A Water Evaluation and Planning-based framework for the long-term prediction of urban water demand and supply

Abstract

Increased usage and non-efficient management of limited resources has created the risk of water resource scarcity. Due to climate change, urbanization, and lack of effective water resource management, countries like Pakistan are facing difficulties coping with the increasing water demand. Rapid urbanization and non-resilient infrastructures are the key barriers in sustainable urban water resource management. Therefore, there is an urgent need to address the challenges of urban water management through effective means. We propose a workflow for the modeling and simulation of sustainable urban water resource management and develop an integrated framework for the evaluation and planning of water resources in a typical urban setting. The proposed framework uses the Water Evaluation and Planning system to evaluate current and future water demand and the supply gap. Our simulation scenarios demonstrate that the demand–supply gap can effectively be dealt with by dynamic resource allocation, in the presence of assumptions, for example, those related to population and demand variation with the change of weather, and thus work as a tool for informed decisions for supply management. In the first scenario, 23% yearly water demand is reduced, while in the second scenario, no unmet demand is observed due to the 21% increase in supply delivered. Similarly, the overall demand is fulfilled through 23% decrease in water demand using water conservation. Demand-side management not only reduces the water usage in demand sites but also helps to save money, and preserve the environment. Our framework coupled with a visualization dashboard deployed in the water resource management department of a metropolitan area can assist in water planning and effective governance.

The application of applied category theory to quantify mission success

“…Key to the approach was maintaining relationships between the models, simulations, and metadata to facilitate reuse. Using a MSAL type scheme, Saleem et al 31 built a graph-based framework to model an urban water supply that addresses many ME limitations previously stated. The graphical model has nested supply and demand entities consisting of a macro-layer, the water supply and neighborhood, a meso layer of the water works, buildings and housing, and a micro-layer of occupants, and water resources.…”

Stakeholders’ Interaction in Water Management System: Insights from a MACTOR Analysis in the R’Dom Sub-basin, Morocco

“…In line with the IWRM approach, the sharing of water data and information among actors, as well as stakeholder participation, represent essential supporting elements for water resources management policy planning and implementation (El Mezouary et al 2020a;Godinez-Madrigal et al 2019;Jarar Oulidi 2019). Several water managers and experts have developed and used various models and analysis tools to support the implementation of water management policies (Cosgrove and Loucks 2015;Elhassnaoui et al 2021;Hermans 2005;Hermans and Thissen 2009;Saleem et al 2021). However, experience has shown a gap between the work of stakeholders and the real use of proposed solutions by water experts, despite their use of new and advanced technologies (Hermans 2005;Pellegrini et al 2019).…”

Water Supply-Demand Situation Analysis Based on a Hierarchical Index System

“…Note that the prediction of water supply is often based on the available water supply for the basin or region of interest under the constraints of water diversion projects (Lv et al 2016;McDonald et al 2014); while that of water demand is mainly based on the quotas that are o cially released such as social and economic development indices, standards and speci cations. Because of this, there are several issues that need to be addressed: (1) the general neglect of ecological issues may lead to less or even no availability of water to be supplied for ecological purposes in the prediction of water supply (Paul and Elango, 2018); (2) the prediction of water demand based on various social and economic indices is highly subjective in nature that is mostly determined by basin or regional planning rather than by actual situation (Saleem et al 2021); (3) the use of water quotas from current standards or speci cations does not take into account the improvement of water-use e ciency in the future (Ray and Shaw, 2016); (4) the prediction of water demand is often complicated considering the complex classi cation of water users, quality and quantity of data required, and choice of appropriate analysis method (Qin et al 2018); (5) the use of a single index like water shortage or water shortage ratio makes it di cult to answer some questions that are more interesting to the authorities, such as the main causes of water shortage, satisfaction degree of rigid water demand, and exploration degree of water supply potential (Distefano and Kelly, 2017;Höllermann et al 2010). In short, it remains di cult to match the scale, layout, structure and speed of social and economic development and water-use e ciency to the availability of water resources, and as a consequence the water demand that is closely associated with population, industrial layout, land and other resources in a given region is very likely to exceed or fall short of the supply capacity of water sources.…”