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In recent years, frequent heavy rains have made Zhengzhou city suffer from the hazards of urban waterlogging. Identifying the spatiotemporal distribution characteristics and driving forces of waterlogging can help improve the current flood-prone situation in Zhengzhou city. Based on the waterlogging data of Zhengzhou from 2020 to 2024, the standard deviation ellipse method, autocorrelation method, kernel density estimation method, and optimal parameter geographic detector were used to systematically analyze the spatiotemporal distribution characteristics of waterlogging points and their driving forces from multiple scales. The results show that the annual distribution of waterlogging points in Zhengzhou is uneven; Spatially, the the focus of waterlogging is located in the old urban area, with significant clustering of waterlogging points at different scales, especially with the strongest spatial clustering within a 3km scale; There is a significant scale effect in the explanatory power of driving factors, with socioeconomic and urban construction driving factors having the greatest explanatory power at different scales, and the combined effect of factors significantly surpasses the independent effects of single factors.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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