Editor's Note: As the "nerve endings of the information age," sensors have penetrated every critical field of the socio-economic landscape. Since October 2025, China Electronics News has invited Guo Yuansheng, Deputy Director of the Science and Technology Committee of the Jiusan Society and Executive Vice Chairman of the China Sensor and IoT Industry Alliance, to launch the column "Guo Yuansheng Explains Sensors." The column focuses on eight major fields and scenarios: power, major equipment, intelligent manufacturing, smart agriculture, smart healthcare and wellness, smart home appliances and consumer electronics, urban security, and the low-altitude economy. Articles such as "Sensors on the Power Generation Side: The Cornerstone of Stable Operation in New Power Systems" and "Energy Storage Sensors Define Three Core Development Directions" have been published in succession, receiving widespread attention and high praise from readers. This article focuses on smart sensors in water conservancy scenarios, elaborating on their application prospects, industry status, and future recommendations to build industry consensus and promote industrial development.
Currently, global water conservancy governance is accelerating into the "intelligent perception era." Developed countries and regions such as Europe and the United States have achieved full coverage of multi-dimensional monitoring of "water volume-water quality-ecology" in major rivers through the linkage of smart sensor networks and AI (Artificial Intelligence) models, significantly improving the efficiency of flood control, disaster reduction, and water resource allocation. For example, the multi-parameter water quality sensors deployed in the Rhine River basin in Germany can monitor 12 indicators in real time, including dissolved oxygen and ammonia nitrogen, and trace pollution events within 2 hours by combining hydrological models. In the flood control system of the Mississippi River in the United States, the collaborative early warning of radar water level gauges and rainfall sensors has reduced the flood response time for downstream cities by 50%.
In China, water conservancy monitoring still faces gaps such as incomplete coverage, insufficient multi-parameter coordination, and weak adaptability to extreme scenarios. From the flood control safety of the Yangtze River Economic Belt to the ecological protection of the Yellow River basin, and from the modernization of irrigation districts under the rural revitalization strategy to the prevention of flash flood disasters in small watersheds, the complexity and extensive geographical nature of water conservancy governance are becoming increasingly prominent. There is a more urgent demand for multi-dimensional sensors with high precision, high reliability, low power consumption, and easy deployment. It can be said that multi-dimensional smart sensors have become a critical driver for upgrading water conservancy safety and precisely regulating water resources. Their full-scenario application and technological evolution are directly related to the implementation effectiveness of the national water security strategy.
I. Macro Background and Boundary Definition of Smart Water Resource Perception Technology Applications
National Strategy and Industry Demand
1. Deployment Requirements of Water Resource Strategic Development Planning for Smart Monitoring
The "15th Five-Year" Water Conservancy Development Plan explicitly proposes to "deepen the intelligent upgrade of hydrological infrastructure, improve the hydrological monitoring station network system with full-area coverage, and promote the integration of monitoring-decision-execution," and delineates three key monitoring areas: First, hydrological monitoring of rivers, lakes, and reservoirs, requiring real-time multi-parameter monitoring of water level, flow, and water quality at important cross-sections of main streams and major tributaries. Second, safety monitoring of water conservancy projects, requiring large reservoirs, sluices, embankments, and other projects to be equipped with structural monitoring sensors for seepage pressure, strain, and displacement. Third, rural water conservancy monitoring, requiring full coverage of soil moisture and irrigation water efficiency monitoring in large-scale irrigation districts and water-saving demonstration projects. In addition, the "Overall Layout Plan for Building a Digital China" includes "smart water conservancy" as a key industry in the digital economy, proposing to build a national-level intelligent water conservancy data dispatch center by 2030, promoting the deep integration of sensor data with water conservancy business systems, and providing decision-making support for flood control, disaster reduction, and water resource allocation.
2. Analysis of Monitoring Pain Points in Flood Control and Disaster Reduction, Ecological Flow Guarantee, and Irrigation District Modernization
Flood control and disaster reduction: Traditional monitoring relies on manual patrols and single-point water level gauges, suffering from slow response and incomplete coverage. For example, in 2022, a small mountainous watershed lacked rainfall-water level linkage monitoring. When a rainstorm triggered a flash flood, the downstream village received only a 15-minute warning, resulting in house damage. Multi-dimensional sensors can issue flood warnings 30-60 minutes in advance through real-time linkage of rainfall, water level, and flow velocity data, solving the pain point of "untimely warning."
Ecological flow guarantee: Basins such as the Yangtze River and the Pearl River need to ensure fish migration and wetland ecological water demand. Traditional monitoring is difficult to synchronously obtain parameters such as flow, water temperature, and dissolved oxygen, leading to a lack of data support for ecological flow regulation. For example, a tributary of the Yangtze River only monitored flow without paying attention to water temperature changes. After the sluice and dam dispatch, the water temperature dropped sharply by 5°C, affecting the reproduction of native fish. Multi-dimensional water quality-hydrological sensors can synchronously capture flow and water quality parameters, providing multi-dimensional basis for ecological flow regulation.
Irrigation district modernization: China has over 100,000 existing irrigation districts, 80% of which still use traditional flood irrigation. Due to the lack of soil moisture and irrigation water monitoring, the water utilization rate is less than 50%. For example, a large irrigation district in the northwest previously relied on manual statistics for irrigation water consumption, with data lagging by 3 days, making it impossible to adjust irrigation plans in time, resulting in an annual water waste of 200m³ per mu. The collaborative application of soil moisture sensors and smart water meters can provide real-time feedback on soil moisture and water consumption, achieving "on-demand irrigation" and solving the pain point of "low water-saving efficiency."
Monitoring Objects and Boundary Division
1. Core Coverage Areas: Natural Watersheds (Rivers, Lakes, and Reservoirs) and Artificial Water Conservancy Projects (Cross-Basin Water Diversion, Irrigation Districts, Sluices, and Dams)
(1) Natural watershed monitoring: Focusing on main streams, tributaries, lakes, and reservoirs, with key monitoring parameters including water level, flow, flow velocity, water quality (COD, ammonia nitrogen, dissolved oxygen), and water temperature. For example, the Yangtze River main stream monitoring covers 108 key cross-sections from the source in Qinghai to the estuary in Shanghai. Each cross-section is equipped with multi-dimensional sensors to achieve synchronous collection of hydrological and water quality data. Lake monitoring for Poyang Lake and Dongting Lake needs to balance water level changes and eutrophication indicators to avoid cyanobacterial blooms.
(2) Artificial water conservancy project monitoring: Includes cross-basin water diversion projects such as the South-to-North Water Diversion, large and medium-sized irrigation districts, sluices, dams, and embankments. The monitoring content is divided into two categories: first, project operation parameters, such as water diversion flow, irrigation water consumption, and sluice opening; second, project safety parameters, such as dam seepage pressure, embankment displacement, and gate strain. For example, the Middle Route of the South-to-North Water Diversion Project sets up one flow-water quality monitoring station every 5 kilometers, while deploying seepage pressure sensors at the Danjiangkou Dam to ensure water diversion efficiency and project safety.
2. Scenario Boundary Distinction: Functional Differences from Urban Water Supply and Drainage Monitoring and Industrial Water Treatment Monitoring
Water conservancy sensor monitoring focuses on macro-level water conditions and project safety at the "watershed level" and "regional level," with clear boundaries compared to urban water supply and drainage monitoring and industrial water treatment monitoring:
(1) Differences from urban water supply and drainage monitoring: Urban water supply and drainage monitoring targets municipal pipe networks, focusing on pipe network pressure, leakage rate, and secondary water supply quality. The sensor deployment density is high (e.g., 10-20 pressure sensors per square kilometer), focusing on "micro" pipe network operation and maintenance. In contrast, water conservancy monitoring targets rivers, lakes, reservoirs, and large irrigation districts. Sensor deployment is mainly based on "cross-sections" and "nodes" (e.g., one cross-section every 50km in the Yangtze River), focusing on "macro" water condition regulation.
(2) Differences from industrial water treatment monitoring: Industrial water treatment monitoring targets factory wastewater discharge, focusing on specific pollutants such as heavy metals and chemical oxygen demand. Sensors need to meet industrial-grade protection (e.g., explosion-proof, anti-corrosion), and data must be connected to environmental protection departments. In contrast, water quality monitoring in water conservancy monitoring targets natural water bodies, focusing on routine water quality indicators (e.g., ammonia nitrogen, dissolved oxygen). The data is used for ecological protection and water resource allocation, without the need to meet special requirements such as industrial explosion-proof standards.
Core Value of Multi-Dimensional Monitoring
1. Single Sensors (e.g., Only Measuring Liquid Level or Flow) Have Obvious Limitations in Practical Applications
(1) Limitations of single liquid level sensors: In 2021, a small-to-medium reservoir only deployed water level gauges without monitoring rainfall and dam seepage pressure. During a rainstorm, the water level gauge showed the water level exceeded the warning line, but because the upstream rainfall trend was unknown, the flood peak could not be predicted, leading to delayed flood discharge dispatch. Meanwhile, the lack of dam seepage pressure monitoring failed to detect minor seepage in the dam in time, nearly causing a dam breach risk.
(2) Limitations of single flow sensors: A northern irrigation district previously only installed flow sensors to statistics irrigation water consumption, without monitoring soil moisture. This resulted in the problem of "irrigating by flow" rather than "irrigating by soil moisture." Even when the soil was saturated, water was still supplied according to the plan, resulting in only a 10% increase in water-saving rate per mu, far below the expected 30%.
(3) Limitations of single water quality sensors: A lake only monitored the dissolved oxygen indicator for cyanobacteria early warning. However, before a cyanobacterial outbreak, because water temperature was not monitored synchronously, the best intervention time was missed when dissolved oxygen became abnormal. The cyanobacteria coverage area expanded by 3 times, and the treatment cost increased by 5 million RMB.
2. Multi-Dimensional Sensor Coordination (Liquid Level + Rainfall + Water Quality) Can Effectively Make Up for the Above Shortcomings, Achieving a Monitoring Effect of 1+1>2. Typical Applications Are as Follows: Taking the Yangtze River Flood Warning and Dongting Lake Ecological Regulation as Examples
(1) Multi-dimensional coordination in Yangtze River flood warning: During the 2023 summer flood season of the Yangtze River, the Yangtze River basin monitoring network integrated four types of sensors: radar water level gauges (measuring water level), tipping bucket rain gauges (measuring rainfall), electromagnetic flowmeters (measuring flow velocity), and multi-parameter water quality analyzers (measuring turbidity and dissolved oxygen). When the water level in the upstream Three Gorges Reservoir area reached 160m (warning level 145m), the rainfall sensor showed continuous rainstorms upstream (cumulative rainfall exceeding 200mm/24h), and the flow velocity sensor showed the flood discharge velocity reached 2.5m/s. After multi-dimensional data linkage, the warning system issued dispatch instructions to the mid-and-downstream flood storage areas 48 hours in advance, avoiding urban waterlogging in 3 county-level cities and reducing direct economic losses by over 2 billion RMB.
(2) Multi-dimensional coordination in Dongting Lake ecological regulation: As an important regulation and storage lake of the Yangtze River, Dongting Lake needs to ensure ecological flow and fish breeding environments. The monitoring network deployed liquid level sensors (measuring lake water level), multi-parameter water quality analyzers (measuring water temperature, dissolved oxygen, ammonia nitrogen), and acoustic Doppler velocimeters (measuring lake water flow velocity). In the spring of 2024, during the fish breeding period, sensors monitored the lake water level dropping to 24m (the lower limit of the ecological water level for fish breeding in Dongting Lake in spring is 23.5m), while the water temperature rose to 18°C (suitable water temperature for fish spawning), but dissolved oxygen dropped to 4mg/L (below the suitable value of 5mg/L). Based on multi-dimensional data, the regulation department synchronously opened sluices and dams for water replenishment (raising the water level to 24.5m) and ecological aeration equipment (raising dissolved oxygen to 5.5mg/L), increasing the fish spawning volume by 25% compared to the previous year, achieving a balance between ecological protection and water resource regulation.
II. Sensor Selection and Practical Applications in Different Water Conservancy Scenarios
Applications in Large Watersheds (Main Rivers, Large Lakes, Key Water Conservancy Projects)
1. Flood Control Safety Monitoring Combination: Radar Water Level Gauge + Electromagnetic Flowmeter + Tipping Bucket Rain Gauge
(1) Core Parameter Analysis:
Radar water level gauge: Uses 26GHz high-frequency radar, with a range of 0-50m and a resolution of ±1mm. It has anti-water vapor and anti-sediment interference capabilities (protection rating IP68, can work stably in environments from -40°C to 85°C), suitable for water level monitoring in open waters such as main rivers and large reservoirs. For example, the radar water level gauges used in the Yangtze River main line can penetrate the water curtain formed by rainstorms, avoiding the interference of raindrops on water level measurement. The data update frequency reaches 1 time/minute, ensuring real-time and accurate water level data during floods.
Electromagnetic flowmeter: Based on Faraday's law of electromagnetic induction, the measurement pipe diameter range is DN300-DN3000, with an accuracy of ±0.5% FS. It can withstand water flow velocities of 0-10m/s (the maximum flow velocity during the Yangtze River flood period is about 5m/s). It has an anti-corrosion lining (rubber or PTFE) and can operate in river water containing sediment and organic matter for a long time. For example, the electromagnetic flowmeters in the Yellow River diversion irrigation district in the lower reaches of the Yellow River can synchronously measure flow and water flow direction, avoiding damage to the irrigation system caused by the backflow of Yellow River water.
Tipping bucket rain gauge: The rain-receiving mouth has a diameter of 200mm, a resolution of 0.1mm, and a rainfall intensity measurement range of 0-4mm/min (the rainstorm intensity standard is 16mm/h). It has an anti-backflow design and can work normally in continuous rainstorm weather. For example, tipping bucket rain gauges deployed in the Pearl River basin form a "rainfall-water level" linkage with radar water level gauges. When the 24-hour rainfall at a single station exceeds 150mm, it automatically triggers the pre-discharge instruction for upstream reservoirs.
(2) Typical Application Scenarios: Yangtze River main line flood control dispatch, Three Gorges Reservoir flood regulation, Poyang Lake super-warning water level response
Implementation Effects and Cases: During the main flood season of the Yangtze River in 2023, 28 sets of "radar water level gauge + electromagnetic flowmeter + tipping bucket rain gauge" monitoring combinations deployed in the Yichang-Wuhan section captured in real time that the discharge flow from the upstream Three Gorges Reservoir increased from 15,000m³/s to 40,000m³/s, while the 24-hour rainfall at the midstream Wuhan station reached 180mm. After multi-dimensional data was transmitted to the Yangtze River Basin Flood Control Command Center via the dedicated water conservancy network, the system automatically calculated the time for the flood to reach Wuhan (about 22 hours) and the peak water level (29.5m). The command center opened the Wuhan river beach flood storage area 18 hours in advance, keeping the Wuhan Guan water level finally controlled at 28.8m (warning level 29.73m), avoiding the flooding of the urban core area and reducing direct economic losses by over 1.5 billion RMB.
2. Structural Safety Monitoring Combination: Seepage Pressure Sensor + Strain Sensor
(1) Core Parameter Analysis:
Seepage pressure sensor: Measurement range 0-2MPa, accuracy ±0.1%FS, response time ≤1s, with automatic temperature compensation function (compensation range -20°C~60°C). The probe is made of stainless steel and can be buried in dam soil or concrete for a long time to monitor changes in dam seepage pressure. For example, the seepage pressure sensors used in the Xiaolangdi Dam are buried up to 30m deep and can capture minor seepage inside the dam (seepage pressure change ≥0.01MPa triggers a warning), avoiding the development of seepage into piping.
Strain sensor: Measurement range -300με~+300με (the elastic strain limit of concrete is about 200με), accuracy ±1με, with anti-electromagnetic interference capability (compliant with GB/T 17626.5 electromagnetic compatibility standard). It can be pasted on the concrete surface of gates and embankments to monitor structural stress deformation. For example, the strain sensors used in the gates of the Middle Route of the South-to-North Water Diversion Project automatically prompt gate overload when the gate opening angle reaches 60° and the strain value exceeds 200με, avoiding gate deformation caused by uneven stress.
(2) Typical Application Scenarios: Xiaolangdi Dam seepage monitoring, Middle Route of the South-to-North Water Diversion gate safety monitoring, Yangtze River embankment deformation monitoring
Implementation Effects and Cases: The Xiaolangdi Dam completed full coverage of structural safety monitoring sensors in 2022. In the spring of 2024, the safety monitoring system found through seepage pressure sensors that the seepage pressure value at monitoring point 3 of the dam rose from 0.8MPa to 0.85MPa (cumulative change of 0.05MPa), while adjacent strain sensors showed a 15με increase in concrete strain. Combining meteorological data (the reservoir water level dropped from 275m to 260m in the previous week, and the stress on the dam changed), technicians judged it as a normal seepage adjustment of the dam, but continued attention was needed. Subsequent 10-day monitoring showed that the seepage pressure value stabilized at 0.83MPa and the strain value returned to the initial level, avoiding the shutdown of dam maintenance caused by misjudgment (one day of shutdown would affect the water diversion flow by about 5 million m³).
3. Water Quality Safety Monitoring Combination: Multi-Parameter Water Quality Analyzer + Dissolved Oxygen Sensor
(1) Core Parameter Analysis:
Multi-parameter water quality analyzer: Can synchronously measure 4 indicators: COD (Chemical Oxygen Demand), ammonia nitrogen, turbidity, and pH value. The COD measurement range is 0-500mg/L (surface water Class III standard COD ≤20mg/L), and the ammonia nitrogen measurement range is 0-10mg/L (surface water Class III standard ammonia nitrogen ≤1mg/L). The response time is ≤3 minutes, and it has an automatic cleaning function (once a week to avoid probe scaling). For example, the multi-parameter water quality analyzers used in the Taihu Lake basin can transmit data via GPRS. When COD exceeds 20mg/L or ammonia nitrogen exceeds 1mg/L, it automatically sends warning SMS to environmental protection and water conservancy departments.
Dissolved oxygen sensor: Measurement range0-20mg/L (suitable dissolved oxygen for fish ≥5mg/L), accuracy ±0.1mg/L, uses fluorescence method for measurement (avoiding the problem of frequent electrolyte replacement), and can work in water temperatures from 0°C to 40°C. For example, the dissolved oxygen sensors used in the Chinese Sturgeon Nature Reserve at the Yangtze River Estuary measure once an hour. When dissolved oxygen drops to 4.5mg/L, it triggers the water replenishment device in the reserve to increase the oxygen content in the water.
(2) Typical Application Scenarios: Taihu Lake cyanobacterial bloom warning, water quality monitoring in the Chinese Sturgeon Nature Reserve at the Yangtze River Estuary, pollutant tracing at the Yellow River Estuary
Implementation Effects and Cases: In the summer of 2023, multi-parameter water quality analyzers in the Taihu Lake basin monitored that the COD in the Meiliang Bay area (water quality target is surface water Class III) rose to 25mg/L and ammonia nitrogen rose to 1.2mg/L, while dissolved oxygen dropped to 4mg/L (precursor to cyanobacterial outbreak). After the monitoring data was synchronized to the Taihu Lake Ecological Regulation Center, staff immediately launched two measures: first, opening the lakeside sluices to introduce clear water from the Yangtze River for dilution (daily water diversion of 5 million m³); second, applying algicidal bacteria agents (20 tons used). Three days later, the COD in the area dropped to 18mg/L, ammonia nitrogen dropped to 0.8mg/L, and dissolved oxygen rebounded to 5.5mg/L, successfully curbing the cyanobacterial outbreak and avoiding the recurrence of the urban water supply crisis caused by the 2007 Taihu Lake cyanobacteria incident.
Applications in Small Watersheds (Tributaries, Irrigation Districts, Flash Flood-Prone Areas, River Estuaries)
1. Irrigation District Precise Regulation Combination: Ultrasonic Water Meter + Capacitive Soil Moisture Sensor
(1) Core Parameter Analysis:
Ultrasonic water meter: Uses the time difference method for measurement, with a range of 1-100m³/h and an accuracy of ±1%FS. It has no mechanical rotating parts (avoiding the failure of traditional mechanical water meters due to sediment blockage), low power consumption design (operating current ≤10mA, supports solar power supply, battery life ≥3 years), and has LoRa wireless transmission function (transmission distance ≥5km). For example, the ultrasonic water meters used in the well irrigation areas of the North China Plain can be bound to farmers' irrigation accounts to achieve "metering by volume," while uploading real-time water consumption data to the irrigation district management platform.
Capacitive soil moisture sensor: Measurement range 0-100%vol (suitable soil moisture for irrigation is 60%-80%vol), accuracy ±2%vol, probe length 15cm (can be inserted into the plow layer soil), with anti-salinization interference capability (suitable for saline-alkali irrigation districts in the northwest), data update frequency 1 time/10 minutes. For example, the soil moisture sensors used in the Ningxia Yellow River Diversion Irrigation District are buried 20cm deep. When the soil moisture drops to 60%vol, it automatically pushes irrigation reminders to farmers' mobile APPs.
(2) Typical Application Scenarios: Water-saving transformation of well irrigation areas in the North China Plain, precise irrigation in the Ningxia Yellow River Diversion Irrigation District, farmland ecological irrigation in the Han River tributaries
Implementation Effects and Cases: In 2024, a county-level irrigation district in the North China Plain (irrigation area of 100,000 mu) completed the transformation of "ultrasonic water meter + capacitive soil moisture sensor," deploying a total of 2,000 ultrasonic water meters (covering all irrigation machine wells) and 500 soil moisture sensors (1 per 200 mu). Before the transformation, the irrigation district adopted a "charging by mu" model, and farmers irrigated based on experience, with an annual water consumption of 420m³ per mu and an irrigation water utilization coefficient of only 0.55. After the transformation, farmers irrigated on demand based on soil moisture sensor data, while ultrasonic water meters statistically recorded water consumption in real time. The annual water consumption per mu dropped to 280m³, the irrigation water utilization coefficient increased to 0.78, and the total annual water saved reached 12 million m³, equivalent to the storage capacity of 8 medium-sized reservoirs. In addition, the irrigation district management department accurately identified 3 high-water-consuming villages (annual water consumption per mu exceeding 300m³) through sensor data, and carried out targeted water-saving technical training, further improving the overall water-saving efficiency of the irrigation district.
2. Flash Flood Warning Monitoring Combination: Pressure Water Level Gauge + Optical Rainfall Sensor + Edge Computing Node
(1) Core Parameter Analysis:
Pressure water level gauge: Based on ceramic piezoresistive sensors, with a range of 0-10m (the river depth in small mountainous watersheds is generally ≤5m), a resolution of ±1mm, and a protection rating of IP68 (can be immersed in water for a long time). It has impact resistance (can withstand the impact of stones brought by flash floods). For example, the pressure water level gauges used in small mountainous watersheds in Southwest China are installed at the bottom of the river. When the water level rise rate is ≥0.5m/h, it automatically triggers a warning.
Optical rainfall sensor: Uses the principle of infrared light scattering, with a resolution of 0.1mm and a rainfall intensity measurement range of 0-8mm/min (rainstorm intensity in mountainous areas can reach 10mm/min). It has no mechanical parts (avoiding the jamming of traditional tipping bucket rain gauges in rainstorms), small size (diameter 10cm), and can be installed on utility poles and mountain guardrails. For example, the optical rainfall sensors used at the flash flood warning points in Wuyi Mountain, Fujian, synchronously send linkage instructions to the pressure water level gauges when the 1-hour rainfall exceeds 20mm.
Edge computing node: Equipped with an ARM Cortex-A7 processor (main frequency 1.2GHz), supports local data storage (capacity ≥16GB) and edge algorithms (such as flood rise rate calculation and warning threshold judgment). It has 4G/LoRa dual-mode transmission (when the 4G signal is interrupted, it automatically switches to LoRa transmission to nearby monitoring stations), with power consumption ≤5W (supports solar power supply). For example, the edge computing nodes deployed in the Nujiang River Valley in Yunnan can calculate the "rainfall-water level" relationship locally. When it is predicted that the water level will exceed the warning level (e.g., 2m) within 30 minutes, there is no need to upload to the cloud, and warning SMS can be directly sent to villagers through the SMS gateway.
(2) Typical Application Scenarios: Flash flood warning in small mountainous watersheds in Southwest China, rainstorm waterlogging monitoring in Fujian hills, flood prevention in mountainous villages in Zhejiang
Implementation Effects and Cases: In August 2023, a small watershed in Wuyi Mountain, Fujian, encountered short-term heavy rainfall (1-hour rainfall reached 35mm, exceeding the linkage threshold of 20mm). The optical rainfall sensor immediately sent a linkage instruction to the pressure water level gauge. The deployed optical rainfall sensor first captured the rainfall anomaly and transmitted the data to the edge computing node; 10 minutes later, the pressure water level gauge monitored the river water level rising from 0.8m to 1.2m, with a rise rate of 0.4m/10min. The edge computing node judged through local algorithms that if the rainfall continued, the water level would exceed 2m (warning level) within 30 minutes, and immediately started the warning: first, broadcasting warning voice to 3 villages within 5 kilometers through LoRa (audio and visual alarms installed at the village entrances); second, sending warning SMS to villagers' mobile phones through 4G (a total of 2,100 messages sent). After receiving the warning, villagers completed the evacuation of personnel in low-lying areas within 30 minutes. Subsequently, the flash flood arrived, and the maximum river water level reached 2.3m, but no casualties were caused, and only a small amount of farmland was flooded. Compared with a similar flash flood event in 2019 (no sensors deployed, causing 3 deaths), the warning effect was significant.
3. River Entry Water Quality Supervision Combination: Portable Multi-Parameter Water Quality Sensor
(1) Core Parameter Analysis:
Portable multi-parameter water quality sensor: Weight ≤2kg (including battery), supports measuring 4 indicators: pH, turbidity, COD, and ammonia nitrogen. The pH measurement range is 0-14 (accuracy ±0.05), and the turbidity measurement range is 0-1000NTU(relevant surface water quality standards specify turbidity requirements for different water bodies). Battery life is ≥8 hours (supports Type-C charging), and data can be synchronized to mobile APPs via Bluetooth 5.0 (synchronization completed within 5 seconds, water quality detection report generated within 1 minute). For example, the portable sensors used by environmental protection law enforcement officers in the Yangtze River Delta region can conduct on-site detection at river entry sewage outfalls, with results available within 5 minutes.
Modular probe design: Probes can be replaced individually (e.g., after the pH probe reaches the end of its life, only the pH module needs to be replaced without replacing the entire device). It has an anti-pollution coating (avoiding cross-contamination of samples during detection) and a calibration cycle of ≥1 month (reducing maintenance costs). For example, the portable sensors used at the river entry monitoring points in the Pearl River Estuary, Guangdong, are calibrated once a month to ensure that the error between detection data and laboratory data is ≤5%.
(2) Typical Application Scenarios: Industrial sewage river entry monitoring in the Yangtze River Delta, rural domestic sewage discharge supervision, ship sewage discharge inspection at the Pearl River Estuary
Implementation Effects and Cases: In March 2024, the environmental protection department of a city in the Yangtze River Delta conducted surprise inspections on 12 industrial river entry sewage outfalls in its jurisdiction, using portable multi-parameter water quality sensors for on-site detection. Among them, the detection at a chemical enterprise's sewage outfall showed: pH value 6.2 (standard range 6-9), turbidity 15NTU (standard ≤3NTU), COD 80mg/L (standard ≤20mg/L), and the data significantly exceeded the standards. Law enforcement officers immediately required the enterprise to stop sewage discharge and used the sensor detection report as evidence (error ≤3% compared with laboratory detection results), imposing a fine of 200,000 RMB according to the law. In addition, in response to the scattered discharge of rural domestic sewage, the city distributed portable sensors to environmental protection coordinators in 10 towns and townships, requiring them to inspect river entry outfalls in their jurisdiction once a month. In the first half of 2024, a total of 18 cases of direct rural sewage discharge were discovered and rectified, increasing the water quality compliance rate of major rivers in the jurisdiction from 85% to 92%.
III. IoT System Layout and Intelligent Upgrade of Water Conservancy Sensors
The water conservancy IoT (Internet of Things) system follows the core logic of the perception layer collecting data → the network layer transmitting data → the application layer analyzing data and outputting decisions. All levels collaborate to achieve intelligent water conservancy management and control. The specific layout is as follows:
Perception Layer: Low-Cost, Highly Adaptable Deployment Strategy
As the "data entry point" of the water conservancy IoT, the deployment density and location of the perception layer directly determine the accuracy and coverage of monitoring data. In response to the extensive geographical nature and topographical complexity of water conservancy scenarios, a "differentiated deployment" strategy needs to be adopted to reduce deployment costs while ensuring monitoring effects.
1. Large Watershed Deployment: "Cross-Section + Key Node" Combination Mode
For main rivers such as the Yangtze River and the Yellow River, as well as large lakes, "control cross-sections" are the core, combined with "key nodes" for supplementary monitoring to form grid coverage. For example, from Yushu in Qinghai to the estuary in Shanghai along the Yangtze River main stream, a total of 108 national-level control cross-sections are set up (average spacing of about 60km). Multi-dimensional sensors (including water level, flow, and water quality) are deployed at each cross-section to achieve full coverage of main stream data. Around key water conservancy projects such as the Three Gorges Dam and Gezhouba Dam, 3-5 auxiliary monitoring points are additionally added (deploying seepage pressure and strain sensors) to strengthen project safety monitoring. This mode not only ensures the continuity of main stream monitoring but also focuses on covering risk areas, reducing deployment costs by 30% compared to "uniform deployment." Taking the middle reaches of the Yangtze River (Yichang to Wuhan) as an example, after adopting the deployment of "6 control cross-sections + 3 dam auxiliary points," the flood monitoring accuracy reached 95%, an increase of 12% compared to before.
2. Small Watershed Deployment: "Grid + Risk Point" Focus Mode
For scenarios such as small mountainous watersheds in Southwest China and irrigation districts in Northwest China, grids are divided and high-risk points are focused on based on "risk levels." For example, in a flash flood-prone small watershed in Southwest China (area of about 50km²), the watershed is first divided into 10 grids (5km² per grid), and 1 optical rainfall sensor is deployed in each grid. Pressure water level gauges are additionally deployed at 3 flood-prone gathering points such as river bends and under bridges. An edge computing node is deployed at the entrance of the downstream village to form a "grid monitoring + risk point focus" deployment system. This mode avoids invalid deployment in low-risk areas, reducing deployment costs by 40% compared to "comprehensive coverage," while the flash flood warning accuracy reaches 90%. Another example is an irrigation district in Northwest China (area of 200,000 mu). According to the grid deployment of "1 soil moisture sensor per 200 mu + 1 ultrasonic water meter per machine well," flow sensors are supplemented at key nodes such as the headworks of the irrigation district and the water diversion outlets of main and branch canals to achieve precise collection of irrigation data. The sensor deployment cost per mu is only 20 RMB.
3. Remote Area Deployment: "Solar Power + Easy Maintenance" Minimalist Mode
For remote areas such as the source of rivers on the Qinghai-Tibet Plateau and desert irrigation districts (where power supply is difficult and operation and maintenance costs are high), a minimalist deployment scheme of "low-power sensors + solar power supply + maintenance-free design" is adopted. For example, at a Yangtze River source monitoring point on the Qinghai-Tibet Plateau (altitude 4500m), solar-powered radar water level gauges (battery life 3 years) and tipping bucket rain gauges (battery life 5 years) are deployed. The sensors adopt an integrated design (no external lines) and are installed on prefabricated concrete bases. Operation and maintenance personnel only need to inspect once a year (replacing batteries and cleaning probes). This mode solves the pain points of "difficult power supply and difficult operation and maintenance" in remote areas, reducing deployment costs by 60% compared to "erecting power supply lines," and achieving a data transmission success rate of 92% (using satellite communication backup).
Network Layer: Multi-Mode Fusion Solution to Solve the "Last Mile" Transmission Problem
Some monitoring points are located in areas without public network coverage, such as mountainous areas and deep river channels. A "multi-mode fusion, emergency backup" transmission network needs to be built to ensure stable data transmission from the perception layer to the application layer.
1. Large Watershed Transmission: "Optical Fiber Private Network + 4G/5G" Primary-Backup Mode
For key water conservancy projects such as the Yangtze River and the South-to-North Water Diversion, a transmission system of "optical fiber private network as primary, 4G/5G as auxiliary" is built. For example, the Middle Route of the South-to-North Water Diversion Project (from Danjiangkou to Beijing) lays dedicated optical fibers along the main canal (transmission rate 100Mbps), connecting all monitoring stations and the central control center to achieve real-time data transmission (delay ≤100ms). In extreme cases of optical fiber interruption (such as optical fiber breakage caused by canal embankment landslides), it automatically switches to the 4G/5G public network (transmission rate 50Mbps, delay ≤200ms) to ensure that critical data (such as gate status and flow data) is not interrupted. In 2023, a section of the Middle Route of the South-to-North Water Diversion experienced optical fiber interruption due to a rainstorm. The system automatically switched to 5G transmission, continuously transmitting gate strain data for 12 hours, avoiding the risk of gate overload, with a data loss rate of 0.
2. Small Watershed Transmission: "LoRa + 4G" Low-Cost Mode
For scenarios such as small mountainous watersheds and rural irrigation districts, a low-cost transmission scheme of "LoRa WAN + 4G" is adopted. LoRa has the advantages of long transmission distance (5-10km), low power consumption (sensor battery life of over 3 years), and low cost (module unit price ≤50 RMB), making it suitable for connecting dispersed sensors. 4G is used to transmit the data collected by the LoRa gateway back to the cloud platform. For example, in the flash flood warning system in Wuyi Mountain, Fujian, pressure water level gauges and optical rainfall sensors are connected to the LoRa gateway at the village entrance via LoRa (transmission distance 3km). The gateway then uploads the data to the municipal water conservancy warning platform via 4G. The transmission cost per single station is only 20 RMB/month (including traffic fees), which is 70% lower than pure 4G transmission. In addition, for mountainous areas without 4G signals, a "LoRa cascade" method (relay transmission by multiple LoRa gateways) is used to transmit data to areas with 4G signals, solving the "signal blind spot" problem. For example, a monitoring point in the Nujiang River Valley in Yunnan achieved data transmission over a distance of 8km through the cascade of 3 LoRa gateways.
3. Emergency Transmission: "BeiDou Short Messages" Bottom-Line Mode
For disaster scenarios such as extreme floods and earthquakes (where conventional communication networks are interrupted), BeiDou short messages are used as an emergency transmission means to ensure the reporting of critical data. BeiDou short messages have the advantages of no ground network dependence, strong anti-interference capability, and wide coverage. The transmission rate is about 100bps, and 120 Chinese characters can be transmitted per time, which is suitable for sending critical information such as water level, rainfall, and disaster conditions. For example, in 2023, a section of the Yellow River encountered an ice flood. Flowing ice caused power outages at 4G base stations along the coast. The deployed radar water level gauges sent water level data to the provincial water conservancy department every 15 minutes via BeiDou short messages ("current water level 12.5m, rise rate 0.1m/h") for 8 hours, providing critical data for ice flood dispatch. Another example is after an earthquake in a mountainous area in Sichuan, where roads were interrupted and communications paralyzed. The deployed tipping bucket rain gauges reported "50mm rainfall within 24 hours after the earthquake" via BeiDou short messages, reminding rescue departments to prevent secondary flash floods and avoiding casualties among rescue personnel.
Application Layer: Scenario-Based Implementation from Data to Decision
The application layer is the "value outlet" of water conservancy sensor data. It needs to combine specific business scenarios such as flood control, irrigation, and ecology to build visualized and intelligent application platforms, realizing the transformation from "data collection" to "decision support."
1. Yangtze River Basin Integrated Flood Control Warning Platform
Integrating data from over 2,000 monitoring stations along the Yangtze River main stream and tributaries (including water level, flow, rainfall, and water quality), a full-process system of "data aggregation-model calculation-warning release" is built. The platform has three core functions: first, real-time visualization, dynamically displaying data from each monitoring point on an electronic map (marking stations exceeding the warning water level in red), and supporting the viewing of historical curves (water level changes in the past 7 days); second, flood evolution simulation, using hydrodynamic models to predict the time and peak water level of the flood reaching downstream cities based on rainfall and flow data (error ≤10%); third, hierarchical warning release, automatically sending warning information (including SMS, audio and visual alarms, and broadcasts) to emergency management departments, cities along the route, and villagers according to flood risk levels (blue, yellow, orange, red). During the 2023 summer flood season of the Yangtze River, the platform predicted the flood peak in the Wuhan section (29.5m) 48 hours in advance, guiding the orderly flood storage in 3 flood storage areas, keeping the actual water level in Wuhan controlled at 28.8m, avoiding urban waterlogging, and improving the warning response efficiency by 30% compared to 2020.
2. North China Irrigation District Intelligent Irrigation Management Platform
Accessing soil moisture sensor and ultrasonic water meter data from 500,000 mu of irrigation districts in the North China Plain, an integrated system of "soil moisture monitoring-water consumption statistics-irrigation dispatch" is built. The platform provides services for two types of users: first, irrigation district management departments, which can view regional soil moisture distribution (divided into three color blocks: "suitable," "water shortage," and "severe water shortage" according to moisture content) and generate irrigation dispatch plans based on the ranking of water consumption in each village (such as "prioritize irrigation in mildly water-shortage areas and restrict flood irrigation in severely water-shortage areas"); second, farmers, who can view the soil moisture of their own farmland through mobile APPs, receive irrigation reminders ("current moisture content 58%, recommend irrigating for 2 hours tomorrow"), and remotely control irrigation valves (supporting timed switching). During the spring irrigation period in 2025, the platform increased the irrigation water utilization coefficient of the irrigation district from 0.65 to 0.78, shortened the average irrigation time per mu by 2 hours, and after farmers' water-saving awareness improved, the proportion of those actively adopting water-saving methods such as sprinkler and drip irrigation increased from 30% to 60%.
3. Dongting Lake Ecological Flow Regulation Platform
Integrating liquid level, flow, and water quality sensor data from Dongting Lake and its incoming tributaries, combined with ecological needs such as fish breeding periods and migratory bird migration periods, a "ecological water level-water quality-flow" linkage regulation system is built. The core logic of the platform is: when sensors monitor that the lake water level is below the ecological lower limit (23.5m), it automatically calculates the required water replenishment volume (based on the rainfall forecast for the next 3 days) and sends a water replenishment request to the Three Gorges Reservoir (coordinated through the Ministry of Water Resources). When it is monitored that the water temperature reaches the suitable temperature for fish spawning (18-22°C) but dissolved oxygen is below 5mg/L, aeration equipment in the lake area (distributed in 10 key areas) is started, and the gates of incoming tributaries are regulated to increase the volume of clear water entering the lake. In the spring of 2024, through sensor data linkage, the platform dispatched water replenishment from the Three Gorges Reservoir 3 times (cumulative water replenishment volume of 1.5 billion m³) and started aeration equipment for 120 hours, achieving a 100% ecological water level guarantee rate during the fish spawning period in Dongting Lake and a 95% dissolved oxygen compliance rate. The number of overwintering migratory birds in Dongting Lake that year increased by 10% compared to the previous year, achieving a balance between ecological protection and water resource regulation.
IV. Technological Innovation and Future Trends of Water Conservancy Sensors
Multi-Parameter Fusion Technology: Upgrade from "Single Monitoring" to "Comprehensive Perception"
Traditional water conservancy sensors mostly monitor single parameters, making it difficult to meet the comprehensive decision-making needs of complex water conservancy scenarios. Multi-parameter fusion technology integrates multiple detection elements in a single sensor module to achieve synchronous collection of multiple indicators such as water level, flow, and water quality. At the same time, algorithms are used to eliminate interference between parameters and improve data accuracy. For example, a "hydrology-water quality integrated sensor" developed by a water conservancy technology enterprise integrates three elements: radar water level detection, electromagnetic flow detection, and fluorescence dissolved oxygen detection. Its volume is only 1/3 of that of traditionally separately deployed sensors, and the cost is reduced by 25%. When applied in Yangtze River tributaries, the sensor can synchronously output water level (±1mm accuracy), flow (±0.5%FS accuracy), and dissolved oxygen (±0.1mg/L accuracy) data, and corrects the influence of water flow velocity on dissolved oxygen measurement through an adaptive algorithm (error reduced from ±0.3mg/L to ±0.1mg/L). In the future, multi-parameter fusion will develop towards "miniaturization and low power consumption." For example, micro-sensors integrating more than 10 water quality indicators can be deployed in small rivers and rural drainage ditches to achieve refined water quality monitoring.
Edge Computing and AI Algorithm Embedding: Reducing Transmission Pressure and Enhancing Real-Time Decision-Making Capability
Water conservancy monitoring data volume is large (annual data volume per station exceeds 10GB). Uploading all data to the cloud will lead to high transmission delay and bandwidth costs. Edge computing technology embeds AI (Artificial Intelligence) algorithms at the sensor or gateway end to achieve local data preprocessing, anomaly detection, and decision judgment, uploading only critical data to reduce transmission pressure. For example, in flash flood warning scenarios, edge computing nodes can run "rainfall-water level" prediction models locally. When it is monitored that the 1-hour rainfall exceeds 20mm and the water level rise rate exceeds 0.5m/h, it directly triggers local warnings without waiting for cloud instructions, shortening the warning response time from 30 seconds to 5 seconds. After a mountainous county deployed edge computing flash flood sensors, a total of 12 local warnings were issued during the 2024 flood season, all of which accurately captured small-scale flash floods without a single missed report. In the future, edge computing will be combined with lightweight AI models. For example, an "irrigation demand prediction model" can be embedded in soil moisture sensors to directly output irrigation suggestions (such as "need to irrigate for 1.5 hours") based on current soil moisture and the 3-day weather forecast, without relying on cloud platforms, making it suitable for remote irrigation district applications.
Deep Integration of BeiDou Short Messages and Sensors: Strengthening Emergency Monitoring Capability in Extreme Scenarios
In response to communication interruption in extreme scenarios such as floods and earthquakes, the deep integration of BeiDou short messages and water conservancy sensors has become a key innovation direction. Currently, some enterprises have developed "BeiDou integrated water level gauges," which directly embed the BeiDou short messages module inside the sensor without the need for external communication equipment. When the conventional network is interrupted, it automatically switches to BeiDou transmission, sending critical data (including water level value, battery power, and device status) every 15 minutes. During the 2023 Yellow River ice flood, 5 BeiDou integrated water level gauges deployed in dense flowing ice areas continuously transmitted water level data via BeiDou for 8 hours, providing the only data source for ice flood dispatch. In the future, BeiDou integration will develop towards "low power consumption and high frequency," such as supporting data transmission every 5 minutes (the current BeiDou short messages standard frequency is 1 time/minute, requiring optimized power consumption control). At the same time, the transmission content will be expanded. In addition to water level and rainfall, engineering safety data such as dam seepage pressure and gate strain can be transmitted, further improving monitoring coverage in extreme scenarios.
Future Trends: From "Monitoring" to "Intelligent Control," Promoting the Transformation of Water Conservancy Governance Models
Sensor self-organizing network and self-healing capability: Future water conservancy sensors will have self-organizing network functions. When a station fails, surrounding sensors will automatically relay and transmit data to avoid monitoring blind spots. For example, if a sensor at a cross-section in the Yangtze River main line sensor network fails, upstream and downstream stations can share data and calculate the water level and flow of the faulty station through LoRa self-organizing networks, ensuring data continuity, with a self-healing time of ≤5 minutes.
Cross-basin data collaboration: Achieving cross-regional collaboration of sensor data from different basins through the National Water Conservancy Data Center. For example, rainfall data from the Yangtze River basin can be synchronized to the Pearl River basin flood control platform to help the Pearl River predict the impact of flood transit in advance. Water quality data from the Middle Route of the South-to-North Water Diversion can be shared with agricultural irrigation districts along the route to guide farmers to adjust irrigation water schemes (avoiding irrigation during water quality sensitive periods), improving the comprehensive utilization efficiency of water resources.
Linkage with intelligent control of water conservancy projects: Sensor data is directly connected to the water conservancy project control system to achieve a closed loop of "monitoring-decision-execution." For example, the reservoir gate control system can automatically adjust the gate opening according to the real-time data of the radar water level gauge (when the water level reaches 80% of the warning level, open 20% of the gate; when it reaches 100% of the warning level, open 50% of the gate), without manual operation, shortening the response time from 10 minutes to 1 minute. After a medium-sized reservoir deployed an intelligent linkage system, the gate dispatch accuracy reached 100% during the 2024 flood season, with no over-water-level flood discharge.
V. Market Size and Industrial Development Pattern of Water Conservancy Sensors
Market Size Breakdown (2024-2027)
1. Global market: According to the Markets and Markets 2025 report, the global water conservancy sensor market size is about 2.45 billion USD, and is expected to grow to 3.76 billion USD by 2028, with a compound annual growth rate (CAGR) of 15.2%. The growth momentum mainly comes from two major sectors: first, water conservancy infrastructure construction in developing countries (such as India's "National Water Mission" plan, which will deploy 500,000 water level and flow sensors from 2024 to 2026); second, the replacement of old sensors in developed countries (such as the US EPA requiring the update of 30% of water quality monitoring sensors nationwide by 2026, driving market demand growth by 18%). By product, water level sensors account for the highest proportion (reaching 35% in 2024), followed by flow sensors (28%) and water quality sensors (22%). Soil moisture sensors are rising due to the demand for smart irrigation and have the fastest growth rate (CAGR reaching 18.5%).
2. Chinese market: According to data from the China Water Conservancy Enterprise Association, the market size of water conservancy sensors in China will be about 15.2 billion RMB in 2030, and is expected to reach 28.6 billion RMB in 2035, with a CAGR of 13.5%, higher than the global average. Among them, policy drive is the core factor: the "15th Five-Year" Water Conservancy Informatization Plan requires full coverage of sensors in all basins and irrigation districts by the end of 2035. In the central water conservancy construction investment in 2035, the proportion of sensor procurement will reach 15.5% (an increase of 5.3 percentage points compared to 2030). By scenario, the flood control monitoring field has the largest scale (accounting for 33% in 2025, about 2.74 billion RMB), the smart irrigation field has the fastest growth rate (CAGR reaching 25.1%, with a scale of about 2.32 billion RMB in 2025), and the ecological flow monitoring field, driven by policies such as the "10-year fishing ban in the Yangtze River," will reach 1.69 billion RMB in 2025 and is expected to double to 3.42 billion RMB in 2028.
Industrial Development Pattern
1. Upstream of the industrial chain: Core component suppliers. The proportion of domestic enterprises has increased significantly, achieving independent and controllable key technologies in the mid-to-low-end field, while still gradually breaking through in the high-end field. For example, for the radar module of water level sensors, a Shenzhen enterprise accounts for 40% of the domestic market share. Its developed 24GHz radar chip has a ranging accuracy of ±1mm, and the cost is 50% lower than that of imported chips. For the fluorescence dissolved oxygen probe of water quality sensors, a Hangzhou enterprise accounts for 35% of the domestic share, with a response time of ≤3 seconds and a lifespan of 2 years, breaking the monopoly of European and American enterprises. In addition, for supporting components such as solar power supply modules and LoRa communication modules, domestic suppliers account for over 80%, supporting the reduction of downstream complete machine costs (complete machine costs decreased by 30% compared to 2020).
2. Midstream of the industrial chain: Complete machine manufacturers and system integrators, showing a pattern of "head concentration + segmentation dispersion." Head enterprises such as Dayu Water-Saving and Xianhe Environmental Protection, relying on the advantages of general contracting for water conservancy projects, occupy high-end markets such as large basins and national-level irrigation districts (the combined share of the two will reach 41% in 2030). For example, the integrated hydrological sensors provided by Dayu Water-Saving for the Middle Route of the South-to-North Water Diversion integrate multi-parameter functions of water level, flow, water quality, and ecology, and over 5,000 units have been deployed. The smart water quality sensor network provided by Xianhe Environmental Protection for Yangtze River ecological monitoring covers 350 monitoring points, with a data accuracy rate of 99%. Segmented field enterprises focus on specific scenarios, such as a Beijing enterprise focusing on flash flood warning sensors, accounting for 30% of the domestic mountainous market share; a Gansu enterprise focusing on irrigation district soil moisture sensors, accounting for over 25% in the northwest market.
3. Downstream of the industrial chain: The application end is mainly government water conservancy departments, large irrigation district management units, and water conservancy project companies, with the procurement model mainly based on bidding. In 2030, the procurement proportion of government water conservancy departments will reach 65% (mainly used for flood control, ecological monitoring, and intelligent regulation), large irrigation district management units will account for 22% (smart irrigation), and water conservancy project companies will account for 13% (supporting new water conservancy projects). The procurement demand for rural small irrigation districts and remote watersheds is shifting from "unified government procurement" to "county and township independent procurement + market-oriented operation." In 2030, the county and township-level procurement scale will increase by 68% compared to 2025, promoting the development of midstream segmented field enterprises.
Conclusion
As the "nerve endings" of water conservancy informatization, the technological evolution and practical application of water conservancy sensors have profoundly changed the traditional water conservancy governance model.
From single-parameter monitoring to multi-parameter fusion, from centralized cloud processing to edge intelligent decision-making, and from conventional communication dependence to BeiDou emergency guarantee, water conservancy sensors have achieved the leap from "data collection" to "intelligent regulation" in core scenarios such as flood control and disaster reduction, smart irrigation, and ecological protection. The rapid growth of market size and the formation of an independent and controllable industrial chain pattern have further laid the foundation for the large-scale application of water conservancy sensors.
In the future, with the development of technologies such as cross-basin data collaboration and sensor self-organizing networks, water conservancy sensors will continue to promote the transformation of water conservancy governance towards "precision, intelligence, and collaboration," providing core technical support for ensuring national water security and achieving efficient utilization of water resources.
Author | Guo Yuansheng, Deputy Director of the Science and Technology Committee of the Central Committee of the Jiusan Society, Executive Vice Chairman of the China Sensor and IoT Industry Alliance
Editor | Yang Pengyue Art Editor | Maria Supervisor | Zhao Chen