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The recognition of global change impacts on catchments and the waters they drain emphasizes the need to better understand and predict both hydrological and biogeochemical dynamics at the terrestrial-aquatic interface. To achieve this great endeavor, a key priority is to substantially increase the number of multi-annual time series, covering a broad range of river types and filling existing geographical gaps (e.g., low-income regions in/and remote areas). However, commercial multi-sensor solutions are not affordable to everyone. The multi-sensor platform consists of a STM32 micro-controller board combined with a data logger module, and a set of sensors to measure hydro-chemical properties both at different depths in soils (adjacent to the streams) as well as within streams: temperature, water level, moisture, electrical conductivity, turbidity, dissolved O2 and CO2. The monitoring system is also equipped with a wireless communication capability using LoRa network technologies. To make our project as accessible as possible, we have designed, built, and programmed the multi-sensor adopting the Open Source Hardware and Software philosophy. Through the complete processes of pre-calibration and in situ measurement, the preliminary results illustrate that the proposed multi-sensor system can provide long-term, high-frequency hydrological and biogeochemical data across land-stream interfaces while keeping the balance of costs and accuracy.
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Gener et al. (2024) studied this question.
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