AI Article Synopsis

  • The study aimed to improve the resilience of Nanchang's water supply by developing a flow simulation model analyzing groundwater conditions at the Youkou emergency source.
  • An optimization model utilizing genetic algorithms was integrated into the simulation to identify cost-effective groundwater extraction methods.
  • The results indicated a significant cost reduction in water supply schemes, with the best strategy considering multiple factors like water level depression and aquifer recovery to ensure efficient use of groundwater resources.

Article Abstract

To enhance the resilience of Nanchang's water supply system and ensure a dependable emergency water supply. Taking youkou emergency groundwater source field as an example, a flow simulation model was developed through an analysis of the hydrogeological conditions in the study area. Additionally, an optimization model based on the genetic algorithm (GA) technique was constructed and integrated into the flow simulation model. Subsequently, various water supply schemes were simulated with the minimum cost of groundwater extraction as the objective function. The results show that the values of the objective function were reduced by 4.92%, 15.67%, and 42.35% for the three different optimization schemes, namely pumping rates, joint pumping rates and the number of wells, and joint pumping rates, number of wells and well location. Ultimately, the optimal emergency water supply scheme was determined by considering a comprehensive range of factors. These factors encompassed considerations such as the area of the water level depression funnel, the dewatering thickness of the aquifer and the recovery of the groundwater level. The practice shows that the simulation-optimization model could effectively simulate complex groundwater flow systems, meeting the objective function and constraints toachieve the optimal exploitation scheme.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10830488PMC
http://dx.doi.org/10.1038/s41598-024-52303-0DOI Listing

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