An Analysis of the Factors in Total Water Consumption Based on Random Forest Regression Algorithm: A Case Study of Guangdong Province

A hierarchical evaluation system is constructed, including four factors (i.e., population, water resources, technology and economy) and nine elements (i.e., total resident population, population density, total water resources, rainfall, water consumption per 10 000 yuan of GDP, water consumption per 10 000 yuan of industrial added value, gross product of the primary industry, gross product of the secondary industry and gross product of the tertiary industry). The entropy method and the random forest regression algorithm are adopted to analyze the factors in the total water consumption in 21 prefecture-level cities in Guangdong Province. Three major results are obtained. First, in the element perspective, the total resident population, the gross product of the tertiary industry and the gross product of the primary industry are the main elements in the total water consumption in Guangdong Pro-vince, while rainfall has the least influence on the total water consumption of the prefecture-level cities in Guangdong Province. Second, in the factor perspective, the influence of the four factors on the total water consumption in Guangdong Province is in descending order: economic factors, population factors, water resources factors and technical factors. Third, based on the element and factor analysis, it can be seen that among the factors of population, water resources, technology and economic, the biggest elements that affect the total water consumption of Guangdong Province are the total resident population, total water resources, water consumption of 10 000 yuan per industrial added value and the gross product of the tertiary industry.