Christos Makropoulos

Spatial ordered weighted averaging: incorporating spatially variable attitude towards risk in spatial multi-criteria decision-making

The paper discusses a decomposition-analysis-aggregation approach to multi-criteria spatial decision-making and proposes a novel aggregation method applicable to problems of the object-location or suitability for application type, concentrating on methodological rather than software development aspects. The approach allows the decision maker to: (a) break the problem down into a series of elementary (easier to understand) problems, (b) analyse them (in the broad sense of the word), and then (c) produce an answer for the complex problem by aggregating the answers derived for the elementary problems. The choice of methodology used for this aggregation is very important as different aggregating techniques may yield different results to the (same) original problem. The method presented here, which is in effect an extension of the ordered weighted averaging (OWA) method into a spatial decision-making technique, is termed spatial ordered weighted averaging (SOWA). The main advantage of the method proposed is the incorporation of spatially variable attitude to risk into the decision-making process. The mathematical background of the method and an example of its application in urban water management are presented and discussed. The authors suggest that the method could be useful as an analytical and decision-making tool for the incorporation of spatially variable risk perception in GIS-based decision support systems.

Source to tap urban water cycle modelling

The continuous expansion of urban areas is associated with increased water demand, both for domestic and non-domestic uses. To cover this additional demand, centralised infrastructure, such as water supply and distribution networks tend to become more and more complicated and are eventually over-extended with adverse effects on their reliability. To address this, there exist two main strategies: (a) Tools and algorithms are employed to optimise the operation of the external water supply system, in an effort to minimise risk of failure to cover the demand (either due to the limited availability of water resources or due to the limited capacity of the transmission system and treatment plants) and (b) demand management is employed to reduce the water demand per capita. Dedicated tools do exist to support the implementation of these two strategies separately. However, there is currently no tool capable of handling the complete urban water system, from source to tap, allowing for an investigation of these two strategies at the same time and thus exploring synergies between the two. This paper presents a new version of the UWOT model (Makropoulos et al., 2008), which adopts a metabolism modelling approach and is now capable of simulating the complete urban water cycle from source to tap and back again: the tool simulates the whole water supply network from the generation of demand at the household level to the water reservoirs and tracks wastewater generation from the household through the wastewater system and the treatment plants to the water bodies. UWOT functionality is demonstrated in the case of the water system of Athens and outputs are compared against the current operational tool used by the Water Company of Athens. Results are presented and discussed: The discussion highlights the conditions under which a single source-to-tap model is more advantageous than dedicated subsystem models.

Impacts of residence time during storage on potential of water saving for grey water recycling system.

Grey water recycling has been generally accepted and is about to move into practice in terms of sustainable development. Previous research has revealed the bacteria re-growth in grey water and reclaimed municipal water during storage. However, in most present grey water recycling practices, impacts of water quality changes during storage on the systems performance and design regulation have not been addressed. In this paper, performance of a constructed wetland based grey water recycling system was analysed by taking the constraint of residence time during storage into account using an object based household water cycle model. Two indicators, water saving efficiency (WSE) and residence time index (RTI), are employed to reflect the systems performance and residence time during storage respectively. Results show that WSE and RTI change with storage tank volumes oppositely. As both high WSE and RTI cannot be achieved simultaneously, it is concluded that in order to achieve the most cost-effective and safe solution, systems with both small grey and green tanks are needed, whilst accepting that only relatively modest water saving efficiency targets can be achieved. Higher efficiencies will only be practicable if water quality deterioration in the green water tank can be prevented by some means (e.g. disinfection).

Design Robustness of Local Water-Recycling Schemes

The implementation of local water recycling and reuse practices is considered as a possible approach to managing issues of water scarcity. The sustainable design and implementation of a water recycle/reuse scheme has to achieve an optimum compromise between costs (including energy) and benefits (potable water demand reduction). Another factor that should be taken into account is the influence of potential changes in climatic conditions to the scheme’s efficiency. These issues were assessed in this study using the urban water optioneering tool. Two water-recycling schemes, a rainwater harvesting and a combination of rainwater harvesting and local greywater recycling, were assessed. The trade-off between potable water demand reduction, capital/operational cost, and energy consumption of the two schemes was derived under three basic climatic conditions (oceanic, Mediterranean, and desert) using evolutionary optimization. Furthermore, the impact of changing climatic conditions on the suggested schemes was ana...

Simulation and spatio-temporal disaggregation of multi-site rainfall data for urban drainage applications

Abstract For urban drainage and urban flood modelling applications, fine spatial and temporal rainfall resolution is required. Simulation methods are developed to overcome the problem of data limitations. Although temporal resolution higher than 10–20 minutes is not well suited for detailed rainfall—runoff modelling for urban drainage networks, in the absence of monitored data, longer time intervals can be used for master planning or similar purposes. A methodology is presented for temporal disaggregation and spatial distribution of hourly rainfall fields, tested on observations for a 10-year period at 16 raingauges in the urban catchment of Dalmuir (UK). Daily rainfall time series are simulated with a generalized linear model (GLM). Next, using a single-site disaggregation model, the daily data of the central gauge in the catchment are downscaled to an hourly time scale. This hourly pattern is then applied linearly in space to disaggregate the daily data into hourly rainfall at all sites. Finally, the spatial rainfall field is obtained using inverse distance weighting (IDW) to interpolate the data over the whole catchment. Results are satisfactory: at individual sites within the region the simulated data preserve properties that match the observed statistics to an acceptable level for practical purposes.

Preliminary flood risk assessment: the case of Athens

Flood mapping, especially in urban areas, is a demanding task requiring substantial (and usually unavailable) data. However, with the recent introduction of the EU Floods Directive (2007/60/EC), the need for reliable, but cost effective, risk mapping at the regional scale is rising in the policy agenda. Methods are therefore required to allow for efficiently undertaking what the Directive terms “preliminary flood risk assessment,” in other words a screening of areas that could potentially be at risk of flooding and that consequently merit more detailed attention and analysis. Such methods cannot rely on modeling, as this would require more data and effort that is reasonable for this high-level, screening phase. This is especially true in urban areas, where modeling requires knowledge of the detailed urban terrain, the drainage networks, and their interactions. A GIS-based multicriteria flood risk assessment methodology was therefore developed and applied for the mapping of flood risk in urban areas. This approach quantifies the spatial distribution of flood risk and is able to deal with uncertainties in criteria values and to examine their influence on the overall flood risk assessment. It can further assess the spatially variable reliability of the resulting maps on the basis of the choice of method used to develop the maps. The approach is applied to the Greater Athens area and validated for its central and most urban part. A GIS database of economic, social, and environmental criteria contributing to flood risk was created. Three different multicriteria decision rules (Analytical Hierarchy Process, Weighted Linear Combination and Ordered Weighting Averaging) were applied, to produce the overall flood risk map of the area. To implement this methodology, the IDRISI Andes GIS software was customized and used. It is concluded that the results of the analysis are a reasonable representation of actual flood risk, on the basis of their comparison with historical flood events.

Assessing the combined benefits of water recycling technologies by modelling the total urban water cycle

This study investigates the potential benefits of new technologies, modern appliances, and innovative techniques that help to improve the performance of the urban water cycle. Urbanisation is a major source of additional pressures (both qualitative and quantitative) on the environment. For example abstractions to cover the increased demands for water supply or alterations of the topographic and geomorphologic properties of the land cover result in considerable changes to the dynamics of the hydrosystem (change of average and maximum values of flows). Sustainable, water-aware technologies, like SUstainable Drainage Systems (SUDS) and rainwater harvesting schemes, can be implemented to reduce these adverse effects. These technologies introduce interactions between the components of the urban water cycle. Rainwater harvesting for example, apart from the potable water demand reduction, may have a significant influence on the generated runoff. Consequently, an integrated modelling of the urban water cycle is necessary for the simulation of the water-aware technologies and the identification of their combined benefits. In this study, two hypothetical developments implement rainwater harvesting schemes and SUDS and are simulated using the Urban Water Optioneering Tool (UWOT), which is capable of using rainfall time series of arbitrary time steps. The two hypothetical developments were studied to investigate the contribution of the water-aware technologies to the minimisation of the environmental pressures. Significantly different urban density was assigned to these developments to highlight the influence of urban density on the efficiency and reliability of the water-aware technologies. The results indicate that: (a) water-saving schemes like rainwater harvesting and greywater treatment can reduce significantly the pressures of new developments (e.g., reduction of potable water demand by 27%); (b) the reliability of the water-aware technologies decreases with urban density; and (c) if localised rainwater harvesting is implemented then the efficiency of the water appliances influences considerably the generated runoff.

Multiobjective optimisation on a budget

Developing long term operation rules for multi-reservoir systems is complicated due to the number of decision variables, the non-linearity of system dynamics and the hydrological uncertainty. This uncertainty can be addressed by coupling simulation models with multi-objective optimisation algorithms driven by stochastically generated hydrological timeseries but the computational effort required imposes barriers to the exploration of the solution space. The paper addresses this by (a) employing a parsimonious multi-objective parameterization-simulation-optimization (PSO) framework, which incorporates hydrological uncertainty through stochastic simulation and allows the use of probabilistic objective functions and (b) by investigating the potential of multi-objective surrogate based optimisation (MOSBO) to significantly reduce the resulting computational effort. Three MOSBO algorithms are compared against two multi-objective evolutionary algorithms. Results suggest that MOSBOs are indeed able to provide robust, uncertainty-aware operation rules much faster, without significant loss of neither the generality of evolutionary algorithms nor of the knowledge embedded in domain-specific models. Extended multi-objective parameterization-simulation-optimisation framework.Development of uncertainty-aware reservoir operation rules.Benchmarking of multi-objective surrogate based optimisation algorithms.Coupling WEAP21 simulation model with MATLAB.

A neurofuzzy spatial decision support system for pipe replacement prioritisation

Spatial Decision Support Systems (SDSS) represent an attempt to assist in the decision making process by a set of intelligent, knowledge-based techniques and as such have an increasingly important role to play as the data required for spatially sensitive decisions become more available in a wide range of problem areas. The urban environment is a complex, spatially sensitive decision-making environment and as such an ideal case study for the application of these techniques and tools. Building knowledge into a system, particularly through linguistic modelling, is a challenge. This paper briefly discusses the development of such an SDSS based on fuzzy inference and describes techniques enabling the incorporation of both expert judgement and field evidence, where available, in an effort to address one of the main criticisms of linguistic (fuzzy) modelling: that of subjectivity.

Flood forecasting in transboundary catchments using the Open Modeling Interface

Using satellite data for flood forecasting in catchments located in mid-latitudes is challenging to engineers and model developers, in no small part due to the plethora of data sets that need to be retrieved, combined, calibrated and used for simulation in real time. The differences between the various satellite rainfall data products and the continuous improvement in their quantity and quality render the development of a single software tool, able to read and process all the different data sets, particularly difficult. Even if such an endeavour was undertaken, the degree of flexibility and extensibility that such a tool would require to accommodate future versions of data sets, available in different file formats as well as different temporal and spatial resolution should not be underestimated. This paper describes the development of a flood forecasting system that addresses this issue through a modular architecture based on the use of the Open Modeling Interface (OpenMI) standard, which facilitates the interaction between a number of separate software components. It is suggested that this approach greatly simplifies programming and debugging and eliminates the need to create spatial and temporal transformation functions without significantly compromising the overall execution speed. The approach and system were tested for forecasting flood events within a particularly challenging transboundary catchment, the Evros catchment, extending between Greece, Bulgaria and Turkey. The system uses two sets of data sources, as an example (NASAs TRMM 3B42 and 3B42RT satellite data sets) to forecast flooding in the Evros catchment. Results indicate that OpenMI greatly facilitates the complex interaction of various software components and considerably increases the flexibility and extensibility of the overall system and hence its operational value and sustainability.