EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Cost-effective full monitoring system for long-term measurements in lake ecosystems

Daniele Strigaro, Massimiliano Cannata, Camilla Capelli, and Fabio Lepori
Daniele Strigaro et al.
  • SUPSI, Istituto scienze della Terra, DACD, Canobbio, Switzerland (

The concomitance of climate changes and human activities effects is a mix of co-factors that can induce unknown dynamics and feedbacks which need to be studied and monitored. Lakes are one of the most affected natural resources. Due to their importance for economy, water supply, tourism it is essential to safeguard their health. Unfortunately, lake monitoring is dominated by very high costs of materials and by proprietary solutions that are a barrier for data interoperability. To this end, an integrated system which uses as much open source licensed technology as possible and is open source itself will be presented. The main idea is to create a complete pipeline that can integrate different data sources by means of processes that can make the time series organized and accessible and then be served via standard services. Data integration allows further analysis of the data to produce new time series either by manual or automatic processes. This proposition also includes the creation of an Automatic High-Frequency Monitoring (AHFM) system built using cost-effective principles and meeting open design requirements. The preliminary results and the applications of this solution will be described such as the calculation of the primary production and the quasi real-time detection of algal blooms. The study area where this system has been developed and tested is Lake Lugano in the southern part of Switzerland, which is a very productive lake affected by climate changes effects. The developed system permits the integration of the historical data measured with the traditional campaigns on the lake with new datasets collected with innovative technologies so that the comparison and validation of datasets can be more easily performed. In this way it is possible to detect biases and create automatic data pipelines to calculate indicators and notify alerts. 

How to cite: Strigaro, D., Cannata, M., Capelli, C., and Lepori, F.: Cost-effective full monitoring system for long-term measurements in lake ecosystems, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15274,, 2023.