Automatic monitoring of surface water quality is a key task in water resource protection, serving as a crucial means for pollution prevention and water quality early warning. Utilizing unmanned, real-time monitoring instruments and modern information technology for data collection, transmission, and storage allows timely and accurate tracking of water quality conditions and dynamic trends.

Features of Water Quality Automatic Monitoring Stations:

Water quality automatic monitoring stations are established at various locations such as rivers, lakes, reservoirs, drinking water sources, groundwater observation points, and nearshore areas within a watershed. These on-site stations function as automated laboratories for continuous monitoring of the water body's quality changes. They objectively record water quality conditions, promptly detect abnormal changes, and enable pollution forecasts for the water body or downstream areas. The stations facilitate studies on water body dispersion and self-purification processes. The overall goal is to understand water quality and pollutant flux, prevent water pollution incidents, and provide technical services to environmental protection management authorities.

Key Monitoring Parameters:

The primary monitoring parameters for water quality automatic monitoring stations, based on practical needs, include the standard five water quality parameters (pH, conductivity, dissolved oxygen, turbidity, temperature), chemical oxygen demand (CODCr), permanganate index, ammonia nitrogen, total phosphorus, total nitrogen, specific heavy metal elements, and river-type Doppler flowmeters.

Significance of Advanced Water Quality Monitoring Technology:

The scientific and modernized approaches in water environmental monitoring technology hold significant importance for timely and effective decision-making in water pollution prevention, control, and management by environmental protection authorities.

In summary, automatic water quality monitoring systems contribute to the comprehensive understanding of water quality conditions, enable pollution forecasting, and support environmental protection management with accurate and real-time data.