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.