To proper manage water resources a key component is the data acquisition through environmental monitoring. A field monitoring allows us to identify changes that may occur in the hydrological regime as a result of climate change and land use and occupation. However, the cost of sophisticated hydrological monitoring equipment’s may be prohibitive for many locations around the world. This work aims to develop a low-cost monitoring platform (LCMP) to be used to densify the hydrological monitoring network for rainfall, small rivers level and water temperature. We started the process by building an open source environmental data collection platform based on the Arduino electronic platform associated with low-cost sensors, GSM shield, a solar panel and a battery. The first step was to test data transmission to a data server through the GPRS network, which worked as expected, just like platforms using professional modems. The second step was the evaluation of the reliability and quality of data for precipitation and water temperature measurements. For precipitation a low-cost tipping bucket rain gauge was used and for temperature low cost sensors (DS18B20) were used. Those sensors were compared to a professional monitoring platform used for official hydrological monitoring. We identified an excellent correlation between both, with coefficient of determination greater than 0.99. The LCNP was kept activated and collecting data for over 150 days without major problems. The cost of the professional solution currently used is close to € 8,200 while the low-cost solution resulted in € 450, approximately, 5.5% of the cost of the professional solution. The next important steps are to validate the level sensor reliability and assess the LCNP durability exposed to weather conditions.
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Low cost automation for hydrological monitoring in water resource management
Published:
12 November 2019
by MDPI
in The 4th International Electronic Conference on Water Sciences
session Managing Water Resources from Aquifers, Rivers and Lakes
Abstract:
Keywords: data; managment; low-cost; arduino