A Methodology for Designing a Roof Rainwater Quality Sensing-Recording-Grading System Using Low-Cost Sensors Paired with Microcontroller Software

We present a methodology for creating a roof rainwater harvesting (RWH) contaminant sensing-recording-grading (SRG) system comprising hardware and software components like low-cost sensors, a solar-powered data logger, a publicly available Arduino Integrated Development Environment (IDE) software, and smart mobile and web applications for data retrieval. We illustrate the prototype SRG system designed for monitoring basic roof-RWH quality parameters (i.e., electrical conductivity (μS/cm), temperature (°C), and depth (mm)) with a temporal frequency of 15 min from February to August 2024 in a rain barrel receiving rooftop runoff from a U.S. Environmental Protection Agency (EPA) building located in Georgia, USA. We established data validation protocols and verified the performance of the sensors by using an alternative set of sensors. We performed minimal data filling and comparable data cleaning for intermittent data gaps, which were partly attributed to extreme weather conditions or hardware or software issues. Analysis of the cleaned data set showed a robust performance of the tested sensors comparable to the validation sensor, with strong Pearson correlation coefficients between the two sensors’ conductivity (0.99) and temperature measurements (1.00) and similar data spreads and mean values. The clean data analysis also showed that the RWH conductivity ranged from 7 to 116 μS/cm, the temperature ranged from 5 to 29 °C, and the depth ranged from 29 to 838 mm, from February to August 2024.

The study provides a firm basis for future demonstrations of additional rainwater quality monitoring efforts supporting the EPA’s green infrastructure practice recommendations.