Affordable sensor networks
In general, the high cost of using standard commercial sensors for water quality and carbon cycling presents a significant limiting factor for implementing high spatio-temporal sensor networks. ‘Affordable’ sensors/devices have a price of at least one order of magnitude lower than an off-the-shelf commercial product. Developments in affordable, open-source computing hardware, such as microprocessors (e.g. Arduino) and single-board microcomputers (e.g. Raspberry Pi) could bridge the gap between low-cost sensing and data logging, with wireless real-time data transmitting (Chan et al., 2021) enabling their use in a wide range of geographic locations and by a range of users, including citizen scientists, particularly IoT networks become more widespread. While there are advantages to adopting citizen science methods for monitoring water quality, there are also several obstacles to overcome. Research indicates that the technology utilized for citizen science water quality monitoring should be cost-effective, easy to use, and capable of producing precise outcomes. In this context, IoT devices and sensors integrated with smartphones show potential as viable solutions (Amador-Castro et al., 2024)
Currently, there are low-cost reported solutions for aquatic measurements of multiple parameters directly relevant to understanding C cycling in aquatic systems (Table 1, column 3). In addition, there are multiple affordable datalogging devices and wireless communication options relying on local-, cellular-, and satellite- based solutions (Levintal et al., 2021). The field of affordable sensors is evolving rapidly, with new capabilities constantly emerging. For example, a compact multi-gas sensing platform for CO2, CH4 and N2O sub-ppm measurements is under development (Wastine et al., 2022). Such a device can be used in automatic flux chambers to quantify, in real-time, emissions of all three main GHGs, from different locations within one river catchment. Despite this, highly specialized equipment will increase monitoring costs, which is only feasible for limited initiatives. With respect to carbon cycling in rivers, there is still a need for affordable solutions for dissolved organic matter (DOM), nutrients, and dissolved gases other than O2 and CO2. The use of low-cost auto-samplers(Carvalho, 2020), portable spectrophotometers (Laganovska et al., 2020) or UV fluorescence spectroscopy (Yeshno et al., 2021) can potentially provide relevant solutions for autonomous water sampling and analysis, thus meeting the need for high-resolution monitoring without excessive costs. However, given the increasing availability of low-cost solutions for deployment by a range of users, these sensors must be developed, deployed, and maintained in line with robust protocols to ensure data accuracy.
In many cases, affordable sensors have not been designed for use in aquatic systems. Installing or developing a sensor station (node) may take longer to implement than standard commercial sensors and require different steps such as waterproofing, calibration, or processing of raw data, which can present barriers to non-technical users (Chan et al., 2021). There are also major challenges with incorporating multiple sensors, possibly with different outputs, into a single and stable working system, for example a monitoring robot. Another barrier is psychological, as affordable sensors can sometimes be wrongly considered less appropriate for rigorous scientific research (Chan et al., 2021)Overcoming these challenges will lead to the development of low-cost sensor nodes, which will increase the affordability of deploying multiple nodes within an environment, increasing the spatial resolution, particularly valuable in areas where unpredictable extreme events are increasingly likely. Increasing accessibility of this technology, to economically developing nations will also be improved.