space and partners. The man-made structures are not just physical obstacles; they can also influence sedimentation, flow profiles, water temperature and oxygen level of the water, which may have adverse effects on migratory fish. Therefore it is important to reduce fragmentation and make promising spawning habitats accessible again. Countrywide, habitat fragmentation is a severe problem. In the Grift system, for example, a boat lock in the Apeldoorn Canal and a hydroelectric power plant (HPP) in the Oude Grift prevent free passage, but barriers are also present elsewhere, only some of which have fish passes.

Fish passes and lamprey tiles

Measures to reduce habitat fragmentation are crucial. Fish passes can be effective, but river lamprey cannot jump like salmon or climb vertical ladders like the related Pacific lamprey (Entosphenus tridentatus) of North America. Furthermore, lamprey, like eel (Anguilla anguilla) among others, have low sprint capacity. They can accelerate, but not very strongly or for very long. All these factors make many fish passes ineffective for the river lamprey.
One possible modification is mounting hard plastic studded or lamprey tiles to barriers. The studs slow the flow and provide grip for the river lamprey’s ‘burst-attach-rest’ mode of locomotion to pass barriers. This consists of a short burst followed by attachment to the substrate with the oral disc to aid recovery for another sprint and is repeated until the barrier is overcome. In the laboratory, studded tiles proved to increase passage efficiency at various flow rates and levels of turbulence (Vowles et al., 2017). In the UK the addition of lamprey tiles for facilitating upstream spawning migration of river lamprey has been studied and found to be effective (Tummers et al., 2018; Lothian et al., 2020).

The Grift basin

The Grift flows along the eastern edge of the Veluwe hills ridge and via the Apeldoorn Canal into the river IJssel (see map). This basin has long comprised important habitats for river lamprey. A preliminary study showed that streams and brooks that flow into the Grift are particularly suitable spawning and nursery habitats (De Bruin et al., 2018). Swimming up the river IJssel, the first major barrier for river lampreys on their way to those streams and brooks is the hydroelectric power plant (HPP) in the Oude Grift south of Hattem, with a height difference of four metres. There are some spawning and nursery habitats downstream of the HPP too, but these are smaller and of lesser quality. Furthermore the closely related non-migratory brook lamprey (Lampetra planeri), a Habitat Directive species of the Veluwe Natura 2000 area, resides in the brooks. River lamprey can spawn with brook lamprey and are even attracted towards brook lamprey by their release of pheromones.

Illustration 2. The River Grift and surrounding area. River lamprey migrate from the IJssel (yellow) via the Apeldoorn Canal (blue) and the Oude Grift, which runs parallel to it, towards the Grift (green) and its tributaries (pink). Red dots: PIT tag stations in 2020-2021, at the weir and in the three tributaries. Blue dot next to HPP = release location 2019-2020. Orange dots = release locations 2020-2021. (WKC = HPP; sluis = lock; stuw = weir; monding = mouth.)

In order to investigate how far upstream river lamprey migrate, 95 river lamprey were caught in the Oude Grift (downstream from the HPP) by means of electrofishing in December 2019. We inserted PIT (Passive Integrated Transponder) tags into them and once they had recovered from further handling (determining length and weight) they were released into the Apeldoorn Canal upstream of the HPP (illustration 2). As soon as these tagged specimens came close (about 1 metre) to the antennas of the PIT detection station near the Bonenburg Estate, their unique number was recorded as well as date and time.
The lock in the Grift near the Bonenburg Estate proved to be an impassable barrier for upstream migration lamprey in the winter of 2019-2020. Although 27 of the 95 tagged river lamprey (28%) reached the Bonenburg weir, some of them within 48 hours, not a single one managed to pass the weir. In principle they may have spawned in the stretch of the canal where they were released. Since no individuals were found with a mobile PIT scanner in the 150 metres below the weir, they evidently left the Grift.

Illustration 3. Bonenburg weir is a relatively small obstacle for migratory fish, which sometimes is even under water. To the left on the weir next to the lamprey tiles, the detection station. With two detection antennas we distinguished between the route via lamprey tiles and via the weir. Photograph: Jeroen Tummers, RAVON.

Lamprey tiles as a solution

To investigate measures of improving passage over the Bonenburg weir, in the winter of 2020-2021 it was equipped with a slope with lamprey tiles (illustration 3). This time we caught 101 adult river lamprey in the Oude Grift and tagged them. Of these, 44 and 57 individuals were released respectively downstream and upstream of the Bonenburg weir. Detection stations recorded the passing lamprey both at the weir and further upstream at entrance to the streams and brooks.
In the monitoring period, of the 44 river lamprey released downstream, 19 individuals passed the weir. Of the total of 76 river lamprey that either passed the weir (19) or were released upstream of it (57), 28 were detected in the upstream brooks with suitable habitat. Of these, 21 specimens were found in the Horsthoekerbeek.
The total number of passages of tagged individuals over the weir was 51, of which 30 via the weir itself and 21 via the lamprey tiles. The number of passages is higher than expected because current velocity may displace river lamprey back over the weir, and because lamprey may have been detected both on the lamprey tiles and on the weir.

Spawning period

In the 2021 spawning season, mid-February to mid-April, together with members of a local fish conservation group, we investigated the presence of river lamprey in the brooks and at the catch location in the Oude Grift using a mobile PIT tag scanner. We found 13 river lamprey, all in the Horsthoekerbeek, also upstream of the fixed PIT station operational at its entrance.
In January 2022 a last catch took place. We caught 157 river lamprey in the Oude Grift and released them upstream of the Bonenburg weir in the Grift. Judging by the results of the previous study period, it is likely that a good proportion of these river lamprey reached the spawning grounds in the streams and brooks and successfully spawned.

Conclusion

This study shows where the problems and opportunities lie for bolstering populations of river lamprey and brook lamprey in the Grift basin, and provides some concrete ideas for meeting the KRW objectives and the Natura 2000 conservation goals.
For the conservation and expansion of populations of river lamprey, greater insight is needed into its migration. This multi-year study has shown that river lamprey favour migration from the IJssel to the Grift system, but that the ascent is hampered by (nearly) impassable man-made structures (the lock at Hattem, the HPP in the Oude Grift and the Bonenburg weir). Lamprey tiles proved relatively effective at one location, but higher efficiency is needed. Targeted modification of the man-made structures or the installation of bypasses is necessary to facilitate passage, if possible without facilitating invasion by undesirable exotic species (such as various kinds of goby) via the Apeldoorn Canal.
Elsewhere in the Netherlands life is also difficult for the river lamprey. In the Meuse, river lampreys are hindered by large weir complexes that deny them access to the Grensmaas (‘Border Meuse’) and the ‘Maas bij Eijsden’, where it is designated as a protected species. Furthermore, in the Roer and Geul tributaries, where the brook lamprey is a target species, there are opportunities for conservation of the river and brook lamprey.

Jeroen Tummers
(RAVON)

Summary

In a three-year study in the Grift drainage basin in Gelderland, river lamprey proved either unable to reach their spawning grounds or able to do so only with difficulty. Reasons are poor connectivity by man-made structures such as a boat lock, a hydroelectric power plant and weirs. River lamprey are poor swimmers, for which large barriers in particular but also many fish passes are impassable. A slope with lamprey tiles installed on a trial basis at a low weir proved relatively effective, but for much-needed protection of this Habitat Directive species, targeted adaptations of all man-made structures are necessary.

Sources

Bruin, A. de, et al., 2018. Study of river lamprey in the Oude Grift. RAVON Nijmegen, report 2017.144.

Lothian, A.J. et al., 2020. River connectivity restoration for upstream‐migrating European river lamprey: The efficacy of two horizontally‐mounted studded tile designs. River Research and Applications 36(10): 2013-2023.

Russon, I.J. & Kemp, P.S., 2011. Experimental quantification of the swimming performance and behaviour of spawning run river lamprey Lampetra fluviatilis and European eel Anguilla. Journal of Fish Biology 78(7): 1965-1975.

Tummers, J.S. et al., 2018. Enhancing the upstream passage of river lamprey at a microhydropower installation using horizontally-mounted studded tiles. Ecological Engineering 125: 87-97.

Vowles, A.S. et al. 2017. Passage of European eel and river lamprey at a model weir provisioned with studded tiles. Journal of Ecohydraulics 2: 88-98.

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DNA fingerprints show origin and microbiological safety in drinking water production

The microbiological quality of drinking water from groundwater is monitored using various indicators. This tells us whether the water is faecally polluted, but not where such pollution comes from. Vitens and Deltares, with the collaboration of Wageningen University, have investigated whether DNA fingerprinting can detect faecal bacteria and identify the source. With that information, drinking water companies would be able to quickly take targeted measures.

Groundwater naturally contains few bacteria, making it in principle highly suited to the production of drinking water. However with some groundwater extraction, there is exchange with surface water. Such is the case for example if the production site is supplied through an infiltration basin, or if it is located close to a river and has a water inflow from the river. The infiltration of surface water to groundwater increases the chance of micro-organisms, including pathogenic or faecal ones, entering the pumped up water. For this reason the quality of the intake water and the wells is subject to enhanced monitoring. Culture-related methods test for several microbial indicators including E. coli, somatic coliphages and Clostridium perfringens bacteria.

For E. coli, the RT-PCR (reverse transcription polymerase chain reaction) screening method has been in use since 2019 alongside the classic culture methods. This method has been developed by the cooperating drinking water laboratories. The advantage of the RT-PCR method is that it shows relatively quickly whether there is faecal pollution present. However RT-PCR does not show where the pollution comes from. Does it come from the surface water, or is there another reason for its presence? Drinking water companies need more information on the potential sources of microbiological pollution in order to be able to take more targeted measures faster.

Is Next Generation Sequencing the answer?

Next Generation Sequencing (NGS) is a method for making a ‘DNA fingerprint’ of the drinking water, which gives a practically complete picture of the microbiological composition of the water that is tested. This makes it possible to monitor bacteria from the surface water throughout the entire drinking water production process and to flag up any changes in good time.
Does this also mean that NGS can be used to establish the origin and microbiological quality of the water used as source for producing drinking water? Is the method suitable for use with relatively pure water samples, and can the data be easily and correctly interpreted? The question is pertinent because with NGS huge volumes of data are collected and the question arises as to how they can be converted into information that can be used to give greater assurance regarding the microbiological safety of drinking water.
These questions were the focus of the two-year study ‘AlTeRnative indicAtor of the origins of miCrobially pollutEd drinking wateR’, or ‘TRACER’ for short.

Four testing sites

Four production sites were chosen for the TRACER study, all four of them influenced by surface water: Engelse Werk, Vechterweerd, Epe and Schalterberg. In the spring of 2019 and 2020 samples were taken from the clear water reservoirs (drinking water), from various wells (groundwater), and from the surface water located nearby. Two different NGS techniques were used to establish the microbiological composition of the samples, of which there were 54 in all. 16S rRNA amplicon sequencing and metagenomic sequencing. The former technique detects only 16S rRNA genes as markers. The latter detects all the DNA that is present, thus including all other living organisms in the water.
The data from the metagenomic sequencing were elaborated in collaboration with Wageningen University’s Microbiology Laboratory. Among other things this allowed us to make use of their Bio-IT pipeline in order to properly identify all DNA sequences and compare them with one another.

DNA fingerprints

The marker genes for 16S rRNA look different for each type of bacterium. This makes them a suitable indicator for determining which bacteria are present in the samples and to what extent. The NGS results were first compared with 16S rRNA genes since bio-IT methods were already available for this. The results were shown in terms of genes in bar charts by location (illustration 1). The charts thus give a picture of the microbiological composition by location, by sample and by type of water.

Illustration 1: Microbiological DNA fingerprints of individual water samples based on the 16S rRNA gene. Water samples are GW = groundwater (well), DW = drinking water, OW = overground (surface) water. The colours reflect the relative contribution of different microbial species.

Principal component analysis (PCA) is then used to show the relationship between the types of sample for each location. As part of this process the fingerprints of the individual samples are compared with one another. For the Engelse Werk and Vechterweerd sites it can be clearly seen (illustration 2) that the samples are clustered according to their various origins. The origin (drinking water, surface water, groundwater) can thus be traced on the basis of the microbiological composition. To a lesser extent this also applies to the Epe site. However, for the Schalterberg site (surface water infiltration) the fingerprints of samples from different sources are far more similar to one another. The influence of the surface water on the drinking water produced is relatively great here in comparison with the other extraction sites. An appreciable number of the micro-organisms from the surface water were seen to have found their way into the drinking water at this location. This is striking, in that the picture at the Epe location is different, even though Epe also makes use of an infiltration basin. The fact that the microbiological composition of the drinking water produced in Epe is far more similar to that of the groundwater points to the filtration effect of the soil in Epe being better than it is in Schalterberg.

Illustration 2. PCA plot of the four locations studied, bringing together the information on the microbiological composition of samples from different sources and from two rounds of sampling.

Deriving a quick indicator

In establishing the bacteriological differences among surface water, groundwater and drinking water, only the 16S rRNA gene was used to fingerprint them. The differences based on this gene prove sufficient to be able to distinguish the types of water from one another. The total metagenome of the water sample of course contains many other genes, a number of which can potentially be used as a quick indicator. For example, algae could be a logical indicator for surface water.
A targeted analysis of genes that are present exclusively in a single type of water can provide a quick answer as to whether exchange takes place with that specific type of water. The relative presence of a hundred different genes was investigated for all samples (metagenomic analysis), and shown in a heat map. The heat map uses colours to indicate the relative presence of each gene by sample. The drinking water samples show a recognisable profile that is easily distinguishable from that of the groundwater and surface water samples. The psbV gene (cytochrome c of cyanobacteria), is particularly noticeable in drinking water samples and can thus be used as a quick indicator of the influence of surface water on groundwater. Meanwhile research has started on the feasibility of using this gene as an indicator.

What have we learnt?

NGS gives a good picture of the microbiological composition of the groundwater used as a source of drinking water and of the origin of the water. Contrary to expectations, it is not necessary to analyse a complete metagenome for this; the simpler 16S rRNA amplicon sequencing method provides the answer. This is a welcome finding, because the elaboration of the sequence data in particular is less complicated in the case of 16S rRNA amplicon sequencing. The elaboration of a metagenome analysis is rather specialized work.
In order to establish the presence of a given type of water, a metagenome analysis is useful if there is a specific indicator (for example, genes involved in the conversion of certain nutrients in groundwater, for which a targeted method of analysis such as qPCR can be developed.)

The TRACER project did not provide any information on the presence of specific pathogenic micro-organisms in the samples, even though the microbiological composition was shown. Identification of the micro-organisms present was mostly to class or family level, because the resolution of the DNA sequences is still too limited to be able to identify bacteria to species level.

Follow-up study

The results of the TRACER study have led Vitens to explore the extent to which increased understanding of microbiological composition with the help of NGS can be used to establish stability of the water quality in groundwater extraction facilities. The MIKROWSEQ project that is meanwhile under way should provide some clarity on this. Over a period of one year this project uses NGS or qPCR to show the microbiological composition of the groundwater at four potentially vulnerable groundwater extraction sites every two months. At each extraction site this is done at several points of the flow path, so that the bacteria’s routes can be followed. By regularly evaluating the stability of the groundwater quality, where possible in combination with the composition of surrounding surface water, any changes in the groundwater quality can be detected at an early stage.

Bas van der Zaan
(Deltares)
Marcelle van der Waals
(Deltares)
Anneke Roosma
(Vitens)
Adrie Atsma
(Vitens)
Merijn Schriks
(Vitens)

Background picture:
Molecular technics help producing microbiologically safe drinking water

Summary

To establish its microbiological quality, drinking water is monitored for several indicators. The indicators show whether the water is faecally polluted, but not the origin of the pollution. This makes it difficult to take targeted measures.

This two-year study, called TRACER, shows that next generation sequencing (NGS) or DNA fingerprinting gives a more complete picture of the microbiological composition of water, in this case drinking water, and of where the pollution might originate. NGS can thus be used to investigate the origin of pathogenic microbiological contamination. On this basis, drinking water companies can take targeted measures to protect the quality of drinking water.

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How can the growth of Waternet’s drinking water distribution network keep pace with that of the city?

Like many other cities, the Amsterdam conglomeration is faced with rising demand for water as a result of population growth and developing industry. Expectations are for water demand to grow even more in hot, dry periods as a result of climate change. The current production and distribution network was not designed to cater to this new level of growing demand. Thus, Waternet is faced by the challenge of how to develop a good approach to growth.

Amsterdam’s water supply currently comes from two production sites, one to the west and one to the east of the city. Waternet intends to meet increasing demand mainly from the east, because that will lead to a better balance between the two production sites. Apart from the capacity of the production sites, the distribution network also needs to be expanded. There are various possible ways of doing this. As a first step in the process of deciding on the best solution, in collaboration with KWR Waternet drew up a definition of the problem, and subsequently worked through a large number of possible solutions with the Gondwana numerical optimisation platform [1]. The horizon for the whole exercise was 2050.

Illustration 1: The study area took in Amsterdam, Amstelveen and Ouder-Amstel. The illustration shows the existing and planned pumping stations, the planned urban expansions and the existing distribution network.

Solutions through numerical optimisation

KWR has developed the Gondwana computational software tool in order to automatically and systematically answer all kinds of design questions regarding the network (numerical optimisation). Gondwana combines a genetic algorithm with hydraulic computation to automatically generate a large number of possible design solutions. It works as follows:

The starting point is the existing network. By making some arbitrary changes to it, a first ‘generation’ of potential new networks is generated.
Examples of changes include: changing the diameter of some pipes on the basis of a list of available diameters, ‘opening up’ potential extra pipes, or changing completely different design aspects such as installing a particular sensor. This first generation of networks is then worked through and assessed with regard to certain pre-established conditions, such as certainty of supply and performance criteria such as costs, and pressure problems resolved. Networks that do not meet the hard conditions stipulated are rejected. Networks that do meet them are compared with each other on the basis of performance criteria. The best performing networks are used to generate a new generation of solutions (by adjusting improving more pipelines and combining networks). In the same way, the new generation is then worked through and assessed too. In this way, generation after generation, the collection of solutions becomes better and better. Ultimately this leads to a collection of possible ideal networks: a Pareto front. The user can compare the different designs on the Pareto front and decide to what extent an improvement in one objective justifies a concession on another.

The technique of designing solutions with numerical optimisation is not new. There are many scientific publications on the subject. These publications deal mainly with smaller standard networks. Practical applications with existing extensive networks are still only available to a very limited extent, however. The difficulties of applying it in practice are twofold: first, translating the problem into mathematical form, and then interpreting the results, taking account of the assumptions made. Collaboration between Waternet (problem owner) and KWR (translation of the problem into a mathematical definition of a problem) is thus essential and requires mutual consultation. In order to transform Waternet’s problem into a mathematically solvable problem definition, it is necessary to jointly define goals, conditions, decision variables and the starting situation of the network.

Defining the starting situation

The first step in defining an optimisation problem is a good description of the starting situation. For this we chose to give a simplified description of the current network, with as consumption the expected peak consumption of 2050. The model was then expanded with nodes (a distribution network exists out of pipes and nodes. Nodes are points where the demand of houses and or businesses are concentrated) with extra consumption (see illustration 1) representing the urban expansion plans. Doubling of the current production capacity in the east and a possible new pumping station in the north of the city were also incorporated as part of the starting situation. Finally a few possible future pipelines (local solutions) were included in the model with an effective diameter of zero. These local solutions can be activated during the optimisation by increasing the diameter if they contribute added value to the solution. This gives Waternet the possibility of assessing the effectiveness of the local solutions and finding an optimal combination. In this optimisation, the adjustment of the diameters of the local solutions and the existing pipelines serves as the decision variable: that which can be adjusted by the algorithm to generate new potential solutions.

Defining objectives

Waternet’s goal is to maintain certainty of supply through to 2050 and beyond. More precisely, to ensure that at the peak time on the peak day in 2050, enough water can be supplied with sufficient pressure. Analyses of the current network, adding in the expected extra demand of 2050 (so including urban development as well as the increase in demand for water due to climate change) show that the current network is incapable of dealing with it and that there are many points where the necessary pressure is not attained. Because in the 30 years to 2050 Waternet will have only limited room in terms of time, money and people, with which to adapt the network, we also looked at which adaptations were the most effective. Or to put it another way: how can we resolve as many deficient pressure points with as few changes as possible. The optimisation chosen therefore assesses the solutions by reference to two objectives:
• minimising the sum of pressures below 230 kPa (33.36 psi), and
• Minimising the number of kilometres of pipe that need to be adapted.
This gives an insight into how much needs to be invested/adapted to attain the desired pressure performance.

Defining the constraints

The network must attain the objectives set but also within a number of constraints. Waternet intends to meet the increasing demand mainly from the east side of the system, because that will lead to a better balance between the two production sites. An analysis of the network shows however that, because of the network’s current hydraulic resistance, it would only be possible to supply the extra water from the western production site. If supply from the west were delimited and equal proportions forced between east and west, an unattainably high pressure would be needed in the eastern pumping station. One of the constraints is that with equal distribution the pressure at this supply point should not exceed 350 kPa (50.77 psi). At the same time, Waternet wishes to take explicit account of security of supply in certain situations of serious disruption of the distribution system, such as non-availability of a pumping station or an important pipeline. To take account of this, 21 disruptive scenarios were elaborated and the six with the most adverse impacts selected for inclusion in the optimisation. The performance of the potential networks in these adverse scenarios is then adopted as a constraint.

Results of the optimisation

With the starting situation, decision variables, objectives and constraints described (table 1), the optimisation platform (Gondwana) can now start calculating.


The optimisation gives 48 solutions per generation and a total of 4,500 generations. This means that a total of 216,000 potential network models were calculated. This ultimately gives a Pareto front of optimised networks, with some networks scoring better for pressure (illustration 2, horizontal axis) but needing more kilometres of adaptation (vertical axis) or vice versa. Within the possibilities indicated by the Pareto front, Waternet has a preference for solutions in which between 100 and 300 kilometres of pipe are adapted. There are two reasons for this. Firstly, solutions involving more than 300 kilometres of adaptation require extra investment and hardly perform any better as regards pressure, while at under 100 kilometres with each small adaptation a respectable profit can still be made. Secondly, 100-300 kilometres of adaptation in the next 30 years means a challenging but not impossible task for Waternet.

Illustration 2: All optimal models and their scores for the two goals defined

On the Pareto front, there are 156 potential networks with between 100 and 300 kilometres of adaptations, all with different performances as regards pressure and different numbers of kilometres to be adapted. To determine which pipes are it is important to tackle, for each pipe we calculated the number of solutions in which that pipe was adapted. The Pareto front also shows which previously devised local solutions will actually be selected and are thus effective in resolving sub-standard pressure. Some local solutions are not much chosen (because there are better ways), while others are nearly always used.

Thanks to this study, Waternet has a better view of the investment needed in order to continue to assure supply in 2050. It is now clear which existing stretches of pipeline must be expanded and which local solutions have added value. With this knowledge, packages of measures can be put together and elaborated.

Bram Hillebrand
(KWR)
Ina Vertommen
(KWR)
Karel van Laarhoven
(KWR)
Joost Louter
(Waternet)
Michael Preng
(Waternet)

Background picture:
Laying water transmission pipelines for Waternet

Summary

Waternet is faced with the challenge of keeping the growth of their distribution infrastructure in pace with that of the city. Together with KWR, Waternet restated this challenge as a mathematical problem that could be solved using the Gondwana numerical optimisation platform. The iterative, systematic approach delivers credible and usable outcomes. The challenge of maintaining ‘security of supply’ in 2050 is tough, but not impossible. It turns out that a large part of the solution may tally with the planned replacement programme. At the same time, it became clear which new trajectories can best be considered.

Sources

[1] Practical Application of Optimisation Techniques to Drinking Water Distribution Problems (easychair.org)

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