Every flood season, urban waterlogging has become a recurring challenge in many cities. It not only disrupts daily life but can also cause property damage and even threaten personal safety. Traditional approaches to waterlogging rely heavily on manual inspections and post-event response, suffering from delayed detection, incomplete information, and coordination difficulties. With the advancement of IoT technology, intelligent waterlogging monitoring systems are transforming this landscape by building an integrated sensing network that covers "rainfall, roads, pipelines, and outlets," enabling early awareness of flood conditions, timely warnings, and rapid emergency response.
Urban waterlogging involves multiple interconnected factors: rainfall intensity, surface runoff, drainage pipeline capacity, and river water levels. Traditional monitoring methods face several limitations:
Sensing Gaps: Rainfall data is scattered, and there is a lack of real-time monitoring of road ponding depth, pipeline flow rates, and drainage outlet status
Delayed Warnings: Reliance on manual reporting or citizen complaints makes it difficult to detect hazardous conditions early
Passive Response: Emergency response and pump station operations rely on experience rather than data-driven decision-making
Information Silos: Data sharing among meteorological, water resources, municipal, and emergency management departments is limited, reducing coordination efficiency
Effectively addressing waterlogging requires a comprehensive sensing system covering "rainfall, surface water, underground pipelines, and drainage outlets."
Intelligent waterlogging monitoring systems adopt a four-layer architecture—sensing layer, network layer, platform layer, and application layer—to achieve a complete closed loop from data collection to decision support.
The sensing layer serves as the "nerve endings" of the system, deploying various sensors and monitoring equipment at key locations to collect raw data:
Rainfall Monitoring: Tipping bucket rain gauges, radar rain sensors, providing real-time rainfall intensity and cumulative precipitation
Road Ponding Monitoring: Ultrasonic and pressure water level sensors to monitor water depth at flood-prone areas such as low-lying sections and underpass tunnels
Pipeline Flow Monitoring: Doppler flow meters, electromagnetic flow meters to measure flow rates and velocities in stormwater and sewer networks
Manhole Water Level Monitoring: Submersible water level sensors to monitor changes in manhole water levels and warn of pipeline surcharge risks
Pump Station Monitoring: Collecting operational status, operating current, and drainage flow from pumping stations
River Water Level Monitoring: Radar water level sensors to monitor river levels and assess the impact of external water levels on urban drainage capacity
Data collected by field monitoring devices must be transmitted reliably to the central platform via stable communication networks. Given that monitoring points are often dispersed and some are located in remote or underground areas, the network layer requires:
Multi-Mode Communication: Support for 4G, 5G, NB-IoT, Ethernet, and other communication methods to adapt to different scenarios
Link Backup: Dual-link configuration for critical points to ensure uninterrupted communication
Local Data Storage: Automatic data caching during network outages with retransmission upon recovery
Low Power Design: Solar power support and low-power operation for locations without grid electricity
The platform layer serves as the system's "brain," responsible for data ingestion, storage, analysis, and distribution:
Multi-Protocol Compatibility: Support for Modbus, water resources industry-specific protocols, mainstream PLC protocols, and others to accommodate equipment from different vendors
Multi-Center Reporting: Simultaneous data push to multiple command centers (water resources, municipal, emergency management)
Edge Computing: Preprocessing at the data source, such as triggering local alarms when water depth exceeds thresholds
Data Standardization: Converting raw data from various formats into standardized formats for analysis and sharing
The application layer provides end users with visualization, warning, and dispatch management capabilities:
Real-Time Monitoring Dashboard: Map-based visualization of real-time data from all monitoring points
Intelligent Alerts: Automatic warnings based on preset thresholds with multiple notification methods (SMS, app push, audible/visual alarms)
Trend Analysis: Historical data analysis to generate trend curves, supporting flood situation assessment
Dispatch Coordination: Auxiliary decision-making for emergency resource allocation based on ponding locations and pump station status
In intelligent waterlogging monitoring systems, the hydrological telemetry terminal serves as the critical bridge connecting sensors to the cloud platform. It integrates data acquisition, edge computing, and multi-protocol communication, specifically designed for hydrological monitoring, flood warning, water resource scheduling, and related water management scenarios.
Hydrological telemetry terminals feature rich data interfaces to connect various sensors:
Analog Input: Connecting 4-20mA or 0-5V output devices such as water level and flow meters
Digital Input: Connecting pulse or switch signals from rain gauges and status switches
Serial Interfaces: RS232, RS485 for connecting intelligent instruments and sensors
Camera Interface: Integrating with on-site cameras to combine video with data
Multi-Network Support: 4G full-band connectivity for compatibility with different carrier networks
Multi-Center Reporting: Simultaneous data transmission to multiple monitoring centers to support hierarchical management
Data Retransmission: Automatic retransmission of data collected during network outages upon recovery
Local Logic Processing: Triggering local alarms or control outputs based on collected data
Data Filtering: Uploading only data that exceeds threshold changes to reduce unnecessary transmissions
Protocol Conversion: Converting proprietary protocols from different vendors into standard protocols
Wide Operating Temperature: -40°C to 85°C operating range for harsh outdoor environments
Ingress Protection: IP67 rating for dust and water resistance
Low Power Consumption: Solar power support and battery backup for locations without grid electricity
Low-lying road sections and underpass tunnels are high-risk areas for waterlogging. Deploying water level monitoring equipment at these locations provides real-time ponding depth data:
Automatic alerts when water depth exceeds warning thresholds
Integration with traffic signals to guide vehicles to alternative routes
Coordination with drainage pump stations for automatic activation
The drainage capacity of stormwater pipelines directly affects surface water accumulation. Monitoring flow rates and water levels at key nodes enables:
Assessment of pipeline load conditions and early warning of surcharge risks
Identification of pipeline blockages or damage to guide maintenance
Evaluation of pipeline drainage capacity in relation to rainfall data
Pump stations are critical infrastructure for urban drainage. Real-time monitoring of pump station operations:
Collecting pump start/stop status, operating current, and drainage flow
Alerting equipment faults to prevent drainage disruptions
Optimizing pump operation strategies based on upstream inflow conditions
River water levels significantly impact urban drainage capacity. When external river levels rise, internal drainage may be impeded, increasing waterlogging risks:
Real-time monitoring of river level changes
Early warning of backwater effects
Providing decision support for pump station operations
Historical Flood-Prone Areas: Prioritize known risk locations based on historical waterlogging records
Low-Elevation Areas: Identify and cover urban low points
Critical Transportation Nodes: Underpass tunnels, major intersections, and other key traffic points
Key Pipeline Nodes: Pipeline junctions, pump station forebays, and other important locations
Water Level Sensor Installation: Ensure sensors are positioned at the lowest points and protected from debris
Power Supply Design: Utilize grid power where available; use solar power for locations without grid access
Communication Assurance: Test on-site signal strength and use antenna extensions when needed
Data Accuracy: Calibrate sensors by comparing with manual measurements
Alert Threshold Setting: Set appropriate warning and alarm thresholds based on historical data and site conditions
Multi-Department Coordination: Ensure data sharing among water resources, municipal, emergency management, and other relevant departments
Combining historical waterlogging data with real-time monitoring information, machine learning algorithms can predict waterlogging probability and ponding trends, further extending warning lead times.
Building digital twin models of urban drainage systems enables simulation of water accumulation under different rainfall scenarios, supporting drainage infrastructure planning and emergency response plan development.
Breaking down data barriers between meteorological, water resources, transportation, and emergency management departments establishes cross-departmental coordination mechanisms, achieving integrated workflows from monitoring and warning to emergency response.
The implementation of urban waterlogging monitoring systems represents a shift from reactive response to proactive warning in urban flood management. Through IoT technology, a comprehensive sensing network covering "rainfall, roads, pipelines, and outlets" enables management authorities to monitor flood conditions in real-time, allocate emergency resources scientifically, and effectively reduce waterlogging-related losses. As technology continues to advance, urban waterlogging monitoring systems will become increasingly intelligent and precise, providing strong support for building resilient cities and ensuring safe urban mobility.