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Coupling the water-energy-food-ecology nexus into a Bayesian network for water resources analysis and management in the Syr Darya River basin

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Abstract
The widespread uncertainty regarding future changes in climate, socioeconomic conditions, and population growth have increased interest in water-energy-food-ecology nexus-based frameworks in relation to the analysis of water resources. A challenge for modeling the water-energy-food-ecology nexus is how to reduce the multidimensional and codependent uncertainties and measure the complicated casual relationships effectively. We propose a methodological solution to the problem, and this solution is demonstrated in this case as an extension to the previous water resource optimization framework. We coupled the water-energy-food-ecology nexus into the Bayesian network, which provides a formal representation of the joint probabilistic behavior of the system, and the method was applied to water resource use analysis and management in the Syr Darya River basin, a transboundary and endorheic basin that has contributed to the Aral Sea ecological crisis as a result of unreasonable water use. The annual scale data of four periods, 1970-1980, 1980-1991, 1991-2005, and 2005-2015, were introduced into the Bayesian network. Before the disintegration of the Soviet Union, the amount of water inflow into the Aral Sea was sensitive to increases in irrigation for agricultural development, increases in water storage of the upstream reservoirs and stochastic runoff. After the disintegration of the Soviet Union, the amount of water inflow into the Aral Sea was sensitive to the inefficient irrigation water use in the downstream areas of Uzbekistan and Kazakhstan and the water storage of the reservoir located upstream of Kyrgyzstan. The change resulted from unresolvable disputes between water use for power generation in the upstream area and irrigation in the downstream area. Comprehensive scenario analysis shows that, in the short term, it would be useful to improve the proportion of food crops, improve the efficiency of water use in relation to salt leaching and irrigation, and prevent drought damage. In the long term, based on the increased use of advanced drip irrigation technology from 50% to 80%, the annual inflow into the Aral Sea will increase significantly, reaching 6.4 km(3) and 9.6 km(3), respectively, and this technology is capable of ameliorating the ecological crisis within the basin.
Keywords
BELIEF NETWORKS, ARAL SEA, DECISION-SUPPORT, RISK-ASSESSMENT, MODEL, TOOL, SUSTAINABILITY, UNCERTAINTY, CLIMATE, IMPACT, Bayesian network, Water-energy-food-ecology nexus, Syr Darya River, Aral, Sea

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MLA
Shi, Haiyang, et al. “Coupling the Water-Energy-Food-Ecology Nexus into a Bayesian Network for Water Resources Analysis and Management in the Syr Darya River Basin.” JOURNAL OF HYDROLOGY, vol. 581, 2020.
APA
Shi, H., Luo, G., Zheng, H., Chen, C., Bai, J., Liu, T., … De Maeyer, P. (2020). Coupling the water-energy-food-ecology nexus into a Bayesian network for water resources analysis and management in the Syr Darya River basin. JOURNAL OF HYDROLOGY, 581.
Chicago author-date
Shi, Haiyang, Geping Luo, Hongwei Zheng, Chunbo Chen, Jie Bai, Tie Liu, Friday Uchenna Ochege, and Philippe De Maeyer. 2020. “Coupling the Water-Energy-Food-Ecology Nexus into a Bayesian Network for Water Resources Analysis and Management in the Syr Darya River Basin.” JOURNAL OF HYDROLOGY 581.
Chicago author-date (all authors)
Shi, Haiyang, Geping Luo, Hongwei Zheng, Chunbo Chen, Jie Bai, Tie Liu, Friday Uchenna Ochege, and Philippe De Maeyer. 2020. “Coupling the Water-Energy-Food-Ecology Nexus into a Bayesian Network for Water Resources Analysis and Management in the Syr Darya River Basin.” JOURNAL OF HYDROLOGY 581.
Vancouver
1.
Shi H, Luo G, Zheng H, Chen C, Bai J, Liu T, et al. Coupling the water-energy-food-ecology nexus into a Bayesian network for water resources analysis and management in the Syr Darya River basin. JOURNAL OF HYDROLOGY. 2020;581.
IEEE
[1]
H. Shi et al., “Coupling the water-energy-food-ecology nexus into a Bayesian network for water resources analysis and management in the Syr Darya River basin,” JOURNAL OF HYDROLOGY, vol. 581, 2020.
@article{8655500,
  abstract     = {The widespread uncertainty regarding future changes in climate, socioeconomic conditions, and population growth have increased interest in water-energy-food-ecology nexus-based frameworks in relation to the analysis of water resources. A challenge for modeling the water-energy-food-ecology nexus is how to reduce the multidimensional and codependent uncertainties and measure the complicated casual relationships effectively. We propose a methodological solution to the problem, and this solution is demonstrated in this case as an extension to the previous water resource optimization framework. We coupled the water-energy-food-ecology nexus into the Bayesian network, which provides a formal representation of the joint probabilistic behavior of the system, and the method was applied to water resource use analysis and management in the Syr Darya River basin, a transboundary and endorheic basin that has contributed to the Aral Sea ecological crisis as a result of unreasonable water use. The annual scale data of four periods, 1970-1980, 1980-1991, 1991-2005, and 2005-2015, were introduced into the Bayesian network. Before the disintegration of the Soviet Union, the amount of water inflow into the Aral Sea was sensitive to increases in irrigation for agricultural development, increases in water storage of the upstream reservoirs and stochastic runoff. After the disintegration of the Soviet Union, the amount of water inflow into the Aral Sea was sensitive to the inefficient irrigation water use in the downstream areas of Uzbekistan and Kazakhstan and the water storage of the reservoir located upstream of Kyrgyzstan. The change resulted from unresolvable disputes between water use for power generation in the upstream area and irrigation in the downstream area. Comprehensive scenario analysis shows that, in the short term, it would be useful to improve the proportion of food crops, improve the efficiency of water use in relation to salt leaching and irrigation, and prevent drought damage. In the long term, based on the increased use of advanced drip irrigation technology from 50% to 80%, the annual inflow into the Aral Sea will increase significantly, reaching 6.4 km(3) and 9.6 km(3), respectively, and this technology is capable of ameliorating the ecological crisis within the basin.},
  articleno    = {124387},
  author       = {Shi, Haiyang and Luo, Geping and Zheng, Hongwei and Chen, Chunbo and Bai, Jie and Liu, Tie and Ochege, Friday Uchenna and De Maeyer, Philippe},
  issn         = {0022-1694},
  journal      = {JOURNAL OF HYDROLOGY},
  keywords     = {BELIEF NETWORKS,ARAL SEA,DECISION-SUPPORT,RISK-ASSESSMENT,MODEL,TOOL,SUSTAINABILITY,UNCERTAINTY,CLIMATE,IMPACT,Bayesian network,Water-energy-food-ecology nexus,Syr Darya River,Aral,Sea},
  language     = {eng},
  pages        = {14},
  title        = {Coupling the water-energy-food-ecology nexus into a Bayesian network for water resources analysis and management in the Syr Darya River basin},
  url          = {http://dx.doi.org/10.1016/j.jhydrol.2019.124387},
  volume       = {581},
  year         = {2020},
}

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