Lally H T, O'Connor I, Jensen O P, Graham C T
Marine and Freshwater Research Centre, Galway-Mayo Institute of Technology (GMIT), Dublin Road, Galway City, Ireland.
Department of Marine and Coastal Sciences, Rutgers University, 71 Dudley Road, New Brunswick, NJ, United States of America.
Sci Total Environ. 2019 Jun 20;670:569-575. doi: 10.1016/j.scitotenv.2019.03.252. Epub 2019 Mar 18.
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.
无人机技术的进步推动了无人机辅助水样采集载荷的发展，使无人机能够从水生生态系统中采集水样和物理化学数据。无人机在水样采集方面的应用为满足大规模水样采集计划所需的生物和物理化学采样的多个方面提供了潜力。本文综述了无人机平台开发所取得的成就；专门设计的水样采集载荷的进展；集成现成探头的进展以及无人机辅助水样采集载荷从淡水环境中获取水样和物理化学数据的能力。然而，无人机辅助水样采集仍处于起步阶段，几个关键限制包括：迄今为止通过无人机采集的水量较小、成功采集样本的比率较低以及限制无人机与操作员之间飞行距离的立法限制。然而，至关重要的是，在使用无人机辅助和传统水样采集方法获得的水化学参数之间观察到明显的不一致。因此，使用无人机获得的水样和物理化学数据可能无法提供满足大规模水样采集计划需求所需的可靠性和准确性水平。旨在解决这些限制并开发无人机进行水样采集潜力的解决方案包括：改装具有更大载荷能力的大型无人机，以便采集更多体积的水；进行技术开发以提高水样采集成功率；规划超视距（BVLOS）操作的实地工作；采用实时物理化学探头；以及整合强大的统计实验设计。此外，需要进行详细的成本效益分析，以调查无人机是否会为水样采集计划带来有意义的财务节省。然而，可以设想，如果未来的研究能够解决当前的这些限制，无人机辅助水样采集将成为一个关键的支持工具。
