A quantitative analysis method for the degree of coupling coordination between drinking water carrying capacity and population spatial aggregation-Reference-Cited by-同舟云学术

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A quantitative analysis method for the degree of coupling coordination between drinking water carrying capacity and population spatial aggregation

Published:2022-05-23 Issue:9 Volume:24 Page:11392-11423
ISSN:1387-585X
Container-title:Environment, Development and Sustainability
language:en
Short-container-title:Environ Dev Sustain

Author:

Lei Yuan,Guoping Chen,Jiasheng Wang,Junsan Zhao,Kun Yang

Funder

National Natural Science Foundation of China

Science Research Foundation of Yunnan Education Bureau

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Economics and Econometrics,Geography, Planning and Development

Link

https://link.springer.com/content/pdf/10.1007/s10668-022-02229-2.pdf

Reference47 articles.

1. Adeba, D., Kansal, M. L., & Sen, S. (2015). Assessment of water scarcity and its impacts on sustainable development in Awash basin, Ethiopia. Sustainable Water Resources Management, 1(1), 71–87. https://doi.org/10.1007/s40899-015-0006-7

2. Anteneh, Y., Gebremariam, Z. G. (2019). Valuing the water supply: ecosystem-based potable water supply management for the Legedadie-Dire catchments, central Ethiopia. Ecological Processes, pp. 8−9. Doi: https://doi.org/10.1186/s13717-019-0160-1

3. Ashoori, N., Dzombak, D. A, Small, M. J. (2017). Identifying water price and population criteria for meeting future urban water demand targets. Journal of Hydrology, 555, 547–556. Doi: https://doi.org/10.1016/j.jhydrol.2017.10.047

4. Brelsford, C., Abbott, J. K. (2017). Growing into water conservation? Decomposing the drivers of reduced water consumption in Las Vegas, NV. Ecological Economics, 133:99–110. Doi: https://doi.org/10.1016/j.ecolecon.2016.10.012

5. Cheng, K., Fu, Q., Meng, J., et al. (2018). Analysis of the Spatial Variation and Identification of Factors Affecting the Water Resources Carrying Capacity Based on the Cloud Model. Water Resources Management, 32(8), 2767–2781. https://doi.org/10.1007/s11269-018-1957-x

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