EXPERTISE / HYDRAULIC MODELLING
Hydraulic Modelling of Water Distribution Networks
I specialize in modelling, calibration and analysis of water distribution networks, combining hydraulic simulation with pressure and flow monitoring, GIS data and operational information to understand system behaviour and support practical engineering decisions.
Water distribution network modelling
My work includes building and analysing hydraulic models of pressurized water distribution systems using network geometry, demand data, asset information and field measurements.
HYDRAULIC MODEL CALIBRATION WORKFLOW
From field data to a validated hydraulic model.
A practical calibration workflow for water distribution networks, connecting network data, field measurements, operating conditions and hydraulic assumptions before model parameters are adjusted.
01What is hydraulic model calibration?Align simulated behaviour with observed field conditions.+
Calibration compares modelled pressure, flow and storage behaviour with monitored values, then refines uncertain parameters while preserving physically realistic network behaviour.
02Data required before calibrationBuild a reliable hydraulic baseline before changing parameters.+
- Network: topology, connectivity, node elevations, pipe length, diameter and material
- Demand: base demand, demand allocation and temporal demand patterns
- Boundary conditions: reservoir heads, tank levels/geometry and source conditions
- Operations: pump status/schedules, valve status, PRV settings and control rules
- Field measurements: pressure and flow observations over the selected calibration period
Minimum calibration evidence: at least one reliable pressure dataset and one representative flow or boundary-condition dataset for the same calibration period.
03Pressure vs hydraulic headSeparate elevation effects from available pressure.+
A large elevation difference does not automatically mean the same pressure is available at the node. Friction losses, demand, controls and dynamic system behaviour reduce the actual pressure available.
04Demand pattern calibrationMatch temporal demand behaviour before forcing hydraulic parameters.+
Compare observed network inflows and demand-sensitive pressure behaviour against the model. Refine base demands, allocation assumptions and time patterns before adjusting roughness or leakage.
05Pipe roughness calibrationUse roughness as a hydraulic parameter—not as a universal correction factor.+
Hazen–Williams or Darcy–Weisbach parameters should remain physically plausible. Excessive roughness changes can hide errors in demand allocation, topology, valve status or elevation data.
06Leakage / emitter calibrationRepresent pressure-dependent losses using field evidence.+
Calibrate emitter coefficients and pressure exponents against minimum-night-flow behaviour, pressure response and known district conditions rather than using arbitrary leakage values.
07Tank, reservoir & boundary conditionsMake the simulated operating state match the real network.+
Confirm tank levels, reservoir heads, pump schedules, PRV settings, valve states and control rules. Boundary-condition errors can create larger discrepancies than parameter uncertainty.
08Validation criteriaCheck both magnitude and temporal behaviour.+
Evaluate pressure and flow residuals, peak behaviour, temporal trends and stability over an independent validation period. A calibrated model should remain credible outside the exact data used for adjustment.
09Common calibration mistakesMost poor calibrations correct the wrong parameter.+
- Incorrect node elevations
- Wrong demand allocation or temporal patterns
- Unmodelled valve or pump status
- Unrealistic roughness adjustments
- Calibrating against one snapshot only
- Confusing pressure with hydraulic head
10Real project exampleFrom field monitoring and calibration to intervention design.+
In the highlighted Desenzano del Garda case, field monitoring, tank/reservoir information and operating controls were integrated into the hydraulic model to support calibration and intervention assessment.
Proposed interventions were evaluated through the calibrated model and are being implemented by the utility. These figures describe modelled potential, not already measured savings.
View the Desenzano case study →Demand-driven and pressure-driven modelling
Both demand-driven and pressure-driven approaches are used depending on network conditions and the engineering objective, particularly when analysing pressure deficiencies, leakage and abnormal operating conditions.
DMA and leakage analysis
District Metered Areas can be analysed using pressure monitoring, flow measurements, minimum night flow, network separation tests and hydraulic simulation to support leakage detection and non-revenue water reduction.
Pressure management
Hydraulic models support assessment of PRV settings, valve configurations, pressure zones and operational changes while evaluating their impact on service pressure and leakage.
Software
MIKE+ · InfoWorks WS Pro · WaterGEMS · EPANET · QGIS · ArcGIS · Python · Excel
Related case study
Water Network Calibration & Leakage Reduction in Italy →