Effect of Urbanization on Aridity Index Changes: A Case Study of Yunnan Province

Abstract

The impact of urbanization on local climate has received widespread attention, with current research primarily focusing on the effects of urbanization on climate variables such as evaporation, precipitation, and temperature. As the Aridity Index (AI) is comprehensively influenced by multiple variables, including potential evapotranspiration, precipitation, and temperature, it is therefore inevitably affected by urbanization. However, the extent of the effect remains unclear. In this study, we analyzed annual AI data from 16 major cities in Yunnan Province from 1980 to 2022. We examined trends in AI and identified breakpoints using linear slope analysis, accumulated anomaly methods, and moving t-tests. Combined with breakpoint analysis and existing research findings, 2000 was identified as the starting point of rapid urbanization in Yunnan Province. The study period was divided into two phases: the pre-urbanization phase (1980–2000) and post-urbanization phase (2001–2022), with a separate analysis of AI trends during these two periods. When considering the differences in development stages among cities, we have conducted a further breakpoint analysis of the AI for the 16 major cities and divided the urbanization phases according to the identified change points for each city. In addition, we established an Urbanization Effects Indicator (AIUE) to quantify the effects of urbanization on AI. Simultaneously, through gray relational analysis, we identified the influence of various urbanization indicators on AI changes and ranked the relative impacts of these indicators. The main findings of this study are as follows: (1) Since the rapid urbanization in 2000, the trend of AI in Yunnan Province has shifted from decreasing to increasing. Before urbanization, the anomaly slope of the AI was -0.006 1, whereas after urbanization, it became 0.004 3, with an AIUE of 0.010 4. Additionally, the AI increased from 1.08 before 2000 to 1.13 after, representing a 4.6% increase. (2) The 16 cities in Yunnan Province exhibited AIUE values ranging from -0.014 7 to 0.018 8. Among these, Lijiang had the highest AIUE value (0.018 8), whereas Wenshan had the lowest (-0.000 2). Notably, the AIUE of 13 cities was found to be greater than zero, indicating that the AI increased at a greater slope after urbanization, which is consistent with the overall trend in Yunnan Province. After urbanization, AI increased in all 16 cities, with Lijiang showing the largest difference (0.152 4) and Xishuangbanna showing the smallest (0.035 0). (3) The gray relational analysis showed that among the five categories of urbanization indicators, population indicators had the greatest impact on AI, with a correlation degree of 0.908. Land indicators followed closely behind, with a degree of 0.838, while the transportation indicators ranked third at 0.700. Environmental indicators ranked fourth, with a degree of 0.599, and economic indicators exhibited the lowest correlation at 0.573. These findings provide a reference for future cities to effectively adapt to and mitigate the impacts of urbanization on urban climate.

Keywords

• urbanization effect
• aridity index
• urban climate
• gray relational analysis
• yunnan province