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Cover -- Title Page -- Copyright Page -- Contents -- List of Contributors -- Preface -- Part I Remote Sensing for Global Drought and Flood Observations -- Chapter 1 Progress, Challenges, and Opportunities in Remote Sensing of Drought -- 1.1. INTRODUCTION -- 1.2. PROGRESS IN REMOTE SENSING OF DRIVERS OF DROUGHT -- 1.3. MULTI-INDICATOR DROUGHT MODELING -- 1.4. DROUGHT AND HEATWAVES FEEDBACKS -- 1.5. REMAINING CHALLENGES AND OPPORTUNITIES -- 1.6. CONCLUSION -- REFERENCES -- Chapter 2 Remote Sensing of Evapotranspiration for Global Drought Monitoring -- 2.1. INTRODUCTION -- 2.2. HISTORICAL SKETCH OF ET REMOTE SENSING STUDIES AND ET DATA PRODUCTS -- 2.3. ESTIMATING ET AND MONITORING DROUGHT WITH GEOSTATIONARY SATELLITE THERMAL OBSERVATIONS -- 2.4. DROUGHT MONITORING PRODUCT SYSTEM BASED ON ET REMOTE SENSING -- 2.5. COMBINING ET REMOTE SENSING WITH MICROWAVE SOIL MOISTURE DATA FOR DROUGHT MONITORING -- 2.6. DISCUSSION -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 3 Drought Monitoring Using Reservoir Data Collected via Satellite Remote Sensing -- 3.1. INTRODUCTION -- 3.2. DROUGHT MONITORING USING REMOTELY SENSED RESERVOIR DATA -- 3.3. ADOPTING REMOTELY SENSED RESERVOIR DATA TO SUPPORT DROUGHT MODELING APPLICATIONS -- 3.4. FUTURE DIRECTIONS -- 3.5. DISCUSSION AND CONCLUSIONS -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 4 Automatic Near-Real-Time Flood Mapping from Geostationary Low Earth Orbiting Satellite Observations -- 4.1. INTRODUCTION -- 4.2. DATA USED -- 4.3. METHODS -- 4.4. APPLICATIONS -- 4.5. VALIDATION -- 4.6. DISCUSSION -- 4.7. SUMMARY -- ACKNOWLEDGMENTS -- REFERENCES -- Chapter 5 Global Flood Observation with Multiple Satellites: Applications in Rio Salado (Argentina) and the Eastern Nile Basin -- 5.1. INTRODUCTION: THE STATE OF THE SCIENCE AND NEED FOR GLOBAL SATELLITE FLOOD MAPPING -- 5.2. METHODS FOR GLOBAL FLOOD OBSERVATION.

Climate-related disaster risks pose a threat to sustainable development today and in the future. Major global agendas, such as the Sendai Framework for Disaster Risk Reduction and the Sustainable Development Goals, address ways of developing effective management strategies for tackling such risks. Risk management is increasingly focusing on low probability but high impact events, next to the more traditional attention on expected losses. We focus on urban riverine flood risk across 200 countries for today, 2030, and 2080, and develop a risk-threshold approach for identifying whether a country is exposed to risk of extreme events and, if so, when and how much. Furthermore, we apply a risk-layer approach to delineate the kinds of risk reduction or financing instruments that may be needed to manage emerging risks at the national level. Based on these country-level results, we analyze the macroeconomic consequences of setting up a global fund as one international option for coping with floods today and in the future. An additional macroeconomic analysis of different funding schemes for capitalizing the global fund provides insights into linking national risk management efforts with global efforts to manage risks. The global fund could be capitalized according to different equality principles. Our results provide an argument for an equity-based capitalization principle rather than a risk-based one, as the former makes damages at the local level a global responsibility.

Climate-related disaster risks pose a threat to sustainable development today and in the future. Major global agendas, such as the Sendai Framework for Disaster Risk Reduction and the Sustainable Development Goals, address ways of developing effective management strategies for tackling such risks. Risk management is increasingly focusing on low probability but high impact events, next to the more traditional attention on expected losses. We focus on urban riverine flood risk across 200 countries for today, 2030, and 2080, and develop a risk-threshold approach for identifying whether a country is exposed to risk of extreme events and, if so, when and how much. Furthermore, we apply a risk-layer approach to delineate the kinds of risk reduction or financing instruments that may be needed to manage emerging risks at the national level. Based on these country-level results, we analyze the macroeconomic consequences of setting up a global fund as one international option for coping with floods today and in the future. An additional macroeconomic analysis of different funding schemes for capitalizing the global fund provides insights into linking national risk management efforts with global efforts to manage risks. The global fund could be capitalized according to different equality principles. Our results provide an argument for an equity-based capitalization principle rather than a risk-based one, as the former makes damages at the local level a global responsibility.

Abstract. Floods have negative effects on the reliable operation of
transportation systems. In China alone, floods cause an average of
∼1125 h of railway service disruptions per year. In this
study, we present a simulation framework to analyse the system vulnerability
and risk of the railway system to floods. First, we developed a novel
methodology for generating flood events at both the national and river basin
scale. Based on flood hazard maps of different return periods, independent
flood events are generated using the Monte Carlo sampling method. Combined
with network theory and spatial analysis methods, the resulting event set
provides the basis for national- and provincial-level railway risk
assessments, focusing in particular on train performance loss. Applying this
framework to the Chinese railway system, we show that the system
vulnerability of the Chinese railway system to floods is highly
heterogeneous as a result of spatial variations in the railway topology and
traffic flows. Flood events in the Yangtze River basin show the largest
impact on the national railway system, with approximately 40 % of the
national daily trains being affected by a 100-year flood event in that
basin. At the national level, the average percentage of daily affected
trains and passengers for the national system is approximately 2.7 % of
the total daily number of trips and passengers. The event-based approach
presented in this study shows how we can identify critical hotspots within a
complex network, taking the first steps in developing climate-resilient infrastructure.

Abstract. Over the past decade global flood hazard models have been developed and
continuously improved. There is now a significant demand for testing
global hazard maps generated by these models in order to understand their
applicability for international risk reduction strategies and for
reinsurance portfolio risk assessments using catastrophe models. We expand
on existing methods for comparing global hazard maps and analyse eight global
flood models (GFMs) that represent the current state of the global flood
modelling community. We apply our comparison to China as a case study and,
for the first time, include industry models, pluvial flooding, and flood
protection standards in the analysis. In doing so, we provide new insights
into how these components change the results of this comparison. We find
substantial variability, up to a factor of 4, between the flood hazard maps in
the modelled inundated area and exposed gross domestic product (GDP) across multiple return periods
(ranging from 5 to 1500 years) and in expected annual exposed GDP. The
inclusion of industry models, which currently model flooding at a higher
spatial resolution and which additionally include pluvial flooding,
strongly improves the comparison and provides important new benchmarks. We
find that the addition of pluvial flooding can increase the expected annual
exposed GDP by as much as 1.3 percentage points. Our findings strongly highlight
the importance of flood defences for a realistic risk assessment in
countries like China that are characterized by high concentrations of
exposure. Even an incomplete (1.74 % of the area of China) but locally
detailed layer of structural defences in high-exposure areas reduces the
expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8 %.

Abstract. Given the increasing impacts of flooding in Jakarta, methods for assessing current and future flood risk are required. In this paper, we use the Damagescanner-Jakarta risk model to project changes in future river flood risk under scenarios of climate change, land subsidence, and land use change. Damagescanner-Jakarta is a simple flood risk model that estimates flood risk in terms of annual expected damage, based on input maps of flood hazard, exposure, and vulnerability. We estimate baseline flood risk at USD 186 million p.a. Combining all future scenarios, we simulate a median increase in risk of +180 % by 2030. The single driver with the largest contribution to that increase is land subsidence (+126 %). We simulated the impacts of climate change by combining two scenarios of sea level rise with simulations of changes in 1-day extreme precipitation totals from five global climate models (GCMs) forced by the four Representative Concentration Pathways (RCPs). The results are highly uncertain; the median change in risk due to climate change alone by 2030 is a decrease by −46 %, but we simulate an increase in risk under 12 of the 40 GCM–RCP–sea level rise combinations. Hence, we developed probabilistic risk scenarios to account for this uncertainty. If land use change by 2030 takes places according to the official Jakarta Spatial Plan 2030, risk could be reduced by 12 %. However, if land use change in the future continues at the same rate as the last 30 years, large increases in flood risk will take place. Finally, we discuss the relevance of the results for flood risk management in Jakarta.

AbstractPeople living in poverty are particularly vulnerable to shocks, including those caused by natural disasters such as floods and droughts. This paper analyses household survey data and hydrological riverine flood and drought data for 52 countries to find out whether poor people are disproportionally exposed to floods and droughts, and how this exposure may change in a future climate. We find that poor people are often disproportionally exposed to droughts and floods, particularly in urban areas. This pattern does not change significantly under future climate scenarios, although the absolute number of people potentially exposed to floods or droughts can increase or decrease significantly, depending on the scenario and region. In particular, many countries in Africa show a disproportionally high exposure of poor people to floods and droughts. For these hotspots, implementing risk-sensitive land-use and development policies that protect poor people should be a priority.

Abstract. In a cross-disciplinary study, we carried out an extensive literature review to increase understanding of vulnerability indicators used in the disciplines of earthquake- and flood vulnerability assessments. We provide insights into potential improvements in both fields by identifying and comparing quantitative vulnerability indicators grouped into physical and social categories. Next, a selection of index- and curve-based vulnerability models that use these indicators are described, comparing several characteristics such as temporal and spatial aspects. Earthquake vulnerability methods traditionally have a strong focus on object-based physical attributes used in vulnerability curve-based models, while flood vulnerability studies focus more on indicators applied to aggregated land-use classes in curve-based models. In assessing the differences and similarities between indicators used in earthquake and flood vulnerability models, we only include models that separately assess either of the two hazard types. Flood vulnerability studies could be improved using approaches from earthquake studies, such as developing object-based physical vulnerability curve assessments and incorporating time-of-the-day-based building occupation patterns. Likewise, earthquake assessments could learn from flood studies by refining their selection of social vulnerability indicators. Based on the lessons obtained in this study, we recommend future studies for exploring risk assessment methodologies across different hazard types.

Abstract. A mega-flood in 1998 caused tremendous losses in China
and triggered major policy adjustments in flood-risk management. This paper
aims to retrospectively examine these policy adjustments and discuss how
China should adapt to newly emerging flood challenges. We show that China
suffers annually from floods despite large-scale investments and policy
adjustments. Rapid urbanization and climate change will exacerbate future
flood risk in China, with cascading impacts on other countries through
global trade networks. Therefore, novel flood-risk management approaches are
required, such as a risk-based urban planning and coordinated water
governance systems with public participation, in addition to traditional
structural protection.

Abstract. In low-lying coastal areas floods occur from
(combinations of) fluvial, pluvial, and coastal drivers. If these flood
drivers are statistically dependent, their joint probability might be
misrepresented if dependence is not accounted for. However, few studies have examined flood risk and risk reduction measures while accounting for
so-called compound flooding. We present a globally applicable framework for
compound flood risk assessments using combined hydrodynamic, impact, and
statistical modeling and apply it to a case study in the Sofala province of
Mozambique. The framework broadly consists of three steps. First, a large
stochastic event set is derived from reanalysis data, taking into account
co-occurrence of and dependence between all annual maximum flood drivers.
Then, both flood hazard and impact are simulated for different combinations
of drivers at non-flood and flood conditions. Finally, the impact of each
stochastic event is interpolated from the simulated events to derive a
complete flood risk profile. Our case study results show that from all
drivers, coastal flooding causes the largest risk in the region despite a
more widespread fluvial and pluvial flood hazard. Events with return periods longer than 25 years are more damaging when considering the observed
statistical dependence compared to independence, e.g., 12 % for the
100-year return period. However, the total compound flood risk in terms of
expected annual damage is only 0.55 % larger. This is explained by the
fact that for frequent events, which contribute most to the risk, limited
physical interaction between flood drivers is simulated. We also assess the
effectiveness of three measures in terms of risk reduction. For our case,
zoning based on the 2-year return period flood plain is as effective as
levees with a 10-year return period protection level, while dry proofing up
to 1 m does not reach the same effectiveness. As the framework is based on
global datasets and is largely automated, it can easily be repeated for
other regions for first-order assessments of compound flood risk. While the
quality of the assessment will depend on the accuracy of the global models
and data, it can readily include higher-quality (local) datasets where
available to further improve the assessment.

Abstract. Coastal flooding is driven by the combination of (high) tide and storm
surge, the latter being caused by strong winds and low pressure in tropical
and extratropical cyclones. The combination of storm surge and the
astronomical tide is defined as the storm tide. To gain an understanding of
the threat posed by coastal flooding and to identify areas that are
especially at risk, now and in the future, it is crucial to accurately model coastal inundation. Most models used to simulate the coastal inundation scale follow a simple planar approach, referred to as bathtub models. The main limitations of this type of models are that they implicitly assume an
infinite flood duration, and they do not capture relevant physical processes.
In this study we develop a method to generate hydrographs called HGRAPHER,
and we provide a global dataset of storm tide hydrographs based on time series
of storm surges and tides derived from the Global Tide and Surge Model
(GTSM) forced with the ERA5 reanalysis wind and pressure fields. These
hydrographs represent the typical shape of an extreme storm tide at a
certain location along the global coastline. We test the sensitivity of the
HGRAPHER method with respect to two main assumptions that determine the
shape of the hydrograph, namely the surge event sampling threshold and
coincidence in the time of the surge and tide maxima. The hydrograph dataset can be used to move away from planar inundation modelling techniques towards dynamic inundation modelling techniques across different spatial scales.

Abstract. In this study, we developed an enhanced approach for
large-scale flood damage and risk assessments that uses characteristics of
buildings and the built environment as object-based information to represent
exposure and vulnerability to flooding. Most current large-scale assessments
use an aggregated land-use category to represent the exposure, treating all
exposed elements the same. For large areas where previously only coarse
information existed such as in Africa, more detailed exposure data are
becoming available. For our approach, a direct relation between the
construction type and building material of the exposed elements is used to
develop vulnerability curves. We further present a method to differentiate
flood risk in urban and rural areas based on characteristics of the built
environment. We applied the model to Ethiopia and found that rural flood
risk accounts for about 22 % of simulated damage; rural damage is
generally neglected in the typical land-use-based damage models, particularly at this scale. Our approach is particularly interesting for studies in areas
where there is a large variation in construction types in the building
stock, such as developing countries.

Abstract. The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical independence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions.