Development Opportunities for Urban Pipeline Networks in 2026 under the Dual Carbon Goals

From “Post-event Drainage” to “Process Control”: Entering a Risk-Governance Cycle

For a long time, urban drainage pipeline-network construction focused on physical capacity—pipe diameters and pump station sufficiency. However, with China’s urban drainage pipeline network exceeding 900,000 km, the complexity of underground records and operational boundaries has increased significantly. While conventional stormwater pipe networks are designed for return periods of 1 to 3 years, modern urban safety requires coping with extreme rainfall scenarios up to once-in-30-year events.

Industry experience shows that 15 cm of standing water affects e-bikes; 30 cm increases vehicle stalling risk; above 50 cm, passage becomes difficult; around 80 cm may trigger high-risk events such as vehicle floating.

The core shift is moving from "post-rain drainage" to a closed loop: pre-rain prevention, in-rain dispatching, and post-rain review. Future competitiveness lies not just in facility capacity, but in risk-identification speed, prediction accuracy, and disposal efficiency.

Market Trends: Renewal, Digital Foundation, and O&M Services

Policy Impact: Standards Upgrades and Data Elements

The policy framework is expanding from simple drainage construction to "urban safety and resilience governance." By 2030, overall goals for urban waterlogging governance should be basically completed. Evaluation criteria are shifting from engineering completion to risk reduction, warning effectiveness, and closed-loop dispatching.

• Standards System: New regulations require cities to establish drainage facility ledgers, waterlogging risk-point lists, and remediation plans. Technology products must evolve from single-point devices to systematic solutions compatible with multi-source data.
• Data Element Policies: Pipeline network data is high-value but sensitive. Projects must meet requirements for data classification, privacy protection, cybersecurity, and critical information infrastructure protection. Compliance capability is becoming as important as technical capability.

Technology Directions: Radar Sensing Moves from “Seeing” to “Accurate Calculation”

Radar technology is becoming the key sensor type in urban flood-control systems, covering rainfall monitoring, level measurement, and underground defect detection.

Waterlogging Early Warning: From Alarming to Decision-Making

Effective early warning requires scenario-specific thresholds. For general roads, 10 cm might be an advisory threshold, while 30 cm triggers closure. For metro entrances or underpasses, stricter thresholds apply (e.g., 5 cm triggers warning, 15 cm closes passage).

Modeling is key. Traditional alarms lag behind reality. Advanced systems build a chain: "Rainfall Input → Surface Runoff → Pipeline Network Runoff → Waterlogging Prediction → Risk Grading → Disposal Recommendations." AI improves nowcasting speed, while hydrologic models explain physical processes.

Case Study: After the July 20, 2021 Zhengzhou extreme rainfall (201.9 mm/hour), many cities strengthened "one point, one strategy" protocols, reducing alarm delays from minutes to seconds through integrated radar-video-IoT systems.

Implementation Challenges

• Incomplete basic data: Missing as-built records and mixed connections.
• Unstable sensor quality: Device drift, communication interruptions, and sediment blockage.
• Localization needs: Generic algorithms fail without local parameter tuning.
• Procedural gaps: Accurate predictions cannot act without clear authority and responsibility links.

Reconstructing Flood-Control Scenarios: Multi-System Coordination

Urban flood control is no longer a single-line battle. It requires joint dispatching among pipeline networks, river channels, pump stations, transportation, and communities. External river water levels can cause backwater effects, reducing drainage capacity if pump stations do not pre-discharge in time.

Industry Landscape: Changing Logic of Competition

Participants are stratifying: sensing-device companies, platform providers, model specialists, and operations service firms. Procurement is shifting from project-based buying to long-term "construction + operation + performance assessment" models.

Key Risks

• Construction over Operation: Systems become "screens without brains" due to lack of maintenance and model updates.
• Data Silos: Inconsistent standards across departments hinder cross-coordination.
• Device Reliability: Harsh underground environments (wetness, corrosion, weak signals) affect longevity.
• Safety Responsibility: False alarms or missed alarms carry legal and operational risks; systems must be explainable and traceable.

Outlook: Resilient Pipe Networks and AI-Native Operations

Facing climate change, the industry is moving from fixed design return periods to dynamic verification and scenario simulation. Design standards must remain flexible, adjustable according to real-time meteorological conditions and urban needs.

AI-Native Operations will embed data acquisition, model computation, warning generation, and dispatch recommendations into a single process. Future systems will automatically distinguish between sensor failure and actual waterlogging, generate risk briefings, and consolidate lessons learned into knowledge bases.

The fusion of radar, video, IoT, and digital twins will lower application barriers. An integrated "sky-air-ground-manhole" sensing network will emerge, utilizing drones, robots, and satellites alongside ground-based sensors.