The practitioner’s toolkit

Learn the workflow.
Check the result.

Eight practical guides with worked examples, downloadable data, calculations and troubleshooting, all explained here.

Learn by doing.

One practice pack connects GIS, hydraulic modelling, demand analysis, forecasting and reporting. All data is synthetic.

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8 articles
Hydraulic modelling

EPANET: build, check and challenge a network

Open a complete teaching model, reconcile flow and headloss, and extend the assessment to demand, storage and outage scenarios.

Practical tutorial · 6 min read
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Hydraulic modelling

InfoWorks WS Pro: demand allocation you can audit

Work through customer hierarchy, allocation rules, zone changes and demand reconciliation before trusting network results.

Practical tutorial · 6 min read
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Water resources

eWater Source: a storage model with a closing balance

Build a daily resource model, distinguish inaccessible storage from a supply rule, and measure shortfall under comparable scenarios.

Practical tutorial · 7 min read
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GIS

QGIS: allocate customers to zones without losing the ledger

Create a clean spatial dataset, resolve duplicate and boundary records, and reconcile zone demand using a fully supplied exercise.

Practical tutorial · 6 min read
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GIS

ArcGIS Pro: build a defensible zone-demand layer

Use geoprocessing, join diagnostics and explicit allocation decisions to turn customer tables into a reliable planning dataset.

Practical tutorial · 6 min read
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Data & AI

Python: turn hourly demand into a checked daily series

Run a complete data audit that detects duplicate and missing intervals, preserves uncertainty and produces a usable engineering output.

Practical tutorial · 6 min read
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Data & AI

Power BI: show hydraulic results without hiding the exceptions

Build a small scenario dashboard with correct data grain, explicit pressure criteria and measures that distinguish events from affected assets.

Practical tutorial · 6 min read
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Data & AI

Machine learning: a forecast with a fair test

Run a complete demand-forecasting experiment with chronological validation, seasonal baselines and a clearly defined operational horizon.

Practical tutorial · 6 min read
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