Literature DB >> 30909034

Can drones be used to conduct water sampling in aquatic environments? A review.

H T Lally1, I O'Connor2, O P Jensen3, C T Graham4.   

Abstract

Advancements in drone technology have seen the development of drone-assisted water sampling payloads resulting in the ability of drones to retrieve water samples and physico-chemical data from aquatic ecosystems. The application of drones for water sampling provides the potential to fulfil many aspects of the biological and physico-chemical sampling required to meet large-scale water sampling programmes. This paper reviews the achievements made in the development of drone platforms; advances in specially designed water sampling payloads; advances in incorporating off-the-shelf probes and the ability of drone-assisted water sampling payloads to capture water and physico-chemical data from freshwater environments. However, drone-assisted water sampling is still in its infancy and several key limitations include the small volume of water captured via drones to date, the low rate of successful sample capture and the legislative restrictions limiting the distance drones can be flown from the operator. Of critical importance, however, are the clear inconsistencies observed between water chemical parameters obtained using drone-assisted and traditional water sampling methods. Consequently, water samples and physico-chemical data obtained using drones may not provide the level of reliability and accuracy needed to meet the needs of large-scale water sampling programmes. Solutions aimed at addressing these limitations and developing the potential of drones to conduct water samples include: modifying larger drones with greater payload capacity, facilitating the capture of greater volumes of water; technological developments to increase success rates of water capture; planning fieldwork for operation beyond visual line of sight (BVLOS); employing real-time physico-chemical probes; and integrating robust statistical experimental designs. In addition, detailed cost benefit analyses are required to investigate if drones would result in a meaningful financial saving to water sampling programmes. However, it is envisaged that drone-assisted water sampling will act as a pivotal supporting tool if such current limitations can be addressed by future research.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Drone platforms; Physico-chemical sensors; Real-time data; Water monitoring; Water sampling payloads; Waterbodies

Year:  2019        PMID: 30909034     DOI: 10.1016/j.scitotenv.2019.03.252

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  3 in total

1.  The Lake Erie HABs Grab: A binational collaboration to characterize the western basin cyanobacterial harmful algal blooms at an unprecedented high-resolution spatial scale.

Authors:  Justin D Chaffin; John F Bratton; Edward M Verhamme; Halli B Bair; Amber A Beecher; Caren E Binding; Johnna A Birbeck; Thomas B Bridgeman; Xuexiu Chang; Jill Crossman; Warren J S Currie; Timothy W Davis; Gregory J Dick; Kenneth G Drouillard; Reagan M Errera; Thijs Frenken; Hugh J MacIsaac; Andrew McClure; R Michael McKay; Laura A Reitz; Jorge W Santo Domingo; Keara Stanislawczyk; Richard P Stumpf; Zachary D Swan; Brenda K Snyder; Judy A Westrick; Pengfei Xue; Colleen E Yancey; Arthur Zastepa; Xing Zhou
Journal:  Harmful Algae       Date:  2021-07-23       Impact factor: 5.905

2.  The Design and Experimental Development of Air Scanning Using a Sniffer Quadcopter.

Authors:  Endrowednes Kuantama; Radu Tarca; Simona Dzitac; Ioan Dzitac; Tiberiu Vesselenyi; Ioan Tarca
Journal:  Sensors (Basel)       Date:  2019-09-06       Impact factor: 3.576

3.  Evaluating the effectiveness of drones for quantifying invasive upside-down jellyfish (Cassiopea sp.) in Lake Macquarie, Australia.

Authors:  Claire E Rowe; Will F Figueira; Brendan P Kelaher; Anna Giles; Lea T Mamo; Shane T Ahyong; Stephen J Keable
Journal:  PLoS One       Date:  2022-01-19       Impact factor: 3.240

  3 in total

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