Water bodies are dynamic systems. Water levels, discharges, temperatures, oxygen conditions, nutrient concentrations and biological processes change over the course of the day and the year. Heavy rainfall, dry periods or unusually warm summers can also influence measurement results considerably.
A single measurement before and after a measure is therefore usually not sufficient. Without a baseline, it is difficult to tell later whether a change is actually due to the measure implemented, to natural fluctuations or to external influences.
A good baseline therefore does not only capture a single point in time. It describes the initial state of a water body spatially, temporally and functionally.
These include:
Only against an initial state described in this way can later changes be assessed transparently.
“Such measurements as you are taking right now – and especially being able to take them continuously – are extremely important.”
– Limnologist in interview
MRV stands for Monitoring, Reporting and Verification – for recording impacts on an ongoing basis, presenting them in an understandable form and assessing them verifiably. For us, MRV is more than a report at the end of a project. It is an end-to-end process.
Relevant water-body data are collected continuously or at suitable intervals. Alongside fixed monitoring stations, profiling measurements, laboratory analyses, satellite data, existing monitoring networks and further data sources can be integrated.
The data collected are quality-assured, consolidated and translated into understandable key figures, maps and reports. Developments and deviations become visible without obscuring the complexity of the water body.
The results are made verifiable using methods, indicators and reference values defined in advance. Data provenance, calculation steps and model assumptions remain traceable.
The result is robust evidence of impact – for project management, funding bodies, permitting authorities, financing partners and other parties involved.
Together we clarify which problem is to be solved and which change is to be achieved. From this we develop a traceable impact chain:
Measure → change in the water body → measurable benefit
This can be, for example, a better oxygen supply, lower nutrient loads, fewer algal events, more stable water quality or avoided greenhouse-gas emissions.
We review existing monitoring points, historical data, reports, maps, satellite data and further sources of information. Data gaps become visible early and can be closed in a targeted way.
In doing so, we do not treat a water body as a uniform surface. Relevant areas are delineated as polygons or functional water-body zones – for example inflows, deep zones, shore zones, pollution hotspots or intervention areas.
The following is defined for every project:
The result is a project-specific baseline: technically sound and at the same time economically feasible.
WAMO water monitoring stations deliver high-frequency data on water quality and water quantity. Depending on the project, they are combined with existing monitoring networks, manual samples, profiling measurements, remote sensing or external data sources.
What matters is not the largest possible number of sensors, but a monitoring network that can reliably capture the relevant change.
Readings alone do not yet explain why a water body is changing. We therefore combine data with biogeochemical understanding, spatial analysis and suitable models.
This makes it possible to examine the interplay between hydrology, temperature, oxygen, nutrients, biological activity and the water-carbon cycle. It creates the basis for planning measures better, adjusting them at an early stage and placing their impact in a sound technical context.
Baseline and project data are evaluated on a comparable basis. Seasonal developments, extreme events and other external influences are taken into account in the interpretation.
The results are presented in reports, key figures and maps. Data sources, processing steps, assumptions and model versions remain openly accessible. A complete audit trail is thus available for later audits and verifications.
| Parameter | What it shows |
|---|---|
| Oxygen | Indicator of stress, prerequisite for life |
| Secchi depth | Correlate of algal mass |
| Temperature | Driver of metabolism and algal growth |
| pH value | Algal activity and buffer capacity |
| Conductivity | Salt inputs, evaporation |
| Phosphorus | Most important nutrient driver of eutrophication |
| Nitrogen | The second central nutrient parameter |
“Having continuity is important – water biologists normally only come out at certain time intervals.”
– Limnologist in interview
Depending on the measure and the type of water body, different dimensions of impact can be considered.
Inland waters are an important part of the water-carbon cycle. Oxygen-poor zones, high nutrient loads and the decomposition of organic matter can promote the formation and release of methane.
The climate effect cannot, however, be derived reliably from individual water-quality readings. This requires a robust baseline, suitable process data and scientifically traceable models.
The Advanced Lake Biochemistry Model (ALBM) brings together relevant biogeochemical processes and leading indicator parameters. Methane emissions are not presented as a directly measured quantity unless direct gas measurement is carried out. Instead, they are determined using a model-based approach, including the assumptions and uncertainties this entails.
Step by step, the climate effect of measures such as de-sludging, restoration, altered through-flow or optimised turbine flows can thus be assessed against the baseline. In the longer term, such evidence can also become relevant for climate-finance and certification models.
Initial survey of water quality, sediment and biodiversity. A prioritised bundle of measures for your lake.
WAMO on site, SWIM remote. Dashboards for the team and for decision-makers – with configurable thresholds.
Annual report on algae, sludge and usability – including budget recommendations and trend analysis.
Optional: methane and biodiversity pathways, packaging for certificate platforms (carbon credits).
Impact targets and indicators for the WFD, climate adaptation, LIFE and EAFRD. We support you through the application.
Everything from a single source – scope and terms per lake and year on request (excl. sensors / capex on demand).
Service package per lake and year – scope and terms on request (excl. sensors / capex on demand).
Five steps – Discover, Measure, Report, Verify, Connect – grouped into two phases: science and market. Click a step to open the detail text.
The number nobody knows: at least 1,300 Mt CO₂ equivalent per year from inland waters (Global Carbon Project). Using GWP-84 (20-year methane horizon), up to 14,700 Mt – comparable to a significant share of global fossil emissions.
What has changed: methane is produced not only in oxygen-poor sediment layers (the old assumption), but also in oxic surface layers – through phytoplankton photosynthesis (IGB Berlin / Prof. Hans-Peter Grossart, Nature Geoscience 2021).
The lever lies in trophic state: between a nutrient-poor and a hypertrophic water body there is roughly a factor of six in greenhouse-gas emissions, carried above all by methane (DelSontro et al. 2018). Reducing nutrient inputs therefore prevents not only algal blooms, but emissions as well.
Hesse-specific savings potential: 1.1 Mt CO₂ per year · €82.5 m in certificate value.
Sources: DelSontro et al. (2018) Limnology and Oceanography Letters · Bartosiewicz et al. (2021) Global Carbon Project · Grossart et al. IGB Berlin
An algal bloom does not develop overnight – it grows over two to three weeks. The sampling frequency determines when it first becomes visible in the data. With monthly sampling, you typically only see it once it is already twelve days above the threshold. With continuous sensor measurement, you see it in real time. The difference is the warning lead time drinking-water treatment can work with – or not.
Twelve days during which algal toxins have already crossed the threshold without anyone knowing. With continuous measurement, this latency shrinks to 60 minutes – the frequency at which WAMO transmits data.
Among other applications, a project-specific MRV concept can be used for:
The monitoring and evaluation design is adapted in each case to the measure, the type of water body, the available data and the verification requirements.
In the Smart City model project “meer.zukunft.seen” run by IKT-Ost AöR, we equipped the lakes of two districts with 21 WAMO stations by spring 2025. Augustus, the first, has been running in Tollensesee since August 2024. The data flows directly to public health and environmental agencies – to avoid manual sampling, give early warning of algal blooms and strengthen the region's climate resilience.
Federal funding via the BMWSB. Sensor partners BadgerMeter and S::CAN. One of 73 Smart City model projects in Germany.
A baseline developed early does not only improve the later evidence of impact. It already helps in deciding which measure makes sense where.
This enables project developers to:
MRV thus becomes an instrument of project development – rather than merely a documentation obligation once the measure has been completed.
We combine water-body monitoring, data integration, modelling and technical evaluation in one end-to-end approach. Existing data and monitoring points are consistently included.
Our aim is a system that stands up to scientific scrutiny, remains understandable for everyone involved in the project and is practical to use in day-to-day operation. Individual readings thus become a coherent picture of the water body – and a measure becomes a demonstrable improvement in the condition of that water body.
The earlier the monitoring design, the initial state and the impact indicators are defined, the stronger the later evidence. We support you in setting up your project on a data-based, verifiable and future-proof footing from the start.
Let us clarify together which data your project needs and what its impact will later be measured against.
