Multi-scenario analysis of green water resource efficiency under carbon emission constraints in the Chengdu-Chongqing urban agglomeration, China: A system dynamics approach

• Dynamic evolution of green water resource efficiency (GWRE) under carbon constraints. • System dynamics model reveals feedback loops impacting GWRE. • Multi-scenario simulations assess GWRE under different development paths. • Policy recommendations for sustainable development in urban agglomerations. Rapid urbanization and industrialization have exerted significant pressure on water resources, presenting dual challenges of low water resource efficiency and high carbon emissions. This study examines the dynamic evolution of green water resource efficiency (GWRE) under carbon emission constraints in Chengdu-Chongqing urban agglomeration (CCUA) from 2005 to 2021 by Super SBM-DEA algorithm. We analyze its dynamic trends using kernel density estimation and standard deviation ellipse methods. Based on the theory of sustainable water resources management, this study then constructs a system dynamics (SD) model that divides GWRE into four subsystems: socio-economic, technological innovation, ecological environment, and water resources. This model is used to explore complex mechanisms and feedback loops influencing GWRE. Five scenarios are then set up: baseline development, economic priority, green innovation, water-saving and emission reduction, and comprehensive development. These scenarios are used to simulate and predict different development paths and evaluate the impact of various key indicators on GWRE. The study finds that: (1) GWRE in the CCUA from 2005 to 2021 has shown a fluctuating upward trend, with the kernel density curve shifting from “short and wide” to “tall and narrow” and the peak moving to the right, indicating a gradual narrowing of GWRE disparities. (2) Model run tests and historical tests on the GWRE system demonstrate that the relative errors between the model’s predictions and actual outcomes are within 5%, confirming the model’s stability and effectiveness. (3) The green innovation and comprehensive development scenarios yield the best outcomes in terms of GWRE and carbon emission control from 2022 to 2035, reflecting the coordinated development of the economy, environment, and society. Finally, this study provides policy implications to enhance technological innovation, optimize industrial structures, and strengthen water ecosystem protection, offering theoretical and policy insights for sustainable development in the CCUA and similar regions.

Authors

Institutions

Publication Details

Journal
Ecological Indicators
Published
2025-01-27
DOI
https://doi.org/10.1016/j.ecolind.2025.113139
Citations
13
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
14.89

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-scenario analysis of green water resource efficiency under carbon emission constraints in the Chengdu-Chongqing urban agglomeration, China: A system dynamics approach

Zhigang Li, Keyao Yu
13 citations
Ecological Indicators
Water resources management and optimization
14.89
article

Multi-scenario analysis of green water resource efficiency under carbon emission constraints in the Chengdu-Chongqing urban agglomeration, China: A system dynamics approach

Zhigang Li, Keyao Yu
article en
13 citations

Abstract

• Dynamic evolution of green water resource efficiency (GWRE) under carbon constraints. • System dynamics model reveals feedback loops impacting GWRE. • Multi-scenario simulations assess GWRE under different development paths. • Policy recommendations for sustainable development in urban agglomerations. Rapid urbanization and industrialization have exerted significant pressure on water resources, presenting dual challenges of low water resource efficiency and high carbon emissions. This study examines the dynamic evolution of green water resource efficiency (GWRE) under carbon emission constraints in Chengdu-Chongqing urban agglomeration (CCUA) from 2005 to 2021 by Super SBM-DEA algorithm. We analyze its dynamic trends using kernel density estimation and standard deviation ellipse methods. Based on the theory of sustainable water resources management, this study then constructs a system dynamics (SD) model that divides GWRE into four subsystems: socio-economic, technological innovation, ecological environment, and water resources. This model is used to explore complex mechanisms and feedback loops influencing GWRE. Five scenarios are then set up: baseline development, economic priority, green innovation, water-saving and emission reduction, and comprehensive development. These scenarios are used to simulate and predict different development paths and evaluate the impact of various key indicators on GWRE. The study finds that: (1) GWRE in the CCUA from 2005 to 2021 has shown a fluctuating upward trend, with the kernel density curve shifting from “short and wide” to “tall and narrow” and the peak moving to the right, indicating a gradual narrowing of GWRE disparities. (2) Model run tests and historical tests on the GWRE system demonstrate that the relative errors between the model’s predictions and actual outcomes are within 5%, confirming the model’s stability and effectiveness. (3) The green innovation and comprehensive development scenarios yield the best outcomes in terms of GWRE and carbon emission control from 2022 to 2035, reflecting the coordinated development of the economy, environment, and society. Finally, this study provides policy implications to enhance technological innovation, optimize industrial structures, and strengthen water ecosystem protection, offering theoretical and policy insights for sustainable development in the CCUA and similar regions.

Ecological IndicatorsVol. 171
Chengdu University of Technology (CN), Yangtze River Pharmaceutical Group (China) (CN)
Chengdu University of Technology
Openalex Percentile: Top 1%
Water resources management and optimization
14.89
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.