The Impacts of Spatially Variable Demand Patterns on Water Distribution System Design and Operation

Open Access articleResilient water distribution systems (WDSs) need to minimize the level of service failure in terms of magnitude and duration over its design life when subject to exceptional conditions. This requires WDS design to consider scenarios as close as possible to real conditions of the WDS to avoid any unexpected level of service failure in future operation (e.g., insufficient pressure, much higher operational cost, water quality issues, etc.). Thus, this research aims at exploring the impacts of design flow scenarios (i.e., spatial-variant demand patterns) on water distribution system design and operation. WDSs are traditionally designed by using a uniform demand pattern for the whole system. Nevertheless, in reality, the patterns are highly related to the number of consumers, service areas, and the duration of peak flows. Thus, water distribution systems are comprised of distribution blocks (communities) organized in a hierarchical structure. As each community may be significantly different from the others in scale and water use, the WDSs have spatially variable demand patterns. Hence, there might be considerable variability of real flow patterns for different parts of the system. Consequently, the system operation might not reach the expected performance determined during the design stage, since all corresponding facilities are commonly tailor-made to serve the design flow scenario instead of the real situation. To quantify the impacts, WDSs’ performances under both uniform and spatial distributed patterns are compared based on case studies. The corresponding impacts on system performances are then quantified based on three major metrics; i.e., capital cost, energy cost, and water quality. This study exemplifies that designing a WDS using spatial distributed demand patterns might result in decreased life-cycle cost (i.e., lower capital cost and nearly the same pump operating cost) and longer water ages. The outcomes of this study provide valuable information regarding design and operation of water supply infrastructures; e.g., assisting the optimal design

Stationary vs non-stationary modelling of flood frequency distribution across northwest England

Extraordinary flood events occurred recently in northwest England, with several severe floods in Cumbria, Lancashire and the Manchester area in 2004, 2009 and 2015. These clustered extraordinary events have raised the question of whether any changes in the magnitude and frequency of river flows in the region can be detected. For this purpose, the annual maximum series of 39 river gauging stations in the study area are analysed. In particular, non-stationary models that include time, annual rainfall and annual temperature as predictors are investigated. Most records demonstrate a marked non-stationary behaviour and an increase of up to 75% in flood quantile estimates during the study period. Annual rainfall explains the largest proportion of variability in the peak flow series relative to other predictors considered in our study, providing practitioners with a useful framework for updating flood quantile estimates based on the dynamics of this highly accessible and informative climate indicator

A Graph-Based Optimization Framework for Large Water Distribution Networks

Water distribution networks (WDNs) have a crucial task: to reliably provide sufficient and high-quality water while optimizing financial resources. Achieving both reliability and resilience is vital. However, oversizing capacities can be costly and detrimental to water quality due to stagnation. Designing WDNs requires the consideration of these factors, resulting in a multi-objective optimization task typically addressed with evolutionary algorithms. Yet, for large WDNs with numerous decision variables, such algorithms become impractical. Complex network analysis offers an efficient approach, particularly with mathematical graphs representing WDNs. Recently, a graph-based multi-objective design approach using a customized measure (demand edge betweenness centrality) and a surrogate method for water quality assessment in large WDNs were developed. This paper combines these graph-based approaches into an optimization framework suitable for complex, real-world WDNs. The framework aims to minimize costs, maximize resilience, and exclude designs with poor water quality. It is demonstrated on a toy example, and its computational efficiency is shown by a real case study with 4000 decision variables, obtaining results in just 18.5 s compared to weeks of computation time with a state-of-the-art evolutionary algorithm

Impact of hybridwater supply on the centralised water system

Traditional (technical) concepts to ensure a reliable water supply, a safe handling of wastewater and flood protection are increasingly criticised as outdated and unsustainable. These so-called centralised urban water systems are further maladapted to upcoming challenges because of their long lifespan in combination with their short-sighted planning and design. A combination of (existing) centralised and decentralised infrastructure is expected to be more reliable and sustainable. However, the impact of increasing implementation of decentralised technologies on the local technical performance in sewer or water supply networks and the interaction with the urban form has rarely been addressed in the literature. In this work, an approach which couples the UrbanBEATS model for the planning of decentralised strategies together with a water supply modelling approach is developed and applied to a demonstration case. With this novel approach, critical but also favourable areas for such implementations can be identified. For example, low density areas, which have high potential for rainwater harvesting, can result in local water quality problems in the supply network when further reducing usually low pipe velocities in these areas. On the contrary, in high demand areas (e.g., high density urban forms) there is less effect of rainwater harvesting due to the limited available space. In these high density areas, water efficiency measures result in the highest savings in water volume, but do not cause significant problems in the technical performance of the potable water supply network. For a more generalised and case-independent conclusion, further analyses are performed for semi-virtual benchmark networks to answer the question of an appropriate representation of the water distribution system in a computational model for such an analysis. Inappropriate hydraulic model assumptions and characteristics were identified for the stated problem, which have more impact on the assessments than the decentralised measures

Rethinking the Framework of Smart Water System: A Review

Throughout the past years, governments, industries, and researchers have shown increasing interest in incorporating smart techniques, including sensor monitoring, real-time data transmitting, and real-time controlling into water systems. However, the design and construction of such a smart water system are still not quite standardized for massive applications due to the lack of consensus on the framework. The major challenge impeding wide application of the smart water network is the unavailability of a systematic framework to guide real-world design and deployment. To address this challenge, this review study aims to facilitate more extensive adoption of the smart water system, to increase effectiveness and efficiency in real-world water system contexts. A total of 32 literature pieces including 1 international forum, 17 peer-reviewed papers, 10 reports, and 4 presentations that are directly related to frameworks of smart water system have been reviewed. A new and comprehensive smart water framework, including definition and architecture, was proposed in this review paper. Two conceptual metrics (smartness and cyber wellness) were defined to evaluate the performance of smart water systems. Additionally, three pieces of future research suggestions were discussed, calling for broader collaboration in the community of researchers, engineers, and industrial and governmental sectors to promote smart water system applications

Automatic generation of water distribution systems based on GIS data

AbstractIn the field of water distribution system (WDS) analysis, case study research is needed for testing or benchmarking optimisation strategies and newly developed software. However, data availability for the investigation of real cases is limited due to time and cost needed for data collection and model setup. We present a new algorithm that addresses this problem by generating WDSs from GIS using population density, housing density and elevation as input data. We show that the resulting WDSs are comparable to actual systems in terms of network properties and hydraulic performance. For example, comparing the pressure heads for an actual and a generated WDS results in pressure head differences of ±4 m or less for 75% of the supply area. Although elements like valves and pumps are not included, the new methodology can provide water distribution systems of varying levels of complexity (e.g., network layouts, connectivity, etc.) to allow testing design/optimisation algorithms on a large number of networks. The new approach can be used to estimate the construction costs of planned WDSs aimed at addressing population growth or at comparisons of different expansion strategies in growth corridors

Morphogenesis of Urban Water Distribution Networks: A Spatiotemporal Planning Approach for Cost-Efficient and Reliable Supply

Cities and their infrastructure networks are always in motion and permanently changing in structure and function. This paper presents a methodology for automatically creating future water distribution networks (WDNs) that are stressed step-by-step by disconnection and connection of WDN parts. The associated effects of demand shifting and flow rearrangements are simulated and assessed with hydraulic performances. With the methodology, it is possible to test various planning and adaptation options of the future WDN, where the unknown (future) network is approximated via the co-located and known (future) road network, and hence different topological characteristics (branched vs. strongly looped layout) can be investigated. The reliability of the planning options is evaluated with the flow entropy, a measure based on Shannon’s informational entropy. Uncertainties regarding future water consumption and water loss management are included in a scenario analysis. To avoid insufficient water supply to customers during the transition process from an initial to a final WDN state, an adaptation concept is proposed where critical WDN components are replaced over time. Finally, the method is applied to the drastic urban transition of Kiruna, Sweden. Results show that without adaptation measures severe performance drops will occur after the WDN state 2023, mainly caused by the disconnection of WDN parts. However, with low adaptation efforts that consider 2–3% pipe replacement, sufficient pressure performances are achieved. Furthermore, by using an entropy-cost comparison, the best planning options are determined

Optimisation of Small Hydropower Units in Water Distribution Systems by Demand Forecasting

The potential of water supply systems for renewable electrical energy production is frequently utilised by a small-scale hydropower unit (SHPU) that utilises the surplus water or pressure. However, fluctuating demand on an hourly and daily basis represents a significant challenge in operating such devices. To address this issue, a control strategy based on demand forecast is implemented, adjusting the SHPU’s inflow based on current demand conditions. Thus, individual days are categorised into control categories with similar flow conditions, and control is optimised for each category using a simplified evolutionary optimisation technique. Coupled with demand forecasts, the SHPU controller evaluates on a daily basis which set of water levels to utilise for the next day to optimise energy production. This approach is implemented in an alpine municipality, and its economic feasibility is evaluated through a long-term simulation over 10 years. This approach resulted in an annual profit increase compared to the reference status based on well-informed expert knowledge. However, it is worth noting that the approach has limited suitability for further improvements within the case study. Nonetheless, SHPUs also contribute to improving water quality and, if the electrical energy generated is directly used to operate the water supply, enhance resilience to grid failures

Enabling Efficient and Sustainable Transitions of Water Distribution Systems under Network Structure Uncertainty

This paper focuses on the performance of water distribution systems (WDSs) during long-term city transitions. A transition describes the pathway from an initial to a final planning stage including the structural and functional changes on the infrastructure over time. A methodology is presented where consecutive WDSs under changing conditions are automatically created, simulated and then analyzed at specific points in time during a transition process of several decades. Consequential WDS analyses include (a) uncertain network structure, (b) temporal and spatial demand variation and (c) network displacement. With the proposed approach, it is possible to identify robust WDS structures and critical points in time for which sufficient hydraulic and water quality requirements cannot be ensured to the customers. The approach is applied to a case study, where a WDS transition of epic dimensions is currently taking place due to a city relocation. The resulting necessity of its WDS transition is modelled with automatically created planning options for consecutive years of the transition process. For the investigated case study, we tested a traditional “doing-all-at-the-end” approach, where necessary pipe upgrades are performed at the last stages of the transition process. Results show that the sole design of the desired final-stage WDS is insufficient. Owing to the drastic network deconstruction and the stepwise “loss of capacity”, critical pipes must be redesigned at earlier stages to maintain acceptable service levels for most of the investigated future scenarios

Ensemble Evaluation and Member Selection of Regional Climate Models for Impact Models Assessment

Climate change increasingly is affecting every aspect of human life on the earth. Many regional climate models (RCMs) have so far been developed to carefully assess this important phenomenon on specific regions. In this study, ten RCMs captured from the European Coordinated Downscaling Experiment (EURO CORDEX) platform are evaluated on the river Chiese catchment located in the northeast of Italy. The models’ ensembles are assessed in terms of the uncertainty and error calculated through different statistical and error indices. The uncertainties are investigated in terms of signal (increase, decrease, or neutral changes in the variables) and value uncertainties. Together with the spatial analysis of the data over the catchment, the weighted averaged values are used for the models’ evaluations and data projections. Using weighted catchment variables, climate change impacts are assessed on 10 different hydro-climatological variables showing the changes in the temperature, precipitation, rainfall events’ features, and the hydrological variables of the Chiese catchment between historical (1991–2000) and future (2071–2080) decades under RCP (Representative Concentration Path for increasing greenhouse gas emissions) scenario 4.5. The results show that, even though the multi-model ensemble mean (MMEM) could cover the outputs’ uncertainty of the models, it increases the error of the outputs. On the other hand, the RCM with the least error could cause high signal and value uncertainties for the results. Hence, different multi-model subsets of ensembles (MMEM-s) of 10 RCMs are obtained through a proposed algorithm for different impact models’ calculations and projections, making tradeoffs between two important shortcomings of model outputs, which are error and uncertainty. The single model (SM) and multi-model (MM) outputs imply that catchment warming is obvious in all cases and, therefore, evapotranspiration will be intensified in the future where there are about 1.28% and 6% value uncertainties for monthly temperature increase and the decadal relative balance of evapotranspiration, respectively. While rainfall events feature higher intensity and shorter duration in the SM, there are no significant differences for the mentioned features in the MM, showing high signal uncertainties in this regard. The unchanged catchment rainfall events’ depth can be observed in two SM and MM approaches, implying good signal certainty for the depth feature trend; there is still high uncertainty about the depth values. As a result of climate change, the percolation component change is negligible, with low signal and value uncertainties, while decadal evapotranspiration and discharge uncertainties show the same signal and value. While extreme events and their anomalous outcomes direct the uncertainties in rainfall events’ features’ values towards zero, they remain critical for yearly maximum catchment discharge in 2071–2080 as the highest value uncertainty is observed for this variable