With the rapid development of the national economy, water conservancy projects are playing an increasingly important role in the national economy. Flood control, in particular, is a crucial aspect that directly affects the development of the national economy. Over the past few decades, water conservancy departments have always regarded flood control and drought relief as top priorities. Based on the flood control work after last year's flood season, in-depth analyses have been conducted, and combined with the epidemic situation this year, we have further reflected on the issue. There are several aspects that have exerted particularly significant impacts: first, exceedance floods, i.e., floods that cannot be controlled by existing water conservancy projects; second, reservoir failures caused by inadequate work; third, mountain flood disasters. Among these three aspects, one is extremely difficult to prevent, and more importantly, they may cause heavy casualties.
According to the latest statistics from the national water conservancy department, there are more than 98,000 reservoirs in China, among which over 94,000 are small-sized ones. Some of these small reservoirs still have safety risks. The dangerous reservoirs among them cannot perform flood control and water retention functions as per their original design capacity, thus failing to play their intended roles.
The solution for the Smart Reservoir Water Level and Storage Monitoring System is based on technologies such as the Internet of Things (IoT) and big data. It builds a central computer monitoring system for reservoirs, which automatically monitors storage-related information of the reservoir—including water level, flow rate, and rainfall—and uploads the collected information to the monitoring center. The monitoring center makes dual judgments based on data and images to avoid misjudgments of on-site conditions. On the other hand, the monitoring center platform displays the basic conditions of the on-site reservoir in real time and conducts analysis and processing of the data.
The Smart Reservoir Water Level and Storage Monitoring System is built on an open network architecture, which is divided into four layers in total: the End Device Layer, Network Transmission Layer, System Application Layer, and Terminal Strategy Layer, in that order.
By leveraging technologies such as the Internet of Things (IoT) and intelligent technology, it enables real-time online management of the reservoir's storage information. Video monitoring devices are used to upload images from monitoring stations, and managers can check the relevant conditions of the reservoir directly through a large screen.
As the core carrier of the Smart Reservoir Water Level Monitoring System, it conducts remote data collection of hydrological data such as the reservoir's water level, flow rate, velocity, rainfall, sediment, and water quality through data communication and collection equipment, and reports real-time data to the management platform.
Composed of a dedicated DTU (Data Transfer Unit) and the public telecommunications network, its main function is to read and process data from various sensors in real time, and send the data to the system platform via 4G/5G, NB-IoT, or Beidou satellites.
The cloud-based integrated data processing platform calculates the reservoir's storage capacity by analyzing data such as water level and flow rate, making it easy for administrators to promptly grasp the reservoir's load-bearing status.
Through the data analysis and transmission of the above three layers, the strategy layer can log in to the monitoring platform in real time to view information such as water level, rainfall conditions, video monitoring, water quality, and data statistics and analysis.
Strengthening the operation management and maintenance of the reservoir hydrological online monitoring system can better exert the system's role in reservoir water resource scheduling and flood control, while providing a basis for reservoir decision-makers to conduct scheduling accurately and scientifically.
Real-Time Flow Monitoring: It displays the latest water level, current rainfall, cumulative rainfall, on-site videos, and other data of each reservoir monitoring point in real time, and presents dynamic curves of water level and rainfall in real time.
Remote Video Monitoring: It supports real-time video monitoring and recording through multiple channels, and can update monitoring data and on-site video photos at regular intervals.
Supervision and Early Warning System: By combining AI big data with system data for analysis, when the reservoir water level is abnormal, the system will trigger alerts by popping up a prompt box, emitting an alarm sound, sending alarm text messages to administrators, and other methods.
Data Research and Judgment Analysis: By sorting out and analyzing the basic data in the system, it directly generates various types of correlation analysis charts.
Integrated pole design enables quick debugging and deployment of front-end stations.
Multiple terminals are used for various types of monitoring, featuring high measurement accuracy and strong anti-interference capability.
Wireless transmission is adopted to break through geographical limitations, with high adaptability.
Based on independently developed wireless RTU (Remote Terminal Unit) products, remote debugging and maintenance of equipment can be realized.
The system platform based on B/S (Browser/Server) architecture allows quick and convenient access to the system.
The exclusive client enables users to check the current equipment status anytime and anywhere.
Multiple measures such as lightning protection, rain protection, moisture protection, and input signal isolation are adopted to ensure equipment safety and stable and reliable performance.
High compatibility, supporting various types of measuring instruments or sensors for water level, rainfall, displacement, etc.
Ultra-low power consumption: Core equipment adopts 2G/3G/4G low-power measurement and control terminals, with an average working current of only 10mA, which greatly reduces the cost of solar-powered equipment and construction difficulty.
The solution for the reservoir water level and storage monitoring system can effectively conduct all-weather real-time monitoring of reservoirs and keep track of the reservoir's water flow conditions in real time. In case of early warning of dangerous situations, response measures can be taken immediately. At the same time, it can use reservoir big data and meteorological data to predict reservoir water levels during the flood season and make relevant arrangements in advance. This is of great significance for the orderly progress of local reservoir water level monitoring, flood control and disaster reduction work.
