In accordance with the rapid proliferation of machine learning (ML) and data management, ML applications have evolved to encompass all engineering disciplines. Owing to the importance of the world’s water supply throughout the rest of this century, much research has been concentrated on the application of ML strategies to integrated water resources management (WRM). Thus, a thorough and well-organized review of that research is required. To accommodate the underlying knowledge and interests of both artificial intelligence (AI) and the unresolved issues of ML in WRM, this overview divides the core fundamentals, major applications, and ongoing issues into two sections. First, the basic applications of ML are categorized into three main groups, prediction, clustering, and reinforcement learning. Moreover, the literature is organized in each field according to new perspectives, and research patterns are indicated so attention can be directed toward where the field is headed. In the second part, the less investigated field of WRM is addressed to provide grounds for future studies. The widespread applications of ML tools are projected to accelerate the formation of sustainable WRM plans over the next decade.

In last three decades, the reliability of water distribution systems (WDSs) has become a major concern, not only for water utilities and academic research communities, but also for society as a whole. Notable research has been conducted on the reliability/availability of WDSs, however, little attention has been paid to quantify the impact of adaptive operations as a response to system failure to enhance the resiliency of WDSs. Here, resilience is defined in the general sense as the ability to recover from a failure to a satisfactory state. In practice, if a system fails to supply water with adequate pressure, the water utility would take action to respond. Adaptive actions include switching on additional pumps as a short-term remedy or maintaining a higher water level in storage tanks as a long-term strategy to satisfy system pressure when a system experiences abnormal conditions. Here, a Monte Carlo simulation based framework for the resilience analysis of WDSs is implemented, considering the imp...

A water distribution network (WDN) is an indispensable element of civil infrastructure that provides fresh water for domestic use, industrial development, and fire-fighting. However, in a large and complex network, operation and management (O&M) can be challenging. As a technical initiative to improve O&M efficiency, the paradigm of “divide and conquer” can divide an original WDN into multiple subnetworks. Each subnetwork is controlled by boundary pipes installed with gate valves or flow meters that control the water volume entering and leaving what are known as district metered areas (DMAs). Many approaches to creating DMAs are formulated as two-phase procedures, clustering and sectorizing, and are called water network partitioning (WNP) in general. To assess the benefits and drawbacks of DMAs in a WDN, we provide a comprehensive review of various state-of-the-art approaches, which can be broadly classified as: (1) Clustering algorithms, which focus on defining the optimal configuration of DMAs; and (2) sectorization procedures, which physically decompose the network by selecting pipes for installing flow meters or gate valves. We also provide an overview of emerging problems that need to be studied.

Water, energy, and food (WEF) have complex interconnections. Water is required to produce energy, while energy is needed for water extraction, treatment, and distribution. The food sector requires water and energy to produce food products, while fertilizer and pesticide from farmland have a negative impact on water quality; however, biomass is a potential alternative energy source. Understanding these interconnections will help determine the developmental framework that connects all of the elements. Some global regions have implemented a variety of sustainable management concepts to manage the natural resources, however, mainly for an individual resource. Furthermore, various computer models have been developed to estimate the interdependency of each resource and to quantify future requirements of WEF; the limitations of current models have opened opportunities for development through the addition of components and features such as feedback analysis, optimization, and visualization. We reviewed the literature to determine the present state of the WEF nexus, especially its global implementation and simulation model. We concluded that the involvement of stakeholders, integration of policies, and development of a nexus simulation model are required for successful implementation of the WEF nexus, which is an emerging issue for a sustainable resources' management.

Uncertainties facing water planners and designers include changes in demand resulting from community growth (temporal and spatial), per capita water use, public perceptions, and regulations. One of the most powerful and intuitive ways to represent these uncertainties in the planning stage is to use scenarios. A scenario represents a realization of the system’s random parameters. Scenario-based analysis provides organizational flexibility by planning for multiple potential future scenarios, each of which may be, although is not necessarily, associated with a probability of occurrence. In this study, a scenario-based multiobjective optimization model for robust optimal design of regional-scale water and wastewater infrastructure is presented. The proposed methodology is demonstrated with an application to the planning of a decentralized water supply and reuse system for a new development area in metropolitan Tucson, where sustainable water supply is a significant issue.

Long-range infrastructure planning is fraught with uncertainties. Population growth may occur faster or slower than expected, regulations may change, and public sentiment can shift. In the face of these uncertainties, water system managers must plan for large infrastructure investments and the questions about when it is desirable to invest in infrastructure and what is the appropriate infrastructure component size to meet growing demands. One of the most powerful and intuitive ways to incorporate uncertainties is to use scenarios that represent plausible futures. Scenario-based planning is gaining acceptance in the water resources community. Preparing for a range of possible futures provides flexibility and adds robustness to the system so it can respond to uncertain events at reasonable costs while maintaining community confidence in their utilities. In this paper, novel scenario-based planning and optimization approaches are presented for the optimal design of regional-scale water supply infrast...