Ecological footprint analysis for urban agglomeration sustainability in the middle stream of the Yangtze River

Research on remote sensing ecological livability index based on Google Earth Engine: a case study from Urumqi-Changji-Shihezi urban cluster

The U-Chang-Shi (Urumqi-Changji-Shihezi) urban cluster, located at the heart of Xinjiang, boasts abundant natural resources. Over the past two decades, rapid urbanization, industrialization, and climate change have significantly threatened the region's ecological livability. To comprehensively, scientifically, and objectively assess the ecological livability of this area, this study leverages the Google Earth Engine (GEE) platform and multi-source remote sensing data to develop a comprehensive evaluation metric: the Remote Sensing Ecological Livability Index (RSELI). This aims to examine the changes in the ecological livability of the U-Chang-Shi urban cluster from 2000 to 2020. The findings show that despite some annual improvements, the overall trend in ecological livability is declining, indicating that the swift pace of urbanization and industrialization has placed considerable pressure on the region's ecological environment. Land use changes, driven by urban expansion and the growth in agricultural and industrial lands, have progressively encroached upon existing green spaces and water bodies, further deteriorating the ecological environment. Additionally, the region's topographical features have influenced its ecological livability; large terrain fluctuations have made soil erosion and geological disasters common. Despite the central plains' vast rivers providing ample water resources, over exploitation and ill-conceived hydrological constructions have led to escalating water scarcity. The area near the Gurbantunggut Desert in the north, with its extremely fragile ecological environment, has long been unsuitable for habitation. This study provides a crucial scientific basis for the future development of the U-Chang-Shi urban cluster and hopes to offer theoretical support and practical guidance for the sustainable development and ecological improvement of the region.

Pixel level spatial variability modeling using SHAP reveals the relative importance of factors influencing LST

As an important indicator of the regional thermal environment, land surface temperature (LST) is closely related to community health and regional sustainability in general, and is influenced by multiple factors. Previous studies have paid scant attention to spatial heterogeneity in the relative contribution of factors underlying LST. In this study of Zhejiang Province, we investigated the key factors affecting daytime and nighttime annual mean LST and the spatial distribution of their respective contributions. The eXtreme Gradient Boosting tree (XGBoost) and Shapley Additive exPlanations algorithm (SHAP) approach were used in combination with three sampling strategies (Province-Urban Agglomeration -Gradients within Urban Agglomeration) to detect spatial variation. The results reveal heterogenous LST spatial distribution with lower LST in the southwestern mountainous region and higher temperatures in the urban center. Spatially explicit SHAP maps indicate that latitude and longitude (geographical locations) are the most important factors at the provincial level. In urban agglomerations, factors associated with elevation and nightlight are shown to positively impact daytime LST in lower altitude regions. In the urban centers, EVI and MNDWI are the most notable influencing factors on LST at night. Under different sampling strategies, EVI, MNDWI, NL, and NDBI affect LST more prominently at smaller spatial scales as compared to AOD, latitude and TOP. The SHAP method proposed in this paper offers a useful means for management authorities in addressing LST in a warming climate.

Combing remote sensing information entropy and machine learning for ecological environment assessment of Hefei-Nanjing-Hangzhou region, China

Urban ecological environment is the basis of citizens' survival and development. A rapid and objective urban ecological environment assessment (UEEA) plays an important role in the urban sustainable development and environment protection. This study established an improved urban ecological comfort index (UECI_IMP), which is based on our previous UECI and fully composed of four remote sensing indicators: normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), land surface temperature (LST), and aerosol optical depth (AOD), representing the greenness, dryness, heat, and atmospheric turbidity, respectively. Combining the entropy method and random forest (RF) algorithm, the weights of four indicators were calculated. To improve the accuracy of UECI_IMP, the gap-filled quarterly mean results of each indicator with 30m resolution were obtained using the harmonic analysis of time series (HANTS) method and spatial-temporal information fusion based on non-local means filter (STNLFFM). UECI_IMP was applied to the Hefei-Nanjing-Hangzhou Region to explore its spatiotemporal changes and response characteristics. Results show that the weights of UECI_IMP fluctuate slightly (within 10%) before and after sensitivity analysis, with good stability and reliability. UECI_IMP in Hangzhou > Hefei ≈ Nanjing, spring ≈ autumn > summer ≫ winter. From 2009 to 2019, UECI_IMP has improved in all 33 districts of the Hefei-Nanjing-Hangzhou Region. The significant improvement of UECI_IMP in 2014-2019 is 4.3 times than that in 2009-2014. The correlation between UECI_IMP and economic index indicates that economic development has a positive impact on the urban ecological environment. The significant degradation of UECI_IMP in the urban expansion area demonstrates a negative impact on the local environment from urban expansion.

Response Relationship between the Regional Thermal Environment and Urban Forms during Rapid Urbanization (2000–2010–2020): A Case Study of Three Urban Agglomerations in China

Urban agglomerations are currently facing regional thermal environment deterioration. However, the relationship between thermal environment changes in urban agglomerations in response to urban expansion and the underlying urban morphology-driven mechanisms is not clear. This study utilized data from the three largest urban agglomerations in China for 2000, 2010, and 2020 to explore the response of regional heat island changes to urban morphological variations induced by urban expansion through the quantification of urban landscape form, correlation analysis, and relative importance analysis. The results indicate that the distribution of heat source and built-up areas in urban agglomerations has clear spatial and temporal consistency. Moreover, a high regional heat island intensity (RHII) cluster was shown in a “strip-like” form in Beijing–Tianjin–Hebei and the Yangtze River Delta, while the Pearl River Delta, with the most rapid expansion and contiguity of heat source areas, showed a “ring-like” form. RHII was positively correlated with the area of urban clusters and the proportion of built-up areas. However, configuration metrics, such as patch aggregation, also positively affected RHII. Thus, different landscape structures with the same impervious surface area percentage resulted in different RHII values. The relative importance of urban form metrics varied in different urbanization stages; the impervious layer rate was dominant for low and high urban intensity levels, while the shape complexity of urban patches primarily mitigated the thermal environment at the medium urban development level. These results revealed the response relationship between the regional thermal environment and urban morphology, providing insights into how we can improve the regional thermal environment through targeted strategies for optimizing urban form patterns for areas at different urbanization stages.

Spatially Heterogeneity Response of Critical Ecosystem Service Capacity to Address Regional Development Risks to Rapid Urbanization: The Case of Beijing-Tianjin-Hebei Urban Agglomeration in China

Urban agglomerations have become the new spatial unit of global economic competition. The intense socioeconomic activities attributed to the development of urban agglomerations are bound to cause damage to the ecosystem services of these urban agglomerations. This study adopts the Beijing-Tianjin-Hebei urban agglomeration in China as the research object, analyzes the spatiotemporal evolution of its critical ecosystem service capacity to address regional ++-development risks from 2000–2018, and employs the Moran’s I and geographically weighted regression model to explore the spatial correlation and spatial heterogeneity in the responses of urbanization and ecosystem services. The study indicates that (1) from 2000–2018, the ecosystem services of the Beijing-Tianjin-Hebei urban agglomeration exhibit an increase and then a decline, reaching the highest index in 2015; (2) the ecosystem services reveal obvious spatial heterogeneity with the Yan and Taihang Mountains region as the boundary; (3) built-up area ratio, GDP density, and population density exhibit highly obvious negative correlation driving characteristics on ecosystem services; and (4) the construction land ratio exerts a notable impact on areas with a high ecosystem services, while the spatial response of the effect magnitude of the population and GDP densities is largely influenced by intensive, high-pollution and energy-consuming industries. This article also proposes strategies for the optimization of ecological resources and spatial control, which are dedicated to mitigating the negative impacts of rapid urbanization processes on ecosystem services.

Pathways to progress sustainability: an accurate ecological footprint analysis and prediction for Shandong in China based on integration of STIRPAT model, PLS, and BPNN

The world has been challenged by achieving the plausible goal of sustainable development. This study aims to evaluate the ecological footprint and ecological carrying capacity and their driving factors of Shandong province in China from 1994 to 2017. Back propagation neural network method is adopted to predict the ecological footprint from 2018 to 2030. The findings are as follows: (1) The growth of ecological footprint has caused the ecological deficit in Shandong. (2) With regards to population, the increase of total population and the urbanization rate will incur the expansion of ecological footprint. (3) In terms of affluence, the elasticity coefficients of GDP per capita, the production value of industrial sectors, and the proportion of output value of the secondary industry in GDP are 0.068, 0.064, and 0.130 respectively. (4) In terms of technology, the elasticity coefficients of internal expenditure on R&D in GDP and patent number are 0.096 and 0.047 respectively, indicating that technological progress can promote ecological footprint in a short term. (6) The results of the prediction show that the ecological footprint of Shandong from 2018 to 2030 in the policy-regulation scenario is far less than that of the business-as-usual scenario. The policy recommendations are suggested to tackle the sustainable development challenges.

Spatial Effects of Urban Agglomeration on Energy Efficiency: Evidence from China

The rapid expansion of large cities in China has substantially increased energy consumption. With ever stringent environmental policy in force, energy efficiency becomes an important issue. As the emergence of these urban agglomerations (UAs) is usually due to externality effects of spatially concentrated factors, this paper investigates how these factors can affect energy efficiency. Based on mono index, which is used to describe the spatial location information, we have constructed the spatial-structure index of UAs. Using panel data on ten major UAs in China from 2008 to 2017, we find that, in the whole sample, there is an inverse relationship between the spatial structure of UAs and energy efficiency: The higher the concentration degree of factors of UAs, the lower the energy efficiency. Across different regions, however, the relationship between spatial structure and energy efficiency is heterogeneous. The concentration degree of factors in the eastern and central regions of China is relatively high, and the spatial structure there does lead to a decrease in energy efficiency. By contrast, UAs in China’s western region are in a period of factor concentration, with spatial structure playing, in that region, a positive role in improving energy efficiency.

Multi-scale effects of urban agglomeration on thermal environment: A case of the Yangtze River Delta Megaregion, China

The phenomenon of urban heat islands has been extensively investigated in recent decades. Due to the complexity of urban systems, this phenomenon may be scale-dependent, particularly for large megaregions where a cluster of cities gather together. Despite many studies focusing on urban heat islands at scales from single-site to regional, and further to global, there are few studies addressing multi-scale effects of large urban agglomeration on thermal environment. In this study, we used the Yangtze River Delta (YRD), one of China's most important megaregions, as a pilot case to examine the spatial-temporal variations of thermal environment and its driving forces at two spatial scales in 2000, 2005 and 2010. At regional scale, the effect of the entire megaregion on thermal environment was characterized by the distribution of the highest surface temperature zone (HTZ), which was closely related to the occurrence of continuously developed land. At city scale, the effect of individual city on thermal environment was characterized by the mean land surface temperature difference (LSTD) between urban and rural areas, which showed a significant positive correlation with the economic factors. In the YRD, the secondary industry output could explain approximately 58% and 39% of the variation of the LSTD in 2000 and 2005, respectively, while in 2010 the tertiary industry output became the important factor and accounted for 36% of the variation of LSTD. Finally, cities with fast urban economic growth rate and large size of urban areas were the priority for adopting more efficient strategies to urban thermal management.

Land use transitions and the associated impacts on ecosystem services in the Middle Reaches of the Yangtze River Economic Belt in China based on the geo-informatic Tupu method

Rapid urbanization in China has greatly exacerbated land use transitions (LUTs), which seriously threaten the ecosystem. The existing literature lacks information on the spatio-temporal analysis of LUTs, and assessments of ecosystem services remain incomplete. This lack of information may limit the formation and implementation of landscape plans and ecologically oriented policies. This study attempts to fill this gap by analysing the geographic features of LUTs with the geo-informatic Tupu method and exploring the responses of ecosystem services to LUTs. A newly revised benefit transfer method that utilizes the land use/land cover change data derived from the Landsat Enhanced Thematic Mapper (ETM) in the Middle Reaches of the Yangtze River Economic Belt (MRYREB) is implemented. The results indicate that the area of construction land continued to increase markedly, while the area of cultivated land declined continuously from 1995 to 2015. This increase in construction land was mainly derived from the occupation of cultivated land. The Tupu units of "forestland → cultivated land," "cultivated land → forestland," "cultivated land → water area," and "water area → cultivated land" were the dominant driving forces of the changes in ecosystem services value (ESV) in the MRYREB. Hotspots of ESV changes were mainly located in the surrounding mountainous areas during 1995-2005 and 2005-2010, while the coldspots during 2010-2015 were mainly located in the plains. The findings in this study have important implications for ecosystem conservation, ecological function zoning, ecological compensation decision-making, and related land development in the MRYREB.

How did the bacterial community respond to the level of urbanization along the Yangtze River?

Bacterial communities in the sediment of the Yangtze River influenced by rapid urbanization have thus far been under-investigated despite the importance of microorganisms as mass transporters. Here, the response patterns of the bacterial community along the Yangtze River to different levels of urbanization were generated using 16S rRNA Miseq sequencing. The results reveal that economic aspects have made the largest contribution (41.8%) to the urbanization along the Yangtze River. A clear declining tendency in the abundance of Chloroflexi and Acidobacteria and a significant increase in the abundance of Bacteroidetes were observed with an elevated urbanization level gradient. Bacterial diversity showed a negative relevance (P < 0.01) to the demographic, economic and social urbanization index. Per capita gross domestic product (GDP) (PCGDP) and the GDP of tertiary industry (GDP3) exhibited significantly (P < 0.05) negative correlations with the bacterial diversity, while a positive relationship between the pH and α-diversity (P < 0.05) was observed. Redundancy analysis revealed that PCGDP was significantly correlated (13.9%, P < 0.01) with the overall bacterial compositions, followed by temperature (10.8%, P < 0.01) and GDP3 (8.4%, P < 0.05). Meanwhile, the GDP3 (35.9%), the ratio of total nitrogen and total phosphorus (N/P) (12.9%) and the PCGDP (8.8%) were revealed to be most significantly related to the metabolic bacteria (P < 0.05). The metabolic functions of the bacteria related to the N-cycle and S-cycle were significant in the sediment of the Yangtze River. The variations of the bacterial community and metabolic function responding to the rapid urbanization were related to the economic development via the influence of the 'mass effect'. In brief, the tertiary industry was significantly correlated with the variations in the composition of the metabolic community and the variations in the overall bacteria were both related to the tertiary and secondary industry.

Ecological Environment Vulnerability and Driving Force of Yangtze River Urban Agglomeration

The vulnerability of ecological environment threatens social and economic development. Recent studies failed to reveal the driving mechanism behind it, and there is little analysis on the spatial clustering characteristics of the vulnerability of urban agglomerations. Therefore, this article estimates ecological environment vulnerability in 2005, 2011, and 2017, determines Moran Index (MI) with spatial autocorrelation model, analyzes the spatial-temporal difference characteristics of ecological environment vulnerability of Yangtze River Urban Agglomeration and the spatial aggregation effect, and discusses its driving factors. The study results estimate that the overall vulnerability index of the Yangtze River Urban Agglomeration is in a mild fragile state. However, most fragile and slightly fragile cities are developing in the direction of moderate to severe vulnerability. The spatial agglomeration effect of the ecological environment vulnerability of the Yangtze River Urban Agglomeration is not obvious, and the effect of mutual ecological environment influence among cities is not obvious. Moreover, the driving factors of ecological environment vulnerability of Yangtze River city group changed from natural factors to social economic factors and then to policy factors. It is necessary to develop an ecological economy, coordinate the spatial agglomeration of urban agglomerations, and make balance the internal differences of urban agglomerations.

A Bibliometrics Review of Water Footprint Research in China: 2003–2018

As water security becomes an increasingly important issue, the analysis of the conflict between water supply and demand has gained significance in China. This paper details a bibliometric review of papers published between 2003 and 2018 on the water footprint in China, one of the global hotspots of water resource research. The tendencies and key points of water footprint research were systematically analyzed based on 1564 articles, comprising 1170 original publications in Chinese from the China National Knowledge Infrastructure database and 394 publications in English from the Web of Science database. The results show that the literature associated with water footprint research has expanded significantly. The number of papers published increased from 104 in 2003–2006 to 735 in 2015–2018. Water footprint research has been applied to agricultural, industrial, and regional water resource management to quantify the impact of human activities on water resources and the environment. Water footprint metrics were extracted for regional comparisons. There are obvious regional characteristics of the water footprint in China, but the uncertainty of results makes further investigation necessary. Further water footprint modeling and field experimental research is needed to explore the water–ecological environment under complex systems.

Sustainability Evaluation Based on a Three-Dimensional Ecological Footprint Model: A Case Study in Hunan, China

Under the concept of green development, the promotion of ecological sustainable development capability has become an important policy objective of the Chinese government. Based on the three-dimensional ecological footprint model, this paper analyzes the ecological footprint, ecological carrying capacity, and ecological sustainable development capacity of Hunan province from 2005 to 2015. The results show that the total ecological footprint of Hunan increases from 2005 to 2015, in which the forest land ecological footprint accounts for the largest proportion. The ecological footprint depth is always greater than 1, indicating that Hunan has been in a state of ecological deficit; in the context of the distribution, the ecological pressure of Hunan shows a “high in surround while low in central” pattern. The results about the ecological footprint diversity index show that although the ecosystem of Hunan is stability, the level of eco-economic development ability is low. The ecological efficiency represented by GDP per unit of ecological footprint shows that Hunan’s ecological efficiency increases with an average rate of 13.12% annually during 2005–2015 because of the improvement of the factor substitution.

Spatial Pattern Evolution and Optimization of Urban System in the Yangtze River Economic Belt, China, Based on DMSP-OLS Night Light Data

It is of great significance to research the spatial pattern of the urban system of the Yangtze River economic belt to analyze the characteristics and laws of the spatial structure of the Yangtze River economic belt and to promote the optimal development of the urban system of the Yangtze River economic zone. In this paper, the time data of the Yangtze River economic zone are corrected using Landsat satellite data and the clustering analysis method. The threshold of the urban built area is obtained by comparing the auxiliary data with other auxiliary data. Based on this threshold, a total of eight typical landscape pattern indicators—including the total area of the landscape, the total patch number, and the aggregation index—are used, and then FRAG-STATS 4.2 software is used to analyze the spatial pattern of urban development in the Yangtze River economic zone from 1992 to 2013. The results show the following: (1) During the period from 1992 to 2013, the urbanization of the Yangtze River economic zone expanded rapidly; the area of urban built-up area increased by a factor of 9.68, the number of patches increased by a factor of 2.39, and the patch density increased greatly, indicating that the Yangtze River economic zone, with an increasing number of towns and urban areas, continues to expand. (2) The complexity of the landscape patch shape gradually increased, the small and medium-sized cities continued to grow, more small towns emerged, and the total length of the border and the average density had average annual growth rates of 21.56% and 21.58%; the degree of aggregation and the mutual influence are increasing. (3) The maximum plaque index and the aggregation index show an overall declining trend. However, there are some fluctuations and disorder in the process of evolution, such as the total area of the landscape, the total patch number and the total patch density, which reflects that the Yangtze River economic zone is in the process of urbanization and has irregular and disordered characteristics.

Long-Term Surface Water Dynamics Analysis Based on Landsat Imagery and the Google Earth Engine Platform: A Case Study in the Middle Yangtze River Basin

Dynamics of surface water is of great significance to understand the impacts of global changes and human activities on water resources. Remote sensing provides many advantages in monitoring surface water; however, in large scale, the efficiency of traditional remote sensing methods is extremely low because these methods consume a high amount of manpower, storage, and computing resources. In this paper, we propose a new method for quickly determining what the annual maximal and minimal surface water extent is. The maximal and minimal water extent in the year of 1990, 2000, 2010 and 2017 in the Middle Yangtze River Basin in China were calculated on the Google Earth Engine platform. This approach takes full advantage of the data and computing advantages of the Google Earth Engine’s cloud platform, processed 2343 scenes of Landsat images. Firstly, based on the estimated value of cloud cover for each pixel, the high cloud covered pixels were removed to eliminate the cloud interference and improve the calculation efficiency. Secondly, the annual greenest and wettest images were mosaiced based on vegetation index and surface water index, then the minimum and maximum surface water extents were obtained by the Random Forest Classification. Results showed that (1) the yearly minimal surface water extents were 14,751.23 km2, 14,403.48 km2, 13,601.48 km2, and 15,697.42 km2, in the year of 1990, 2000, 2010, and 2017, respectively. (2) The yearly maximal surface water extents were 18,174.76 km2, 20,671.83 km2, 19,097.73 km2, and 18,235.95 km2, in the year of 1990, 2000, 2010, and 2017, respectively. (3) The accuracies of surface water classification ranged from 86% to 93%. Additionally, the causes of these changes were analyzed. The accuracy evaluation and comparison with other research results show that this method is reliable, novel, and fast in terms of calculating the maximal and minimal surface water extent. In addition, the proposed method can easily be implemented in other regions worldwide.

Impacts of rapid urbanization on the water quality and macroinvertebrate communities of streams: A case study in Liangjiang New Area, China

Rapid urbanization in China has dramatically deteriorated the water quality of streams and threatening aquatic ecosystem health. This study aims to 1) assess the impacts of urbanization on water quality and macroinvertebrate composition and 2) address the question of how urbanization affects macroinvertebrate distribution patterns. Environmental variables over multispatial scales and macroinvertebrate community data were collected on April (dry season) and September (wet season) of 2014 and 2015 at 19 sampling sites, of which nine had a high urbanization level (HUL), six had moderate urbanization level (MUL) and four had low urbanization level (LUL), in the Liangjiang New Area. The results of this study showed that macroinvertebrate assemblages significantly varied across the three urbanization levels. The sensitive species (e.g., EPT taxa) were mainly centralized at LUL sites, whereas tolerant species, such as Tubificidae (17.3%), Chironomidae (12.1%), and Physidae (4.61%), reached highest relative abundance at LUL sites. The values of family biotic index (FBI) and biological monitoring working party (BMWP) indicated the deterioration of water quality along urbanization gradient. Seasonal and inter - annual changes in macroinvertebrate communities were not observed. The results of variation partitioning analyses (CCAs) showed that habitat scale variables explained the major variation in macroinvertebrate community composition. Specifically, the increased nutrient concentrations favored tolerant species, whereas high water flow and substrate coarseness benefitted community taxa richness, diversity and EPT richness. Considering the interactions between scale-related processes, the results of this study suggested that urbanization resulted in less diverse and more tolerant stream macroinvertebrate assemblages mainly via increased nutrient concentrations and reduced substrate coarseness.

Smart neighbourhood

Purpose

This paper aims to identify the key factors to design efficient, healthy and potentially economical neighbourhood places in the surroundings of smart cities to reduce the urban polarization for the sustainable urban development.

Design/methodology/approach

A two-stage methodology is followed. First, the key factors for neighbourhood are identified from literature studies. The selected factors are validated by sample t-tests. Second, the total interpretive structural modeling is used to interpret the complexity of relationships among various factors. Further, cross-impact matrix multiplication is applied for classification analysis to find the most driving factors for neighbourhood design.

Findings

The contribution of this research is to show hierarchical relationships among the various factors to design the neighbourhood places as smart from the perspectives of city planners and decision makers.

Research limitations/implications

The applicability of the research findings is limited to developing countries mainly where population is large and most of cities have high pressure on its infrastructure to fulfil the citizens’ demands.

Practical implications

This paper will aid policymakers, city planners and government officials to design a sustainable smart city model in which smart neighbourhood would also be the potential solution to decrease pressure on a city’s critical infrastructure especially in developing countries.

Social implications

A smart city could be considered as the centre point of smart initiatives to develop a place smart, and it should continue beyond the city boundaries to enhance the facilities, services, resources utilization and working environment in neighbourhood places also.

Originality/value

The study explores the various literature on neighbourhood planning and then link with smart city development as current need of urban development scenario. The authors propose a hierarchical relation framework to develop the neighbourhood places as smart places to meet the future demand of urbanization in developing countries like India.

Using multivariate techniques to assess the effects of urbanization on surface water quality: a case study in the Liangjiang New Area, China

Rapid urbanization in China has been causing dramatic deterioration in the water quality of rivers and threatening aquatic ecosystem health. In this paper, multivariate techniques, such as factor analysis (FA) and cluster analysis (CA), were applied to analyze the water quality datasets for 19 rivers in Liangjiang New Area (LJNA), China, collected in April (dry season) and September (wet season) of 2014 and 2015. In most sampling rivers, total phosphorus, total nitrogen, and fecal coliform exceeded the Class V guideline (GB3838-2002), which could thereby threaten the water quality in Yangtze and Jialing Rivers. FA clearly identified the five groups of water quality variables, which explain majority of the experimental data. Nutritious pollution, seasonal changes, and construction activities were three key factors influencing rivers' water quality in LJNA. CA grouped 19 sampling sites into two clusters, which located at sub-catchments with high- and low-level urbanization, respectively. One-way ANOVA showed the nutrients (total phosphorus, soluble reactive phosphorus, total nitrogen, ammonium nitrogen, and nitrite), fecal coliform, and conductivity in cluster 1 were significantly greater than in cluster 2. Thus, catchment urbanization degraded rivers' water quality in Liangjiang New Area. Identifying effective buffer zones at riparian scale to weaken the negative impacts of catchment urbanization was recommended.