Tough, cheap sensor uses satellite signals to monitor water levels
Water level sensors serve an important purpose in rivers, warning of floods and unsafe recreational conditions. A new one is claimed to be not only more robust and reliable than others, but also considerably less expensive.
According to scientists at Germany's University of Bonn, conventional water level sensors suffer from one or more limitations – they get damaged in floods, they're difficult to read remotely, they don't measure water levels continuously, or they're too costly. Led by Dr. Makan Karegar, the researchers developed an alternative that doesn't have such problems.
The device takes the form of an antenna that is installed adjacent to a river, out of the water. It continuously receives GPS and GLONASS satellite signals – part of each signal is received directly from the satellite, while the rest is received indirectly, after it's been reflected off the river's surface. The further down the surface is relative to the antenna, the longer the distance the reflected radio waves end up traveling.
When the indirect part of each signal is superimposed over the directly received part, interference patterns result. By analyzing those patterns, an onboard Raspberry Pi microcomputer is able to determine the current water level to within an accuracy of plus or minus ~1.5 cm (0.6 in). That data is transmitted to authorities via existing mobile networks.
The whole setup costs only about €150 (US$156) to build, and can be powered by a solar panel. In fact, one of the sensors has been in use for two years on the Lower Rhine river. That said, the technology currently only works on rivers that are at least 40 m (131 ft) wide – otherwise, much of the reflected signal comes from land. It is hoped that by refining the Raspberry Pi software, that figure can be reduced considerably.
Both the open-source code and the plans for the device are freely available via the project website. The research is described in a paper that was recently published in the journal Water Resources Research.
Source: University of Bonn