Optimizing water resources allocation in the Haihe River basin under groundwater sustainability constraints
Martinsen, Grith1,2,3,4; Liu, Suxia1,3; Mo, Xingguo1,3; Bauer-Gottwein, Peter2,3,4
Corresponding AuthorLiu, Suxia(liusx@igsnrr.ac.cn)
AbstractThis study applies a hydroeconomic optimization method for water resources management in the highly water stressed Haihe River basin. A multi-objective, multi-temporal deterministic hydroeconomic optimization model has been built to quantify the economic trade-offs and reveal minimum cost strategies when reducing groundwater abstraction to sustainable levels. A complex basin representation, with approximate to 140,000 decision variables is formulated where each decision variable represents a flow-path from a water source to a sink. Available water sources are runoff generated by the sub-basins upstream the nine major surface water reservoirs, the inter-basin transfers from Yellow River and South to North Water Transfer Project (SNWTP) and the natural groundwater recharge to the three main groundwater aquifers. Water demands, i.e. sinks, are aggregated for each model sub-basin in categories of the major agricultural users, domestic, industrial and ecological water demands. Each demand is associated with a curtailment cost and groundwater abstraction with a pumping cost. Groundwater overdraft is constrained in each model scenario, ranging from unlimited overdraft in the plain area groundwater aquifer to sustainable abstractions over an 8-year period. Inflow upstream Yuqiao reservoir, and the inter-basin transfers from SNWTP and Yellow River are identified as the water resources with the highest increase in average shadow prices when limiting groundwater overdraft. An increase in inflow shadow prices of 37.5% indicates that these water sources will be most valuable if sustainable groundwater abstraction should be achieved. The shadow prices of water sources reveal when and where in the Haihe River basin users are curtailed if water resources are managed in the most optimal way. Average shadow prices of 1.6 yuan/m(3) for all surface water sources in the sustainable abstraction scenarios shows that overdraft can be avoided by curtailment of users with a willingness-to-pay 1.6 yuan/m(3). The shadow prices of the existing surface water reservoirs represented in the model shows that no costs can be saved from expanding their capacities. Finally, the cost of achieving sustainable groundwater abstraction with present water resource availability is found to be minimum 8.2 billion yuan/year.
KeywordHaihe River China hydroeconomic optimization linear programming groundwater sustainability spatio-temporal economic trade-offs decision support
Indexed BySCI
Funding ProjectNational Key Research and Development Program of China[2016YFC0401402] ; National Natural Science Foundation of China[41471026]
Funding OrganizationNational Key Research and Development Program of China ; National Natural Science Foundation of China
WOS Research AreaPhysical Geography
WOS SubjectGeography, Physical
WOS IDWOS:000471039300006
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Document Type期刊论文
Corresponding AuthorLiu, Suxia
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
2.Tech Univ Denmark, Dept Environm Engn, DK-2800 Lyngby, Denmark
3.Univ Chinese Acad Sci, Sino Danish Ctr Educ & Res, Coll Resources & Environm, Beijing 100049, Peoples R China
4.Sino Danish Ctr Educ & Res, DK-8000 Aarhus, Denmark
Recommended Citation
GB/T 7714
Martinsen, Grith,Liu, Suxia,Mo, Xingguo,et al. Optimizing water resources allocation in the Haihe River basin under groundwater sustainability constraints[J]. JOURNAL OF GEOGRAPHICAL SCIENCES,2019,29(6):935-958.
APA Martinsen, Grith,Liu, Suxia,Mo, Xingguo,&Bauer-Gottwein, Peter.(2019).Optimizing water resources allocation in the Haihe River basin under groundwater sustainability constraints.JOURNAL OF GEOGRAPHICAL SCIENCES,29(6),935-958.
MLA Martinsen, Grith,et al."Optimizing water resources allocation in the Haihe River basin under groundwater sustainability constraints".JOURNAL OF GEOGRAPHICAL SCIENCES 29.6(2019):935-958.
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