Abstract: Some problems of aquaculture water quality monitoring systems, such as wiring difficulties, low performance-price ratio and short of flexibility, still exist. This paper analyzes the limitations of the existing aquaculture water quality monitoring systems and the new aquaculture water quality monitoring systems based on wireless sensor networks. The proposed system uses sensor nodes to obtain data of water temperature, pH value and dissolved oxygen concentration; a sink node is used to collect data from the sensor nodes through a wireless sensor network and monitoring center to process data downloaded from the sink node through RS232 serial port, and present to users. The hardware platform of the sensor node is composed of a processing module, a sensor module, wireless communication and a power module. The processing module uses a MSP430F149 as the processing core. The sensor module uses PHG-96FS pH combination electrodes and DOG-96DS dissolved oxygen electrodes to measure water quality parameters. Since sensor output signals are weak and noisy, a signal conditioning circuit is designed to amplify and filter the weak signals so as to meet the requirement of input range of the A/D converter. The wireless communication module uses an RF905 RF chip and its periphery circuits to receive and send data. The power module uses an LT1129-3.3 chip, an LT1129-5 chip, a Max660 chip and their periphery circuits to supply 3.3 V and ±5 V voltage for the processing module, wireless communication and the sensor module. The system software consists of two parts, the node software and monitoring software. The node software, which is compiled using C Language in IAR Embedded Workbench, can complete data acquisition and processing, wireless transmission, and serial communication. The monitoring software, which is compiled using vb6.0, can provide users with a visual image of real-time data monitoring platform. Furthermore, the correction and reliability of system are verified. The results demonstrate that the average packet loss rate is 0.77%, and the relative errors of pH value, temperature and dissolved oxygen are less than 1.40%, 0.27% and 1.69%, respectively. Our study showed that the system with characteristics of higher acquisition frequency, smaller size, lower cost, and good flexibility, can implement real-time monitoring of water quality parameters in a wide range of water types.