Optimal Allocation Model of Water Resources in Tidal Flat Development of Coastal Areas

• Published in: Journal of coastal research 2018-06, Vol.84 (sp1), p.89-93
• Main Authors: Huang, Xianfeng, Chen, Yingqin, Fang, Guohua
• Format: Article
• Language: English
• Subjects: Algorithms; Area; Beach development; Biodiversity; Biological evolution; Case studies; coastal areas; Coastal zone; Coasts; Construction; Desalination; Ecological monitoring; Economic models; Economics; Evolutionary genetics; Feasibility studies; Fitness; Genes; Genetic algorithms; Hydroelectric power; Irrigation; Iterative methods; Land area; Land use; multi-objective genetic algorithm; Multiple objective analysis; R&D; Rain; Reproductive fitness; Research & development; Resource allocation; Science; Seawater; Soil; Soil water; the optimization of water resources; Tidal flats; Water conservation; Water consumption; Water resources; Water rights; Water use
• ISSN: 0749-0208; 1551-5036
• DOI: 10.2112/SI84-013.1

Huang, X.; Chen, Y., and Fang, G., 2018. Optimal allocation model of water resources in tidal flat development of coastal areas. In: Wang, D. and Guido-Aldana, P.A. (eds.), Select Proceedings from the 3rd International Conference on Water Resource and Environment (WRE2017). Journal of Coastal Research, Special Issue No. 84, pp. 89–93. Coconut Creek (Florida), ISSN 0749-0208. As a result of economic and population development in coastal areas, the conflict of water utilization is becoming increasingly serious. To ensure rational utilization, the optimal allocation model of water resources was constructed for the development of coastal tidal flats based on the analysis of the coastal area development model. The goal of optimal allocation was to achieve optimal economic, social, and ecological benefits under the conditions of coordinated use of water and soil resources. Due to the complexity of the water resources system, the model used various land areas, in addition to economic, social, and ecological data, to establish target measures, and a multi-objective genetic algorithm was used to solve the problem. Following each iteration, individuals' fitness was ranked and constantly updated according to population evolution, since individuals learn from the fittest and genes are improved accordingly. The coastal area of Dongtai in Jiangsu province, China, was considered a case study, in which the scheme of the city's water resources was optimized. The optimal allocation results show that by 2020, the agricultural and construction land will have increased, and the unused land will decrease, with the construction land area being 36185 hm2; thus, conforming to the future trend of Dongtai land utilization. The results verify the rationality and feasibility of the model and the algorithm, which provides ideas and experience for the optimal allocation of water resources during beach development in coastal areas.