Kourosh Behzadian

Advantages of integrated and sustainability based assessment for metabolism based strategic planning of urban water systems

Despite providing water-related services as the primary purpose of urban water system (UWS), all relevant activities require capital investments and operational expenditures, consume resources (e.g. materials and chemicals), and may increase negative environmental impacts (e.g. contaminant discharge, emissions to water and air). Performance assessment of such a metabolic system may require developing a holistic approach which encompasses various system elements and criteria. This paper analyses the impact of integration of UWS components on the metabolism based performance assessment for future planning using a number of intervention strategies. It also explores the importance of sustainability based criteria in the assessment of long-term planning. Two assessment approaches analysed here are: (1) planning for only water supply system (WSS) as a part of the UWS and (2) planning for an integrated UWS including potable water, stormwater, wastewater and water recycling. WaterMet(2) model is used to simulate metabolic type processes in the UWS and calculate quantitative performance indicators. The analysis is demonstrated on the problem of strategic level planning of a real-world UWS to where optional intervention strategies are applied. The resulting performance is assessed using the multiple criteria of both conventional and sustainability type; and optional intervention strategies are then ranked using the Compromise Programming method. The results obtained show that the high ranked intervention strategies in the integrated UWS are those supporting both water supply and stormwater/wastewater subsystems (e.g. rainwater harvesting and greywater recycling schemes) whilst these strategies are ranked low in the WSS and those targeting improvement of water supply components only (e.g. rehabilitation of clean water pipes and addition of new water resources) are preferred instead. Results also demonstrate that both conventional and sustainability type performance indicators are necessary for strategic planning in the UWS.

Metabolism-modelling approaches to long-term sustainability assessment of urban water services

Abstract There is a discernible need for a holistic, long-term and sustainability approach in decision-making in water and wastewater utilities around the world. Metabolism-based modelling, which can quantify various flows within an urban water system (UWS), has shown its effective usability for a more comprehensive understanding of the impacts of intervention strategies and can be used by any water utility for future planning of UWS. This study presents the main principles of a holistic Sustainability Assessment Framework which can be simulated by using two analytical, conceptual, mass-balance-based models to quantify relevant key performance indicators (KPIs) associated with the metabolic flows of the urban water cycle. These two models are WaterMet2 (WM2) and dynamic metabolism model (DMM), developed recently under the aegis of the EU TRUST (Transitions to the Urban Water Services of Tomorrow) project. There are clear differences between the two models which make them useful in different contexts and circumstantial situations. DMM is a mass-balance consistent model which quantifies and presents annually-aggregated performance values for system wide energy consumption, emissions, environmental impacts and costs for the entire UWS though it is also possible to derive corresponding indicators for individual sub-systems (e.g. water distribution and wastewater transport). WM2 is the opposite of this, it is a distributed metabolism model which simulates water related and other resource flows throughout the UWS components with a higher resolution both spatially (e.g. multiple water resources and service reservoirs) and temporally (e.g. daily and monthly), and thereby is useful in contexts where utilities would like to focus on further details of the UWS metabolism with the aim to understand and solve specific problems. Overall, these two complementary metabolism-based approaches enable any water utility to quantitatively explore and understand the influences of different external drivers and intervention strategies on future performance profiles linked to any physical, environmental and economic criteria.

Comprehensive risk management using fuzzy FMEA and MCDA techniques in highway construction projects

AbstractThis paper presents a comprehensive framework to manage the main risk events of highway construction projects within three stages: (1) identification of potential risks; (2) assessment and prioritisation of identified risks based on fuzzy FMEA; (3) identification of appropriate response. The main criteria analysed for prioritising potential risk events are cost, time and quality which are quantified and combined using fuzzy AHP. A new expert system is suggested for identifying an appropriate risk response strategy for a risk event based on risk factor, control number and risk allocation. The best response action for a risk event is then identified with respect to the same criteria using “scope expected deviation” (SED) index. The proposed methodology is demonstrated for management of risk events in a construction project of Bijar-Zanjan highway in Iran. For the risk event of “increase in tar price”, deviation from the target values of the criteria is analysed for business-as-usual state plus two r...

Protective spur dike for scour mitigation of existing spur dikes

To alleviate the scour depth around a series of existing spur dikes (SDs), a protective SD located upstream of the first was experimentally investigated. To determine the optimal design parameters, various values, lengths, angles and the spacing of a protective SDs were experimentally tested under different clear-water conditions in a straight river reach and a fixed flow depth. To investigate the behaviour of the flow field around the SDs, acoustic Doppler velocimeter was used to measure instantaneous velocity components on a rough rigid bed. The results indicate that a properly designed protective SD is able to decrease the average of the maximum scour depth around the main SDs. The optimum design parameters of a protective SD are recommended for each length for a particular experiment.

LEAKAGE CONTROL IN WATER DISTRIBUTION NETWORKS BY USING OPTIMAL PRESSURE MANAGEMENT: A CASE STUDY

More than thirty percent of drinking water loss through water distribution systems (WDS) in Iran has made a major concern for Iranian water utilities, which has been located in a semi-arid area. In many cases, invisible leakage in the pipelines of WDS, particularly old WDSs, causes a high proportion of total annual losses. Pressure management is a well known and useful tool for reducing invisible leakage since leak is a pressure dependent function. This paper presents an optimization model for pressure management by optimizing pressure reducing valves (PRV) locations and settings. The PRVs location and setting is formulated here as an optimization problem with: (1) the objective function of maximizing the coverage of end-node users’ pressures in an appropriate range; (2) the objective function of minimizing total leakage in the network. Genetic algorithm is used here as the optimization model, in which EPANET toolkit is used as the simulation engine. The model is applied to a case study in Iran known as Mahalat WDS which has assigned a high value of water loss in the networks. The results show that the system is able to considerably moderate the high pressure values and total value of drinking water which is annually lost.

Reduction of Local Scouring with Protective Spur Dike

One of the main parameters in design of spur dikes is the estimation of local scour depth around their tail. Spur dikes are usually built in series and their stability depends on the stability of the first spur dike. In this research, an experimental investigation is carried out in order to reduce local scouring around the first spur dike in a series of spur dikes (4 spur dikes). A smaller protective spur dike perpendicular to the flow direction is proposed to substantially reduce the local scouring. All experiments are performed in the experimental flume with moving bed. Also, all the spur dikes are rigid, and are made of pressurized plywood, straight and non-submerged. For various experimental lengths (L) and distances (X) of the protective spur dike, different value of relative velocity u / u c is calculated. Finally, in favor of statistical analysis which has been done on the experimental data, an empirical equation for the relative scouring is derived.

An Evolutionary Model for Operation of Hydropower Reservoirs

In this study, an optimization model is developed for monthly operation of a multi-purpose hydropower reservoirs using genetic algorithm. The real value encoding approach is used considering alternative representation, selection, crossover, and mutation schemes. The constraints are handled using the Multiplicative Penalty Method (MPM) function, in order to evaluate the objective function in deferent conditions. The reliability of water allocation to different demands and hydropower generation are evaluated using an economic objective function which has been calculated based on the actual value of water and energy of Karoon-I Reservoir in southwestern part of Iran. The results of this study have shown the importance of selecting a suitable mutation operator for reducing the computational run time of the optimization model. The robustness and efficiency of genetic algorithm in developing the operation policies for a multi-purpose hydropower reservoir is discussed in the paper.

Rehabilitation of a Water Distribution System Using Sequential Multiobjective Optimization Models

AbstractIdentification of the optimal rehabilitation plan for a large water distribution system (WDS) with a substantial number of decision variables is a challenging task, especially when no supercomputer facilities are available. This paper presents an initiative methodology for the rehabilitation of WDS based on three sequential stages of multiobjective optimization models for gradually identifying the best-known Pareto front (PF). A two-objective optimization model is used in the first two stages where the objectives are to minimize rehabilitated infrastructure costs and operational costs. The optimization model in the first stage applies to a skeletonized WDS. The PFs obtained in Stage 1 are further improved in Stage 2 using the same two-objective optimization problem but for the full network. The third stage employs a three-objective optimization model by minimizing the cost of additional pressure reducing valves (PRVs) as the third objective. The suggested methodology was demonstrated through use o...

The Local Nexus Network: Exploring the Future of Localised Food Systems and Associated Energy and Water Supply

The Local Nexus Network is addressing the intersection of two important emerging research areas, re-distributed manufacturing and the food-energy-water nexus. It is an on-going initiative which aims to develop an evidence-based comprehensive research agenda and foster an inclusive community of researchers and stakeholders for sustainable local food-energy-water nexuses. This paper presents the conceptual framing for understanding the challenges of local nexus, reports empirical findings around a particular case study, and makes initial reflections on the research and practical challenges and opportunities.

Estimation of peak outflow in dam failure using neural network approach under uncertainty analysis

This paper presents two Artificial Neural Network (ANN) based models for the prediction of peak outflow from breached embankment dams using two effective parameters including height and volume of water behind the dam at the time of failure. Estimation of optimal weights and biases in the training phase of the ANN is analysed by two different algorithms including Levenberg—Marquardt (LM) as a standard technique used to solve nonlinear least squares problems and Imperialist Competitive Algorithm (ICA) as a new evolutionary algorithm in the evolutionary computation field. Comparison of the obtained results with those of the conventional approach based on regression analysis shows a better performance of the ANN model trained with ICA. Investigation on the uncertainty band of the models indicated that LM predictions have the least uncertainty band whilst ICA’s have the lowest mean prediction error. More analysis on the models’ uncertainty is conducted by a Monte Carlo simulation in which 1000 randomly generated sets of input data are sampled from the database of historical dam failures. The result of 1000 ANN models which have been analysed with three statistical measures including p-factor, d-factor, and DDR confirms that LM predictions have more limited uncertainty band.