Crucial elements and technical implementation of intelligent monitoring networks

Enhanced statistical evaluation of fluorescence properties to identify dissolved organic matter dynamics during river high-flow events

Fluorescence spectroscopy has become a widely used technique to characterize dissolved organic matter (DOM) and organic hazardous micro-pollutants in natural and human-influenced water bodies. Especially in rivers highly impacted by municipal and industrial wastewater treatment plants' effluents, the fluorescence signal at low-flow is mainly dominated by these discharges. At river high-flow, their influence decreases due to dilution effects, and at the same time, other compounds of DOM, stemming from diffuse inputs, can increase or even dominate. Therefore, whereas the analysis of DOM is little informative on the changing sources and pathways of emissions, fluorescence spectroscopy can enhance our understanding and our possibilities of monitoring such dynamics in river catchments. This paper analyzed samples from seven high-flow events in an Austrian river. Firstly, independent DOM components were discriminated using a parallel factor analysis (PARAFAC) to show the varying composition of DOM during different phases of high-flow events. Furthermore, partial least squares (PLS) and sparse PLS (sPLS) regression were applied to identify excitation and emission wavelengths, serving as proxy parameters for quantifying dissolved organic carbon (DOC) and chloride. The PLS models show the best prediction accuracy but use the entire excitation-emission matrix in exchange. In selecting predictors, the use of excitation and emission wavelengths adjusted via sPLS is superior to the extracted PARAFAC components. The sPLS model yields 16 wavelength combinations for DOC (RMSE_sPLS = 0.41 mg L^-1) and 18 wavelength combinations for chloride (RMSE_sPLS = 2.21 mg L^-1). In contrast to other established optical measurement methods, which require different calibrations for low- and high-flow conditions, these models based on sPLS succeed in quantifying those parameters across the entire range of flow conditions and events of various magnitudes with a relative precision of about 5 %. These results show how the application of multivariate statistical techniques enhances the exploitation of the information provided by fluorescence spectroscopy.

Improving the assessment of polluted sites using an integrated bio-physico-chemical monitoring framework

Soil - water pollution resulting from anthropogenic activities is a growing concern internationally. Effective monitoring techniques play a crucial role in the detection, prevention, and remediation of polluted sites. Current pollution monitoring practices in many geographical locations are primarily based on physico-chemical assessments which do not always reflect the potential toxicity of contaminant 'cocktails' and harmful chemicals not screened for routinely. Biomonitoring provides a range of sensitive techniques to characterise the eco-toxicological effects of chemical contamination. The bioavailability of contaminants, in addition to their effects on organisms at the molecular, cellular, individual, and community level allows the characterisation of the overall health status of polluted sites and ecosystems. Quantifying bioaccumulation, changes to community structure, faunal morphology, behavioural, and biochemical responses are standard procedures employed in biomonitoring studies in many High-Income Countries (HICs). This review highlights the need to integrate biomonitoring tools alongside physico-chemical monitoring techniques by using 'effect-based' tools to provide more holistic information on the ecological impairment of soil-water systems. This paper considers the wider implementation of biomonitoring methods in Low to Middle Income Countries (LMICs) and their significance in pollution investigations and proposes an integrated monitoring framework that can identify toxicity drivers by utilising 'effect-based' and 'risk-based' monitoring approaches.

Adaptive Water Sampling Device for Aerial Robots

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.

Designing the National Network for Automatic Monitoring of Water Quality Parameters in Greece

Water quality indices that describe the status of water are commonly used in freshwater vulnerability assessment. The design of river water quality monitoring programs has always been a complex process and despite the numerous methodologies employed by experts, there is still no generally accepted, holistic and practical approach to support all the phases and elements related. Here, a Geographical Information System (GIS)-based multicriteria decision analysis approach was adopted so as to contribute to the design of the national network for monitoring of water quality parameters in Greece that will additionally fulfill the urgent needs for an operational, real-time monitoring of the water resources. During this cost-effective and easily applied procedure the high priority areas were defined by taking into consideration the most important conditioning factors that impose pressures on rivers and the special conditions that increase the need for monitoring locally. The areas of increased need for automatic monitoring of water quality parameters are highlighted and the output map is validated. The sites in high priority areas are proposed for the installation of automatic monitoring stations and the installation and maintenance budget is presented. Finally, the proposed network is contrasted with the current automatic monitoring network in Greece.

Autonomous In Situ Measurements of Noncontaminant Water Quality Indicators and Sample Collection with a UAV

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.

In Situ Water Quality Measurements Using an Unmanned Aerial Vehicle (UAV) System

An unmanned aerial vehicle-assisted water quality measurement system (UAMS) was developed for in situ surface water quality measurement. A custom-built hexacopter was equipped with an open-source electronic sensors platform to measure the temperature, electrical conductivity (EC), dissolved oxygen (DO), and pH of water. Electronic components of the system were coated with a water-resistant film, and the hexacopter was assembled with flotation equipment. The measurements were made at thirteen sampling waypoints within a 1.1 ha agricultural pond. Measurements made by an open-source multiprobe meter (OSMM) attached to the unmanned aerial vehicle (UAV) were compared to the measurements made by a commercial multiprobe meter (CMM). Percent differences between the OSMM and CMM measurements for DO, EC, pH, and temperature were 2.1 %, 3.43 %, 3.76 %, and <1.0 %, respectively. The collected water quality data was used to interpret the spatial distribution of measurements in the pond. The UAMS successfully made semiautonomous in situ water quality measurements from predetermined waypoints. Water quality maps showed homogeneous distribution of measured constituents across the pond. The concept presented in this paper can be applied to the monitoring of water quality in larger surface waterbodies.

Water quality monitoring strategies - A review and future perspectives

The reliable assessment of water quality through water quality monitoring programs (WQMPs) is crucial in order for decision-makers to understand, interpret and use this information in support of their management activities aiming at protecting the resource. The challenge of water quality monitoring has been widely addressed in the literature since the 1940s. However, there is still no generally accepted, holistic and practical strategy to support all phases of WQMPs. The purpose of this paper is to report on the use cases a watershed manager has to address to plan or optimize a WQMP from the challenge of identifying monitoring objectives; selecting sampling sites and water quality parameters; identifying sampling frequencies; considering logistics and resources to the implementation of actions based on information acquired through the WQMP. An inventory and critique of the information, approaches and tools placed at the disposal of watershed managers was proposed to evaluate how the existing information could be integrated in a holistic, user-friendly and evolvable solution. Given the differences in regulatory requirements, water quality standards, geographical and geological differences, land-use variations, and other site specificities, a one-in-all solution is not possible. However, we advance that an intelligent decision support system (IDSS) based on expert knowledge that integrates existing approaches and past research can guide a watershed manager through the process according to his/her site-specific requirements. It is also necessary to tap into local knowledge and to identify the knowledge needs of all the stakeholders through participative approaches based on geographical information systems and adaptive survey-based questionnaires. We believe that future research should focus on developing such participative approaches and further investigate the benefits of IDSS's that can be updated quickly and make it possible for a watershed manager to obtain a timely, holistic view and support for every aspect of planning and optimizing a WQMP.