Journal of Water Resources Planning and Management

A cyclic storage (CS) system is an extension to standard conjunctive use (SCU) of surface water (SW) and groundwater (GW) in which the SW bodies and GW aquifer(s) are treated as physically interconnected and operationally joint parallel storage facilities. Rule-based exchange of regulated water between surface reservoir(s) and GW aquifer(s) is the key element of a CS system that differentiates it from the SCU of SW and GW as usually practiced. This paper presents a novel multiobjective optimization model to develop a tradeoff between the sustainability index of water allocation to irrigated agriculture and energy required for GW pumping. The sustainability index, as defined in this paper, addresses reliability, vulnerability, and resilience. A solution to the large-scale multiperiod, multiobjective, mixed-integer nonlinear model was obtained using the $\epsilon$-constraint method. The model maximizes the sustainability index while keeping the pumping energy at its minimum. Results show that CS operation strategy considerably improves the sustainability index compared to the SCU strategy. It is also shown how, for a given sustainability index, the required energy for pumping GW would decrease. Results may help decision-makers identify optimal policies and assess different policies under CS and SCU strategies. Agricultural-sector and system operators must become familiar with the predominance of CS over SCU for its real-world application.

Although good water governance (GWG) is a widely accepted concept, mistaking its principles for silver bullet approaches has hindered its successful applications. This highlights the idea that one-size-fits-all thinking does not satisfy the need to navigate toward sustainable outcomes in ever-changing complex water systems. This also indicates that endeavors toward governing water systems must be tailored to the specific context that these systems are nested within. Scholars have pointed out the importance of residents’ input in contextualizing water governance practices. With that being said, this paper proposes an innovative approach to tailoring principles of GWG to the context by building an analytical framework upon which survey research was conducted. The survey, it took input from three categories of residents, namely experts, authorities, and experienced locals. Analyzing the data led to a group decision-making problem that was approached using fuzzy risk-based multiple-attribute decision-making methods, including technique for order of preference by similarity to ideal solution and ordered weighted averaging, while considering the amount of consensus among mentioned groups. Furthermore, to validate the results of the decision-making problem analysis, additional interviews were conducted to get a more pragmatic picture of the situation. Sistan Delta in Iran was selected as a case study mainly due to the current undesirable situation and also the international social, political, and environmental significance of the area. This study aims to take the first step of rethinking water governance in the area. The results indicated that to operationalize good governance, the principles of collaboration, legitimacy, adaptability, and trust and engagement must be prior considerations to redefine the water governance structure in the Sistan region.

The effects of drinking water system infrastructure on water quality and health following intrusion events have not been extensively studied. This study proposes a coupling of hydraulic and water-quality modeling with quantitative microbial risk assessment (QMRA) to characterize microbial infection risks. Two networks were considered based on their network configuration. We assumed a continuous intrusion of enterovirus under three scenarios. The location of vulnerable and influential nodes in a looped and a branched network were compared, followed by a comparison of chlorine booster placement to reduce infection risks. The most vulnerable nodes in the branched network were generally downstream of the intrusion site, whereas those for the looped network were in the middle of the network due to tank dynamics. Influential injection nodes for the looped network were also in the middle of the network but mostly located at the upstream nodes for the branched network. A single chlorine booster yielded a risk reduction (47.6%) for the branched network, greater than for the looped network (nearly none). Two chlorine boosters reduced the looped network risks more notably (63%). The generalizability of these results to other networks likely depends upon specific network hydraulics and variability in municipal drinking water use. This work will help public water system managers in identifying vulnerable points in their distribution system and optimal locations for risk reduction strategy implementation.

The leakage control in water distribution networks (WDNs) is of high concern in the water supply industry. One direct and effective way to reduce leakage is to adopt leakage detection and localization methods to guide water utilities to repair broken pipes in time. In order to achieve higher accuracy in the leakage detection process in WDN with multiple leaks, a novel multiple leak detection and localization framework (MLDLF) based on existing pressure and flow measurements is proposed. The MLDLF decomposed the problem into three substages: model calibration, leakage identification, and leakage localization. After using the calibrated hydraulic model to predict pressure values and estimate overall leakage flow in each area in the first stage, the data-driven methods, STLK, including the seasonal and trend decomposition using loess (STL decomposition) and the $k$-means clustering method, were performed in the identification stage to distinguish different leakage scenarios so as to determine the occurrence time of every leakage event. Finally, combined with the stepwise model–based fault diagnosis method, leakages were located gradually with high computational efficiency. A case study of applying MLDLF to the WDN of L-Town showed that 56.52% of the leakage events were successfully identified and located with the economic score reaching €264,873, indicating the robustness and good applicability of MLDLF in identifying and localizing all types of leaks under multiple leakage scenarios.