Abstract

As the principal part of economic and social development, the demographic factor is the fundamental factor driving the change of water resources, and achieving the harmony of human and water has been one of the most important tasks to promote high-quality development. Based on Maslow’s hierarchy of needs theory, this article applied panel data for 19 years and employed impulse response functions and threshold models to do a mechanism analysis of the impact of population structure changes on the water consumption changes of the three main industries. The study found the following: Firstly, the urban population promotes an increase of the total water consumption, industrial water consumption, and domestic water consumption, which suppresses agricultural water consumption and shows an inverted “N” trend. Secondly, the aging population has expanded the total water consumption, and agricultural and domestic water demand, and reduced industrial water consumption. Thirdly, food consumption helps to reduce the total water consumption and agricultural water consumption, but increases the industrial water consumption and the growth rate rises. Fourthly, the increase in the proportion of agricultural employment reduces the total water consumption, and agricultural and domestic water consumption, and increases industrial water consumption. Fifthly, the total water consumption and domestic water consumption both increase with the improvement of the population education level, while the agricultural water consumption declines first and then rises. The empirical results can provide a reference for analyzing the driving mechanisms of regional water consumption changes.

Highlights

  • Introduction iationsThe IPCC (Intergovernmental Panel on Climate Change) Assessment Report, ClimateChange 2021: The Physical Science Basis, reveals that the ecological environment is deteriorating, and water resources, as the basic resource for carrying human civilization, are a fundamental need for human survival and development, and water scarcity will seriously restrict the sustainable development of mankind

  • Compared with the VAR model, the panel vector auto-regression model (PVAR) model improves the accuracy and stability of model estimation

  • Referring to existing literature [27,40], the population structure is divided into the urban−rural structure of population (URS), age structure of population (ASP), population consumption structure (PCS), population employment structure (PES) and population education level (PEL)

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Summary

Population Age Structure

In the theory of the human life cycle, there are significant differences in consumption demand and lifestyle among different age groups. After entering the young and middle-aged stage of life, with the increase of income and the change of family lifestyle, people have more tours, showers, and cooking, which will inevitably increase water consumption; it will improve water utilization efficiency and reduce water consumption due to the use of water-saving facilities. In the elderly age period, due to the longer periods spent at home, water consumption rises [25]. The elderly spend more on food than the young and middle-aged population, especially on healthcare cash crops, increasing the demand for agricultural water [33]. This paper hypothesizes that the increase of the elderly population in the population age structure can increase water consumption

Population Consumption Structure
Population Employment Structure
Population Education Structure
Other Factors
Model Establishment
PVAR Model
STIRPAT Model
Threshold Model
Industrial Water Consumption Variables
Variables Affecting Industrial Water Consumption
Descriptive Statistics of Data
Impulse Response Analysis
Impulse Response
Impulse Response Analysis of Population Consumption Structure Change to Water
Impulse Response Analysis of Population Employment Structure Change to Water
Impulse Response Analysis of Population Education Level Change to Water
Threshold Effect Analysis
F Value p Value p Value
Non-Demographic Regression Results
Model Robustness Test
Conclusions and Water Resources
Conclusions
Findings
Water Resources Management Recommendations

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