Abstract
Resilient 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.
Highlights
Build resilience in infrastructure systems is an emerging need for the aim of sustainable development
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
The resilience is defined as the degree to which the system minimizes level of service failure magnitude and duration, and maximizes the time to level of service failure, over its design life when subject to exceptional conditions
Summary
Build resilience in infrastructure systems is an emerging need for the aim of sustainable development. How to design a resilient infrastructure system is still an open question. The resilience is defined as the degree to which the system minimizes level of service failure magnitude and duration, and maximizes the time to level of service failure, over its design life when subject to exceptional conditions (reproduced based on [1]). The worst case would be that the designed system directly fails to serve as expected after implementation in practice. This may happen if the design scenarios considered have non-marginal differences from the real conditions, and make the real conditions unexpected. To quantify the impacts resulting from the differences
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