Impact of rapid urbanization on the threshold effect in the relationship between impervious surfaces and water quality in shanghai, China☆
Graphical abstract
Introduction
Rapid urbanization leads to changes in water quality (Kumar et al., 2015; Naqvi et al., 2016); a regression model shows that approximately 94% of the variation in water quality can be explained by industrial landscape in Shanghai, China (Ren et al., 2003). Impervious surfaces is a result of urban expansion, and has recently emerged as an environmental indicator, especially for water quality, in that, during storm events, nitrogen and phosphorus nutrients, microbes, heavy metals, and organic toxic substances accumulated on impervious surfaces are transported into water by runoff (Kuang et al., 2013; Lu et al., 2014; Morabito et al., 2016; Moriasi et al., 2007; Santos Ferreira et al., 2016).
Numerous studies concluded that the threshold effect is a factor in the relationship between the percentage of total impervious area (PTIA) and water quality (Kato and Ahern, 2011; Pearson et al., 2018), but a few studies also found no threshold effect in some areas (Kuang, 2012). It was found that the expansion and aggregation of impervious surfaces were the reasons for stream deterioration in regions with higher PTIA (Ilias et al., 2008; Jordan et al., 2014a, 2014b, Li et al., 2018, Peters, 2009, Thornhill et al., 2017, Xiao et al., 2016). As one of the key parameters of water quality and river health, the theory of threshold effect has been practically applied in river basin planning and management in many countries (Li et al., 2016; Mantas et al., 2016).
However, in most studies, a specific rather than long time period was observed to focus on the threshold effect with regard to the relationship between impervious surfaces and water quality. Most of these studies selected natural watersheds as study areas, such that watershed boundaries could be delineated using GIS techniques (Pandey et al., 2009, 2011; Rajasekhar et al., 2018). There are very few studies concerning areas with complex river networks and unclear watershed boundaries, such as Shanghai (adjacent to East China Sea), one of the largest cities in the world, where human activities and rapid urbanization since the 1980s have considerably altered the regional surfaces, including both land uses and the river network. Threshold effect is of great significance for urban planning and river management. However, it is unclear whether the threshold changed during past urbanization decades.
This study aims to determine the effects of the threshold in the relationship between impervious surfaces and water quality in Shanghai (a high-density river network area), detect if there is a temporal variation trend of the threshold, and disclose the factors, like meteorological conditions, influencing the thresholds for water quality indicators.
There are two hypotheses of this study, firstly, with the improvement of urban management, water quality in urban area will get better and better, it will get closer and closer to rural area, and eventually there may be no difference between urban and rural. In the earlier stage of urbanization, non-point source pollution caused by impervious surfaces may be more significant, therefore, the threshold effect between PTIA and water quality is more obvious. However, in the later stage, the impervious surfaces of the city becomes cleaner and the rainwater collection capacity is getting more developed, so there is less non-point source pollution, and PTIA might no longer be an important factor determining water quality, the threshold effect is no longer apparent. Secondly, the threshold effect would be affected by many factors, in which meteorological conditions may not be ignored. According to the theory of heat island effect and rain island effect, area with higher PTIA will lead to higher air temperature, which will further lead to decreased water quality, that is, temperature would intensify the threshold effect, and area with more precipitation will increase non-point source pollution and cause deteriorated water quality, so increased precipitation will also exacerbate the threshold effect between PTIA and water quality.
To achieve the objectives of this study, a rapid urbanization period (1989–2010) was used to determine how the threshold effect manifests and changes within the relationship between impervious surfaces and water quality. Firstly, a total of 240 sample land uses in Shanghai were selected to obtain impervious surface coefficients (ISC) of each land use. Secondly, geographical buffers were created as proxies of hydrological units to demonstrate their relationship, and a segmented regression model in R software was used to determine the threshold of the relationship between impervious surfaces and water quality. Finally, the impact of rapid urbanization and meteorological conditions on the threshold effect were discussed.
Section snippets
Study area
This study focuses on Shanghai, China, one of largest cities in the world, with a population of 24.00 million (2018) and an area of 6,340.50 km2. It is located on the Yangtze River Delta, a plain, reticular river network area facing the East China Sea (Wang et al., 2012). There are 43,104 streams in Shanghai with a very high stream density of 4.54 km/km2 (Shanghai Water Authority, 2018), and 48 monitoring stations were established for water quality in most main river channels (Fig. 1).
PTIA increased from 1989 to 2010 in shanghai
From Fig. 2, the average PTIA of the 48 hydrological units increased significantly, and the quantity of hydrological units with lower PTIA decreased significantly. The average PTIA of all hydrological units increased from 32.44% to 44.76% from 1994 to 2010 in Shanghai. For the year 1989, PTIA is 44.66% because the land use data mentioned above included only half of Shanghai—many suburban areas were missing. Respectively, for the composition of PTIA, the percentage of hydrological units with
Threshold of the PTIA
Arnold and Gibbons (1996) found that a PTIA more than 10% signaled a substantial change in water quality, and a PTIA above 30% indicated a second substantial change. Kim et al. (2016) found significant positive linear relationships between the percentage of impervious surface area (PISA, similar to PTIA) and BOD, CODMn, TOC, and TP and defined the threshold value of PISA for these parameters as 9.80%. Conway (2007) indicated that a rapid increase in pH may be associated with an impervious
Conclusions
There is an obvious threshold effect between impervious surfaces and all water quality indicators, except DO, which shows a linear negative relationship with impervious surfaces. The threshold and threshold effect size is different in terms of water quality indicators. The threshold is not a constant but increases with urbanization level, which may be due to the enforcement of stream management projects. In addition, the impact of impervious surfaces on water quality decreased significantly
Funding
This study was funded by the National Key R&D Program of China (No. 2019YFC0408205) and National Natural Science Foundation of China (No. 41101550).
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
We would like to thank Professor Wu Jianping of the Key Laboratory of Geographic Information Science, Ministry of Education of East China Normal University for his work in the interpretation of the Shanghai remote sensing data. Thanks also give to Shanghai Meteorological Information and Technical Support Center.
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This paper has been recommended for acceptance by Charles Wong.