Spatial heterogeneity of the effects of river network patterns on water quality in highly urbanized city

被引:5
作者
Wang, Yuanyuan [1 ,2 ]
Wang, Weixian [1 ,2 ]
Liu, Lijuan [1 ,2 ]
Wang, Rongjia [1 ,2 ]
Tang, Xiangyu [1 ,2 ]
Li, Yan [1 ,2 ]
Li, Xiaoyu [1 ]
机构
[1] Zhejiang A&F Univ, State Key Lab Subtrop Silviculture, Hangzhou 311300, Zhejiang, Peoples R China
[2] Zhejiang A&F Univ, Coll Forestry & Biotechnol, Hangzhou 311300, Zhejiang, Peoples R China
关键词
River network patterns; Water quality; River-dense plain urban area; Geographically weighted regression (GWR); model; GEOGRAPHICALLY WEIGHTED REGRESSION; LAND-USE; POLLUTION; AREA;
D O I
10.1016/j.scitotenv.2024.173549
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
River water quality deterioration is a serious problem in urban water environments. River network patterns affect water quality by influencing the flow, mixing, and other processes of water bodies. However, the effects of urban river network patterns on water quality remain poorly understood, thereby hindering the urban planning and management decision-making process. In this study, the geographically weighted regression (GWR) model was used to explore the spatial heterogeneity of the relationship between river network pattern and water quality. The results showed that the river network has a complex structure, high connectivity, and relatively even distribution and morphology. Important river structure indicators affecting water quality included the water surface ratio (Wp) and multifractal features (Delta alpha, Delta f) while important river connectivity indicators included circuitry (alpha) and network connectivity (gamma). River structure has a more complex effect on water quality than connectivity. This study recommends that the Wp should be increased in agricultural areas and appropriately reduced in urban built-up areas, and the number of river segments and nodes should be controlled within a rational configuration. Our study provides key insights for evaluating and optimizing the river network patterns to improve water quality of urban rivers. In the future, the land use intensity, hydrological processes, and human
引用
收藏
页数:12
相关论文
共 36 条
[1]   Geographically weighted regression: A method for exploring spatial nonstationarity [J].
Brunsdon, C ;
Fotheringham, AS ;
Charlton, ME .
GEOGRAPHICAL ANALYSIS, 1996, 28 (04) :281-298
[2]   A Study on the Relationship between Land Use Change and Water Quality of the Mitidja Watershed in Algeria Based on GIS and RS [J].
Chen, Dechao ;
Elhadj, Acef ;
Xu, Hualian ;
Xu, Xinliang ;
Qiao, Zhi .
SUSTAINABILITY, 2020, 12 (09)
[3]   Influence of water body area on water quality in the southern Jiangsu Plain, eastern China [J].
Deng, Xiaojun .
JOURNAL OF CLEANER PRODUCTION, 2020, 254
[4]   Correlations between water quality and the structure and connectivity of the river network in the Southern Jiangsu Plain, Eastern China [J].
Deng, Xiaojun .
SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 664 :583-594
[5]   Remote sensing imagery segmentation in object-based analysis: A review of methods, optimization, and quality evaluation over the past 20 years [J].
Ez-zahouani, Badia ;
Teodoro, Ana ;
El Kharki, Omar ;
Jianhua, Liu ;
Kotaridis, Ioannis ;
Yuan, Xiaohui ;
Ma, Lei .
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT, 2023, 32
[6]   The Changes of Wetland Network Pattern Associated with Water Quality in the Pearl River Delta, China [J].
Fan, Xiaoyun ;
Cui, Baoshan ;
Zhao, Hui ;
Zhang, Zhiming .
CLEAN-SOIL AIR WATER, 2012, 40 (10) :1064-1075
[7]  
Fotheringham S.A., 2002, Geographically Weighted Regression: The Analysis of Spatially Varying Relationships
[8]   Mapping the world's free-flowing rivers [J].
Grill, G. ;
Lehner, B. ;
Thieme, M. ;
Geenen, B. ;
Tickner, D. ;
Antonelli, F. ;
Babu, S. ;
Borrelli, P. ;
Cheng, L. ;
Crochetiere, H. ;
Macedo, H. Ehalt ;
Filgueiras, R. ;
Goichot, M. ;
Higgins, J. ;
Hogan, Z. ;
Lip, B. ;
McClain, M. E. ;
Meng, J. ;
Mulligan, M. ;
Nilsson, C. ;
Olden, J. D. ;
Opperman, J. J. ;
Petry, P. ;
Liermann, C. Reidy ;
Saenz, L. ;
Salinas-Rodriguez, S. ;
Schelle, P. ;
Schmitt, R. J. P. ;
Snider, J. ;
Tan, F. ;
Tockner, K. ;
Valdujo, P. H. ;
van Soesbergen, A. ;
Zarfl, C. .
NATURE, 2019, 569 (7755) :215-+
[9]   A modelling method for simulating nitrogen dynamics under the hydrodynamic context of river network [J].
Hui, Cizhang ;
Li, Yi ;
Liao, Ziying ;
Zhang, Wenlong ;
Yang, Zhengjian .
JOURNAL OF HYDROLOGY, 2023, 625
[10]   Drinking Water Quality and Public Health [J].
Li, Peiyue ;
Wu, Jianhua .
EXPOSURE AND HEALTH, 2019, 11 (02) :73-79