Managing water resources and their connection to land and energy

Effective management is a key to ensuring the current and future sustainability of land, water and energy resources. Identifying the complexities of such management is not an easy task, especially since past studies have focussed on studying these resources in isolation from one another. However, with rapid population growth and an increase in the awareness of a potential change in climatic conditions that may affect the demand for and supply of food, water and energy, there has been a growing need to integrate the planning decisions relating to these three resources. The paper shows the visualisation of linked resources by drawing a set of interconnected Sankey diagrams for energy, water and land. These track the changes from basic resource (e.g. coal, surface water, groundwater and cropland) through transformations (e.g. fuel refining and desalination) to final services (e.g. sustenance, hygiene and transportation). The focus here is on the water analysis aspects of the tool, which uses California as a detailed case study. The movement of water in California is traced from its source to its services by mapping the different transformations of water from when it becomes available, through its use, to further treatment, to final sinks (including recycling and reuse of that resource). The connections that water has with energy and land resources for the state of California are highlighted. This includes the amount of energy used to pump and treat water, and the amount of water used for energy production and the land resources which create a water demand to produce crops for food. By mapping water in this way, policy-makers and resource managers can more easily understand the competing uses of water (environment, agriculture and urban use) through the identification of the services it delivers (e.g. sanitation, agriculture, landscaping), the potential opportunities for improving the management of the resource (e.g. building new desalination plants, reducing the demand for services), and the connections with other resources which are often overlooked in a traditional sector-based management strategy.

Visualising a stochastic model of California Water Resources Using Sankey Diagrams

This paper describes a novel approach to the analysis of supply and demand of water in California. A stochastic model is developed to assess the future supply of and demand for water resources in California. The results are presented in the form of a Sankey diagram where present and stochastically-varying future fluxes of water in California and its sub-regions are traced from source to services by mapping the various transformations of water from when it is first made available for use, through its treatment, recycling and reuse, to its eventual loss in a variety of sinks. This helps to highlight the connections of water with energy and land resources, including the amount of energy used to pump and treat water, the amount of water used for energy production, and the land resources that create a water demand to produce crops for food. By mapping water in this way, policy-makers can more easily understand the competing uses of water, through the identification of the services it delivers (e.g. sanitation, food production, landscaping), the potential opportunities for improving themanagement of the resource and the connections with other resources which are often overlooked in a traditional sector-based management strategy. This paper focuses on a Sankey diagram for water, but the ultimate aim is the visualisation of linked resource futures through inter-connected Sankey diagrams for energy, land and water, tracking changes from the basic resources for all three, their transformations, and the final services they provide.

An integrated representation of the services provided by global water resources

Water is essential not only to maintain the livelihoods of human beings but also to sustain ecosystems. Over the last few decades several global assessments have reviewed current and future uses of water, and have offered potential solutions to a possible water crisis. However, these have tended to focus on water supply rather than on the range of demands for all water services (including those of ecosystems). In this paper, a holistic global view of water resources and the services they provide is presented, using Sankey diagrams as a visualisation tool. These diagrams provide a valuable addition to the spatial maps of other global assessments, as they track the sources, uses, services and sinks of water resources. They facilitate comparison of different water services, and highlight trade-offs amongst them. For example, they reveal how increasing the supply of water resources to one service (crop production) can generate a reduction in provision of other water services (e.g., to ecosystem maintenance). The potential impacts of efficiency improvements in the use of water are also highlighted; for example, reduction in soil evaporation from crop production through better farming practices, or the results of improved treatment and re-use of return flows leading to reduction of delivery to final sinks. This paper also outlines the measures needed to ensure sustainable water resource use and supply for multiple competing services in the future, and emphasises that integrated management of land and water resources is essential to achieve this goal. © 2013 Elsevier Ltd.

Weighted least squares with expectation-maximization algorithm for burst detection in U.K. water distribution systems

Flow measurement data at the district meter area (DMA) level has the potential for burst detection in the water distribution systems. This work investigates using a polynomial function fitted to the historic flow measurements based on a weighted least-squares method for automatic burst detection in the U.K. water distribution networks. This approach, when used in conjunction with an expectationmaximization (EM) algorithm, can automatically select useful data from the historic flow measurements, which may contain normal and abnormal operating conditions in the distribution network, e.g., water burst. Thus, the model can estimate the normal water flow (nonburst condition), and hence the burst size on the water distribution system can be calculated from the difference between the measured flow and the estimated flow. The distinguishing feature of this method is that the burst detection is fully unsupervised, and the burst events that have occurred in the historic data do not affect the procedure and bias the burst detection algorithm. Experimental validation of the method has been carried out using a series of flushing events that simulate burst conditions to confirm that the simulated burst sizes are capable of being estimated correctly. This method was also applied to eight DMAs with known real burst events, and the results of burst detections are shown to relate to the water company's records of pipeline reparation work. © 2014 American Society of Civil Engineers.

Modular risk modeling and management of water infrastructure disaster incidents

Water supply and wastewater control are critical elements of society's infrastructure. The objective of this study will be to provide a generic risk assessment tool to provide municipalities and the nation as a whole with a quantifiable assessment of their vulnerability to water infrastructure threats. The approach will prioritize countermeasures and identify where research and development is required to further minimize risk. This paper outlines the current context, primary concerns and state-of-the art in critical infrastructure risk management for the water sector and proposes a novel approach to resolve existing questions in the field. The proposed approach is based on a modular framework that derives a quantitative risk index for varied domains of interest. The approach methodology is scaleable and based on formal definitions of event probability and severity. The framework is equally applicable to natural and human-induced hazard types and can be used for analysis of compound risk events.