Drones, also known as unmanned aerial vehicles (UAVs) or small unmanned aircraft (SUAs) have seen rapid technological advancement in recent decades. This has resulted in an ever-growing array of applications such as aerial surveillance, rescue operations, border patrol tasks, and precision farming
Image Credit: Yevhenii Chulovskyi/Shutterstock.com
Drones are also being used more frequently in the fields of resource and environmental observation as they can track quick changes in environmental variables, including plant growth, hydrological processes, and destruction in the aftermath of catastrophic weather events like hurricanes.
Drones provide scientists with in-depth information and verification of vegetation change, flow measurements, and at-risk areas for floods in aquatic ecosystems, as well as data from unreachable ranges of freshwater and coastal systems in a cost-effective manner.
However, such progress in water quality assessment is extremely desirable, particularly for large-scale routine monitoring programs.
The goal of a new study published in the journal Science of The Total Environment was to see if a drone-deployed payload could: i) accurately collect physiochemical data and water samples, ii) be of sufficient volume to meet the needs of large-scale water quality management programs like the WFD, and iii) produce similar water chemistry and physiochemical outcomes to traditional boat water sampling.
From September to November 2019, field trials were held at Ballquirke Lake and Loughs Fee, Inagh, Conn, Derg, and Mask in the west of Ireland.
Three water samples were taken at each of the 12 locations using each of the two collection techniques, conventional boat-based water sampling and drone-based water sampling, for a total of 72 water samples to compare water chemistry parameters between the two sampling techniques and to examine the variability associated with each sampling techniques. Table 1 reveals the information.
Table 1. Key characteristics of lakes sampled during field trials. Source: Graham, et al., 2022
||No. of sampling locations
||Co-ordinates for sampling locations
||Lake surface area (ha)
||Maximum depth (m)
||Water framework directive alkalinity statusa
||Water framework directive typology classa
a Data taken from Inland Fisheries Ireland National Research Survey Programme Fish Stock Assessments 2015 & 2016 (Kelly et al., 2016; Kelly et al., 2017, Kelly et al., 2017; McLoone et al., 2017).
b Data taken from the EPA Maps portal (EPA, 2019).
To eliminate any biosecurity hazards, all sampling equipment was cleaned with distilled water before each consecutive sample collection, and all field equipment was cleaned with Virkon Aquatic.
The data from the last 90 seconds of the 4-minute period were kept for the physico-chemical parameters to guarantee that the probes had enough time to adapt from capturing data while in flight.
The coefficient of variation was determined from the three samples at each sampling location for each parameter and sampling mode to see if the variability and clarity differed between boat and drone acquired data.
The non-parametric Wilcoxon signed-rank tests were used to analyze data that were non-normally generated and showed heterogeneous variability, even after suitable treatment.
Results and Discussion
Drone water sampling collected 2 L of water from each of the 36 sampling flights. No significant differences between the conventional boat and drone water sampling techniques for alkalinity, hardness, true color, silica, TON, TP, Chl-a, and permeability (Figure 1) were revealed by the paired sample t-tests.
Figure 1. Comparison of water chemistry variables collected using traditional boat (x-axis) and drone (y-axis) water sampling. Image Credit: Graham, et al., 2022.
A statistical analysis of variability discovered no statistically significant difference in total variability between the information recorded by drone and boat water sampling techniques. Furthermore, the accuracy of each variable revealed only one substantial difference, for hardness, with greater variability in boat collected samples than in drone collected samples (Table 2).
Table 2. Results of paired t-test and Wilcoxon-signed rank tests used to assess precision, using the coefficient of variation (CV%), between water chemistry variables at each sampling location between paired samples collected via traditional boat and drone water sampling methodologies. Significant differences are highlighted in bold. Source: Graham, et al., 2022
||No. of pairs
TON = Total oxidised nitrogen, TP = Total phosphorous, DO = dissolved oxygen.
a Square root transformed.
b Wilcoxon signed rank test.
This study revealed the significant ability of drones to effectively and consistently collect large volumes of water in a manner appropriate for large water monitoring programs such as the EU WFD, National Aquatic Resource Surveys in the United States, and the United Nations Global Environment Monitoring System for Freshwater.
While no substantial variations in any of the water chemistry variables calculated in the laboratory were found between samples collected by boat and drone, there was a statistically significant difference in pH captured on the data logging EXO Sonde.
While many researchers hope to advance drone technology for water sampling, there is a remarkable lack of statistical comparisons of water chemistry parameters between conventional boats and drone-assisted water sampling in the literature. This is likely due to limited sample size and reproduction.
It is crucial that adequate volumes of water can be gathered by tailored payloads deployed by drones, and that these amounts of water can be captured reliably for drone technology to be applied meaningfully in large-scale water monitoring projects. Doing so will help to realize their full potential to collect water samples cleaner and more effectively.
Early studies in this field, which considerably developed the use of drone technology in water sampling, had varying degrees of success in catching the quantity of water for which they were constructed.
In conclusion, this study shows that drone technology can be used to collect high precision, exact water physiochemical data and large volume samples from aquatic ecosystems reliably and safely, meeting many of the requirements of large-scale water monitoring programs.
This research systematically overcame many important technological limitations in the implementation of drone technology, including the relatively small volume of water retrieved by drones for evaluations, the low rate of success in collecting the desired volume of water, and, most importantly, the clear discrepancies in water chemistry results of previous studies between drone and conventional boat water sampling techniques.
As a result, drone technology could be used to gather water samples from lakes in a more dependable, faster, and cost-effective manner than traditional techniques such as using boats, which is safer for professionals and reduces biosecurity risk.
More research is needed to determine whether drone technology can be used to collect water samples for evaluations of priority substances, typically gathered in specialized glass vessels. As well as this, the capacity and cost-benefit analyses of using drone technology to gather large volume water samples in remote areas that are unreachable using conventional boat sampling must be assessed.
Graham, C. T., O’Connor, I., Broderick, L., Broderick, M., Jensen, O., Lally, H. T. (2022) Drones can reliably, accurately and with high levels of precision, collect large volume water samples and physio-chemical data from lakes. Science of The Total Environment, 824, p. 153875. Available Online: https://www.sciencedirect.com/science/article/pii/S0048969722009676.
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