Articles | Volume 25, issue 2
https://doi.org/10.5194/hess-25-901-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-25-901-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A novel causal structure-based framework for comparing a basin-wide water–energy–food–ecology nexus applied to the data-limited Amu Darya and Syr Darya river basins
Haiyang Shi
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
University of Chinese Academy of Sciences, 19 (A) Yuquan Road,
Beijing, 100049, China
Department of Geography, Ghent University, Ghent 9000, Belgium
Sino-Belgian Joint Laboratory of Geo-Information, Ghent, Belgium
Geping Luo
CORRESPONDING AUTHOR
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
University of Chinese Academy of Sciences, 19 (A) Yuquan Road,
Beijing, 100049, China
Research Centre for Ecology and Environment of Central Asia,
Chinese Academy of Sciences, Urumqi, China
Sino-Belgian Joint Laboratory of Geo-Information, Ghent, Belgium
Hongwei Zheng
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
Chunbo Chen
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
Olaf Hellwich
Department of Computer Vision & Remote Sensing, Technische
Universität Berlin, 10587 Berlin, Germany
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
Tie Liu
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
Sino-Belgian Joint Laboratory of Geo-Information, Ghent, Belgium
Shuang Liu
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
Jie Xue
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
Peng Cai
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
Department of Geography, Ghent University, Ghent 9000, Belgium
Huili He
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
Department of Geography, Ghent University, Ghent 9000, Belgium
Friday Uchenna Ochege
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
University of Chinese Academy of Sciences, 19 (A) Yuquan Road,
Beijing, 100049, China
Tim Voorde
Department of Geography, Ghent University, Ghent 9000, Belgium
Sino-Belgian Joint Laboratory of Geo-Information, Ghent, Belgium
Philippe Maeyer
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang, 830011, China
University of Chinese Academy of Sciences, 19 (A) Yuquan Road,
Beijing, 100049, China
Department of Geography, Ghent University, Ghent 9000, Belgium
Sino-Belgian Joint Laboratory of Geo-Information, Ghent, Belgium
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Cited
5 citations as recorded by crossref.
- The effect of farmland on the surface water of the Aral Sea Region using Multi-source Satellite Data J. Shi et al. 10.7717/peerj.12920
- Numerical study on the climatic effect of the Aral Sea H. He et al. 10.1016/j.atmosres.2021.105977
- Using Synthetic Remote Sensing Indicators to Monitor the Land Degradation in a Salinized Area T. Yu et al. 10.3390/rs13152851
- Analysis of the Impacts of Environmental Factors on Rat Hole Density in the Northern Slope of the Tienshan Mountains with Satellite Remote Sensing Data H. Shi et al. 10.3390/rs13224709
- Comprehensive evaluation and sustainable development of water–energy–food–ecology systems in Central Asia J. Qin et al. 10.1016/j.rser.2021.112061
5 citations as recorded by crossref.
- The effect of farmland on the surface water of the Aral Sea Region using Multi-source Satellite Data J. Shi et al. 10.7717/peerj.12920
- Numerical study on the climatic effect of the Aral Sea H. He et al. 10.1016/j.atmosres.2021.105977
- Using Synthetic Remote Sensing Indicators to Monitor the Land Degradation in a Salinized Area T. Yu et al. 10.3390/rs13152851
- Analysis of the Impacts of Environmental Factors on Rat Hole Density in the Northern Slope of the Tienshan Mountains with Satellite Remote Sensing Data H. Shi et al. 10.3390/rs13224709
- Comprehensive evaluation and sustainable development of water–energy–food–ecology systems in Central Asia J. Qin et al. 10.1016/j.rser.2021.112061
Latest update: 25 Mar 2023
Short summary
Some river basins are considered to be very similar because they have a similar background such as a transboundary, facing threats of human activities. But we still lack understanding of differences under their general similarities. Therefore, we proposed a framework based on a Bayesian network to group watersheds based on similarity levels and compare the causal and systematic differences within the group. We applied it to the Amu and Syr Darya River basin and discussed its universality.
Some river basins are considered to be very similar because they have a similar background such...
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