This study proposes a novel optimization framework to reduce the environmental footprint of water conveyance in water distribution systems (WDSs). The research introduces the Nonlinear Chaotic Honey Badger Algorithm (NCHBA), a robust optimization method that enhances exploration and convergence speed using chaotic maps and a nonlinear control parameter. The algorithm outperforms existing methods in solution accuracy and convergence speed, achieving a 27% reduction in energy consumption when applied to a water network with variable-speed pumps. A multi-objective variant, MONCHBA, is developed to optimize pump scheduling in large-scale WDSs, balancing energy consumption, pressure levels, and water quality risk. Results show that variable-speed pumps improve energy efficiency and WDS reliability compared to single-speed pumps. The study evaluates the performance of NCHBA and MONCHBA on benchmark functions and real-world WDSs, demonstrating their effectiveness in achieving optimal Pareto fronts. The proposed algorithms are applied to the C-Town WDS, a large-scale network with 399 nodes and 443 pipes, to optimize pump scheduling under two scenarios: variable-speed and fixed-speed pumps. The results highlight the benefits of variable-speed pumps in reducing energy costs, maintenance expenses, and water quality risks. The study concludes that NCHBA and MONCHBA provide a robust and efficient solution for optimizing WDS operations, contributing to sustainable water management and reduced carbon footprints.This study proposes a novel optimization framework to reduce the environmental footprint of water conveyance in water distribution systems (WDSs). The research introduces the Nonlinear Chaotic Honey Badger Algorithm (NCHBA), a robust optimization method that enhances exploration and convergence speed using chaotic maps and a nonlinear control parameter. The algorithm outperforms existing methods in solution accuracy and convergence speed, achieving a 27% reduction in energy consumption when applied to a water network with variable-speed pumps. A multi-objective variant, MONCHBA, is developed to optimize pump scheduling in large-scale WDSs, balancing energy consumption, pressure levels, and water quality risk. Results show that variable-speed pumps improve energy efficiency and WDS reliability compared to single-speed pumps. The study evaluates the performance of NCHBA and MONCHBA on benchmark functions and real-world WDSs, demonstrating their effectiveness in achieving optimal Pareto fronts. The proposed algorithms are applied to the C-Town WDS, a large-scale network with 399 nodes and 443 pipes, to optimize pump scheduling under two scenarios: variable-speed and fixed-speed pumps. The results highlight the benefits of variable-speed pumps in reducing energy costs, maintenance expenses, and water quality risks. The study concludes that NCHBA and MONCHBA provide a robust and efficient solution for optimizing WDS operations, contributing to sustainable water management and reduced carbon footprints.