Which common urban characteristic contributes most directly to the environmental problem of flooding?

12.8 Concluding Remarks

Urban flooding is a major problem in many parts of the world and is one of the most natural disastrous event which takes place every year, especially in the coastal cities. Urban flood, being a natural disaster, cannot be avoided; however, the losses occurring due to flooding can be prevented by proper flood mitigation planning. As such, it is necessary to have a proper estimation of flood extent and flood hazard for the different flow conditions so that proper flood evacuation and disaster management plan can be prepared in advance. The coastal urban flooding is a complex phenomenon which may occur in various forms such as: urban flooding due to high intensity rainfall; due to inadequate drainage and flooding caused by overtopping in the channels or rivers; flooding due to high tides, etc. In coastal urban cities like Mumbai, mostly severe flood scenarios take place due to combination of surface flooding, channel overtopping, and tidal flooding. For effective coastal urban flood management and mitigation plans, the possible flooding scenario is to be simulated for extreme rainfall events, or various return periods of rainfall and other design scenarios. This chapter discussed the integrated approach of coastal urban flood simulation using computer models, GIS, and remotely sensed data. Various urban flood models available are discussed briefly. Two of the urban flood models, viz. IFAM and HEC-HMS-RAS, are discussed in detail and their applications are illustrated through two case studies.

The IFAM model is an integrated raster-based flood inundation model where overland flow has been modeled using the 1D mass balance approach, 1D channel flow has been modeled using diffusion wave approximation, and floodplain flow has been modeled using the quasi-2D storage cell-based model. The model has been applied for a coastal urban watershed of Navi Mumbai for an extreme rainfall event of July 26, 2005. The case study demonstrated the application of IFAM model for urban flood simulation. The HEC-HMS-RAS is an open source model which can be effectively used in flood simulation, as demonstrated in the second case study. As demonstrated, both models have good potential to be used in urban flood simulation studies. Flood plain and flood hazard maps generated by these models can be used as flood evacuation planning and flood disaster management planning by the municipal authorities.

3.4.2 Cities and Flood Vulnerability

In Asia, urban flooding is a frequent phenomenon. Almost every city is vulnerable to urban flooding in one way or another, and urban dwellers are at high risk. In urban environments, farmland, vegetation cover, and bare soil have been converted into built-up areas. As a result, water runs off of the concrete structures, sometime known as pluvial flooding or urban flooding. In urban areas, with rapid increase in impermeable surfaces and urban development, the likelihood of flooding has increased. Similarly, the intensity of urban floods becomes higher with prolonged rainfall. The probability of urban flooding is expected to further increase with changing climate (Carmin et al., 2013). In Asia, numerous coastal cities are exposed to both urban and coastal floods, whereas inland cities are vulnerable to flash floods, river floods, or urban floods. In developing countries, human encroachments onto the active flood channel, poor flood management strategies, lack of flood early warning systems, and disposal of solid waste in drainage lines are the major causes of urban flooding.

In Asian cities, populations grow gradually, and these new residents need shelter to accommodate their needs. As urban populations increase, the existing resources and infrastructure are more and more pressured. At the same time, land values increase, and higher buildings are constructed to fulfill the housing demand. Finally, the most pronounced aspect of cities in the developing world is haphazard urban expansion over valuable natural resources. In all these cases, poor people are the ones who have no choice but to build shelter on illegal, unsafe land in high-risk zones. This situation, where people consistently encroaching onto the flood prone areas narrow the channel and in turn reduce the channel carrying capacity, is very common in almost every megacity. These are some of the major factors contributing to enormous flood damage in urban areas.

Hat 1: Data owners and providers

The insurance industry holds extensive data on where and when losses from damages have occurred, where claims have been paid out, and in some cases the cause of the damage, and therefore where risks and exposure are most significant. The data are used internally to develop models and to understand consequences of a variety of risks, including more recently, climate change. Catastrophe risk modeling chains are one of the main tools of the (re)insurance industry. These models offer a comprehensive analysis of the entire risk loss chain: hazard, vulnerability, and damage. Beyond the compensation role of the (re)insurance industry, new roles in prevention are emerging, notably through risk modeling (Le Quesne et al., 2017; Quantin, 2018). These tools developed by the insurance industry for estimating and managing catastrophic insurance risks can be adapted to assess the impacts of extreme weather events predicted with climate change and evaluating the effectiveness of nature-based protective or preventive measures (CCR, 2018; Walker et al., 2016; DERRIS Project, 2018; Narayan et al., 2016).

Mainstreaming natural solutions into decision-making requires an expansion of high-quality demonstration projects provided through practical methodologies (indicators and criteria) and good documentations (Van Wesenbeeck et al., 2017). The integration of NBS in risk modeling remains a challenge, although there are now relevant examples on the use of risk modeling to assess the role of NBS (CCR, 2018; Beck and Lange, 2016; Beck et al., 2018; Cohn, 2017; Maynard et al., 2017; Reguero et al., 2018). Relying on the catastrophe loss risk structure, the (re)insurance industry could be able to identify hazard areas and the most exposed areas, quantify damages for different NBS scenarios, and compare solutions with methods such as cost–benefit analysis (CBA) and multicriteria analysis (MCA).

27.2.5.3 Drivers for the adoption of WSUD approaches

The primary drivers for adoption of the SCC were to address the worsening problems of urban flooding, water pollution, and water security. In Wuhan, climate change and further urbanization are projected to exacerbate existing flood risks (Dai et al., 2017). The seriousness of the flood risk was demonstrated in 2016, when more than 30 people were killed in an urban flood (Dai et al., 2017). Water pollution is also a critical issue for Wuhan as more than one-third of the rivers exceed prescribed water quality standards (Dai et al., 2017). Water pollution is caused by partially treated domestic and industrial wastewater being discharged to the river together with pollutants from contaminated road surfaces and agriculture.

Road Surface Water Balance

Road water is an important parameter to judge the wetness of road surface. For urban road, road water depth is used to predict urban flooding (Yin et al., 2016; Zhou et al., 2017), which is a severe disaster especially in developing and coastal cities. To forecast the road water depth, road water balance equation (Meng, 2018) was built. Fig. 2 is the schematic map of road surface water balance. The main variables which control the road water depth are precipitation, impervious surface evaporation (Meng, 2018), roof interception, drainage and infiltration (if the porosity is not zero).

6.3.1.6 Sponge Cities

The concept of Sponge Cities is another natural flood management technique which is being implemented in China (Radcliffe, 2017). Following recent urban flooding problems, which caused significant loss of life and severe economic impacts, the Chinese government has implemented the Sponge Cities program to improve flooding using LID processes. It aims to make the city act like a sponge to absorb rainfall, rather than cause runoff. The program is based in 30 cities, including Beijing and Shanghai, and is described in more detail in Chapter 1. Each city receives USD$60–90M per year over 3 years to implement sponge city initiatives, all of which align well with both natural flood management and WSUD. The initiative includes natural ecosystem conversion, degraded ecosystem restoration and remediation, and LID practices, as opposed to conventional gray infrastructure (Jiang et al., 2017). At this early stage, there is little available evidence of its effectiveness, and there is much to be done to finalize implementation of the strategy (Liu et al., 2017). However, interested practitioners are advised that the Sponge Cities initiative may well provide significant research opportunities in the realm of flood and peak flow management in the coming years.

SDG 11: Make cities and human settlements inclusive, safe, resilient, and sustainable

Nature in cities has been shown to benefit water quality and quantity in numerous ways, including through improved retention of stormwater, reduced peak flows and urban flooding, enhanced aquifer recharge, and improved water quality in urban lakes, rivers, and streams (Keeler et al., 2019). NBS are often presented as win-wins for cities by improving urban welfare, enhancing resilience and adaptation to climate change, and supporting habitat for urban biodiversity. However, recent work has also highlighted the potential negative consequences of implementing NBS in the form of ecosystem “disservices” such as degraded air quality and pollen production from tree canopy, nutrient loading to urban lakes from decomposing leaf litter, and infrastructure damage from tree roots and limbs. Particularly in cities, the benefits of NBS are mediated by complex social, ecological, and technical factors that impact where, when, and for whom NBS deliver benefits or costs (Keeler et al., 2019; McPhearson et al., 2015).

Case study 1: Reducing urban flood risk in China

Rapid urbanization like the kind that China has experienced in the first quarter of the twenty-first century brings many challenges: ecological degradation, water pollution, heat-island effects, and urban flooding. Such urbanization—combined with changing rainfall patterns linked to climate change—increases flood risk and decreases urban resilience (Qiao et al., 2020). In 2013, the Chinese government responded with the national Sponge City Construction Project (SCCP), originally aimed at addressing stormwater management, which quickly grew into a much larger program (Qiao et al., 2020). The term “sponge city” refers to the city’s new ability to respond to environmental changes and natural hazards by absorbing and purifying water during weather events and then releasing the stored water during times of scarcity (Qiao et al., 2020). As the director of water management at Arcadis China, Wen Mei Dubbelaar, explains, the purpose is to “give space back to the river…[instead of] fighting the water” (Li, 2019). With anticipated costs around USD 1.5 trillion (10 trillion Yuen) and covering 657 cities, the goal of the SCCP is to combine gray and green infrastructure to help reverse the effects of rapid urbanization through rainwater harvesting, ecological restoration, more effective flood control, and water quality improvements (Jia et al., 2017).

Despite national support, implementation of the SCCP has faced several challenges including: lack of understanding regarding NBS within provincial and local government offices, limited technical guidance for implementing combined gray and green infrastructure, lack of close coordination among local stakeholders and the national government, and financial hurdles (Jia et al., 2017; Chen and Guo, 2019). To enhance local coordination and overcome these challenges, Sponge City pilot cities have set up “Sponge City Offices” where all bureaus connected to urban water management are now represented, mirroring the close multiagency collaboration for the SCCP at the ministry level (Jia et al., 2017). Local authorities are also able to adapt SCCP projects to fit their needs. As of 2017, nearly 130 cities across China were creating plans to become sponge cities (Liu et al., 2017).

The SCCP is a central part of China’s DRR strategy and reflects all four priorities from the Sendai Framework: it understands disaster risk, strengthens the governance needed to manage that risk, invests in resilience, and enhances preparedness for a better response. In other words, it moves from reactive to proactive management of urban flooding, with an emphasis on flexible solutions designed to function for decades to come.

3.2 Disaster risk in a changing climate

There is high confidence that warming trends and increasing temperature extremes have been observed across most of the Asian region over the past century (Hijioka et al., 2014). Increasing numbers of warm days and decreasing numbers of cold days have been observed, with the warming trend continuing into the new millennium. Precipitation trends including extremes are characterized by strong variability, with both increasing and decreasing trends observed in different parts and seasons of Asia. The evidence indicates that climate has changed in Asia and future climate change will threaten resilience and negate development in the region.

Future risks that have been identified for Asia cover present time, the near term, a world that is 2-degrees warmer and a world that is 4-degrees warmer (Hijioka et al., 2014). The risks are based on available literature and expert judgment. A majority of the risks have a direct impact on society in terms of health, well-being, and safety. The key risks identified cover a range of fast-onset and slow-onset hazards. They are as follows:

Key Risk 1: Increased [coastal, riverine, and urban] flooding leading to widespread damage to infrastructure and settlements in Asia (medium confidence).

Key Risk 2: Increased risk of heat-related mortality (high confidence).

Key Risk 3: Increased risk of drought-related water and food shortage causing malnutrition (high confidence).

Key Risk 4: Increased risk of flood-related deaths, injuries, infectious diseases, and mental disorders (medium confidence).

Key Risk 5: Increased risk of water- and vector-borne diseases (medium confidence).

Key Risk 6: Increased risk of crop failure and lower crop production could lead to food insecurity in Asia (medium confidence).

Key Risk 7: Water shortage in arid areas of Asia (medium confidence).

Key Risk 8: Exacerbated poverty, inequalities, and new vulnerabilities (high confidence).

Key Risk 9: Coral reef decline in Asia (high confidence).

Key Risk 10: Mountain-top extinctions in Asia (high confidence).

In Asia, extreme precipitation is expected to trigger fast-onset floods and landslides, where the impacts are concentrated in urban areas. This has serious implication for Southeast Asia where the majority of disasters that affect the region are fast-onset and climate driven. Between 1970 and 2008 over 95% of fatalities due to climate-related disasters were in developing countries (IPCC, 2012). In low-income countries, losses amount to about 0.3% of the GDP and in high-income countries they are 10-fold lower, at 0.1% of the GDP. However, economic losses are highest in middle-income countries, with losses amounting up to 1% of the GDP.

Extreme climate events linked to precipitation and high temperatures are also expected to trigger slow-onset events and have an increasing impact on human health, food and water security, livelihoods, poverty, and create new vulnerabilities, with the type and magnitude of impact varying across Asia. More frequent and intense heat waves in Asia will increase mortality and morbidity in vulnerable groups. Increases in heavy rain and temperature will increase the risk of diarrheal diseases, dengue fever, and malaria. Increases in floods and droughts are expected to exacerbate rural poverty.

9.1.1 Individual responsibility versus national policy choices

In a sparsely populated area (often with agricultural use), responsibilities are mostly clear and straightforward. The population has a large individual responsibility. Often there are no or very rudimentary flood defenses and flood alerts are not always available. In the 21st Century, however, the state is almost always responsible for flood alerts and the state or private insurance companies can provide flood insurance. With the way flood risk is perceived, the reliability of flood alerts and the cost of insurance will influence personal choices.

In the past, inhabitants often fended for themselves. They were flooded frequently and often developed a local strategy to cope with floods. Building houses on artificial mounds and stilts can be considered a traditional way of coping with floods. Examples of artificial mounds as local flood prevention solutions along North Sea coast in the Netherlands and Germany were first described by Plinius the Elder (who lived from AD 29 to AD 79) [DUI 84]. Traditional houses in deltas in South East Asia were often built on stilts. Another example is the houses in the Meuse valley in the Netherlands at the beginning of the 20th Century, with tiled floors. Tiled floors allow for flooding of the ground floor. After a flood (often weeks or months), cleaning is easy and life can continue.

In case the occurrence of a flood is an exception, inhabitants of flood-prone areas tend to forget the flood risk. This can be because of a certain high level of flood protection like in the Netherlands [SLO 12] or because flood events such as flash floods happen very locally [MEA 15]. There is insufficient local memory and institutional memory, especially at the local and regional government levels. Furthermore, it is difficult to remain aware of flood risk when the population density of an area increases and many people come from other areas e.g. people who retire on the French coast [KOL 10]. In such situations, when a new flood occurs, damages are relatively high. The houses for instance, are, built and furnished in such a way that they are extra vulnerable for floods. In addition, the inhabitants are not aware that they can take precautionary measures, such as moving the car to higher ground and moving furniture upstairs in the house. This phenomenon is illustrated by the experiences with the river floods from December 1993 to January 1995 in the Netherlands and Germany. The January 1995 flood levels [RWS 95] were higher than December 1993 [RWS 94]. However, the 1995 damages were significantly lower due to improved precautionary measures by the inhabitants (removing cars and furniture on time) and by the authorities, e.g. more temporary dikes [GOU 95]. A second example is the experiences in Cologne, Germany. The damages in Cologne in the 1995 flood were some 40% of those from 1993 (30 million euros in 1995 versus 70 million euros in 1993). For the whole Rhine basin in Germany, the damages were 0.75 billion euros in the winter of 1993/1994 and 0.25 billion euros in 1995 [ENG 97].

The room for individuals, choices is, however, limited. This is because individuals depend on policy choices, or the lack of choices, at national, regional or local government levels. These policy choices determine flood risk management measures, where people can live, which areas can be developed, if there are flood defenses, how they are maintained, if there is an affordable flood insurance and if sufficient money is being put into the existing flood defenses (improvement and maintenance). In many cases, the physical planning is not based on flood risk management issues. This was the case in the Netherlands from the 1960s and 1970s onwards. The urban flooding in 1998 due to an extreme rainfall event was a wakeup call [SLO 12]. That is the reason why, in the Netherlands, ample attention is paid to this aspect through the national Delta Program in the Physical Planning Adaptation Subprogram1. Measures to reduce damages from extreme rainfall events are relatively cheap to implement. Existing infrastructure can be used in a different way, and natural reserves, often wetlands, can be used as temporary flood storage. This asks for a collaborative approach. Local infrastructure is often renewed every 20 to 30 years. New infrastructure can be adapted easily and at low cost to not cause additional harm. The region of Delfland in the Netherlands (The Hague and Rotterdam) suffered from comparable extreme rainfall events in 1998 and 2013. However, the 2013 events hardly caused any damage, due to some investments and different protocols (personal communication with the flood risk managers).

In essence, flood risk management is always a trade-off between physical planning, acceptance and adaptation to flooding (building house above normal flood levels), protecting areas at risk with flood defenses, emergency services (see Figure 1) and tools to stimulate recovery as insurance and disaster funds.