Risk Assessment on Regional Water Scarcity in Guangdong Province Based on Principal Component Analysis
基于主成分分析的广东省区域水资源紧缺风险评价

Guangdong province, located in the south of China, can generally be classified as the tropical and semitropical zones with plentiful precipitation of an uneven distribution over space and time. This study assesses the risk of water resources of cities of Guangzhou, Shenzhen, Zhuhai, Shantou, Foshan, and Zhanjiang in Guangdong Province by analyzing data associated with water resources, meteorology, demography, economy, as well as environmental protection. Three criteria including water resources, social state, and response of drought control consisting of 18 indicators, were adopted to build a risk assessment system. The principal component analysis method was used to reasonably determine the weight of each indicator. The system is unique in simplifying the data structure and synthesizing information reflected by a variety of data sources, largely obviating the subjectivity involved in some traditional evaluation methods. The weighted indicators were summed up as the risk indices (e.g., resource risk index, use risk index, management risk index, and total risk index) to quantify the risk degree of water scarcity across the study cities. Results showed that agricultural cultivation area, qualified rate of industrial sewage, and water consumption of 10,000 Yuan GDP are the key indicators to determine the risk of the study areas. This might be indicative of the risk of water scarcity being most affected by human activities. Differences in resource risk index, use risk index, and management risk index among different regions were likely to be as a result of varying degrees of drought severity for different cities. Zhanjiang was found to be a high-risk area experiencing water scarcity, followed by Foshan and Guangzhou. Shantou, Zhuhai, and Shenzhen showed relatively lower risks. It was also found that in the principal component analysis method, the weight for each indicator is determined by the indicator information and the system efficiency, suffering from less subjectivity. It can obviate the case of the same weight for all assessment systems, which means that the same indicator in the principal component analysis method can have different weights for varying regions. The study provides a basis for risk assessment on regional water scarcity. As the risk would continue to increase and even threat the sustainable development of society, it is suggested that governments at all levels highlight the situation of water scarcity and raise the awareness of people on this issue. Great effort should be made in the future to protect and efficiently utilize water resources.