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Water sampling is a fundamental practice for obtaining essential environmental data, enabling the analysis and quality testing of water from natural or industrial sources. It is vital in understanding water quality changes over time, identifying contaminant sources, and supporting water management plans. Traditional sampling methods, including spot (bottle) sampling and in-situ readings, can be labor-intensive and limited by accessibility. To address these challenges, the utilization of drones has emerged as an innovative approach. Drones offer the potential to automate field quality control and streamline water sampling efforts for data collection in diverse water environments. This paper focuses on the design and development of a water sampling system integrated with a drone, featuring an automatic lock mechanism activated after rigorous field quality control, ensuring the reliable collection of water samples in various scenarios.

Collecting water samples for laboratory analysis from hard-to-reach surface areas such as post-industrial reservoirs (for example, tailings depositories) or overgrown lakes and ponds poses several difficulties, and it is potentially dangerous for the persons carrying out such activity. This can be improved by the use of unmanned aerial vehicles (UAVs) while ensuring an adequate level of safety and full compliance with the requirements of PN-ISO standards. This article presents the possibility of using the BSP in the option of autonomous (automatic) operation, allowing for the collection of water samples intended for physico-chemical tests, from hard-to-reach surface reservoirs, following the provisions of the relevant PN-ISO standards.

Monitoring of aquatic habitats for water quality and biodiversity requires regular sampling, often in off-shore locations and underwater. Such sampling is commonly performed manually from research vessels, or if autonomous, is constrained to permanent installations. Consequentially, high frequency ecological monitoring, such as for harmful algal blooms, are limited to few sites and/or temporally infrequent. Here, we demonstrate the use of MEDUSA, an Unmanned Aerial-Aquatic Vehicle which is capable of performing underwater sampling and inspection at up to 10 m depth, and is composed of a multirotor platform, a tether management unit and a tethered micro Underwater Vehicle. The system is validated in the task of vertical profiling of Chlorophyll-a levels in freshwater systems by means of a custom solid sample filtering mechanism. This mechanism can collect up to two independent samples per mission by pumping water through a pair of glass-fibre GF/F filters. Chlorophyll levels measured from the solid deposits on the filters are consistent and on par with traditional sampling methods, highlighting the potential of using UAAVs to sample aquatic locations at high frequency and high spatial resolution.

Introduction: Of all natural resources, water is one of the most essential and precious resources. It forms 70% of our body weight and acts as a necessary vehicle for all metabolic processes in the body. Water is exposed to various contaminants animal wastes, human wastes, etc. which affect the biological quality of water. So, water quality monitoring becomes an essential component for formulating measures and addressing the issues to safeguard public health. Aim: To assess the bacteriological quality of drinking water in a rural tertiary healthcare institute in Haryana Materials and Methods: This descriptive, record-based, study was conducted in Bhagat Phool Singh Government Medical College for Women Khanpur, Kalan, Sonepat, Haryana, India (rural tertiary healthcare institute), from 1st January 2016 to 31st December 2018. The water samples were collected, transported, and analysed according to the World Health Organisation (WHO) guidelines for drinking water quality assessment and the Indian Council Medical Research (ICMR). Incomplete records with respect to inadequate samples and reporting issue were excluded from the study. Data were analysed using Statistical Package for the Social Sciences (SPSS) version 22.0. Results: Out of a total of 422 tested water samples 244 (58%) were found satisfactory while 178 (42%) unsatisfactory i.e. unfit for human consumption. From March to mid-June (summer season) 56 (31%) and from mid-June to mid-September (rainy season), 74 (42%) of water samples were found unsatisfactory while, 63 (26%) water samples were observed fit for human consumption in mid-September to mid-December (postmonsoon season) and 76 (31%) in mid-December to February season (winter season). Seasonal variations were recorded for water quality reporting. Conclusion: Comprehensive planning and feasible approach are to be followed prior to hot weather and rainy season for the provision of safe and potable drinking water.

The unmanned aerial manipulator (UAM) is a kind of aerial robot that combines a quadrotor aircraft and an onboard manipulator. This paper focuses on the problems of structure design, system modeling, and motion control of an UAM applied for water sampling. A novel, light, cable-driven UAM has been designed. The drive motors installed in the base transmit the force and motion remotely through cables, which can reduce the inertia ratio of the manipulator. The Newton–Euler method and Lagrangian method are adopted to establish the quadrotor model and manipulator model, respectively. External disturbances, model uncertainty, and joint flexibility are also accounted for in the two submodels. The quadrotor and manipulator are controlled separately to ensure the overall accurate aerial operation of the UAM. Specifically, a backstepping control method is designed with the disturbance observer (BC-DOB) technique for the position loop and attitude loop control of the quadrotor. A backstepping integral fast terminal sliding mode control based on the linear extended state observer (BIFTSMC-LESO) has been developed for the manipulator to provide precise manipulation. The DOB and LESO serve as compensators to estimate the external disturbances and model uncertainty. The Lyapunov theory is used to ensure the stability of the two controllers. Three simulation cases are conducted to test the superior performance of the proposed quadrotor controller and manipulator controller. All the results show that the proposed controllers provide better performances than other traditional controllers, which can complete the task of water quality sampling well.

Cost-effective remediation is increasingly dependent on high-resolution site characterization (HRSC), which is supposed to be necessary prior to interventions. This paper aims to evaluate the use of low-flow purging and sampling water level data in estimating the horizontal hydraulic conductivity of soils. In a new quali-quantitative view, this procedure can provide much more information and knowledge about the site, reducing time and costs. In case of high heterogeneity along the well screen, the whole procedure, as well as the estimation method, could be less effective and rigorous, with related issues in the purging time. The result showed significant permeability weighted sampling, which could provide different results as the pump position changes along the well screen. The proposed study confirms this phenomenon with field data, demonstrating that the use of multiparameter well logs might be helpful in detecting the behaviour of low-permeability layers and their effects on purging and sampling. A lower correlation between low-flow permeability estimations and LeFranc test results was associated with high heterogeneity along the screen, with a longer purging time. In wells P43, MW08 and MW36, due to the presence of clay layers, results obtained differ for almost one order of magnitude and the purging time increases (by more than 16 min). However, with some precautions prior to the field work, the low-flow purging and sampling procedure could become more representative in a shorter time and provide important hydrogeological parameters such as hydraulic conductivity with many tests and high-resolution related results.

Abstract Objective A quantitative PCR (qPCR) assay for the detection of redside shiner (Richardsonius balteatus) environmental DNA (eDNA) was designed as a side product of a larger project aimed at using eDNA to determine the presence and geographic extent of native and non-native fishes in the reservoirs and associated tributaries above the three mainstem dams (Ross, Diablo, Gorge) on the Skagit River, Washington, USA. The eDNA survey results can be used to help guide additional sampling efforts that include traditional sampling methods, such as electrofishing and netting. Results The redside shiner qPCR assay (RSSCOI_540-601) was validated by testing for sensitivity using redside shiner genomic DNA from three different populations and by testing for specificity against 30 potentially sympatric species. No non-target amplification was observed in our validation tests. We then evaluated the assay on field-collected water samples where there are known populations of redside shiner and a negative control site where the target species is known to be absent. The field-collected water samples tested positive at the redside shiner sites and tested negative at the negative control site. The assay could provide resource managers with an effective means for surveying and monitoring redside shiner populations.

Abstract A participatory research team, concerned about water quality around Lake Geneva, particularly in the Montreux Bay region where some were lifeguards, ran sampling campaigns to determine summertime levels of lake water pollution. The participants were brought together serendipitously through a course organized by academic researchers and ‘biohackers’ from the community laboratory, Hackuarium. After discussion about lifeguards’ gastrointestinal and dermatological ailments each season, the decision to pursue this participatory research project was made. In order to assess water quality, thereby testing the hypothesis that unsuspected pollution enters the lake each summer season, microbiological plating of water samples was proposed. Volunteers collected and analysed water samples over summer seasons (8 weeks in 2016, 2017 and 2020) from three sites around Montreux Bay, with tap and local river water samples as controls. Contamination of lake water was measured using standard microbiological methods, with growth media allowing quantitative assessment of abundance of several bacterial species. In particular, the focus was to quantify Escherichia coli, the classic bioindicator organism for raw sewage contamination. These open science data reveal peaks of bioindicator and other bacterial pollution in lake water samples during all sampling years. For the initial two sampling campaigns, increased microbial burdens occurred during a popular music festival, and were not simply dependent upon rainfall. In contrast, only scattered, lower level bioindicator pollution events occurred across the sampling period during the pandemic summer of 2020, when the festival was cancelled. This study confirms the power of participatory research: dedicated people on a budget can do meaningful environmental monitoring. These analyses suggest that better management, both to support water quality monitoring and for event organization, is essential, as sewage treatment facilities near many popular festivals, internationally, may need to cope with increased wastewater from visitors.

A newly developed water sampling system enables autonomous detection and sampling of underwater oil plumes. The Midwater Oil Sampler collects multiple 1-L samples of seawater when preset criteria are met. The sampler has a hydrocarbon-free sample path and can be configured with several modules of six glass sample bottles. In August 2019, the sampler was deployed on an autonomous underwater vehicle and captured targeted water samples in natural oil seeps offshore Santa Barbara, CA, USA.

In 2007, ten bioretention cells were constructed in Oklahoma as part of a full-scale technology project to demonstrate stormwater phosphorus reduction. The filter media used was amended with 5%, Class C fly ash by weight to increase phosphorus and heavy metal retention. In 2014, core samples were collected from four of the cells, and three were instrumented for continuous water monitoring for the following year. This paper will review the design, construction, computer modeling of phosphorus retention, and measured phosphorus removal after seven years of operation. Total phosphorus retained in the sampled cells showed reductions in effluent water concentrations of 68 to 75%, while total effluent mass reductions of 51 to 93% were achieved. Total phosphorus accumulation in the cells measured in cores ranged from 0.33 to 0.60 kg/year, which was somewhat greater than the annual calculated effluent reduction of 0.27 to 0.41 kg/year. While good, phosphorus retention was not as high as computer modeling predicted. Other research on the cells, including hydraulics, heavy metal adsorption, and microbial transport, is summarized. Experimental challenges with phosphorus extraction from samples are also discussed. All experience and results suggest that fly ash amendments are an effective option for phosphorus removal in bioretention cells.

Good ecological and chemical status of water represents the most important aim of the Water Framework Directive 2000/60/EC, which implies respect of water quality standards at the level of entire river basin (2008/105/EC and 2013/39/EC). This especially refers to the control of pesticide residues in surface waters. In order to achieve the set goals, a continuous monitoring program that should provide a comprehensive and interrelated overview of water status should be implemented. However, it demands the use of appropriate analysis techniques. Until now, the procedure for sampling and quantification of residual pesticide quantities in aquatic environment was based on the use of traditional sampling techniques that imply periodical collecting of individual samples. However, this type of sampling provides only a snapshot of the situation in regard to the presence of pollutants in water. As an alternative, the technique of passive sampling of pollutants in water, including pesticides has been introduced. Different samplers are available for pesticide sampling in surface water, depending on compounds. The technique itself is based on keeping a device in water over a longer period of time which varies from several days to several weeks, depending on the kind of compound. In this manner, the average concentrations of pollutants dissolved in water during a time period (time-weighted average concentrations, TWA) are obtained, which enables monitoring of trends in areal and seasonal variations. The use of these techniques also leads to an increase in sensitivity of analytical methods, considering that pre-concentration of analytes takes place within the sorption medium. However, the use of these techniques for determination of pesticide concentrations in real water environments requires calibration studies for the estimation of sampling rates (Rs). Rs is a volume of water per time, calculated as the product of overall mass transfer coefficient and area of the receiving phase exposed to the external environment, and it is substance specific.

The changes in water quality owing to recirculation of water in mineral processing plants can compromise the plant performance as well as maintenance needs. Therefore, mining process water quality assessment is becoming critical. Nevertheless, very few studies have investigated the suitability of the current analysis methodology practiced in certified laboratories for evaluating mining process water quality. This article presents two case studies to highlight the major issues encountered when performing sampling for physicochemical and chemical parameters in process water at two European mine sites using procedures from two certified laboratories. In addition, microorganisms were shown to be abundant in process waters and likely affect the mining water chemistries. However, the protocols used for microbial studies are not optimal for mining process samples, and need to be improved. The results showed difficulties in providing satisfactory results when analyzing control samples. Additionally, the analysis results presented a strong imbalance in TDS and sulfur compounds. Several potential causes associated with the poor quality of the analysis results have been outlined with a specific focus on the preservation methods. A literature review on the degradation of thiosalts suggested that the current preservation procedures are not suitable for preserving sulfur compounds. Moreover, the results indicated that the water matrix strongly influenced the validity of the chosen analysis method. In conclusion, the analysis methods should be customized for the different mining water matrix types in order to ensure the accuracy and reproducibility of the results.

Water quality monitoring and predicting the changes in water characteristics require the collection of water samples in a timely manner. Water sample collection based on in situ measurable water quality indicators can increase the efficiency and precision of data collection while reducing the cost of laboratory analyses. The objective of this research was to develop an adaptive water sampling device for an aerial robot and demonstrate the accuracy of its functions in laboratory and field conditions. The prototype device consisted of a sensor node with dissolved oxygen, pH, electrical conductivity, temperature, turbidity, and depth sensors, a microcontroller, and a sampler with three cartridges. Activation of water capturing cartridges was based on in situ measurements from the sensor node. The activation mechanism of the prototype device was tested with standard solutions in the laboratory and with autonomous water sampling flights over the 11-ha section of a lake. A total of seven sampling locations were selected based on a grid system. Each cartridge collected 130 mL of water samples at a 3.5 m depth. Mean water quality parameters were measured as 8.47 mg/L of dissolved oxygen, pH of 5.34, 7 µS/cm of electrical conductivity, temperature of 18 °C, and 37 Formazin Nephelometric Unit (FNU) of turbidity. The dissolved oxygen was within allowable limits that were pre-set in the self-activation computer program while the pH, electrical conductivity, and temperature were outside of allowable limits that were specified by Environmental Protection Agency (EPA). Therefore, the activation mechanism of the device was triggered and water samples were collected from all the sampling locations successfully. The adaptive water sampling with Unmanned Aerial Vehicle-assisted water sampling device was proved to be a successful method for water quality evaluation.

Monitoring and analysis of open air basins is a critical task in waste water plant management. These tasks generally require sampling waters at several hard to access points, be it real time with multiparametric sensor probes, or retrieving water samples. Full automation of these processes would require deploying hundreds (if not thousands) of fixed sensors, unless the sensors can be translated. This work proposes the utilization of robotized unmanned aerial vehicle (UAV) platforms to work as a virtual high density sensor network, which could analyze in real time or capture samples depending on the robotic UAV equipment. To check the validity of the concept, an instance of the robotized UAV platform has been fully designed and implemented. A multi-agent system approach has been used (implemented over a Robot Operating System, ROS, middleware layer) to define a software architecture able to deal with the different problems, optimizing modularity of the software; in terms of hardware, the UAV platform has been designed and built, as a sample capturing probe. A description on the main features of the multi-agent system proposed, its architecture, and the behavior of several components is discussed. The experimental validation and performance evaluation of the system components has been performed independently for the sake of safety: autonomous flight performance has been tested on-site; the accuracy of the localization technologies deemed as deployable options has been evaluated in controlled flights; and the viability of the sample capture device designed and built has been experimentally tested.

The objective of this research was to conduct in situ measurements of electrical conductivity (EC), pH, dissolved oxygen (DO), and temperature, and collect water samples simultaneously at different depths using an unmanned aerial vehicle (UAV). The UAV system consists of a hexacopter, water sampling cartridges (WSC), and a sensor node. Payload capacity and endurance of the UAV were determined using an indoor test station. The UAV was able to produce 106 N of thrust for 10 min with 6.3 kg of total takeoff weight. The thrust-to-weight ratio of the UAV was 2.5 at 50% throttle. The decision for activating the water sampling cartridges and sensor node was made autonomously from an onboard microcontroller. System functions were verified at 0.5 m and 3.0 m depths in 6 locations over a 1.1 ha agricultural pond. Average measurements of EC, pH, DO, and temperature at 0.5 m depth were 42 µS/cm, 5.6, 8.2 mg/L, and 31 °C, while the measurements at 3 m depth were 80 µS/cm, 5.3, 5.34 mg/L, and 24 °C, respectively. The UAV-assisted autonomous water sampling system (UASS) successfully activated the WSC at each sampling location. The UASS would reduce the duration of water quality assessment and help practitioners and researchers to conduct observations with lower operational costs. The developed system would be useful for sampling and monitoring of water reservoirs, lakes, rivers, and ponds periodically or after natural disasters.

Cold seeps, hydrothermal vents, deep water coral reefs, and submarine canyon systems are hotspot habitats characterized by intermediate to high fluid advection. They are shaped by a complex interplay of physical, biological, geochemical, and geological processes. Biogeochemical and physicochemical gradients in these ecosystems are frequently extremely steep and temporally and spatially variable. Zones of elevated microbial activity, such as the methane-sulfate interface at cold-seep sites, usually encompass no more than a few millimeters. Recovery of samples for further shipboard analysis from such hotspot zones generally causes severe artifacts in the biogeochemical gradients. Hence, to quantify chemical gradients, microbial processes, and transport rates in deep-sea hotspot ecosystems, we have developed and operated a variety of specialized in situ instruments (Figure 1).