44,569 research outputs found

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

    No full text
    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 This paper reviews the extensive role of non-point sources, in particular the outdated agricultural practices, with respect to nutrient and contaminant contributions.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

    Enhancing Ontario’s Rural Infrastructure Preparedness: Inter-Community Service Sharing in a Changing Climate — Environmental Scan

    Get PDF
    Given the research that has been done in this environmental scan and the gaps found in this research, it is our aim to find out: What types of service sharing are going on in Ontario municipalities, particularly in rural/remote areas? How can inter-community service sharing (ICSS) benefit the asset management planning process in these rural/remote areas to enhance capacities for climate change resilience? Climate change (CC) will exacerbate deterioration to existing infrastructure and increase replacement costs. Improved preparedness reduces risks and increases efficiency, readiness and coping capacity. To increase the preparedness of Ontario rural communities, this project develops CC-Prepared Inter-Community Service Sharing (ICSS) as an innovative strategy that expands cost-effective solutions within Ontario’s standardized Asset Management Planning (AMP) process. Overseen by a Project Advisory Board (PAB), it identifies a suite of best practice ICSS processes and principles and a range of factors and indicators that influence the uptake of ICSS as a viable and practical opportunity targeted to enhance rural infrastructure preparedness for CC. It utilizes a multimethod, interdisciplinary approach involving an environmental scan, interviews, a survey and case studies and develops an ICSS Toolkit consisting of reports, workbook, policy brief and media kit. Knowledge translation and transfer (KTT) includes blogs, teleconferences, articles, presentations and a workshop. For small rural Ontario communities, this study enhances management of CC impacts on infrastructure through the development of a CC-Prepared ICSS strategy, increasing anticipatory, collective actions that reduce dam age and increase efficiencies. It informs sound municipal/provincial level programs and policies about innovative ICSS that benefit rural communities through the identification of Ontario-wide trends, case study best practises and action-oriented recommendations
    • 

    corecore