Controlling evaporation loss from water storages

[Executive Summary]: Evaporation losses from on-farm storage can potentially be large, particularly in irrigation areas in northern New South Wales and Queensland where up to 40% of storage volume can be lost each year to evaporation. Reducing evaporation from a water storage would allow additional crop production, water trading or water for the environment. While theoretical research into evaporation from storages has previously been undertaken there has been little evaluation of current evaporation mitigation technologies (EMTs) on commercial sized water storages. This project was initiated by the Queensland Government Department of Natural Resources and Mines (NRM) with the express aim of addressing this gap in our knowledge. The report addressed i) assessment of the effectiveness of different EMT’s in reducing evaporation from commercial storages across a range of climate regions, ii) assessment of the practical and technical limitations of different evaporation control products, and iii) comparison of the economics of different EMT’s on water storages used for irrigation

Road traffic pollution monitoring and modelling tools and the UK national air quality strategy.

This paper provides an assessment of the tools required to fulfil the air quality management role now expected of local authorities within the UK. The use of a range of pollution monitoring tools in assessing air quality is discussed and illustrated with evidence from a number of previous studies of urban background and roadside pollution monitoring in Leicester. A number of approaches to pollution modelling currently available for deployment are examined. Subsequently, the modelling and monitoring tools are assessed against the requirements of Local Authorities establishing Air Quality Management Areas. Whilst the paper examines UK based policy, the study is of wider international interest

United States data collection activities and requirements, volume 1

The potential market for a data collection system was investigated to determine whether the user needs would be sufficient to support a satellite relay data collection system design. The activities of 107,407 data collections stations were studied to determine user needs in agriculture, climatology, environmental monitoring, forestry, geology, hydrology, meteorology, and oceanography. Descriptions of 50 distinct data collections networks are described and used to form the user data base. The computer program used to analyze the station data base is discussed, and results of the analysis are presented in maps and graphs. Information format and coding is described in the appendix

CleAir monitoring system for particulate matter. A case in the Napoleonic Museum in Rome

Monitoring the air particulate concentration both outdoors and indoors is becoming a more relevant issue in the past few decades. An innovative, fully automatic, monitoring system called CleAir is presented. Such a system wants to go beyond the traditional technique (gravimetric analysis), allowing for a double monitoring approach: the traditional gravimetric analysis as well as the optical spectroscopic analysis of the scattering on the same filters in steady-state conditions. The experimental data are interpreted in terms of light percolation through highly scattering matter by means of the stretched exponential evolution. CleAir has been applied to investigate the daily distribution of particulate matter within the Napoleonic Museum in Rome as a test case

The Hierarchic treatment of marine ecological information from spatial networks of benthic platforms

Measuring biodiversity simultaneously in different locations, at different temporal scales, and over wide spatial scales is of strategic importance for the improvement of our understanding of the functioning of marine ecosystems and for the conservation of their biodiversity. Monitoring networks of cabled observatories, along with other docked autonomous systems (e.g., Remotely Operated Vehicles [ROVs], Autonomous Underwater Vehicles [AUVs], and crawlers), are being conceived and established at a spatial scale capable of tracking energy fluxes across benthic and pelagic compartments, as well as across geographic ecotones. At the same time, optoacoustic imaging is sustaining an unprecedented expansion in marine ecological monitoring, enabling the acquisition of new biological and environmental data at an appropriate spatiotemporal scale. At this stage, one of the main problems for an effective application of these technologies is the processing, storage, and treatment of the acquired complex ecological information. Here, we provide a conceptual overview on the technological developments in the multiparametric generation, storage, and automated hierarchic treatment of biological and environmental information required to capture the spatiotemporal complexity of a marine ecosystem. In doing so, we present a pipeline of ecological data acquisition and processing in different steps and prone to automation. We also give an example of population biomass, community richness and biodiversity data computation (as indicators for ecosystem functionality) with an Internet Operated Vehicle (a mobile crawler). Finally, we discuss the software requirements for that automated data processing at the level of cyber-infrastructures with sensor calibration and control, data banking, and ingestion into large data portals.Peer ReviewedPostprint (published version

Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

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