A scenario analysis-based optimal management of water resources supply and demand balance: A case study of Chengdu, China

Abstract

Water resources scarcity has threatened the coordinative development of demographics, society and economy. As a typical rapidly urbanizing area and an emerging megacity in China, Chengdu is confronting the pressure of inadequate water supply. The present study divides the macroeconomic factors that affect the water resource supply and demand balance into six major subsystems: water resources supply, water demand, water drainage, population, ecological environment and economy. The combining variable interaction description and predictive simulation models are applied to simulate the water supply and demand ratio (S:D) from 2005 to 2035. Further, this study designs different development scenarios to simulate the change of S:D ratios by altering the parameter values of driving factors. The results show that: (1) the S:D ratio will decline if the current development scenario continues, implying the serious water resources shortage and the severe water supply-demand conflict in Chengdu; (2) socio-economic water demand and wastewater/rainwater reuse are the key driving parameters of S:D ratio, especially the water consumption per ten thousand yuan of industrial value-added; (3) the S:D ratio will increase from 0.92 in the current baseline scenario to 1.06 in the integrated optimization scenario in 2025, and the long-term planning brings 2035 from 0.71 to 1.03, with the proportion of unconventional water supply rise to 38% and 61%, respectively. This study can provide a decision-making tool for policy-makers to explore plausible policy scenarios necessary for bridging the gap between the water supply and demand in megacities.

Statistical Assessment of High-Resolution Climate Model Rainfall Data in the Ciliwung Watershed, Indonesia

“…Rainfall is an essential variable in the water supply-demand calculations. Thus, it is crucial for water resource management (Sharafatmandrad and Mashizi, 2021;Yu et al, 2022) and disaster mitigation (Dhanesh et al, 2020;Nuryanto et al, 2020), especially to predict the occurrence of flood and drought events. The accuracy of water resource assessment is affected by the limited monitoring of rainfall at a finer spatial resolution, as it is mostly not measured except in a few stations.…”