Author(s)

José O. Payero^1*, Michael W. Marshall¹, Ali Mirzakhani Nafchi², Ahmad Khalilian¹, Bhupinder S. Farmaha¹, Rebecca Davis¹, Wesley Porter³, George Vellidis³

¹Clemson University Edisto Research and Education Center, Blackville, USA.
²Cornell University, Ithaca, USA.
³University of Georgia, Tifton, USA.

Runoff is an important component of the water balance of agricultural fields. Accurate measurement or estimation of agricultural runoff is important due to its potential impact on water quantity and quality. Since runoff from agricultural fields is sporadic and is often associated with irrigation and/or intense rainfall events, manually measuring runoff and collecting water samples for water quality analysis during runoff events is inconvenient and impractical. In the fall of 2017, a field site was selected at the Clemson University Edisto Research and Education Center with the objective of developing, constructing, and testing an Internet of things (IoT) flume system to automatically measure runoff and collect water samples. In 2018, an automatic IoT system was developed and installed consisting of six stainless steel H-flumes (22.9-cm), which measured runoff from six adjacent research plots under two different cultural regimes (cover crop and no cover crop). An electronic eTape sensor was installed in the flume and used to measure the water level or the flume’s head. Open-source electronic (Arduino) devices and a cloud-based platform were then used to create a wireless sensor network and IoT system to automatically record the amount of runoff (hydrograph) coming from each section, collect water samples and transmit the data to a Cloud server (Thingspeak.com) where the data can be viewed remotely in real-time. The IoT flume system has been operating successfully and reliably for more than two years.

Flume, Runoff, Water Quality, Cover Crop, Erosion

Payero, J. , Marshall, M. , Nafchi, A. , Khalilian, A. , Farmaha, B. , Davis, R. , Porter, W. and Vellidis, G. (2021) Development of an Internet of Things (IoT) System for Measuring Agricultural Runoff Quantity and Quality. Agricultural Sciences, 12, 584-601. doi: 10.4236/as.2021.125038.