CN 11-5366/S     ISSN 1673-1530
“风景园林,不只是一本期刊。”

蓝绿协同视角下城市湖泊湿地温湿效应场时空特征——以武汉菱角湖为例

Temporal and Spatial Characteristics of the Temperature and Humidity Effect Field of Urban Lake Wetlands from a Blue-Green Synergy Perspective: A Case Study of Lingjiao Lake in Wuhan

  • 摘要:
    目的 城市湖泊湿地对区域环境具有重要的调节功能和环境效益,蓝绿协同布局可加强其温湿效应。基于蓝绿协同视角探究城市湖泊湿地温湿效应场时空特征,为城市蓝绿空间区域环境效应的优化提升提供方法支持。
    方法 以武汉菱角湖及其周边300 m建成环境绿地作为研究对象,采用样带法实测湖泊周边300 m内不同缓冲区建成环境绿地内空气温度、相对湿度,选取蓝绿因素、建成环境因素和气象因素为变量,建立土地利用回归(land use regression, LUR)模型,系统研究这些因素对城市湖泊湿地温湿效应场的作用方式、作用强度和作用范围。
    结果 城市湖泊湿地与周边300 m建成环境绿地表现出显著的协同降温增湿效应,平均降温梯度为0.19℃/100 m、增湿梯度为0.70%/100 m;城市湖泊湿地周边不同缓冲区范围影响温湿度的关键变量具有显著差异性;交通密度越低、绿地郁闭度越高、叶面积指数越大,蓝绿空间协同降温效应越显著。
    结论 基于蓝绿因素、建成环境因素和气象因素建立LUR模型,揭示城市蓝、绿空间具有明显的伴生效应和物理层级的空间交互作用,为蓝绿协同视角下城市湖泊湿地区域环境效应的整体提升提供建议和支持。

     

    Abstract:
    Objective Urban lake wetlands possess significant regulatory functions and environmental benefits for regional environments. A synergistic layout of water and green spaces can enhance their temperature and humidity effects. Focusing on maximizing the regional environmental effects of urban lake wetlands, it is of great practical significance for the planning and protection of the built environment of urban lake wetlands to strengthen and optimize the construction of green spaces in the surrounding built environment, and to explore the coupling relationship between the morphological composition and layout structure of green spaces in the built environment and the temperature and humidity effects of urban lake wetlands.
    Methods Taking Lingjiao Lake and its surrounding 300 m built environment green space in the main urban area of Wuhan as the research area, this area is characterized by dense buildings and a complex composition of the built environment, including green spaces, plazas, commercial areas, and residential zones. In this study, the diurnal air temperature and relative humidity in July 2024 were measured as indicators. Using a combination of transect-based quantitative measurements and land use regression (LUR) models, a comprehensive assessment and data statistical analysis were conducted to systematically investigate the spatiotemporal characteristics of air temperature and relative humidity effect field of urban lake wetlands.
    Results This research comprehensively analyzed the factors influencing air temperature and relative humidity in the built environment surrounding urban lake wetlands, based on a combination of LUR models. The results indicate that: 1) The LUR model based on the key influencing variables consists of water area, surrounding green space and built environment factors within 300 m buffer and meteorological factors and indicators of air temperature and relative humidity were successfully established, with the adjusted R 2 of 0.607 and 0.779 for air temperature and relative humidity, respectively, and the adjusted LOOCV R 2 of 0.763 and 0.957, respectively. Based on the correlation analysis of LUR model variables, the prediction variables for air temperature are ρT100, ρT25, DR, HB25, and ILA, while ρT50, ρB25, PW25, ILA, DB, and T for relative humidity. 2) The coupling of urban lakes and wetlands with surrounding green spaces has a significant effect on improving temperature and humidity. For air temperature, the combined blue-green effect of the 300 m buffer zone (T300 mTLake) is 0.58 ℃, with a gradient of 0.19 ℃/100 m; for relative humidity, the combined blue-green effect of the 300 m buffer zone (φRHLakeφRH300 m) is 2.11%, with a gradient of 0.70%/100 m. 3) The key influencing factors of air temperature and relative humidity in different buffer zones and surrounding green spaces vary significantly. Within a 50 m buffer zone, ρT is the only positively correlated variable with T; Regarding RH, the influencing variables are ρT, PW, and PG. Within a 100 m buffer zone, ρB has a significant impact on T, while ρT is the most significant variable affecting T and RH; Regarding RH, the significant influencing variables include PW, DR, and ρT. Within the buffer zones of 200 m and 300 m, ρB, ρT, and FSV (sky view factor) have significant effects on T and RH. In summary, the lower the traffic density, the higher the green space canopy density, and the larger the leaf area index, the more significant the synergistic cooling effect of blue-green space.
    Conclusion This research, from the perspective of blue-green collaboration, examines how urban built environment and land use factors affect temperature and humidity in terms of mechanism, intensity, and scope. According to the LUR models consists of blue-green factors, built environment factors, and meteorological factors, it summarizes the spatio-temporal characteristics of the temperature and humidity effect field of urban lake wetlands, and reveals the associated effects of blue and green spaces and their physical-level spatial interactions, providing support for enhancing the environmental effects of urban lake wetland. Based on the findings, the following strategies for improving the temperature and humidity regulation of urban blue-green space systems are proposed: 1) Control the proportion of transportation infrastructure around urban water bodies; keep main roads at least 60 m away from water spaces to maximize the regulatory function of blue-green spaces. 2) Protect urban blue lines, green lines, and blue-green space effect lines; limit building density to an approximately 0.35 within 300 m buffer. 3) Select plant communities with high leaf area index (ILA>2.0), canopy density (ρC>0.77), and large crown width for green spaces around lakes, optimizing green space structures and increasing the proportion of multi-layered vegetation.

     

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