EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

CIANOMOD Project. A data gathering and analysis structure for the remote monitoring of algae blooms in inland waters based on Internet of Things

Juan Antonio Pascual-Aguilar1, Jesús Morón-López2, Cristina Rodríguez-Sánchez3, Francisco Carreño4, Joaquín Vaquero3, Ángel G. Pompa-Pernía5, and Myriam Mateos-Fernández3
Juan Antonio Pascual-Aguilar et al.
  • 1IMDEA WATER Institute (Proyecto CIANOMOD), Geomatics Unit, Alcalá de Henares, Spain (
  • 2Institute of Plant Science and Resources, Okayama University, Kurashiki city, Japan
  • 3Electronics Technology Department, Rey Juan Carlos University, Madrid, Spain
  • 4Geology Department, Rey Juan Carlos University, Madrid
  • 5IMDEA WATER Institute, Alcalá de Henare, Spain

Harmful Algae Blooms (HAB) are now a topic of increasing interest due to the consequences they trigger on the quality of aquatic ecosystems and human health. Cyanobacterial (blue-green algae) proliferation, recurrence and distribution in water bodies around the world is caused by the sum of different climatic and anthropic factors. Manual sampling techniques are not sufficient to satisfy an adequate monitoring; hence, new strategies are needed to its continuous monitoring and possible prediction in affected areas. Real-time sampling techniques provide continuous recording and immediate data reception, which facilitates HABs monitoring with a very fine spatial-temporal resolution. However, these emerging tools are in their very early development stage and some relevant issues still constrain their applicability by many water management agencies. The objective of this work is to implement the same Remote Monitoring System (RMS) architecture in two different water bodies in Iberian Peninsula and to test its suitability for HABs monitoring. To this end, we deployed two plug-and-play nodes based on YSI technologies, two customised nodes based-on Libelium Waspmote and one Libelium weather station in the freshwater As Conchas reservoir, in NW Spain, and the shallow L'Albufera brackish water lagoon in Eastern Mediterranean shoreline.  After that, we evaluate the representativeness of the collected data by performing a Pearson correlation test between the deployed nodes and satellite images. The results show that the more heterogeneous the environment is, the more nodes must be deployed in different areas for a longer time to obtain a realistic view of the water body status. Therefore, this study provides critical and empirical data to implement a profitable and effective real-time monitoring system in other HAB-affected areas.

Acknowledgements: This work was supported by the Spanish Fundación Biodiversidad, Ministry for Ecological Transition and the Demographic Challenge (CianoMOD Project, CA_CC_2018).

How to cite: Pascual-Aguilar, J. A., Morón-López, J., Rodríguez-Sánchez, C., Carreño, F., Vaquero, J., Pompa-Pernía, Á. G., and Mateos-Fernández, M.: CIANOMOD Project. A data gathering and analysis structure for the remote monitoring of algae blooms in inland waters based on Internet of Things, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1122,, 2021.