Determining the location of River Dam Group based on set cover Model: A case study of Zambezi River Basin


Determining the location of River Dam Group based on set cover Model: A case study of Zambezi River Basin


Tianlong Wang1*, Xiaorui Tao2, Dongkun Wu1, Haotian Feng2

1College of Civil Engineering & Architecture, China Three Gorges University, Yichang, 443002, China. 2College of Economics & Management, China Three Gorges University, Yichang, 443002, China


Taking the Zambezi River Basin as a typical case, this paper studied the location problem of dam group. Based on the topographical and elevation maps of the Zambezi River Basin, we evaluated each region by five indicators (Water head difference elevation, Geological environment, Climatic environment, Population distribution and Biodiversity), and selected the 22 candidate dam sites. Meanwhile, the relative feasibility index of dam construction is calculated by the entropy weight-grey correlation analysis. On this basis, combined with the water management capacity of the dam, a set coverage model of dam selection is established, and the neighborhood adaptive particle swarm optimization algorithm (NAPSO) is used to solve the 12 most suitable dam sites. Comparing with the water management capacity of the original Kariba Dam, the new dams’ water storage and flood control capacity, hydroelectric power generation capacity, domestic water supply capacity and other water supply capacity have been increased by 235.92%, 250.62%, 189.66% and 223.61% respectively. Our study can provide some guidance for the site selection project of river dam group.


Keywords: Dam site selection; Set coverage model; NAPSO; Entropy weight-grey correlation analysis


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How to cite this article:
Tianlong Wang, Xiaorui Tao, Dong-kun Wu, Haotian Feng. Determining the location of River Dam Group based on set cover Model: A case study of Zambezi River Basin. Scientific Research and Reviews, 2021; 14:122. DOI: 10.28933/srr-2021-03-1005


References:

1. Willis M, Pearson O, Illes Z, et al. An observational study of alemtuzumab following fingolimod for multiple sclerosis [J]. Neurol Neuroimmunol Neuroinflamm, 2017, 4 (2): e320.
2. Xing Meng, Jingqiu Zhang and Haiyong Zhu. Comparison of basic model and solving method in facility location problem [J]. Journal of Beijing Union University, 2012,26 (003): 11-15. (In Chinese).
3. Xi Ren and Tianke Kang. Application of multi-standard analysis method (MCA) in hydropower station site selection project [J]. Journal of Guizhou University (Natural Science Edition), 2013, 30 (05): 31. (In Chinese).
4. Shuhui Liu, Wuqun Cheng, Gao Fen, Shaogang Song and Guofang Kang. GM model predicts agricultural water consumption and water-sav-ing irrigation forms [J]. Water-saving Irrigation, 2007 (08): 14-16. (In Chinese).
5. Runhua Ai. Study on location and scale design of reservoir project [J]. Water Conservancy Science and Cold region Engineering, 2019 (4). (In Chinese).
6. Heng Wang. Design of river multi-dam system based on multi-objective optimization–taking Kaliba Dam as an example [J]. China High-tech Zone, 2018 (13): 216. (In Chinese).
7. ZAMCOM/SADC/SARDC. The Status Report on Integrated Flood and Drought Map-ping [R]. SARDC, 2015.
8. Asami Miketa and Bruno Merven. SOUTHERN AFRICAN POWER POOL: Planning and Pro-spects for Renewable Energy [R]. IRENA, 2013.
9. Sifeng Liu. Grey system Theory and its Application (Fifth Edition) [M]. Beijing: science Press, 2010. (In Chinese).
10. Harare. Gaborone. Zambezi Environment Outlook 2015 [R]. ZAMCOM, SADC, SARDC, 2015.
11. Shuqin Li and Jingui Shi. Present situation of water resources and its utilization in Africa [J]. KuaiBao of Water Conservancy and Hydro-power, 2009. 30 (01): 7-9. (In Chinese).
12. Wei Wang, Lianghong Wu, Zhenzu Liu, Jian Li, Rui Jia and Hongqiang Zhang. Optimal scheduling of surface water source heat pump units based on neighborhood adaptive particle swar-m optimization algorithm [J]. Systems Science and Mathematics: 1-14. (In Chinese).


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