The optimization of water networks supports the decision‐making process by identifying the optimal trade‐off between costs and performance (e.g., resilience and leakage). A major challenge in the ...domain of water distribution systems (WDSs) is the network (re)design. While the complex nature of WDS has already been explored with complex network analysis (CNA), literature is still lacking a CNA of optimal water networks. Based on a systematic CNA of Pareto‐optimal solutions of different WDSs, several graph characteristics are identified, and a newly developed CNA design approach for WDSs is proposed. The results show that obtained designs are comparable with results found by evolutionary optimization, but the CNA approach is applicable for large networks (e.g., 150,000 pipes) with a substantially reduced computational effort (runtime reduction up to 5 orders of magnitude).
Key Points
Patterns of optimal water networks are identified with complex network analysis
A network theory‐based design approach is developed, which partly outperforms a multiobjective evolutionary design approach
The new approach achieves runtime reductions up to 5 orders of magnitude and is capable of designing large networks (>150,000 pipes)
High accuracy models are required for informed decision making in urban flood management. This paper develops a new holistic framework for using information collected from multiple sources for ...setting parameters of a 2D flood model. This illustrates the importance of identifying key urban features from the terrain data for capturing high resolution flood processes. A Cellular Automata based model CADDIES was used to simulate surface water flood inundation. Existing reports and flood photos obtained via social media were used to set model parameters and investigate different approaches for representing infiltration and drainage system capacity in urban flood modelling. The results of different approaches to processing terrain datasets indicate that the representation of urban micro-features is critical to the accuracy of modelling results. The constant infiltration approach is better than the rainfall reduction approach in representing soil infiltration and drainage capacity, as it describes the flood recession process better. This study provides an in-depth insight into high resolution flood modelling.
•New holistic framework is developed to handle multi-source data and urban features.•Flood data from social media are a useful source for setting the model parameters.•Urban micro-features can significantly influence simulated inundation extent and depth.•Constant infiltration can better represent drainage capacity than the rainfall reduction approach in the study.•This study provides an in-depth insight into high resolution urban flood modelling.
Water, energy, food, land and climate form a tightly-connected nexus in which actions on one sector impact other sectors, creating feedbacks and unanticipated consequences. This is especially because ...at present, much scientific research and many policies are constrained to single discipline/sector silos that are often not interacting (e.g., water-related research/policy). However, experimenting with the interaction and determining how a change in one sector could impact another may require unreasonable time frames, be very difficult in practice and may be potentially dangerous, triggering any one of a number of unanticipated side-effects. Current modelling often neglects knowledge from practice. Therefore, a safe environment is required to test the potential cross-sectoral implications of policy decisions in one sector on other sectors. Serious games offer such an environment by creating realistic ‘simulations’, where long-term impacts of policies may be tested and rated. This paper describes how the ongoing (2016–2020) Horizon2020 project SIM4NEXUS will develop serious games investigating potential plausible cross-nexus implications and synergies due to policy interventions for 12 multi-scale case studies ranging from regional to global. What sets these games apart is that stakeholders and partners are involved in all aspects of the modelling definition and process, from case study conceptualisation, quantitative model development including the implementation and validation of each serious game. Learning from playing a serious game is justified by adopting a proof-of-concept for a specific regional case study in Sardinia (Italy). The value of multi-stakeholder involvement is demonstrated, and critical lessons learned for serious game development in general are presented.
► In the study, two parameters were applied to 2D coarse grid urban flood modelling. ► The building coverage ratio (BCR) represented the storage area occupied by buildings. ► The conveyance reduction ...factor (CRF) reflected the confined flow paths. ► The outcome showed the model can avoid the errors due to terrain averaging. ► It also provided more accurate results at a marginally increased computing cost.
The latest information and communications technology has enabled flood modelling in urban areas using high quality terrain data to simulate the detailed flow dynamics in local areas. However, the computational cost rises exponentially as the resolution goes finer. The advance of computing hardware is still a limiting factor for large-scale area or risk/uncertainty analysis modelling with fine resolution that describes the details of building features. Grid coarsening is the straightforward way to reduce the computing efforts for 2D flood modelling. The traditional approach to grid coarsening usually takes the average elevation of a fine grid as the new terrain model for the coarse grid. This approach often results in loss of information that introduces errors to modelling. In this study, the building features in coarse grids were abstracted using the building coverage ratio (BCR) and the conveyance reduction factor (CRF) parameters in a 2D model to simulate flooding in urban areas. The outcome of 2D case studies showed the proposed model can minimise the errors due to terrain averaging and provide a much better accuracy of modelling results at a marginally increased computing cost.
A System Dynamics Model (SDM) assessing water scarcity and potential impacts of socio-economic policies in a complex hydrological system is developed. The model, simulating water resources deriving ...from numerous catchment sources and demand from four sectors (domestic, industrial, agricultural, external pumping), contains multiple feedback loops and sub-models. The SDM is applied to the Merguellil catchment, Tunisia; the first time such an integrated model has been developed for the water scarce Kairouan region. The application represents an early step in filling a critical research gap. The focus of this paper is to a) assess the applicability of SDM for assessment of the evolution of a water-scarce catchment and b) to analyse the current and future behaviour of the catchment to evaluate water scarcity, focusing on understanding trends to inform policy.
Baseline results indicate aquifer over-exploitation, agreeing with observed trends. If current policy and social behaviour continue, serious aquifer depletion is possible in the not too distant future, with implications for the economy and environment. This is unlikely to occur because policies preventing depletion will be implemented. Sensitivity tests were carried out to show which parameters most impacted aquifer behaviour. Results show non-linear model behaviour. Some tests showed negligible change in behaviour. Others showed unrealistic exponential changes in demand, revenue and aquifer water volume. Policy-realistic parameters giving the greatest positive impact on model behaviour were those controlling per-capita domestic water demand and the pumped volume to coastal cities. All potentially beneficial policy options should be considered, giving the best opportunity for preservation of Kairouan aquifer water quantity/quality, ecologically important habitats and the agricultural socio-economic driver of regional development. SDM is a useful tool for assessing the potential impacts of possible policy measures with respect to the evolution of water scarcity in critical regions. This work was undertaken for the EC FP7 project ‘WASSERMed’.
► A System Dynamics Model of a complex water scarce system is presented. ► The baseline run indicates net aquifer depletion to 2050. ► Parameter tests hint at the complex non-linearity in the system. ► Reducing coastal pumping holds most promise for re-establishing recharge behaviour. ► Any viable water-saving policy should be considered given the current situation.
► Multi layers are used to represent separate parts of a coarse cell bisected by buildings. ► The building coverage ratio (BCR) represents the storage area occupied by buildings. ► The conveyance ...reduction factor (CRF) reflects the confined flow paths. ► Each layer has its own BCR and CRF parameters to describe building situations. ► The model can improve modelling accuracy with limited extra computational cost.
Regular grids are commonly used in 2D flood modelling due to wide availability of terrain models and low pre-processing required for input preparation. Despite advances in both computing software and hardware, high resolution flood modelling remains computationally demanding when applied to a large study area when the available time and resources are limited. Traditional grid coarsening approach may reduce not only the computing demands, but also the accuracy of results due to the loss of detailed information. To keep key features that affect flow propagation within coarse grid, the approach proposed and tested in this paper adopts multiple layers in flood modelling to reflect individual flow paths separated by buildings within a coarse grid cell. The cell in each layer has its own parameters (elevation, roughness, building coverage ratio, and conveyance reduction factors) to describe itself and the conditions at boundaries with neighbourhood cells. Results of tests on the synthetic case study and the real world urban area show that the proposed multi-layered approach greatly improves the accuracy of coarse grid modelling with an insignificant additional computing cost. The proposed approach has been tested in conjunction with the UIM model by taking the high resolution results as the benchmark. The implementation of the proposed multi-layered methodology to any regular grid based 2D model would be straightforward.
AbstractWater distribution system (WDS) models may improve system control when applied using real-time data, and in doing so, help meet consumer and regulatory demands. Such real-time modeling often ...overlooks the multiple sources of system uncertainty that cascade into model forecasts and affect the identification of robust operational solutions. This paper considers key uncertainties in WDS modeling and reviews promising approaches for uncertainty quantification and reduction in the modeling cascade from calibration, through data assimilation, to model forecasting. An uncertainty framework exemplifying how such methods may be applied to propagate uncertainty through the real-time control process is outlined. Innovative methods to constrain uncertainty when the time-horizon and data availability limit such thorough analysis are also discussed, alongside challenges that need to be addressed to incorporate uncertain information into the control decision. Further work evaluating the value of these methods in light of computational resources, and the nature of model errors in real WDS, is required. Such work is necessary to demonstrate the benefits of considering model and data uncertainty, leading to robust control decisions.
This paper proposes a many-objective optimization model for the flexible design of water distribution networks (WDNs), including four objectives. Two objectives are related to the WDNs' hydraulic ...capacity, the minimization of the pressure deficit and the undelivered demand. The third objective is the traditional cost minimization while the fourth minimizes carbon emissions. These objectives concern network reliability, and financial and environmental concerns. They can give rise to solutions embedding new trade-off in design perspectives. There is a gap in the literature when it comes to dealing with many-objective problems for designing and constructing a WDN over a long-term planning horizon and using a staged design scheme that includes the consideration of uncertainty. A solution obtained through this process can be implemented in the first stage and the WDN is prepared for the possible occurrence of various future scenarios. These scenarios can consider expansions of WDNs to different development areas, in different time stages. Furthermore, defining a multi-staged design allows implementing the design of the first stage and reassessing the whole process in the end of each stage when more plausible future scenarios can be investigated. The solution of complex problems such as these needs improved algorithms to produce the Pareto front and so enable the trade-off between the objectives to be examined. An enhanced algorithm, based on the simulated annealing concept and capable of handling the critical scalability issues encountered in previous algorithms with respect to drawing the Pareto front for many-objective problems where a high-dimensional space is involves, is presented. The results obtained allow a thorough analysis of trade-offs between objectives and confirm the importance of considering the minimization of all those four objectives and the advantages of using a flexible approach to design WDNs to better inform decision makers.
•Many-objective model to design WDNs that can be expanded over the planning horizon.•Flexible solutions to adapt WDN as new information becomes available.•Approach to define solutions that can cope with multiple plausible scenarios.•Enhanced Simulated Annealing Algorithm for solving many-objective problems.
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