2019•IOP Conference Series Earth and Environmental ScienceOpen access

Conceptual framework of hierarchical water demand

Baodeng Hou, Ruixiang Yang, J H Wang, Weihua Xiao, Yong Zhao, Hao Wang

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Abstract

Abstract Water resources demand analysis is one of the basic and core contents of water resources planning, allocation and management. Its mechanism analysis is the focus, hot spot and difficult point of future social water cycle research. Aiming at the problems of lack of mechanism of water resources demand analysis and the large forecasting results, Maslow’s hierarchical theory of demand is introduced into the field of water resources demand. Based on the characteristics of individual water demand mechanism, the mechanism and characteristics of human demand for water resources in the process of life, production and ecological construction are analyzed, and the hierarchical theory of water resources demand is established accordingly. The theory divides water demand from low to high into three levels: rigid demand, elastic demand and luxury demand, and combines water demand at each level into three levels: basic water demand, reasonable water demand and representational water demand. Finally, based on this theory, the water demand forecasting method is discussed. The research results enrich the theory and method of water demand prediction, and lay a theoretical foundation for scientific prediction of future water demand.

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Abstract Water resources demand analysis is one of the basic and core contents of water resources planning, allocation and management. Its mechanism analysis is the focus, hot spot and difficult point of future social water cycle research. Aiming at the problems of lack of mechanism of water resources demand analysis and the large forecasting results, Maslow’s hierarchical theory of demand is introduced into the field of water resources demand. Based on the characteristics of individual water demand mechanism, the mechanism and characteristics of human demand for water resources in the process of life, production and ecological construction are analyzed, and the hierarchical theory of water resources demand is established accordingly. The theory divides water demand from low to high into three levels: rigid demand, elastic demand and luxury demand, and combines water demand at each level into three levels: basic water demand, reasonable water demand and representational water demand. Finally, based on this theory, the water demand forecasting method is discussed. The research results enrich the theory and method of water demand prediction, and lay a theoretical foundation for scientific prediction of future water demand.

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Available abstract

Abstract Water resources demand analysis is one of the basic and core contents of water resources planning, allocation and management. Its mechanism analysis is the focus, hot spot and difficult point of future social water cycle research. Aiming at the problems of lack of mechanism of water resources demand analysis and the large forecasting results, Maslow’s hierarchical theory of demand is introduced into the field of water resources demand. Based on the characteristics of individual water demand mechanism, the mechanism and characteristics of human demand for water resources in the process of life, production and ecological construction are analyzed, and the hierarchical theory of water resources demand is established accordingly. The theory divides water demand from low to high into three levels: rigid demand, elastic demand and luxury demand, and combines water demand at each level into three levels: basic water demand, reasonable water demand and representational water demand. Finally, based on this theory, the water demand forecasting method is discussed. The research results enrich the theory and method of water demand prediction, and lay a theoretical foundation for scientific prediction of future water demand.

Key concepts: Demand management, Water resources, Demand forecasting, Supply and demand, Effective demand, Derived demand, On demand, Demand patterns

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