The impact of agricultural activities on water quality: a case for collaborative catchment-scale management using integrated wireless sensor networks

The challenge of improving water quality is a growing global concern, typified by the European Commission Water Framework Directive and the United States Clean Water Act. The main drivers of poor water quality are economics, poor water management, agricultural practices and urban development. This paper reviews the extensive role of non-point sources, in particular the outdated agricultural practices, with respect to nutrient and contaminant contributions. Water quality monitoring (WQM) is currently undertaken through a number of data acquisition methods from grab sampling to satellite based remote sensing of water bodies. Based on the surveyed sampling methods and their numerous limitations, it is proposed that wireless sensor networks (WSNs), despite their own limitations, are still very attractive and effective for real-time spatio-temporal data collection for WQM applications. WSNs have been employed for WQM of surface and ground water and catchments, and have been fundamental in advancing the knowledge of contaminants trends through their high resolution observations. However, these applications have yet to explore the implementation and impact of this technology for management and control decisions, to minimize and prevent individual stakeholder’s contributions, in an autonomous and dynamic manner. Here, the potential of WSN-controlled agricultural activities and different environmental compartments for integrated water quality management is presented and limitations of WSN in agriculture and WQM are identified. Finally, a case for collaborative networks at catchment scale is proposed for enabling cooperation among individually networked activities/stakeholders (farming activities, water bodies) for integrated water quality monitoring, control and management

Smart environmental monitoring and assessment technologies (SEMAT)- a new paradigm for low-cost, remote aquatic environmental monitoring

Expense and the logistical difficulties with deploying scientific monitoring equipment are the biggest limitations to undertaking large scale monitoring of aquatic environments. The Smart Environmental Monitoring and Assessment Technologies (SEMAT) project is aimed at addressing this problem by creating an open standard for low-cost, near real-time, remote aquatic environmental monitoring systems. This paper presents the latest refinement of the SEMAT system in-line with the evolution of existing technologies, inexpensive sensors and environmental monitoring expectations. We provide a systems analysis and design of the SEMAT remote monitoring units and the back-end data management system. The system's value is augmented through a unique e-waste recycling and repurposing model which engages/educates the community in the production of the SEMAT units using social enterprise. SEMAT serves as an open standard for the community to innovate around to further the state of play with low-cost environmental monitoring. The latest SEMAT units have been trialled in a peri-urban lake setting and the results demonstrate the system's capabilities to provide ongoing data in near real-time to validate an environmental model of the study site

A GIS–Integrated Wireless Sensors Network Tool for Water Risk Monitoring – Case of Khanh Hoa Water Supply and Sewerage Company, Vietnam

This paper investigates the feasibility of deploying a wireless sensor network (WSN) to monitor raw water quality at 2 major water treatment plants (WTPs) sites, operated by the The Khanh Hoa Water Supply and Sewerage Company (KHAWASSCO) in Vietnam: Canh Vo and Xuan Canh on the Cai River. The main aim is to propose a WSN for both WTPs which includes 2 clusters of sensors with 4 nodes each in order to monitor various parameters of water quality. Data management is integrated with a geographical information system (GIS) tool in order to provide a comprehensive spatio-temporal database in real time. This will assist decision makers in improving the management of the raw water quality at Cai River

Wireless in-situ sensor network for agriculture and water monitoring on a river basin scale in Southern Finland: evaluation from a data user's perspective

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Experiences and recommendations in deploying a real-time, water quality monitoring system

Monitoring of water quality at a river basin level to meet the requirements of the Water Framework Directive (WFD) using conventional sampling and laboratory-based techniques poses a significant financial burden. Wireless sensing systems offer the potential to reduce these costs considerably, as well as provide more useful, continuous monitoring capabilities by giving an accurate idea of the changing environmental and water quality in real time. It is unlikely that the traditional spot/grab sampling will provide a reasonable estimate of the true maximum and/or mean concentration for a particular physicochemical variable in a water body with marked temporal variability. When persistent fluctuations occur, it is likely only to be detected through continuous measurements, which have the capability of detecting sporadic peaks of concentration. Thus, in situ sensors capable of continuous sampling of parameters required under the WFD would therefore provide more up-to-date information, cut monitoring costs and provide better coverage representing long-term trends in fluctuations of pollutant concentrations. DEPLOY is a technology demonstration project, which began planning and station selection and design in August 2008 aiming to show how state-of-the-art technology could be implemented for cost-effective, continuous and real-time monitoring of a river catchment. The DEPLOY project is seen as an important building block in the realization of a wide area autonomous network of sensors capable of monitoring the spatial and temporal distribution of important water quality and environmental target parameters. The demonstration sites chosen are based in the River Lee, which flows through Ireland's second largest city, Cork, and were designed to include monitoring stations in five zones considered typical of significant river systems-these monitor water quality parameters such as pH, temperature, depth, conductivity, turbidity and dissolved oxygen. Over one million data points have been collected since the multi-sensor system was deployed in May 2009. Extreme meteorological events have occurred during the period of deployment and the collection of real-time water quality data as well as the knowledge, experience and recommendations for future deployments are discussed

Development of wireless passive water quality catchment monitoring system

To maintain the quality of aquatic ecosystems, good water quality is needed. The quality of water needs to be tracked in real-time for environmental protection and tracking pollution sources. This paper aims to describe the development and data acquired for water catchment quality monitoring by using a passive system which includes location tagging. Wireless Passive Water Quality Catchment Monitoring (WPWQCM) System is used to check and monitor water quality continuously. The condition of water in terms of acidity, temperature and light intensity needs to be monitored. WPWQCM System featured four sensors which are a temperature sensor, light intensity sensor, pH sensor and GPS tracker that will float in water to collect the data. GPS tracker on passive water catchment monitoring system is a new feature in the system where the location of water can be identified. With the extra feature, water quality can be mapped and in the future, the source of disturbance can be determined. UMP Lake was chosen to check and monitor the water quality. The system used wireless communication by using XBee Pro as a medium of communication between CT-Uno board and PC

Monitoring, Modelling and Management of Water Quality

Different types of pressures, such as nutrients, micropollutants, microbes, nanoparticles, microplastics, or antibiotic-resistant genes, endanger the quality of water bodies. Evidence-based pollution control needs to be built on the three basic elements of water governance: Monitoring, modeling, and management. Monitoring sets the empirical basis by providing space- and time-dependent information on substance concentrations and loads, as well as driving boundary conditions for assessing water quality trends, water quality statuses, and providing necessary information for the calibration and validation of models. Modeling needs proper system understanding and helps to derive information for times and locations where no monitoring is done or possible. Possible applications are risk assessments for exceedance of quality standards, assessment of regionalized relevance of sources and pathways of pollution, effectiveness of measures, bundles of measures or policies, and assessment of future developments as scenarios or forecasts. Management relies on this information and translates it in a socioeconomic context into specific plans for implementation. Evaluation of success of management plans again includes well-defined monitoring strategies. This book provides an important overview in this context