Lei Chaogui, Wang Qiang, Wang Yuefeng, Han Longfei, Yuan Jia, Yang Liu, Xu Youpeng
Department of Hydrology and Water Resources Management, Institute for Natural Resource Conservation, Kiel University, Olshausenstr. 75, 24118 Kiel, Germany; School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China.
School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China.
Sci Total Environ. 2022 Jun 10;824:153684. doi: 10.1016/j.scitotenv.2022.153684. Epub 2022 Feb 5.
Given environmental or hydrological functions influenced by changing river networks in the development of rapid urbanization, a clear understanding of the relationships between comprehensive urbanization (CUB) and river network characteristics (RNC), storage capacity (RSC), and regulation capacity (RRC) is urgently needed. In the rapidly urbanized Tai Lake Plain (TLP), China, various methods and multisource data were integrated to estimate the dynamics of RNC, RSC, and RRC as well as their interactions with urbanization. The bivariate Moran's I methods were applied to detect and visualize the spatial dependency of RNC, RSC, or RRC on urbanization. Geographically weighted regression (GWR) model was set up to characterize spatial heterogeneity of urbanization influences on RNC, RSC and RRC. Our results indicated that RNC, RSC and RRC variables each showed an overall decreasing trend across space from 1960s to 2010s, particularly in those of tributary rivers. RNC, RSC, or RRC had globally negative correlations with CUB, respectively, but looking at local scale the spatial correlations between each pair were categorized as four types: high-high, high-low, low-low, and low-high. GWR was identified to accurately predict the response of most RNC, RSC, or RRC variables to CUB (R: 0.6-0.8). The predictive ability of GWR was spatially non-stationary. The obtained relationships presented different directions and strength in space. All variables except for the water surface ratio (Wp) were more positively affected by CUB in the middle eastern parts of TLP. Drainage density, RSC and RRC variables were more negatively influenced by CUB in the northeast compared to other parts. The quantitative results of spatial relationships between urbanization and RNC, RSC or RRC can provide location-specific guidance for river environment protection and regional flood risk management.
在快速城市化发展过程中,鉴于河流水系变化对环境或水文功能的影响,迫切需要清楚了解综合城市化(CUB)与河网特征(RNC)、蓄水能力(RSC)和调节能力(RRC)之间的关系。在中国快速城市化的太湖平原(TLP),综合运用了各种方法和多源数据来估算RNC、RSC和RRC的动态变化及其与城市化的相互作用。采用双变量莫兰指数(Moran's I)方法来检测和可视化RNC、RSC或RRC对城市化的空间依赖性。建立地理加权回归(GWR)模型来刻画城市化对RNC、RSC和RRC影响的空间异质性。我们的结果表明,从20世纪60年代到21世纪10年代,RNC、RSC和RRC变量在空间上总体呈下降趋势,尤其是在支流中。RNC、RSC或RRC分别与CUB在全球范围内呈负相关,但在局部尺度上,每对之间的空间相关性可分为四种类型:高高、高低、低低和低高。结果表明,GWR能够准确预测大多数RNC、RSC或RRC变量对CUB的响应(R:0.6 - 0.8)。GWR的预测能力在空间上是非平稳的。所得到的关系在空间上呈现出不同的方向和强度。除水面率(Wp)外,太湖平原中东部分地区的所有变量受CUB的正向影响更大。与其他地区相比,东北地区的排水密度、RSC和RRC变量受CUB的负面影响更大。城市化与RNC、RSC或RRC之间空间关系的定量结果可为河流环境保护和区域洪水风险管理提供特定地点的指导。