Design and Optimization of a Sustainable Automated Irrigation System for Enhanced Water Management in Small-Scale Fishpond

Abstract

Efficient water management is essential for improving productivity and sustainability in small-scale aquaculture systems. Traditional manual irrigation practices often result in inconsistent water quality, excessive water consumption, and increased labor requirements, which negatively affect fish growth and farm profitability. This study developed and evaluated a sustainable automatic irrigation system designed to optimize water management in small-scale fishponds through real-time monitoring and automated control of critical water quality parameters. The system integrates an Arduino Mega microcontroller with temperature, pH, and dissolved oxygen sensors to regulate water exchange using a water pump and solenoid valve powered by a solar-assisted energy system.

A 90-day experimental evaluation was conducted using two identical 1,000-L IBC plastic tanks stocked with African catfish (Clarias gariepinus). One tank was managed using conventional manual irrigation, while the other employed the developed automated irrigation system. Daily measurements of water temperature, pH, and dissolved oxygen were collected and analyzed using independent samples t-tests at a 5% level of significance. Water consumption, fish survival, and economic performance were likewise evaluated.

Results demonstrated that the automated irrigation system maintained significantly more stable water quality than the manual system. The automated setup achieved lower average water temperature (29.87°C), more favorable pH (7.72), and higher dissolved oxygen concentration (5.94 mg L⁻¹), all of which were significantly different from those observed under manual irrigation (p < 0.05). Water consumption was reduced by 40%, decreasing from 7,500 L in the manual system to 4,500 L in the automated system over the experimental period. Higher fish survival (92%) resulted in greater gross income (₱8,050), net income (₱5,050), and return on investment (16.83%) compared with conventional management.

The findings demonstrate that integrating sensor-based automation with sustainable energy provides an effective and economically viable approach for improving water management, conserving freshwater resources, and enhancing productivity in small-scale aquaculture operations.