Framework for evaluating the performance of water quality sensors

Ensuring water quality requires continuous monitoring and assessment. Traditional approaches, based on manual sampling and laboratory analysis, are time-consuming, labour-intensive, and costly. Sensor-based technologies offer real-time water quality monitoring with high sensitivity, selectivity, cost-effectiveness, and operational efficiency. However, before field deployment, sensors must undergo rigorous validation to ensure accuracy, reliability, and long-term performance. Implementing validation protocols is essential to achieve consistency, reproducibility, and comparability of sensor performance across diverse monitoring locations and environmental conditions. This study proposes a structured validation framework, providing a systematic methodology to evaluate water quality sensors. To demonstrate its applicability, a commercially procured pH sensor was validated under controlled laboratory conditions using standard buffer solutions. The results indicate that the sensor showed the accuracy of 97.58 % in the acidic range (pH 1–6), 98.84 % at neutral pH (pH 7), and 94.38 % in the basic range (pH 8–14). Precision analysis showed intraday variability between 0.89–1.75 % RSD and interday variability between 0.71–2.85 % RSD, with strong linearity (R² = 0.9988), confirming consistent and reproducible performance. These results confirm that standards-based validation offers assurance of the sensor’s operational reliability and accuracy. While validation with standards is a critical first step, comprehensive assessment requires testing across different water matrices, where complex ionic composition, organic matter, and interfering species may influence sensor performance. To ensure sustained performance, it is also recommended that the sensor undergo field validation following installation and be periodically reassessed, typically every six months. This study establishes the foundation for a robust validation framework that can be extended to diverse sensors and water matrices, thereby ensuring reliable real-world applications. Moreover, the framework serves as a benchmark for future sensor validation studies, enhancing comparability, reproducibility, and standardization in water quality monitoring research.