Flood risk and its reduction in China

<p>Despite massive flood protection efforts, undertaken in China for millennia, disastrous floods continue to plague the country. We discuss flood hazard and flood risk in China, starting from observed changes and variability and then dealing with flood risk management and projections. We also refer to recognized unsolved problems in hydrology.</p><p><strong>Observed changes and variability</strong></p><p>First, we review results of change detection in observed records of variables related to water abundance, such as intense precipitation, high river flow, and flood damage in China. There is a strong inter-annual and inter-decadal variability, part of which may be due to climate variability, i.e. oscillation in the ocean-atmosphere system (ENSO - <em>El Ni</em><em>ño</em>-Southern Oscillation and PDO – Pacific Decadal Oscillation). Particular large flood events (e.g. in 1998 and 2016) coincide with high values of ENSO indices.</p><p><strong>Flood risk management</strong></p><p>In its efforts to reduce flood risk, China has undertaken both structural and non-structural measures. An emergency manager's nightmare is when several serious emergencies (e.g., covid pandemic and flooding) happen at once, as in the unprecedented covid year 2020, when also record-breaking precipitation occurred in China. Yet, emergency management made it possible to constrain the flood loss.</p><p><strong>Flood risk projections</strong></p><p>In the warming climate, flood risk is likely to increase over much of China. Projections of flood loss changes for global warming scenarios from 1.5° to 4.0°C above the preindustrial temperature are presented. Projections are based on runoff simulations by a hydrological model driven by multiple downscaled general circulation models, the national GDP projected at shared socio­economic pathways, and the “intensity–loss rate” function. Flood losses in China are projected to soar in the future, particularly in lowland regions subject to rapid economic growth. There is a considerable difference between flood losses corresponding to two global climate policy target thresholds, 1.5° and 2.0°C, amounting to over US$60 billion.</p><p>Available flood projections for China are not consistent. Since the spread is large, projections have to be interpreted with caution, because of the impact on decisions related to climate change adaptation and flood risk reduction.</p>

Floods are among the most costly natural hazards that affect Europe and Germany, demanding a continuous adaptation of flood risk management. While social and economic development in recent years altered the flood risk patterns mainly with regard to an increase in flood exposure, different flood events are further expected to increase in frequency and severity in certain European regions due to climate change. As a result of recent major flood events in Germany, the German flood risk management shifted to more integrated approaches that include private precaution and preparation to reduce the damage on exposed assets. Yet, detailed insights into the preparedness decisions of flood-prone households remain scarce, especially in connection to mental impacts and individual coping strategies after being affected by different flood types. This thesis aims to gain insights into flash floods as a costly hazard in certain German regions and compares the damage driving factors to the damage driving factors of river floods. Furthermore, psychological impacts as well as the effects on coping and mitigation behaviour of flood-affected households are assessed. In this context, psychological models such as the Protection Motivation Theory (PMT) and methods such as regressions and Bayesian statistics are used to evaluate influencing factors on the mental coping after an event and to identify psychological variables that are connected to intended private flood mitigation. The database consists of surveys that were conducted among affected households after major river floods in 2013 and flash floods in 2016. The main conclusions that can be drawn from this thesis reveal that the damage patterns and damage driving factors of strong flash floods differ significantly from those of river floods due to a rapid flow origination process, higher flow velocities and flow forces. However, the effects on mental coping of people that have been affected by flood events appear to be weakly influenced by different flood types, but yet show a coherence to the event severity, where often thinking of the respective event is pronounced and also connected to a higher mitigation motivation. The mental coping and preparation after floods is further influenced by a good information provision and a social environment, which encourages a positive attitude towards private mitigation. As an overall recommendation, approaches for an integrated flood risk management in Germany should be followed that also take flash floods into account and consider psychological characteristics of affected households to support and promote private flood mitigation. Targeted information campaigns that concern coping options and discuss current flood risks are important to better prepare for future flood hazards in Germany.

China is highly susceptible to flood disasters and subjected to great damage every year. Furthermore, the flood frequency has exhibited an increasing trend in recent years. Most flood events, including flash floods and river flood, are induced by rainfall. This study investigates annual variations of rainfall occurrence over China during the period from 2000 to 2015 at the national and regional scale using daily rainfall data from the Tropical Rainfall Measuring Mission. The Mann-Kendall test is performed for trend detection, and statistical data of flood damage published by China’s government, including destroyed crop area, damaged buildings, direct economic loss, percentage of GDP (gross domestic product), and death toll are correlatively analysed with rainfall occurrences. The results show that storm rain events show the greatest variation among three rainfall types (moderate rain, heavy rain and storm rain). The variation coefficients of rainfall over Northeast China, North China, and Northwest China are the highest, whereas that for Southwest China is the smallest. Moderate rain, heavy rain over Central China, and moderate rain over Southwest China exhibits decreasing trends, whereas the remaining exhibit increasing trends. The correlation between the rainfall occurrences and these flood damage indices at the national scale shows that only direct economic loss has a strong positive correlation with rainfall occurrences, and the other indices have weaker correlations. The correlation is strong in three north regions, except for death toll in Northwest China. In contrast, the correlation between flood damage and rainfall is weak in East China, Central China, Southwest China, and South China. Overall, death toll is strongly correlated with the number of damaged buildings, implying that flood fatalities in China are likely associated with building collapse, and are dominated by specific extreme events. This study can provide a scientific reference for flood management in China.

The rapid growth of impervious areas in urban basins worldwide has increased the number of impermeable surfaces in cities, leading to severe flooding and significant economic losses for civilians. This trend highlights the urgent need for methodologies that assess flood hazards and specifically address the direct impact on pedestrians, which is often overlooked in traditional flood hazard analyses. This study aims to evaluate a methodology for assessing the risk to pedestrians from hydrodynamic forces during urban floods, with a specific focus on Cúcuta, Colombia. The methodology couples research outcomes from other studies on the impact of floodwaters on individuals of different ages and sizes with 1D/2D hydrological modeling. Advanced computational algorithms for image recognition were used to measure water levels at 5‐s intervals on November 6, 2020, using drones for digital elevation model data collection. In Cúcuta, where flood risk is high and drainage infrastructure is limited, the PCSWMM (Computer‐based Urban Stormwater Management Model) was calibrated and validated to simulate extreme flood events. The model incorporated urban infrastructure details and geomorphological parameters of Cúcuta's urban basin. Four return periods (5, 10, 50, 100), with extreme rainfall of 3 h, were used to estimate the variability of the risk map. The output of the model was analyzed, and an integrated and time‐varying comparison of the results was done. Results show that the regions of high‐water depth and high velocity could vary significantly along the duration of the different extreme events. Also, from 5 to 100 years return period, the percentage of area at risk increased from 9.6% to 16.6%. The pedestrian sensitivity appears much higher than the increase in velocities or water depth individually. This study identified medium to high‐risk locations, which are dynamic in time. We can conclude dynamics are spatiotemporal, and the added information layer of pedestrians brings vulnerability information that is also dynamic. Areas of immediate concern in Cúcuta can enhance pedestrian safety during flash flood events. The spatiotemporal variation of patterns requires further studies to map trajectories and sequences that machine learning models could capture.

This study applied the interaction of social vulnerability and hazard to assess flood risk in three urbanized areas within the Pasig‐Marikina‐Laguna‐Lake catchment: Manila, Marikina, and Parañaque in Metro Manila, Philippines. This study examined risk patterns across different flood return periods (5, 50, and 100 years) in these urban river environments and provided both city‐wide and localized risk assessments. The social vulnerability to flood index (SVFI) was calculated using socioeconomic indicators, while the hazard index was derived from flood depth categories. Results show that city‐level risk indices are low to moderate, with Marikina consistently having the highest risk, followed by Manila and Parañaque. However, localized assessments reveal high‐risk areas within cities, with Manila being the most vulnerable to frequent floods (5‐year return period) and Marikina to less frequent but extreme events (50‐ and 100‐year return periods). Parañaque maintains the lowest risk profile across all scenarios. This study highlights the importance of considering both citywide trends and localized high‐risk areas in flood risk management. It provides valuable insights for disaster management planners and policymakers, enabling the development of targeted strategies for sustainable urban river management and flood risk reduction in rapidly urbanizing river systems. The methodology presented applies to other urban areas that face similar flood risks.

A city-wide approach to reduce the uncertainty regarding the spatial variability of urban flooding events is required in urban catchments. The goal of this study is the development of a modelling framework independent of the spatial scale to address the most hazardous areas in the current state and the future. The framework starts with the definition of the study objectives (e.g. reducing flood risk), which have a direct impact on the spatial and temporal scale, the used model approach, the data requirement and the level of detail. Furthermore, potentially hazardous areas will be identified with the potential flood risk index (PFRIi). The determination of this is a risk-based approach (R=E*V*H) which combines the exposition (E) with the vulnerability (V) and the hazard (H). The population density of each object and the total number of persons in the catchment will quantify the exposition. The vulnerability includes the number of past damage events and the object use. How accurate the modelled hazard is considered, depends on the used model approach: i) GIS-based; ii) only 1D; iii) only 2D; iv) 1D/2D models. The combination of H and V resulted in the risk factor (RFi) in four levels of detail depending on the used model approach. This allows both, the quantification of hazardous areas at the current state and the change of the PFRIi by future scenarios such as climate change and urbanization.PFRIi = nP,k * RFi / (Ak * ∑P)                                                                                                                                                                                     PFRIi=Potential Flood Risk Index; nP,k= number of Persons on a private ground k; Ak=total object area; =total number of persons in the catchment; Rfi= risk factor depending on the used model approach kThe GIS-based flow path analysis as the first level of detail can be used to identify the urban flooding hot spots. This allows the identification of hazardous sub-catchments in a city or high-risk private ground in a catchment quantified by the PFRIGIS. This is useful for further detailed analysis with other model approaches (e.g. 1D/2D model). The next steps are the implementation of the demonstrated framework for each level of detail in the city of Graz in Austria. Furthermore, the framework will integrate different climate scenarios based on a high-resolution climate model to address the impact of climate change on the urban drainage system quantified by the PFRIi.Keywords: urban flooding, urban flood modelling, risk assessment, future changes

The Northland river is characterised by having a short stream and large catchments. Heavy rains in the region trigger the rapid rise of the water levels and causes flooding, affecting the urban community in the flood plain with flash floods and river overflow as double threats. The government-initiated programs to protect urban communities such as ‘predict and mitigate’ but primarily focuses on physical infrastructure protection. While providing infrastructure is beneficial, developing a resilient community comprises more holistic strategies. There is a need for improving the local capacity to enhance resilience. A resilient, human-focused mitigation strategy which includes the affected communities, as well as the existing infrastructure, can reduce flood risks more efficiently. This paper explores the ways the Northland communities follow to mitigate existing flood risks, including their perceptions of the current flood protection strategies. This study investigates also the social and cultural elements that influence responses to flood risks. The main recommendation, of the study advocates a community-based risk management plan to complement the government’s strategy to efficiently mitigate flood risk in the urban Northland.

A novel framework for urban flood risk assessment: Multiple perspectives and causal analysis

Integration of quantitative precipitation forecasts with real-time hydrology and hydraulics modeling towards probabilistic forecasting of urban flooding

Floods are one of the most devastating natural hazards around the world, and flash floods are extremely dangerous to property and human lives. This study reviews the current flash flood forecasting in China and proposes a new methodology to develop a flash flood potential index (FFPI) based on GIS to further improve China's flash flood guidance system and national weather forecasting services. We collected datasets required to calculate the FFPI and tested a series of schemes to determine the method to calculate the FFPI over China. The result indicates that the calculated China's FFPI distribution can represent the risk of flash flood well, especially in Central and Southeast China. It is also implied that the southwest and western complex terrains are more susceptible to rain storms. Then we chose Yunnan Province as a test-bed and also yielded good results which can offer reference to the current China's flash flood forecasting system. Further research can be placed on incorporation of soil moisture and rainfall frequency components into the FFPI calculation method for dynamic warning and forecasting of flash floods.

In previous assessments of UK flood risk, flood hazard has often been poorly represented by low skill models. Meanwhile, assessments of future flood risk have lacked a detailed representation of future flood exposure. This study represents a significant step forward in both flood hazard and future exposure representation. Using a state-of-the-art climate-conditioned hydrodynamic model for fluvial, pluvial and coastal flooding paired with the latest UK shared socioeconomic projections of population (UK-SSP), we explore how climate-induced changes in flood hazard interact with increasing exposure due to population changes. Using a detailed exposure dataset, we are also able to explore discrepancies in current and future flood risk between residential property types.Our model values current yearly residential economic floods losses at £894 million, with fluvial flooding accounting for approximately 75% of these. This flood risk is not borne equally between the devolved British nations, however. In Scotland and Wales approximately 30% of local authorities have over £100 of annual flood losses per property, whereas only 4% of local authorities in England experience such levels. There are also significant discrepancies in flood risk by property type. Flats and terraced housing experience almost twice the rate of yearly inundations than detached and semi-detached housing. Under a high emissions climate scenario (RCP 8.5), by 2070 we estimate flood risk will increase by 29% whilst under a low emissions scenario (RCP 4.5) flood risk will increase by 10%. Similarly to current flood risk, these increases too are not borne equally across regions and property types.Whilst climate change is set to drive an increase in flood risk over the next 50 years, our study suggests that population dynamics may have potential for offsetting relative flood risk rises. In all SSP projections studied here (SSP1, SSP2 and SSP5), an increase in population drives an increase in the yearly rate of property inundations. As such, the highest increases in flood risk due to population change are seen in SSP5 (+50%). However, due to population growth predominantly occurring in low flood risk areas, relative flood risk decreases most in SSP5 (-10%). Similar changes, although smaller in magnitude, are seen under SSP1 and SSP2. Despite these decreases in relative flood risk due to population change, when paired to climate change, we still see significant increase in flood risk over the next 50 years. Consequently, low emissions scenarios, such as SSP1/RCP2.6, see the lowest increases in flood risk by 2070 (+5%). These results show a clear need for climate change mitigation actions in order to limit flood risk increases. However, this study presents a promising signal where population growth may limit the burden of increased flood risk, due to climate change.

Floods are the most common disaster in Canada. As results of rapid urbanization and climate changes, both frequency and risks of floods have been increased in Canadian urbanized areas, where the disasters have usually costlier impacts than in rural areas. Imagery data and technologies of optical remote sensing are helpful and can be applied for urban flood response and pre-disaster preparation. Especially high and very high optical remote sensing can be used for precise mapping of the floodwater distribution in dense urban areas and providing key information for disaster response management. In addition, the geospatial information about urban land surface and urban growth derived from optical remote sensing imagery can be the key inputs for urban flood risk analyses. In recent years, several case studies for different urban flood types, including fluvial (Calgary 2013, Ottawa-Gatineau 2017) and pluvial (the Greater Toronto Area) floods in Canada, have been carried out at Canada Centre for Mapping and Earth Observation, Natural Resources Canada. Methodologies/framework for urban floodwater mapping have been developed based on high resolution optical data, as well as the impacts of urban growth on the urban flash flood risks have been investigated using model simulations with remote sensing derived maps as inputs. This presentation demonstrates results from three Canadian urban flood case studies and introduces remote-sensing-based methodologies for different types of urban floods.

[Departement_IRSTEA]Eaux [TR1_IRSTEA]ARCEAU

In this chapter, the notion of flood risk is interpreted and factors influencing flood risk: hazard, exposure, and vulnerability are examined. A holistic perspective on changing flood risk is provided. Economic losses from floods have greatly increased over last decades, principally driven by the growing exposure of assets at risk. It has not been found possible to attribute observed rain-generated peak streamflow trends to anthropogenic climate change, generally. Based on physical reasoning, increases in the frequency and intensity of heavy rainfall should contribute to increase in risk of precipitation-generated local flooding (e.g., flash flooding and urban flooding) in many areas.

Assessing the influence of human activities on flash flood susceptibility in mountainous regions of Vietnam