Urban Surface Water Quality, Flood Water Quality and Human Health Impacts in Chinese Cities. What Do We Know?

Abstract

Climate change and urbanization have led to an increase in the frequency of extreme water related events such as flooding, which has negative impacts on the environment, economy and human health. With respect to the latter, our understanding of the interrelationship between flooding, urban surface water and human health is still very limited. More in-depth research in this area is needed to further strengthen the process of planning and implementation of responses to mitigate the negative health impacts of flooding in urban areas. The objective of this paper is to assess the state of the research on the interrelationship between surface water quality, flood water quality and human health in urban areas based on the published literature. These insights will be instrumental in identifying and prioritizing future research needs in this area. In this study, research publications in the domain of urban flooding, surface water quality and human health were collated using keyword searches. A detailed assessment of these publications substantiated the limited number of publications focusing on the link between flooding and human health. There was also an uneven geographical distribution of the study areas, as most of the studies focused on developed countries. A few studies have focused on developing countries, although the severity of water quality issues is higher in these countries. The study also revealed a disparity of research in this field across regions in China as most of the studies focused on the populous south-eastern region of China. The lack of studies in some regions has been attributed to the absence of flood water quality monitoring systems which allow the collection of real-time water quality monitoring data during flooding in urban areas. The widespread implementation of cost effective real-time water quality monitoring systems which are based on the latest remote or mobile phone based data acquisition techniques is recommended. Better appreciation of health risks may lead to better flood risk management. In summary, there is still a limited understanding of the relationship between urban surface water quality, flood water quality and health impacts. This also holds true for Chinese cities. Given the widespread and frequent occurrence of urban flooding, further research into this specific cross-cutting field is mandatory.

Objectives and Indexes for Implementation of Sponge Cities—A Case Study of Changzhou City, China

“…In the Yangtze river delta, local governments such as the provincial and city governments have to implement the sponge city construction in new development areas. The water system of these areas consists of a dense river network with a slow flow rate of the rivers [8,14]. These newly developed urban areas are receiving irregular precipitation, and have a weak water environmental buffering capacity and thus comprise a vulnerable ecosystem.…”

“…Sea-level rise, economic development, and increased frequencies and intensities of storms will require that we continuously have to invest in adapting our flood risk management (FRM) systems, including flood protection infrastructure such as levees, dams and urban drainage systems [3][4][5][6][7]. Water pollution in developed coastal regions due to the higher industrialization and rapid urbanization has become a very critical environmental issue and require proper scientific and effective measures to solve this problem [8]. Dealing with this crisis calls for a multi-stakeholder approach (involving governments, local councils, and citizens).…”

“…A sponge city refers to sustainable urban development including flood control, water conservation, water quality improvement and natural ecosystem protection. It envisions a city with a water system which operates like a sponge to absorb, store, infiltrate and purify rainwater and releases it for reuse when needed [8]. The sponge city program, launched by the Chinese government in 2014, takes inspiration from the low impact development (LID), best management practices (BMPs) and best planning practices (BPPs) and green infrastructure (GI) in the US [17,18] and Canada [19,20] sustainable drainage systems or sustainable urban drainage systems (Sus Drain/SUDSs) and integrated urban water management (IUWM) in the UK [21,22], alternative techniques (ATs) in France [23] and other European countries [24] and water sensitive urban design (WSUD) in Australia [25] and New Zealand [26].…”

Using Real-Time Data and Unsupervised Machine Learning Techniques to Study Large-Scale Spatio–Temporal Characteristics of Wastewater Discharges and their Influence on Surface Water Quality in the Yangtze River Basin

“…Luckily, at present, more data are available and data-driven approaches and statistical (or numerical) models are now playing an increasingly important role in water management, so that environmental decision support systems (EDSSs) are more reliable and are capable of coping with real-world environmental systems [9][10][11]. Numerous researchers have analyzed real-time data to support the management of urban water and water supplies in developed countries [12][13][14][15], but this approach has not often been used to manage large rural watersheds or wastewater [16,17].…”

Water Quality Evaluation of the Yangtze River in China Using Machine Learning Techniques and Data Monitoring on Different Time Scales

“…Statistical and numerical models enable environmental decision support systems (EDSS) to be more reliable and powerful in coping with real-world environmental systems [15]. Real-time data are widely used in urban water management and by water utilities in developed countries [16][17][18][19][20], but rarely in rural watershed management, especially in large watershed management [21,22]. In China, the rapidly growing economy and population is generating widely distributed polluted surface water throughout the country.…”