Four areas that together form a complete picture of your network: hydraulic and process modelling, GIS and data, monitoring and reality capture.
We build hydraulic models of water supply networks for master planning, development assessment and operational optimisation. We model pressure conditions, flows, capacities and the network’s sensitivity to changes in demand, valve configuration or pumping regime. For developers we prepare connection and sizing assessments with clearly defined boundary conditions and alternatives.
For utilities we also address fire-flow scenarios, failures and inter-zone connections, so the impact on supply and pressure can be estimated. Where data allow, we add water quality as a supplementary layer, or propose which measurements are needed to increase confidence. We prepare models so they can be updated continuously and reused — not as a one-off calculation.
We assess sewer systems dynamically, focusing on rainfall-runoff processes, sewer capacity and interaction with structures (pumping stations, tanks, WWTPs). For CSOs we analyse overflow frequency and volume, identify limiting reaches and propose alternative measures including their comparison.
A major topic is I/I (inflow & infiltration), where we combine modelling with measurement analysis to separate base flows from rainfall contributions. In more complex areas we can couple a 1D sewer model with 2D surface flow to assess local flooding and risk. We always tie the model to a decision: what the client should change, where, in what order and with what effect.
For WWTPs we use process modelling to assess the existing technology, future load scenarios and the effectiveness of proposed measures. The goal is process stability, robustness against fluctuations and optimised operating parameters — not an “ideal” state under laboratory conditions.
Models make it possible to test interventions without risk to real operations and to compare alternatives on a common basis. Where data are available, the work can progress towards a digital twin of the process line that supports continuous setpoint tuning.
For pressure pipelines and pumping systems we also address transients (water hammer), a frequent cause of failures and hidden damage. The analysis covers pump trips, valve closures, transitions between operating regimes and potential sub-atmospheric pressures.
The output is an identification of risk states and a design of protective measures. For utilities this is a practical tool to reduce failure rates; for developers and designers it is an essential step towards a safe design.
For complex hydraulic nodes or process structures where a 1D schematic is not enough, we apply 3D (CFD) modelling. It is used mainly to understand local losses, recirculation, undesirable flow patterns or behaviour at high flows.
CFD helps validate proposed modifications to structures in order to reduce the risk of surcharging or operational problems. The outputs complement the network model — detail for the “critical spot”.
We treat GIS as the primary layer of asset records and topology, without which quality modelling cannot be done sustainably. We handle cleaning, consolidation and logical checking of GIS data (nodes, connectivity, attributes, directionality).
We configure data models so they can be synchronised efficiently with the hydraulic model and so that network changes do not “break” the model. For utilities this means less manual work and a lower risk of errors during updates.
When digitalising water systems, the problem is often not a “lack of data” but its quality, consistency and usability. We build data pipelines (ETL) for importing, cleaning and regularly updating data from SCADA, measurements and other sources.
We set rules for units, timestamps, missing values and anomaly detection so the data are reliable for calibration and decision support. An audit trail matters too — it must be clear which data were used, where they came from and what transformations they went through.
A real step towards digital twin solutions requires connecting the hydraulic or process model with operational data. In practice this means mapping SCADA tags onto model objects and defining update cycles and the rules under which the model is considered “valid”.
We configure the logic of model boundary conditions so incoming data cannot create inconsistent states. Continuous validation is part of this — comparing the computation with measurements and identifying where the system has deviated.
We translate model and data outputs into KPIs and reports usable by operators and management alike. These are typically map layers of risk, surcharging, pressure problems, sensitive locations or the impacts of measures.
For utilities we prepare decision dashboards that allow rapid assessment of network status and scenario impacts. The emphasis is on interpretation: numbers need context, an uncertainty range and recommended next steps.
We always design a measurement campaign around what the model or analysis needs to prove — calibration, capacity verification, I/I, pressure conditions or emergency scenarios. We select sites and measurement types so they capture the decisive flow relationships and critical nodes.
We define the time resolution, campaign duration and quality-control approach so the data are a usable signal rather than “noise”. The aim is a data foundation that increases model accuracy and reduces decision uncertainty.
If the model is to serve operations, a one-off measurement is often not enough and a continuous data flow should be set up. We help define which quantities are worth transmitting via telemetry and how to integrate them into the data environment.
We address the practical aspects: latency, outages, signal quality and the rules by which the model or dashboard handles them. Such a setup is a prerequisite for an operational twin, where the model is updated regularly and used for decision-making.
We process data systematically: unit normalisation, checking for time offsets, removing clearly erroneous values and annotating events (interventions, failures, regime changes). We then define calibration metrics and targets according to the type of system.
Calibration is not a one-off “fit” but an iterative process in which the model must match key operating regimes while remaining stable. For digital twin solutions we also prepare the logic of continuous validation, so the model can stay “alive” even as the network or operations change.
A new, distinctive differentiator in our portfolio.
In process facilities (WWTPs, pumping stations, valve chambers) the documentation often does not match reality or is hard to use for maintenance. Reality capture (laser scanning, or photogrammetry) makes it possible to create accurate “as-built” documentation quickly and in high detail.
Such an output suits clash detection, reconstruction planning and above all day-to-day orientation within the facility. We can prepare the captured data so it can be reused for a 3D model and subsequent integration into GIS/asset management.
The Scan-to-BIM-to-GIS workflow is a way to turn reality capture data into a BIM model and then convert it into 3D GIS layers that are usable in practice. It makes the most sense for “indoor” assets inside facilities, which standard GIS often does not cover accurately enough.
In 3D GIS, asset information can be attached and linked to the maintenance system. This creates a “single source of truth” where an operator or maintenance technician can find a specific element, its history and related documents directly from the map or model.
