Multi-scenario modelling of urban spatial growth under water resources and aquatic ecological environmental constraints
Water is fundamental to human survival and urban development. Rapid global urbanization has created contradictions among urban space growth, water resources, and environmental constraints. Although existing studies have examined the role of environmental factors in urban expansion, current research...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25007332 |
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| Summary: | Water is fundamental to human survival and urban development. Rapid global urbanization has created contradictions among urban space growth, water resources, and environmental constraints. Although existing studies have examined the role of environmental factors in urban expansion, current research on urban spatial expansion still primarily focuses on the characteristics and drivers of land use change, with relatively less attention paid to how water resources and aquatic ecological environmental constraints influence on the pattern and sustainability of urban expansion. To address this gap, we developed a novel urban spatial growth model that synergistically considers water resources, the environment, population growth, economic development, and land use. System dynamics (SD), water ecologically sensitive area identification, and the conversion of land use and its effects at small region extent (CLUE-S) model was used to simulate urban spatial growth in multiple scenarios. The results show that (1) the SD and CLUE-S models can effectively and accurately reflect changes in urban land use, and the prediction error of the SD model was <10 %. A logistic model based on spatial autocorrelation can explain the driving factors of land use in the study area. Moreover, through comparison and verification with actual land cover data interpreted by remote sensing in 2015 and 2020, the kappa indices of the CLUE-S model simulation results were 0.9432 and 0.9848, respectively, meeting the accuracy requirements; (2) Under different development scenarios in SD, such as the Status Quo Continuation scenario (S1), Priority Urban Development scenario (S2), and Ecological Protection Priority scenario (S3), varying outcomes were projected for Changsha by 2030. In S1, the population is expected to reach 14.2827 million, with challenges to the water supply–demand balance. The S2 scenario indicated an increasing threat of water pollution, whereas S3 highlighted the importance of controlling population growth for water ecosystem restoration; (3) Simulation results for land use change in Changsha in 2030 reveal significant increases in construction land area under different scenarios, while areas of other land types decreased. Specifically, under Plan A, construction land was projected to increase by 35.7 % in S1, 68.83 % in S2, and 1.66 % in S3. Under Plan B, construction land was expected to increase by 36.63 % in S1, 67.99 % in S2, and 1.64 % in S3; (4) Based on scenario simulations, optimization strategies for urban space development were proposed to achieve a beneficial balance between urban construction and the water environment. This study offers a framework for simulating different urban development scenarios under water resource and environmental constraints and identifying the hotspots of urban land expansion, which can provide a scientific basis for urban water environment management objectives, demarcation of development space boundaries, and protection of water ecological space. The results are of great significance for promoting the sustainability of urban spatial development. |
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| ISSN: | 1470-160X |