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🗺️ Water Distribution Network Analysis - Complete Guide

Modeling, calibration, and optimization of municipal water supply networks for pressure, flow, and reliability.

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Case Studies
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Water Distribution Network Analysis - Complete Guide

It's like using math and computers to make sure water reaches every home at the right pressure and amount, without waste...

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Knowledge Base

15 pages
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Key Concepts

Water Distribution
Network AnalysisHydraulic Modeling
Fundamentals
EPANET Software
Workflow
Pipe Roughness
Coefficients
Demand Allocation
Methods
Critical Node
Identification
Pressure-Dependent
Demand Modeling

Visual overview of key concepts and their relationships

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Real Projects

5 cases
Calibration of Lagos Metropolitan Water NetworkZone 1Zone 2Zone 3Zone 4×1.32×1.45×1.58×1.62×1.68Demand Multiplier:CI Mains: C = 92 → 78PVC Laterals: C = 140 → 115Roughness (C-value):Challenge: >25% pressure error (undocumented pipe replacements, unaccounted demand growth)Sensors: 87 pressure loggers • 14 flow metersMain trunkZonal demandPipe roughness

Calibration of Lagos Metropolitan Water Network

Nigerian utility upgrading aging infrastructure across 12 zones

Challenge: Persistent model–field mismatch (>25% pressure error) due to undocumented pipe r...
Real-Time Pump Scheduling for Barcelona’s Tertiary Reservoir System ⚠️ Challenge: 34% OPEX energy cost • Low-pressure complaints (peak afternoon) MPC Engine 24-hr demand + tariff + level constraints Demand Forecast Tariff Windows Level Bounds Fill Timing 02–05 & 22–03 Pressure Setpoint 42–58 m (dynamic) • Minimize Σ(Power × Tariff) • Tank bounds: 0–100%

Real-Time Pump Scheduling for Barcelona’s Tertiary Reservoir System

Integration of SCADA-controlled pumps feeding elevated storage tanks serving high-elevation districts

Challenge: Excessive energy costs (34% of OPEX) and frequent low-pressure complaints during...

Leak Localization in Tokyo’s Historic Cast-Iron Network Using ITA

Detection and isolation of leaks in 80+ year-old underground CI pipes beneath dense urban corridors

Challenge: Acoustic methods ineffective due to soil attenuation and ambient noise; conventi...
Climate-Adaptive ReinforcementCape Town Drought-Resilient NetworkReservoirDead-endLow pressureLoop ClosureΔReliability/ΔCapEx = 3.7BoosterStationAI DynamicPressure ZoneMin Storage Threshold:18.2 MLSupply NodeChallengeLoop ClosureBooster

Climate-Adaptive Reinforcement of Cape Town’s Drought-Resilient Network

Post-Day Zero resilience upgrade following 2018 water crisis

Challenge: System unable to maintain minimum pressure during prolonged low-storage operatio...
Water Quality Model Validation: DTSS Supply Branch Inlet C₀ = 2.0 mg/L Node 1 (3.2 km) Node 2 (7.8 km) Node 18 (12.4 km) C = 0.14 mg/L Pipe wall with biofilm k_wall = 1.82×10⁻⁵ s⁻¹ k_bulk = 0.32 hr⁻¹ 12-month field data (18 biofilm sampling sites) Challenge: C < 0.2 mg/L at Node 18 Dual-Reaction Chlorine Decay Model Inlet / Flow Validated node Critical node Pipe wall/biofilm

Water Quality Model Validation for Singapore’s Deep Tunnel Sewerage System (DTSS) Supply Branch

Chlorine decay modeling across 42 km of precast concrete trunk mains supplying NEWater-integrated distribution zones

Challenge: Disinfectant residual dropping below 0.2 mg/L at farthest nodes despite design d...
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Downloads

6 resources
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Learning Path

23 lessons

Master Water Distribution Network Analysis through a structured learning path — from fundamentals to advanced applications.

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