Scenarios for urban water management futures: A systematic review

Shall we always use hydraulic models? A graph neural network metamodel for water system calibration and uncertainty assessment

Representing reality in a numerical model is complex. Conventionally, hydraulic models of water distribution networks are a tool for replicating water supply system behaviour through simulation by means of approximation of physical equations. A calibration process is mandatory to achieve plausible simulation results. However, calibration is affected by a set of intrinsic uncertainty sources, mainly related to the lack of system knowledge. This paper proposes a breakthrough approach for calibrating hydraulic models through a graph machine learning approach. The main idea is to create a graph neural network metamodel to estimate the network behaviour based on a limited number of monitoring sensors. Once the flows and pressures of the entire network have been estimated, a calibration is carried out to obtain the set of hydraulic parameters that best approximates the metamodel. Through this process, it is possible to estimate the uncertainty that is transferred from the few available measurements to the final hydraulic model. The paper sparks a discussion to assess under what circumstances a graph-based metamodel might be a solution for water network analysis.

Evaluation of Regional Water Resources Management Performance and Analysis of the Influencing Factors: A Case Study in China

Water resources management (WRM) is a global strategic issue. Effectively evaluating WRM performance and analyzing its influencing factors have strong practical significance for improving regional WRM performance. Data envelopment analysis (DEA) is one of the most popular models to measure the efficiency of decision-making units (DMUs). Taking regional WRM performance as efficiency DMUs, this paper proposes the indicator system to quantify WRM performance from the perspectives of resource endowments, economic and technological development, and ecosystem protection. The WRM performance of 31 provincial administrative regions in mainland China from 2013 to 2019 are measured, and the temporal and spatial changes are explored using the window DEA model and the Malmquist index model. Finally, the Tobit model is used to quantitatively analyze the affecting factors. The results indicate that: (1) in 2015 and 2019, WRM performance of Sichuan, Shaanxi, Xinjiang, Inner Mongolia, and Guangxi were slightly higher than that in other years, and the areas with more room for WRM performance improvements were areas with abundant water resources; (2) from 2013 to 2019, China’s overall WRM performance showed a slow rise, and there were obvious fluctuations in 2018; (3) the improvement in WRM performance was primarily the result of an improvement to comprehensive technical efficiency changes (EC), whereas technological progress changes (TC) have largely restricted China’s WRM performance; (4) the main influencing factors of WRM performance in China were as follows: industrial development level, water resources utilization rate, and urban sewage discharge per capita.