Developing a Real-time Flood Monitoring System Using Low-cost IOT Stations

Abstract

The National Capital Region of the United States (NCR) is exposed to coastal, riverine, and interior floods. As aquatic events are expected to become more intense with climate change (CC), monitoring and warning systems are essential to support flood resilience. Additionally, sea level rise, which is another consequence of CC, may lead to the increase of damage caused by storm surge and high flood water in coastal communities. The purpose of this research is to develop a low-cost real-time flood monitoring and warning system in the NCR. The NCR is one of the most growing regions of the country where around 13 million people live. Researchers from the Flood Hazards Research Laboratory at the George Mason University developed a sensor module that measures water level and provides real-time information to flood forecast models and alert the community via a web portal. The solar-powered station consists of a Mayfly data logger, a Maxbotix ultrasonic sensor, and a communication device. A prototype was developed using a new transmitter called the Digi XBee LTE. Tests were conducted to evaluate power autonomy and ensure proper transmission of the data online. The station was successfully developed during this work and will be added to the Integrated Flood Forecast System (iFLOOD, https://iflood.vse.gmu.edu/). iFLOOD is an experiment to incorporate multi-scale and multi-temporal physical processes for flood prediction. The sensors will be deployed in the NCR and improve the data for iFLOOD, which has a SMS-based alert system to notify the public of approaching events.