Types identification and development tracking of urban water scarcity in China: A case study of 32 major cities
Year: 2023
Type: article
Abstract: This study creates an evaluation index system for the degree of urban water scarcity based on the results of previous research and uses principal component analysis (PCA) to assess the level of water scarcity in 32 major cities in China from 2011 to 2020. The types and distribution characteristics of water scarcity are identified, along with the dominant physical meaning of the principal components, using the group-based multi-trajectory modeling (GBMTM) method. In addition, the types of scarcity and the potential risks of managing water resources during the process of urban expansion are discussed. The results showed that: (1) Significant regional variability exists in the water resource deficit, as demonstrated by the fact that it worsens gradually from the southeast to the northwest and is constrained by resource endowment. There, most cities with water scarcity are distributed in Northern China. (2) Resource-engineering coupling-constrained water scarcity is prevalent in major cities of Northwest China, resource-constrained and management-constrained water scarcity is prevalent in most parts of North and Northeast China; engineering-constrained and water-quality-constrained water scarcity is prevalent in many cities of Southern China. (3) The complexity of the urban water scarcity problem increases with the severity of the water deficit. Also, the motivating factors change over time. For instance, the intertwined impact of urban growth and GDP growth frequently results in the conversion of urban water scarcity types or the dominant position and can even cause the risk of urban water scarcity to materialize. (4) The likelihood of management-constrained water scarcity increases with the increase of city size and GDP. Also, the pace at which management-constrained water scarcity contributes to urban development is proportionate. The study also discovered that the GBMTM model can accurately distinguish separate clusters from various development trajectories. It can be utilized as a crucial tool for tracking the evolution of dynamic data in hydrology and water resources fields.
Source: 自然资源学报
Authors: Xiao-wei ZHAO, Hong-bo ZHANG, Tong-fang LI, Zhao-xia YE, Chao-wei XUE, Yu-rou ZHANG, Zhi-fang YANG
Institution: Chang'an University
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4387625630