Results of an urban water distribution network performance evaluation attempt in Greece

The need for efficient water resources management is currently more pressing than ever, considering population growth and increased reliability requirements, under climate change conditions. On average, one-third of the total water abstracted for urban uses is being lost due to leaks and breaks occurring in water distribution networks. This means that significant amounts of water and revenues are being lost, forcing water utilities to consider developing effective water loss and Non-Revenue Water reduction strategies. Additionally, all water utilities operating in EU countries should, by the end of 2010, develop and implement appropriate water pricing policies that will guarantee the recovery of the full cost of the water being used. This strict obligation makes the reduction of water losses an even more urgent goal that the water utilities have to achieve. The first step towards all the above-mentioned goals is to safely evaluate the performance level of the water network. Thus, the IWA Task Forces on Water Losses and Performance Indicators (PIs) developed specific tools (e.g., the standard international water balance and various PIs), to help water utilities use a common language that will assist know-how and experience exchange through an effective benchmarking process. The paper presents the results of using the above-mentioned IWA tools, in the case of the Larisa city water distribution network in Greece. This is the first time that such an attempt has taken place in Greece. During this process, the problems faced and the ways to tackle them are analyzed, focusing on the role of key factors that had to do with local conditions. Larisa's results are compared to data available from similar cases. Sensitivity analysis was used to check the impact of the variables' uncertainty to the results. Finally, water loss reduction measures are proposed towards an effective pressure management strategy and a proactive pipe maintenance policy based on safely estimating the pipes' optimum replacement time.     

A hydrological investigation using a lumped water balance model: the Aison River Basin case (Greece)

The purpose of the present paper is to investigate the hydrological components of the Aison River Basin in northern Greece. The orography of the area and the increasing irrigation needs require a specifically adapted hydrological model in order to address water management issues. With this aim in view, a parsimonious lumped simulation–optimization model with a snowmelt routine is elaborated in a monthly time step. The Nelder–Mead algorithm is applied for automatic optimization of the model parameters using the Nash criterion as an objective function. The model results are also evaluated by additional statistical criteria. In order to further reduce data uncertainty influence, annual actual evapotranspiration values are compared with those derived using three empirical methods (Turk, Coutagne and Schreiber methods). Model outputs were shown to be a good estimation of the hydrological cycle components, indicating that water losses represent almost 62% of the total precipitation volume.     

Large metropolitan water demand forecasting using DAN2, FTDNN,and KNN models: A case study of the city of Tehran,Iran

Efficient operation of urban water systems necessitates accurate water demand forecasting. We present daily, weekly, and monthly water demand forecasting using dynamic artificial neural network (DAN2), focused time-delay neural network (FTDNN), and K-nearest neighbor (KNN) models for the city of Tehran. The daily model investigates whether partitioning weekdays into weekends and non-weekends can improve forecast results; it did not. The weekly model yielded good results by using the summation of the daily forecast values into their corresponding weeks. The monthly results showed that partitioning the year into high and low seasons can improve forecast accuracy. All three models offer very good results for water demand forecasting. DAN2, the best model, yielded forecasting accuracies of 96%, 99%, and 98%, for daily, weekly, and monthly models respectively.     

Ecological network analysis of an urban water metabolic system: Model development, and a case study for Beijing

Using ecological network analysis, we analyzed the network structure and ecological relationships in an urban water metabolic system. We developed an ecological network model for the system, and used Beijing as an example of analysis based on the model. We used network throughflow analysis to determine the flows among components, and measured both indirect and direct flows. Using a network utility matrix, we determined the relationships and degrees of mutualism among six compartments - 1) local environment, 2) rainwater collection, 3) industry, 4) agriculture, 5) domestic sector, and 6) wastewater recycling - which represent producer, consumer, and reducer trophic levels. The capacity of producers to provide water for Beijing decreased from 2003 to 2007, and consumer demand for water decreased due to decreasing industrial and agricultural demand; the recycling capacity of reducers also improved, decreasing the discharge pressure on the environment. The ecological relationships associated with the local environment or the wastewater recycling sector changed little from 2003 to 2007. From 2003 to 2005, the main changes in the ecological relationships among components of Beijing's water metabolic system mostly occurred between the local environment, the industrial and agricultural sectors, and the domestic sector, but by 2006 and 2007, the major change was between the local environment, the agricultural sector, and the industrial sector. The other ecological relationships did not change during the study period. Although Beijing's mutualism indices remained generally stable, the ecological relationships among compartments changed greatly. Our analysis revealed ways to further optimize this system and the relationships among compartments, thereby optimizing future urban water resources development.     

Changing from intermittent to continuous water supply and its influence on service level benchmarks: a case study in the demonstration zone of Nagpur,India

A dearth in infrastructure and operations significantly reduces the expected benefits of safe drinking water provision. Intermittent water supplies are characterized by inefficient demand and supply management owing to operational inadequacies eventually causing physical deterioration of infrastructure and inconvenience to consumers, resulting in consumer dissatisfaction. Conversion from intermittent to continuous water supply was undertaken in a demonstration zone of Nagpur, India, with a population of about 150,000 people. Data related to the infrastructural, operational, managerial and financial capabilities were used to determine service level benchmarks (SLBs) — pre- and post-intervention — to quantify the improvement due to continuous water supply interventions. The post-intervention data analysis clearly indicated substantial improvement in post-intervention SLBs, consequently paving the way for the conversion of the water supply of the entire city to continuous mode.     

An ensemble wavelet bootstrap machine learning approach to water demand forecasting: a case study in the city of Calgary,Canada

This paper explores a hybrid wavelet, bootstrap and neural network (WBNN) modeling approach for daily (1, 3 and 5 day) urban water demand forecasting in situations with limited data availability. This method was tested using 3 years of daily water demand and meteorological data for the city of Calgary, Alberta, Canada. The performance of the WBNN method was compared to that of three other methods: traditional neural networks (NN), wavelet NNs (WNN), and bootstrap-based NN (BNN) models. While the hybrid WBNN and WNN models equally provided 1-day lead-time forecasts of greater accuracy than those obtained with other methods, for longer lead-time (3- or 5-day) forecasts the WBNN model alone outperformed the other models. The confidence bands generated using the WBNN model displayed the uncertainty associated with the forecasts.     

Using Bayesian statistics to estimate the coefficients of a two- component second-order chlorine bulk decay model for a water distribution system

Most chlorine decay models for the bulk phase in a water distribution system consider only chlorine concentration and time. Clark [1998. Chlorine demand and trihalomethane formation kinetics: a second-order model. J. Environ. Eng. 124(1), 16-24] first proposed a two-component second-order chlorine decay model based on the concept of competing reacting substances. A corrected mathematical formulation is developed and, because the recent findings suggested that not all natural organic matter (NOM) is involved in the chlorine decay process, an additional parameter is introduced. A parameter assignment method employing Bayesian statistical analysis incorporating Monte Carlo Markov chain (MCMC) with Gibbs sampling to make inferences, is employed in the estimation of model parameters. Three parameters are estimated for the model, namely the ratio of chlorine to TOC, the chlorine reaction rate, and a fraction factor of TOC which represents the true amount of TOC involved in chlorine decay process. Water samples taken from Goderich in the summer of 2005, are used for estimating the parameters.     

Long-term impact of water desalination plants on the energy and carbon dioxide balance of Victoria,Australia: a case study from Wonthaggi

In 2007, the state government of Victoria, Australia, announced plans to build a large desalination plant with a capacity of 150 million m³ per year of desalinated water. Currently, the only feasible source for significant expansion of the greenhouse-gas neutral (GGN) energy generation in the state is wind power. A criterion for GGN of a desalination plant has been formulated. In a case of no greenhouse gas contribution from the desalination plant, the criterion is satisfied if the annual growth of the electrical energy generated by GGN sources is around 6–9% for the period 2010–2070. Higher annual growth of 18% for the period 2008–2015, 8% annually for the period 2015–2035 and 6% annual growth thereafter are required if the desalination plant is contributing to the greenhouse-gas balance of the state.     

Use of multiple indicators to assess the pollution condition of urban streams: a case study of Bloemspruit,Free State Province,South Africa

The Bloemspruit in the Free State, South Africa, is being polluted by increasing anthropogenic activities alongside the stream. Water quality, macro‐invertebrate diversity and macro‐invertebrate habitats were studied to determine the extent of pollution. Pollution condition was quantified by calculating several indicators. The study revealed that Bloemspruit is highly polluted for the majority of the sampling sites. Two sites had fair water quality, while the water quality at the other sites was either marginal or poor. SASS 5 scores revealed that most macro‐invertebrate families present were pollution tolerant, indicating the poor state of the water. According to the modified IHAS (mIHAS) scores, macro‐invertebrate habitats at two sites were fair, seven adequate/fair and two poor. The relatively low values of the IHI scores confirm that the majority of the sites were affected by human activities. One site was classified as being largely modified because of the degrading effect of a wastewater treatment plant (WWTP) nearby.