Salinity Intrusion and Seasonal Water Quality Variations in the Tidal Canals of Cochin

The study conducted on the salinity intrusion and seasonal water quality variations in the tidal canals of cochin. The main objectives are, salinity intrusion profile, water quality variation of the surface water of the canals,hierarchical utility of the water bodies and to understand the non-conservative components in the water body. The parameters monitored werepH,temperature,alkalinity,conductivity,DO(dissolvedoxygen),COD(chemical oxygen demand),BOD(biochemical oxygen demand0,chloride, total hardness, calcium hardness, dissolved phosphate, nitrate, total iron, sulphate, turbidity, total coliform and SUVA at 254nm. The tidal canals of GCDA were found to be creeks extending to the interior, canals inter connecting parts of the estuary or canals with seasonally broken segments. Based on utility the canals could be classified as: canals heavely polluted and very saline,canals polluted by urban waste , canals having fresh water for most part of the year and not much polluted, fresh water bodies heavily polluted. During the rainy months carbon fixation by plankton is nonexistent,and during the dry months Chitrapuzha becomes a sink of phosphate. The study indicated abiotic subrouts for dissolved phosphate and revealed the potential pitfalls in LOICZ modeling exercise on sewage ladentidal canals. It was also found that all canals except for the canals of West cochin and chittoorpuzha have fresh water for some part of the year. The water quality index in the durable fresh water stretches was found to be of below average category.

Assessing the significance of climate and community factors on urban water demand

Ensuring adequate water supply to urban areas is a challenging task due to factors such as rapid urban growth, increasing water demand and climate change. In developing a sustainable water supply system, it is important to identify the dominant water demand factors for any given water supply scheme. This paper applies principal components analysis to identify the factors that dominate residential water demand using the Blue Mountains Water Supply System in Australia as a case study. The results show that the influence of community intervention factors (e.g. use of water efficient appliances and rainwater tanks) on water demand are among the most significant. The result also confirmed that the community intervention programmes and water pricing policy together can play a noticeable role in reducing the overall water demand. On the other hand, the influence of rainfall on water demand is found to be very limited, while temperature shows some degree of correlation with water demand. The results of this study would help water authorities to plan for effective water demand management strategies and to develop a water demand forecasting model with appropriate climatic factors to achieve sustainable water resources management. The methodology developed in this paper can be adapted to other water supply systems to identify the influential factors in water demand modelling and to devise an effective demand management strategy.

A relational contract for water demand management

For necessary goods like water, under supply constraints, fairness considerations lead to negative externalities. The objective of this paper is to design an infinite horizon contract or relational contract (a type of long-term contract) that ensures self-enforcing (instead of court-enforced) behaviour by the agents to mitigate the externality due to fairness issues. In this contract, the consumer is induced to consume at firm-supply level using the threat of higher fair price for future time periods. The pricing mechanism, computed in this paper, internalizes the externality and is shown to be economically efficient and provides revenue sufficiency.

Seasonal water quality monitoring in the Klamath River estuary, 1991-1994

The California Department of Fish and Game's Natural Stocks Assessment Project (NSAP) collected water quality data at high tides on a monthly basis from February 1991 to October 1994, and during low tides from March 1992 to June 1994 in the Klamath River estuary to describe water quality conditions. NSAP collected data on water temperature, dissolved oxygen, salinity, depth of saltwedge, and Klamath River flow. Klamath River flows ranged from 44.5 cubic meters per second (1570 cfs) in August 1994 to 3832.2 cubic meters per second (135,315 cfs) in March 1993. Saltwater was present in the estuary primarily in the summer and early fall and generally extended 2 to 3 miles upstream. Surface water temperatures ranged from 6-8° C in the winter to 20-24° C in the summer. Summer water temperatures within the saltwedge were generally 5 to 8° C cooler than the surface water temperature. Dissolved oxygen in the estuary was generally greater than 6 to 7 ppm year-round. A sand berm formed at the mouth of the river each year in the late summer or early fall which raised the water level in the estuary and reduced tidal fluctuation so that the Klamath estuary became essentially a lagoon. I hypothesize the formation of the sand berm may increase the production of the estuary and help provide favorable conditions for rearing juvenile chinook salmon.

Space heating and hot water demand analysis of dwellings connected to district heating scheme in UK

To achieve CO2 emissions reductions the UK Building Regulations require developers of new residential buildings to calculate expected CO2 emissions arising from their energy consumption using a methodology such as Standard Assessment Procedure (SAP 2005) or, more recently SAP 2009. SAP encompasses all domestic heat consumption and a limited proportion of the electricity consumption. However, these calculations are rarely verified with real energy consumption and related CO2 emissions. This paper presents the results of an analysis based on weekly head demand data for more than 200 individual flats. The data is collected from recently built residential development connected to a district heating network. A methodology for separating out the domestic hot water use (DHW) and space heating demand (SH) has been developed and compares measured values to the demand calculated using SAP 2005 and 2009 methodologies. The analysis shows also the variance in DHW and SH consumption between both size of the flats and tenure (privately owned or housing association). Evaluation of the space heating consumption includes also an estimation of the heating degree day (HDD) base temperature for each block of flats and its comparison to the average base temperature calculated using the SAP 2005 methodology.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

Hybrid Water Demand Forecasting Model Associating Artificial Neural Network with Fourier Series

This paper addressed the problem of water-demand forecasting for real-time operation of water supply systems. The present study was conducted to identify the best fit model using hourly consumption data from the water supply system of Araraquara, Sa approximate to o Paulo, Brazil. Artificial neural networks (ANNs) were used in view of their enhanced capability to match or even improve on the regression model forecasts. The ANNs used were the multilayer perceptron with the back-propagation algorithm (MLP-BP), the dynamic neural network (DAN2), and two hybrid ANNs. The hybrid models used the error produced by the Fourier series forecasting as input to the MLP-BP and DAN2, called ANN-H and DAN2-H, respectively. The tested inputs for the neural network were selected literature and correlation analysis. The results from the hybrid models were promising, DAN2 performing better than the tested MLP-BP models. DAN2-H, identified as the best model, produced a mean absolute error (MAE) of 3.3 L/s and 2.8 L/s for training and test set, respectively, for the prediction of the next hour, which represented about 12% of the average consumption. The best forecasting model for the next 24 hours was again DAN2-H, which outperformed other compared models, and produced a MAE of 3.1 L/s and 3.0 L/s for training and test set respectively, which represented about 12% of average consumption. DOI: 10.1061/(ASCE)WR.1943-5452.0000177. (C) 2012 American Society of Civil Engineers.

Urban water demand model: the case study of Emilia Romagna (Italy)

Water is the driving force in nature. We use water for washing cars, doing laundry, cooking, taking a shower, but also to generate energy and electricity. Therefore water is a necessary product in our daily lives (USGS. Howard Perlman, 2013). The model that we created is based on the urban water demand computer model from the Pacific Institute (California). With this model we will forecast the future urban water use of Emilia Romagna up to the year of 2030. We will analyze the urban water demand in Emilia Romagna that includes the 9 provinces: Bologna, Ferrara, Forli-Cesena, Modena, Parma, Piacenza, Ravenna, Reggio Emilia and Rimini. The term urban water refers to the water used in cities and suburbs and in homes in the rural areas. This will include the residential, commercial, institutional and the industrial use. In this research, we will cover the water saving technologies that can help to save water for daily use. We will project what influence these technologies have to the urban water demand, and what it can mean for future urban water demands. The ongoing climate change can reduce the snowpack, and extreme floods or droughts in Italy. The changing climate and development patterns are expected to have a significant impact on water demand in the future. We will do this by conducting different scenario analyses, by combining different population projections, climate influence and water saving technologies. In addition, we will also conduct a sensitivity analyses. The several analyses will show us how future urban water demand is likely respond to changes in water conservation technologies, population, climate, water price and consumption. I hope the research can contribute to the insight of the reader’s thoughts and opinion.

Intra-annual patterns of tracheid size in the Mediterranean tree Juniperus thurifera as an indicator of seasonal water stress

Because climate can affect xylem cell anatomy, series of intra-annual cell anatomical features have the potential to retrospectively supply seasonal climatic information. In this study, we explored the ability to extract information about water stress conditions from tracheid features of the Mediterranean conifer Juniperus thurifera L. Tracheidograms of four climatic years from two drought-sensitive sites in Spain were compared to evaluate whether it is possible to link intra-annual cell size patterns to seasonal climatic conditions. Results indicated site-specific anatomical adjustment such as smaller and thicker tracheids at the dryer site but also showed a strong climatic imprint on the intra-annual pattern of tracheid size. Site differences in cell size reflected expected structural adjustments against cavitation failures. Differences between intra-annual patterns, however, indicated a response to seasonal changes in water availability whereby cells formed under drought conditions were smaller and thicker, and vice versa. This relationship was more manifest and stable at the dryer site