文献类型：期刊文献

中文题名：多尺度下西南喀斯特山地城市内涝空间分布特征与驱动力分析:以贵阳市为例

英文题名：Analysis of spatial and temporal distribution characteristics and driving factors of inundation in karst mountains, Southwest China at multi-scales: Taking Guiyang City as an example

作者：郑佳薇 尹昌应 戴丽 周方 赵禹韩

第一作者：郑佳薇

机构：[1]贵州师范大学地理与环境科学学院,贵州贵阳550025;[2]贵州省山地资源与环境遥感应用重点实验室,贵州贵阳550025;[3]贵州理工学院建筑与城市规划学院,贵州贵阳550003

第一机构：贵州师范大学地理与环境科学学院,贵州贵阳550025

年份：2023

卷号：54

期号：2

起止页码：33-46

中文期刊名：水利水电技术（中英文）

外文期刊名：Water Resources and Hydropower Engineering

收录：CSTPCD;;北大核心:【北大核心2020】；

基金：国家自然科学基金项目(41561038);贵州省科学技术基金项目(黔科合基础[2017]1409)。

语种：中文

中文关键词：多尺度;喀斯特;山地城市;内涝;地理探测器;城市空间结构

外文关键词：multi-scale;karst;mountainous cities;inundation;Geo detector;urban spatial structure three-dimensional characteristics of buildings

摘要：【目的】针对现有城市内涝空间格局及驱动因素研究多集中于平原地区,难以为喀斯特山地城市提供参考这一问题,【方法】以贵阳市为研究区,建立2016—2020年内涝数据集,运用核密度估计法、标准差椭圆法和全局空间自相关探究内涝空间分布特征,并运用Spearman相关分析和地理探测器在多尺度上(即250 m、500 m和1 000 m)揭示贵阳市内涝的驱动机制。【结果】结果表明:(1)贵阳市内涝具有集聚效应,集聚中心位于云岩区和南明区,内涝分布方向经历了由“南-北”向“东南-西北”的转变;(2)城市空间结构、土地利用类型、地形和人口密度是内涝的主要驱动因子,特别是城市空间结构中容积率对内涝的驱动力最强,q值为0.374;(3)各驱动因子之间的交互作用类型以双因子增强为主,其中容积率∩建筑拥挤度的协同作用对内涝的影响最显著,q值为0.574;(4)内涝与城市空间结构、土地利用类型、地形间的相关性随研究尺度的增加而减弱,而土壤和地质则相反。【结论】内涝多集聚于云岩区和南明区;影响内涝发生的主要因素是城市空间结构、土地利用类型、地形和人口;内涝影响因素具有较强的尺度效应,因此结合研究区特点确定适当的尺度,可以更准确地识别内涝的主要驱动因素。
[Objective] To address the problem that existing studies on the spatial pattern and drivers of inundation are mostly focused on plain areas, which is difficult to provide reference for karst mountainous cities. [Methods] This study takes Guiyang city as the study area, establishes the inundation dataset from 2016 to 2020, explores the spatial distribution characteristics of inundation using kernel density estimation metho d, standard deviation ellipse method and global spatial autocorrelation, and uses Spearman correlation analysis and geographic probes at multiple scales(i.e., 250 m, 500 m and 1 000 m) to reveal the The driving mechanisms of inundation in Guiyang city were investigated by using Spearman correlation analysis and geographic probes at multiple scales(i.e., 250 m, 500 m and 1 000 m). [Results] The results show that(1) inundation in Guiyang has a clustering effect, with the clustering centers located in Yunyan and Nanming districts, and the distribution direction of inundation undergoes a shift from “south-north” to “southeast-northwest”;(2) urban spatial structure, land use type, topography and population density are the driving mechanisms of inundation.(2) urban spatial structure, land use type, topography and population density are the main driving factors of inundation, especially the volume ratio of urban spatial structure has the strongest driving force on inundation, with a q value of 0.374;(3) the interaction type between the driving factors is mainly two-factor enhancement, among which the synergistic effect of volume ratio ∩ building congestion has the most significant effect on inundation, with a q value of 0.574;(4) the correlation between inundation and urban spatial structure, land use type, and topography decreases with increasing study scale, while the opposite is true for soils and geology. [Conclusion] inundation is mostly concentrated in Yunyan and Nanming districts;the main factors influencing the occurrence of inundation are urban spatial structure, land use type, topography and population;the influencing factors of inundation have strong scale effects, so determining the appropriate scale with the characteristics of the study area can identify the main driving factors of inundation more accurately.