Flood-induced mortality across the globe: Spatiotemporal pattern and influencing factors

Sunny-Day Flooding and Mortality Risk in Coastal Florida

Sea-level rise is likely to worsen the impacts of hurricanes, storm surges, and tidal flooding on coastal access to basic services. We investigate the historical impact of tidal flooding on mortality rates of the elderly population in coastal Florida using administrative records of individual deaths, demographics, and residential location combined with tidal gauge and high-resolution elevation data. We incorporate data capturing storm and precipitation events into our empirical model to distinguish between disruptions from routine sunny-day flooding and less predictable tropical storm-induced flooding. We find that a 1-standard-deviation (20-millimeter) increase in tidal flooding depth increases mortality rates by 0.46% to 0.60% among those aged 65 or older. Our estimates suggest that future sea-level rises may contribute to an additional 130 elderly deaths per year in Florida relative to 2019, all else being equal. The enhanced risk is concentrated among residents living more than nine minutes away from the nearest hospital. Results suggest that tidal flooding may augment elderly mortality risk by delaying urgent medical care.

Flood exposure and pregnancy loss in 33 developing countries

Floods have affected billions worldwide. Yet, the indirect health impacts of floods on vulnerable groups, particularly women in the developing world, remain underexplored. Here, we evaluated the risk of pregnancy loss for women exposed to floods. We analyzed 90,465 individual pregnancy loss records from 33 developing countries, cross-referencing each with spatial-temporal flood databases. We found that gestational flood exposure is associated with increased pregnancy loss with an odds ratio of 1.08 (95% confidence interval: 1.04 - 1.11). This risk is pronounced for women outside the peak reproductive age range (<21 or >35) or during the mid and late-stage of pregnancy. The risk escalated for women dependent on surface water, with lower income or education levels. We estimated that, over the 2010s, gestational flood events might be responsible for approximately 107,888 (CIs: 53,944 - 148,345) excess pregnancy losses annually across 33 developing countries. Notably, there is a consistent upward trend in annual excess pregnancy losses from 2010 to 2020, and was more prominent over Central America, the Caribbean, South America, and South Asia. Our findings underscore the disparities in maternal and child health aggravated by flood events in an evolving climate.

Tropical cyclone-specific mortality risks and the periods of concern: A multicountry time-series study

BACKGROUND

More intense tropical cyclones (TCs) are expected in the future under a warming climate scenario, but little is known about their mortality effect pattern across countries and over decades. We aim to evaluate the TC-specific mortality risks, periods of concern (POC) and characterize the spatiotemporal pattern and exposure-response (ER) relationships on a multicountry scale.

METHODS AND FINDINGS

Daily all-cause, cardiovascular, and respiratory mortality among the general population were collected from 494 locations in 18 countries or territories during 1980 to 2019. Daily TC exposures were defined when the maximum sustained windspeed associated with a TC was ≥34 knots using a parametric wind field model at a 0.5° × 0.5° resolution. We first estimated the TC-specific mortality risks and POC using an advanced flexible statistical framework of mixed Poisson model, accounting for the population changes, natural variation, seasonal and day of the week effects. Then, a mixed meta-regression model was used to pool the TC-specific mortality risks to estimate the overall and country-specific ER relationships of TC characteristics (windspeed, rainfall, and year) with mortality. Overall, 47.7 million all-cause, 15.5 million cardiovascular, and 4.9 million respiratory deaths and 382 TCs were included in our analyses. An overall average POC of around 20 days was observed for TC-related all-cause and cardiopulmonary mortality, with relatively longer POC for the United States of America, Brazil, and Taiwan (>30 days). The TC-specific relative risks (RR) varied substantially, ranging from 1.04 to 1.42, 1.07 to 1.77, and 1.12 to 1.92 among the top 100 TCs with highest RRs for all-cause, cardiovascular, and respiratory mortality, respectively. At country level, relatively higher TC-related mortality risks were observed in Guatemala, Brazil, and New Zealand for all-cause, cardiovascular, and respiratory mortality, respectively. We found an overall monotonically increasing and approximately linear ER curve of TC-related maximum sustained windspeed and cumulative rainfall with mortality, with heterogeneous patterns across countries and regions. The TC-related mortality risks were generally decreasing from 1980 to 2019, especially for the Philippines, Taiwan, and the USA, whereas potentially increasing trends in TC-related all-cause and cardiovascular mortality risks were observed for Japan.

CONCLUSIONS

The TC mortality risks and POC varied greatly across TC events, locations, and countries. To minimize the TC-related health burdens, targeted strategies are particularly needed for different countries and regions, integrating epidemiological evidence on region-specific POC and ER curves that consider across-TC variability.

Recent decreasing precipitation and snowmelt reduce the floods around the Chinese Tianshan Mountains

Understanding and managing mountain floods has become increasingly urgent, with global climate change and human activities exacerbating flood risk. However, flood research in Tianshan Mountains, a typical flood-prone mountainous region in China, is still insufficient. Here, we customized a set of flood research methods based on rainstorms and extreme snowmelt events, including a new flood counting method that comprehensively considered the frequency and magnitude of floods and the methods of flood classification and change attribution. We found that floods around the Chinese Tianshan Mountains (CTM) increased from 2014 to 2016 but decreased rapidly from 2016 to 2021, with storm floods, snowmelt floods, and mixed floods accounting for 38.3 %, 26.5 %, and 34.6 % of total flood events, respectively. The variation of floods was most significantly correlated with the average and extreme precipitation, followed by the temperature-driven average snowmelt change. Furthermore, atmospheric circulation anomalies and water vapor input from the western boundary of CTM caused decreasing precipitation and storm floods. Meanwhile, the warming hiatus also greatly impacted declining flood frequency. Notably, flood frequency is projected to rebound soon because of the rising precipitation and temperature, infrastructure aging, and reservoir abandonment, implying the present flood decline unsustainable. Our research develops a strategy to investigate short-term flood anomalies under climate oscillations around the CTM, providing insights into flood research and prevention in global mountainous regions.

Mortality risks associated with floods in 761 communities worldwide: time series study

OBJECTIVE

To evaluate lag-response associations and effect modifications of exposure to floods with risks of all cause, cardiovascular, and respiratory mortality on a global scale.

DESIGN

Time series study.

SETTING

761 communities in 35 countries or territories with at least one flood event during the study period.

PARTICIPANTS

Multi-Country Multi-City Collaborative Research Network database, Australian Cause of Death Unit Record File, New Zealand Integrated Data Infrastructure, and the International Network for the Demographic Evaluation of Populations and their Health Network database.

MAIN OUTCOME MEASURES

The main outcome was daily counts of deaths. An estimation for the lag-response association between flood and daily mortality risk was modelled, and the relative risks over the lag period were cumulated to calculate overall effects. Attributable fractions of mortality due to floods were further calculated. A quasi-Poisson model with a distributed lag non-linear function was used to examine how daily death risk was associated with flooded days in each community, and then the community specific associations were pooled using random effects multivariate meta-analyses. Flooded days were defined as days from the start date to the end date of flood events.

RESULTS

A total of 47.6 million all cause deaths, 11.1 million cardiovascular deaths, and 4.9 million respiratory deaths were analysed. Over the 761 communities, mortality risks increased and persisted for up to 60 days (50 days for cardiovascular mortality) after a flooded day. The cumulative relative risks for all cause, cardiovascular, and respiratory mortality were 1.021 (95% confidence interval 1.006 to 1.036), 1.026 (1.005 to 1.047), and 1.049 (1.008 to 1.092), respectively. The associations varied across countries or territories and regions. The flood-mortality associations appeared to be modified by climate type and were stronger in low income countries and in populations with a low human development index or high proportion of older people. In communities impacted by flood, up to 0.10% of all cause deaths, 0.18% of cardiovascular deaths, and 0.41% of respiratory deaths were attributed to floods.

CONCLUSIONS

This study found that the risks of all cause, cardiovascular, and respiratory mortality increased for up to 60 days after exposure to flood and the associations could vary by local climate type, socioeconomic status, and older age.

Fatal drowning in Indonesia: understanding knowledge gaps through a scoping review

Little is known about unintentional drowning deaths in Indonesia, the world's fourth most populous and largest archipelagic country. This study aimed to describe the epidemiology and risk factors of unintentional drowning in Indonesia and explore existing health promotion and drowning prevention approaches in Indonesia within a socio-ecological health promotion framework. A scoping review, guided by PRISMA-ScR, was conducted to locate peer-reviewed studies and government reports/policy documents published until May 2023, in English or Indonesian language, using MEDLINE (Ovid), CINAHL, Informit, PsycINFO (ProQuest), Scopus, SafetyLit, BioMed Central and Google Scholar, Indonesian journal databases (Sinta, Garuda) and government agencies websites around the terms: drown, swim, flood, hurricane, cyclone, disaster, water rescue and maritime/boat safety. This review identified 32 papers. However, a paucity of information on unintentional drowning rates, risk factors and prevention in Indonesia was noted. The unavailability of a coordinated national drowning data collection system in Indonesia, from which national and subnational subcategory data can be collected, underlines the possibility of under-representation of drowning mortality. The association between various exposures and drowning incidents has not been fully investigated. An over-reliance on individual-focused, behaviour-based, preventive measures was observed. These findings highlight the need for improving drowning surveillance to ensure the availability and reliability of drowning data; and strengthening research to understand the risk factors for drowning and delivery of drowning prevention programs. Further policy development and research focusing on health promotion approaches that reflect a socio-ecological approach to drowning prevention in Indonesia is imperative.

Global short-term mortality risk and burden associated with tropical cyclones from 1980 to 2019: a multi-country time-series study

BACKGROUND

The global spatiotemporal pattern of mortality risk and burden attributable to tropical cyclones is unclear. We aimed to evaluate the global short-term mortality risk and burden associated with tropical cyclones from 1980 to 2019.

METHODS

The wind speed associated with cyclones from 1980 to 2019 was estimated globally through a parametric wind field model at a grid resolution of 0·5° × 0·5°. A total of 341 locations with daily mortality and temperature data from 14 countries that experienced at least one tropical cyclone day (a day with maximum sustained wind speed associated with cyclones ≥17·5 m/s) during the study period were included. A conditional quasi-Poisson regression with distributed lag non-linear model was applied to assess the tropical cyclone-mortality association. A meta-regression model was fitted to evaluate potential contributing factors and estimate grid cell-specific tropical cyclone effects.

FINDINGS

Tropical cyclone exposure was associated with an overall 6% (95% CI 4-8) increase in mortality in the first 2 weeks following exposure. Globally, an estimate of 97 430 excess deaths (95% empirical CI [eCI] 71 651-126 438) per decade were observed over the 2 weeks following exposure to tropical cyclones, accounting for 20·7 (95% eCI 15·2-26·9) excess deaths per 100 000 residents (excess death rate) and 3·3 (95% eCI 2·4-4·3) excess deaths per 1000 deaths (excess death ratio) over 1980-2019. The mortality burden exhibited substantial temporal and spatial variation. East Asia and south Asia had the highest number of excess deaths during 1980-2019: 28 744 (95% eCI 16 863-42 188) and 27 267 (21 157-34 058) excess deaths per decade, respectively. In contrast, the regions with the highest excess death ratios and rates were southeast Asia and Latin America and the Caribbean. From 1980-99 to 2000-19, marked increases in tropical cyclone-related excess death numbers were observed globally, especially for Latin America and the Caribbean and south Asia. Grid cell-level and country-level results revealed further heterogeneous spatiotemporal patterns such as the high and increasing tropical cyclone-related mortality burden in Caribbean countries or regions.

INTERPRETATION

Globally, short-term exposure to tropical cyclones was associated with a significant mortality burden, with highly heterogeneous spatiotemporal patterns. In-depth exploration of tropical cyclone epidemiology for those countries and regions estimated to have the highest and increasing tropical cyclone-related mortality burdens is urgently needed to help inform the development of targeted actions against the increasing adverse health impacts of tropical cyclones under a changing climate.

FUNDING

Australian Research Council and Australian National Health and Medical Research Council.

Urban flood risk assessment characterizing the relationship among hazard, exposure, and vulnerability

Risk assessment is an effective means to alleviate urban flood disasters and has attracted the attention of many studies. However, most previous studies about urban flood risk assessment often focused more on urban inundation area and depth, less on the inter-relationship of the components of risk. In this study, an urban flood risk assessment approach that characterizes the relationship among the three components of risk "hazard-exposure-vulnerability" (H-E-V) is developed. Firstly, eleven flood risk indicators are selected based on the flood simulation results of urban flood model and statistical data to establish the urban flood risk assessment index system. Then, the combination of analytic hierarchy process (AHP) and entropy weight method is employed to determine the weight of each indicator and the comprehensive urban flood risk is assessed. Most importantly, the coupling coordination degree model (CCDM) is used to reveal the relationship among H-E-V. After applying this method to Haikou city, China, the results show that the comprehensive effect and the coupling coordination degrees among H-E-V have a multidimensional impact on urban flood risk. For example, some sub-catchments, although at high risk of flooding, may experience a potential waste of resources. Urban flood assessment can be made more detailed and three-dimensional by comparing hazard, exposure, and vulnerability horizontally. Understanding and grasping the internal relationships among these three risk components can help implement flood prevention measures, optimize the allocation of flood prevention resources, and effectively reduce urban flood risks.

Compound and successive events of extreme precipitation and extreme runoff under heatwaves based on CMIP6 models

Global warming accelerates the rate of interregional hydrological cycles, thus leading to a significant increase in the frequency and intensity of global extreme events. An extreme event that causes other extreme events within a short period of time is a successive event. Compound and successive extreme events are more harmful than single extreme events. Therefore, this study revealed the evolution characteristics of compound heatwave and extreme precipitation/runoff events (CHP/CHR), successive heatwave and extreme precipitation/runoff events (SHP/SHR). The population exposure of the four compound events was assessed in the future. The results are as follows: (1) the frequencies of CHP, CHR, SHP, and SHR have all shown a significant upward trend since the Industrial Revolution, especially at low and high latitudes. Under the future SSP585 scenario, CHP and CHR had the largest change rates from 2065 to 2099 at 2.01 events/decade and 1.86 events/decade, respectively. (2) The proportion of severe and extreme events increased significantly in various regions from 1970 to 2014. SHP and SHR have the largest proportion of severe/extreme events in 2015-2039/2065-2099. (3) The CHP and CHR changes in the historical period mainly occurred at high latitudes, while SHP and SHR had the largest change rates in low latitudes. The temperature was dominant compound and successive events in the future. The intensity of the compound event was much larger than that of its corresponding successive event under the high-emission scenario. (4) Climate effect had the most obvious impact on the change of population exposure. Compared with the SSP126 scenario, the population exposure change of the compound event increased by 3.1 times and 3.2 times under the SSP585 scenario during 2065-2099 and 2015-2039, respectively.

Comments and recommendations on Sponge City - China's solutions to prevent flooding risks

Background

/Objective: Flooding risk is a global issue, and various approaches have been established to prevent flooding risk around the world. China is one of the heavily flood-affected countries and has been implementing the Sponge City program since 2015 to defend against flooding. Unfortunately, flooding has been common in China in recent years, causing severe health risks to citizens. This research mainly focuses on (a) evaluating the implementation of China's Sponge City program and the associated impacts on human health and (b) exploring the future improvement of the Sponge City program in China.

Methods

The Interpretive Document Approach was used to explore an inclusive review of the Sponge City program and its implications on human health.

Results

/Findings: The Sponge City program in China is still insufficient to prevent flooding risks effectively. In the past eight years, 24/34 provinces have recorded flooding, which caused a total of 4701 deaths and over 525.5 billion RMB (around 72.9 billion US$) in economic loss. Till now, only 64/654 cities have promulgated local legislation to manage sponge city construction, although the Sponge City was implemented in 2015. Besides, the completed Sponge City program constructions cannot fully prevent flooding risks, the flood prevention capacity is limited. The Sponge City program is not granted priority, lacking national legislation hinders Sponge City program implementation in China.

Conclusions

China needs to make national legislation on the Sponge City program and update the Sponge City program technology guidelines. Local governments should implement Sponge City construction according to local geographic environments.

Human Settlement Resilience Zoning and Optimizing Strategies for River-Network Cities under Flood Risk Management Objectives: Taking Yueyang City as an Example

The dense river network and large population in the southern region of China are vulnerable to flooding stress, which challenges the construction of human settlements. This paper analyzes the causes of flood risk and the dilemma of human settlement improvement in river-network cities, introduces the principle of resilience to human settlements, and conducts a quantitative study on the resilience of human settlements in river-network cities with the goal of flood risk management. Taking Yueyang city, a river-network city in the Yangtze River Basin, as the empirical research object, we conduct a flood resilience zoning of the human settlements based on the flood risk assessment model and use the GIS spatial overlay method to correct the resilience of the current human living space against the territorial spatial planning of Yueyang city. Ultimately, we propose a strategy for optimizing human settlements under flood risk management. The results show that (1) the highest-risk and high-risk areas of Yueyang city were mainly located in Dongting Lake and its interconnected water system, the southwest local area and the southeastern fringe, while the low-risk and lowest-risk areas were mainly located in the northeast local area and the northwestern fringe, with low flood stress risk. (2) The spatial system of human settlement resilience was constructed based on the flood risk assessment level. Among them, the human settlement flood resilience zoning of Yueyang city was divided into five categories from low to high: human settlement control zone, restriction zone, buffer zone, construction zone and expansion zone; the flood resilience zoning of Yueyang city’s current living space was divided into three categories from low to high: structure adjustment zone, flood restriction zone and development stability zone. (3) The specific control implementation and execution of the human settlements in Yueyang city mainly focus on the interrelationship between the risk of flooding in the watershed and the development of human activities through zoning regulation and collaborative management to optimize the human settlements. The study results can provide positive intervention and guidance for constructing urban and rural territorial spatial prevention planning and improving human living quality in river-network cities in China.

Insurance Issues as Secondary Stressors Following Flooding in Rural Australia-A Mixed Methods Study

Flood events can be dramatic and traumatic. People exposed to floods are liable to suffer from a variety of adverse mental health outcomes. The adverse effects of stressors during the recovery process (secondary stressors) can sometimes be just as severe as the initial trauma. Six months after extensive flooding in rural Australia, a survey of 2530 locals was conducted focusing on their flood experiences and mental health status. This mixed methods study analysed (a) quantitative data from 521 respondents (21% of total survey respondents) who had insurance coverage and whose household was inundated, 96 (18%) of whom reported an insurance dispute or denial; and (b) qualitative data on insurance-related topics in the survey’s open comments sections. The mental health outcomes were all significantly associated with the degree of flood inundation. The association was strong for probable PTSD and ongoing distress (Adjusted Odds Ratios (AORs) with 95% confidence intervals 2.67 (1.8–4.0) and 2.30 (1.6–3.3), respectively). The associations were less strong but still significant for anxiety and depression (AORs 1.79 (1.2–2.7) and 1.84 (1.2–2.9)). The secondary stressor of insurance dispute had stronger associations with ongoing distress and depression than the initial flood exposure (AORs 2.43 (1.5–3.9) and 2.34 (1.4–3.9), respectively). Insurance was frequently mentioned in the open comment sections of the survey. Most comments (78% of comments from all survey respondents) were negative, with common adverse trends including dispute/denial, large premium increases after a claim, inconsistencies in companies’ responses and delayed assessments preventing timely remediation.

Blue-Green Infrastructure for Flood and Water Quality Management in Southeast Asia: Evidence and Knowledge Gaps

In Southeast Asia, projections of rapid urban growth coupled with high water-related risks call for large investments in infrastructure-including in blue-green infrastructure (BGI) such as forests, parks, or vegetated engineered systems. However, most of the knowledge on BGI is produced in the global North, overlooking the diversity of urban contexts globally. Here, we review the literature on BGI for flood risk mitigation and water quality improvement in Southeast Asian cities to understand the scope of practical knowledge and identify research needs. We searched for evidence of local types of BGI in peer-reviewed and grey literature and assessed the performance of BGI based on hydrological, societal, and environmental metrics. The body of literature on BGI in Southeast Asia is small and dominated by wealthier countries but we found evidence of uptake among researchers and practitioners in most countries. Bioretention systems, constructed wetlands, and green cover received the most attention in research. Evidence from modelling and laboratory studies confirmed the potential for BGI to address flooding and water quality issues in the region. However, practical knowledge to mainstream the implementation of BGI remains limited, with insufficient primary hydrological data and information on societal and environmental impacts. In addition, the performance of BGI in combination with grey infrastructure, under climate change, or in informal settlements is poorly studied. Future research and practice should focus on producing and sharing empirical data, ultimately increasing the regional knowledge base to promote efficient BGI strategies.

Impact of Coastal Disasters on Women in Urban Slums: A New Index

Coastal hazards, particularly cyclones, floods, erosion and storm surges, are emerging as a cause for major concern in the coastal regions of Vijayawada, Andhra Pradesh, India. Serious coastal disaster events have become more common in recent decades, triggering substantial destruction to the low-lying coastal areas and a high death toll. Further, women living in informal and slum housing along the Vijayawada coastline of Andhra Pradesh (CAP), India, suffer from multiple social, cultural and economic inequalities as well. These conditions accelerate and worsen women’s vulnerability among this coastal population. The existing literature demonstrates these communities’ susceptibility to diverse coastal disasters but fails to offer gender-specific vulnerability in urban informal housing in the Vijayawada area. Accordingly, the current study developed a novel gender-specific Women’s Coastal Vulnerability Index (WCVI) to assess the impact of coastal disasters on women and their preparedness in Vijayawada. Field data was collected from over 300 women through surveys (2) and workshops (2) between November 2018 and June 2019, and Arc-GIS tools were used to generate vulnerability maps. Results show that women are more vulnerable than men, with a higher death rate during coastal disaster strikes. The current study also found that gender-specific traditional wear is one of the main factors for this specific vulnerability in this area. Furthermore, the majority of the women tend to be located at home to care for the elders and children, and this is associated with more fatalities during disaster events. Homes, particularly for the urban poor, are typically very small and located in narrow and restricted sites, which are a barrier for women to escape from unsafe residential areas during disasters. Overall, the research reveals that most of the coastal disaster events had a disproportionately negative impact on women. The results from this present study offer valuable information to aid evidence-based policy- and decision-makers to improve existing or generate innovative policies to save women’s lives and improve their livelihood in coastal areas.

Risks to the Health of Russian Population from Floods and Droughts in 2010‒2020: A Scoping Review

Climate change and natural disasters caused by hydrological, meteorological, and climatic causes have a significant and increasing direct and indirect impact on human health, leading to increased mortality and morbidity. Russia is a country that suffers from frequent climatic and weather disasters. This is mainly due to its vast territory, complex geographical and ecological environment, and widely varying climatic conditions. This review provides information on climatological and hydrological extremes in Russia in 2010–2020, floods and droughts, and their impact on the health and well-being of the country’s population. A literature search was conducted using electronic databases Web of Science, Pubmed, Science Direct, Scopus, and e-Library, focusing on peer-reviewed journal articles published in English and in Russian from 2010 to 2021. Four conceptual categories were used: “floods”, “droughts”, “human health”, and “Russia”. It is concluded that while most hazardous weather events cannot be completely avoided, many health impacts can potentially be prevented. The recommended measures include early warning systems and public health preparedness and response measures, building climate resilient health systems and other management structures.

The Characteristics and Evaluation of Future Droughts across China through the CMIP6 Multi-Model Ensemble

Understanding historical and future drought patterns is crucial to acclimation and the mitigation of drought. The negative impact of China’s droughts on the social economy has attracted attention; however, there is still no comprehensive or long-term monitoring pattern for future droughts. Here we evaluated the precipitation and temperature simulation capability of Coupled Model Intercomparison Project Phase 6 (CMIP6) and evaluated the temporal and spatial pattern of droughts during 1961–2099 across China. The results show that the multi-model ensemble mean (MME) is more representative of the observed precipitation and temperatures across China than the single climate model. China experienced an overall drying trend in the historical period. After 1991, the drought frequency (DF), drought duration (DD), and drought intensity (DI) in the northwest of the Inland River Basin and in the Yangtze River Basin increased significantly. Compared with the historical period, China will suffer more frequent drought events, although the DD and DI will be weakened under SSP1-2.6 and SSP2-4.5, while China will experience longer DD and more serious drought events under SSP3-7.0 and SSP5-8.5. The Hai River Basin and Huai River Basin are expected to have more serious drought trends in summer. Compared with historical periods, the drought trend will increase by 2.9–5.7 times and 1.1–4.2 times, respectively. The results can be used for decision making regarding future drought control.

Poplar's Waterlogging Resistance Modeling and Evaluating: Exploring and Perfecting the Feasibility of Machine Learning Methods in Plant Science

Floods, as one of the most common disasters in the natural environment, have caused huge losses to human life and property. Predicting the flood resistance of poplar can effectively help researchers select seedlings scientifically and resist floods precisely. Using machine learning algorithms, models of poplar's waterlogging tolerance were established and evaluated. First of all, the evaluation indexes of poplar's waterlogging tolerance were analyzed and determined. Then, significance testing, correlation analysis, and three feature selection algorithms (Hierarchical clustering, Lasso, and Stepwise regression) were used to screen photosynthesis, chlorophyll fluorescence, and environmental parameters. Based on this, four machine learning methods, BP neural network regression (BPR), extreme learning machine regression (ELMR), support vector regression (SVR), and random forest regression (RFR) were used to predict the flood resistance of poplar. The results show that random forest regression (RFR) and support vector regression (SVR) have high precision. On the test set, the coefficient of determination (R²) is 0.8351 and 0.6864, the root mean square error (RMSE) is 0.2016 and 0.2780, and the mean absolute error (MAE) is 0.1782 and 0.2031, respectively. Therefore, random forest regression (RFR) and support vector regression (SVR) can be given priority to predict poplar flood resistance.

Spatial pattern of the population casualty rate caused by super typhoon Lekima and quantification of the interactive effects of potential impact factors

BACKGROUND

Typhoons greatly threaten human life and property, especially in China. Therefore, it is important to make effective policy decisions to minimize losses associated with typhoons.

METHODS

In this study, the GeoDetector method was used to quantify the determinant powers of natural and socioeconomic factors, and their interactions, on the population casualty rate of super typhoon Lekima. The local indicator of spatial association (LISA) method was followed to explore the spatial pattern of the population casualty rate under the influence of the identified dominant factors.

RESULTS

Both natural and socioeconomic factors were found to have significantly impacted the population casualty rate due to super typhoon Lekima. Among the selected factors, maximum precipitation was dominant factor (q = 0.56), followed by maximum wind speed (q = 0.45). In addition, number of health technicians (q = 0.35) and number of health beds (q = 0.27) have a strong influence on the population casualty rate. Among the interactive effects of 12 influencing factors, the combined effects of maximum precipitation and ratio of brick-wood houses, the maximum precipitation and ratio of steel-concrete houses, maximum precipitation and number of health technicians were highest (q = 0.72). Furthermore, high-risk areas with very high casualty rates were concentrated in the southeastern part of Zhejiang and northern Shandong Provinces, while lower-risk areas were mainly distributed in northern Liaoning and eastern Jiangsu provinces.

CONCLUSIONS

These results contribute to the development of more specific policies aimed at safety and successful property protection according to the regional differences during typhoons.

A Catalogue of Tropical Cyclone Induced Instantaneous Peak Flows Recorded in Puerto Rico and a Comparison with the World’s Maxima

Peak streamflow rates from the Insular Caribbean have received limited attention in worldwide catalogues in spite of their potential for exceptionality given many of the islands’ steep topographic relief and proneness to high rainfall rates associated with tropical cyclones. This study compiled 1922 area-normalized peak streamflow rates recorded during tropical cyclones in Puerto Rico from 1899 to 2020. The results show that the highest peak flow values recorded on the island were within the range of the world’s maxima for watersheds with drainage areas from 10 to 619 km2. Although higher tropical cyclone rainfall and streamflow rates were observed on average for the central–eastern half of Puerto Rico, the highest of all cyclone-related peaks occurred throughout the entire island and were caused by tropical depressions, tropical storms, or hurricanes. Improving our understanding of instantaneous peak flow rates in Puerto Rico and other islands of the Caribbean is locally important due to their significance in terms of flooding extent and its associated impacts, but also because these could serve as indicators of the implications of a changing climate on tropical cyclone intensity and the associated hydrologic response.

Integrated Framework for Detecting the Areas Prone to Flooding Generated by Flash-Floods in Small River Catchments

In the present study, the susceptibility to flash-floods and flooding was studied across the Izvorul Dorului River basin in Romania. In the first phase, three ensemble models were used to determine the susceptibility to flash-floods. These models were generated by a combination of three statistical bivariate methods, namely frequency ratio (FR), weights of evidence (WOE), and statistical index (SI), with fuzzy analytical hierarchy process (FAHP). The result obtained from the application of the FAHP-WOE model had the best performance highlighted by an Area Under Curve—Receiver Operating Characteristics Curve (AUC-ROC) value of 0.837 for the training sample and another of 0.79 for the validation sample. Furthermore, the results offered by FAHP-WOE were weighted on the river network level using the flow accumulation method, through which the valleys with a medium, high, and very high torrential susceptibility were identified. Based on these valleys’ locations, the susceptibility to floods was estimated. Thus, in the first stage, a buffer zone of 200 m was delimited around the identified valleys along which the floods could occur. Once the buffer zone was established, ten flood conditioning factors were used to determine the flood susceptibility through the analytical hierarchy process model. Approximately 25% of the total delimited area had a high and very high flood susceptibility.

Understanding dynamics of population flood exposure in Canada with multiple high-resolution population datasets

In recent years, geospatial data (e.g. remote sensing imagery), and other relevant ancillary datasets (e.g. land use land cover, climate conditions) have been utilized through sophisticated algorithms to produce global population datasets. With a handful of such datasets, their performances and skill in flood exposure assessment have not been explored. This study proposes a comprehensive framework to understand the dynamics and differences in population flood exposure over Canada by employing four global population datasets alongside the census data from Statistics Canada as the reference. The flood exposure is quantified based on a set of floodplain maps (for 2015, 1 in 100-yr and 1 in 200-yr event) for Canada derived from the CaMa-Flood global flood model. To obtain further insights at the regional level, the methodology is implemented over six flood-prone River Basins in Canada. We find that about 9% (3.31 million) and 11% (3.90 million) of the Canadian population resides within 1 in 100-yr and 1 in 200-yr floodplains. We notice an excellent performance of WorldPop, and LandScan in most of the cases, which is unaffected by the representation of flood hazard, while Global Human Settlement and Gridded Population of the World showed large deviations. At last, we determined the long-term dynamics of population flood exposure and vulnerability from 2006 to 2019. Through this analysis, we also identify the regions that contain a significantly larger population exposed to floods. The relevant conclusions derived from the study highlight the need for careful selection of population datasets for preventing further amplification of uncertainties in flood risk. We recommend a detailed assessment of the severely exposed regions by including precise ground-level information. The results derived from this study may be useful not only for flood risk management but also contribute to understanding other disaster impacts on human-environment interrelationships.

An Entropic Approach to Estimating the Instability Criterion of People in Floodwaters

People are always susceptible to a loss of stability in urban floodwaters that leads to serious casualties. Thus, the safety criterion for the instability of people in floodwaters must be determined. In this study, the hydrodynamic criterion of the instability of people in floodwaters in terms of the incipient velocity and water depth is derived using the probability method based on Shannon entropy theory. The derived model can characterize variations in the incipient velocity of people in floodwaters with respect to the inundating water depth. Furthermore, a comparison with seven experimental datasets available in the literature shows the validity of the proposed entropy-based model considering data scattering. A sensitivity analysis of the derived model to some of the incorporated parameters was performed, and the qualitative results are in accordance with our understanding of the physical mechanism of the instability of people in floodwaters. Taking the physical parameters (height and mass) of Chinese adults and children as a representative example, this study also showed the vulnerability degree of Chinese adults and children subject to floodwaters. These findings could provide a reference for administrators and stakeholders for flood hazard mitigation and flood strategy management. This study shows that an entropy-based method could be a valuable addition to existing deterministic models for characterizing the instability criterion of people in an urban flooding event.

A New Hybrid Firefly–PSO Optimized Random Subspace Tree Intelligence for Torrential Rainfall-Induced Flash Flood Susceptible Mapping

Flash flood is one of the most dangerous natural phenomena because of its high magnitudes and sudden occurrence, resulting in huge damages for people and properties. Our work aims to propose a state-of-the-art model for susceptibility mapping of the flash flood using the decision tree random subspace ensemble optimized by hybrid firefly–particle swarm optimization (HFPS), namely the HFPS-RSTree model. In this work, we used data from a flood inventory map consisting of 1866 polygons derived from Sentinel-1 C-band synthetic aperture radar (SAR) data and a field survey conducted in the northwest mountainous area of the Van Ban district, Lao Cai Province in Vietnam. A total of eleven flooding conditioning factors (soil type, geology, rainfall, river density, elevation, slope, aspect, topographic wetness index (TWI), normalized difference vegetation index (NDVI), plant curvature, and profile curvature) were used as explanatory variables. These indicators were compiled from a geological and mineral resources map, soil type map, and topographic map, ALOS PALSAR DEM 30 m, and Landsat-8 imagery. The HFPS-RSTree model was trained and verified using the inventory map and the eleven conditioning variables and then compared with four machine learning algorithms, i.e., the support vector machine (SVM), the random forests (RF), the C4.5 decision trees (C4.5 DT), and the logistic model trees (LMT) models. We employed a range of statistical standard metrics to assess the predictive performance of the proposed model. The results show that the HFPS-RSTree model had the best predictive performance and achieved better results than those of other benchmarks with the ability to predict flash flood, reaching an overall accuracy of over 90%. It can be concluded that the proposed approach provides new insights into flash flood prediction in mountainous regions.

Study of the Allocation of Regional Flood Drainage Rights in Watershed Based on Entropy Weight TOPSIS Model: A Case Study of the Jiangsu Section of the Huaihe River, China

During the flood season, various regions in a watershed often have flood drainage conflicts, when the regions compete for flood drainage rights (FDR). In order to solve this problem, it is very necessary to study the allocation of FDR among various regions in the watershed. Firstly, this paper takes fairness, efficiency and sustainable development as the allocation principles, and comprehensively considers the differences of natural factors, social development factors, economic development factors and ecological environment factors in various regions. Then, an indicator system for allocation of FDR among regions in the watershed is established. Secondly, an entropy weight Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model is used to construct the FDR allocation model among regions in the watershed. Based on a harmony evaluation model, a harmony evaluation and comparison are carried out on the FDR allocation schemes under three different allocation principles. Finally, taking the Jiangsu section of the Huaihe River watershed as an example, the FDR of eight cities in the watershed are allocated and evaluated to see if the allocation scheme is harmonious. The results show that the allocation scheme of FDR based on the principles of fairness, efficiency and sustainable development has the highest degree of harmony, which can meet the FDR demands in various regions in the watershed, avoid the occurrence of flood drainage conflicts among regions, form an orderly flood drainage situation and promote the harmonious development of the watershed.

How to Account for the Human Motion to Improve Flood Risk Assessment in Urban Areas

Floods are critical disasters affecting urban areas and their users. Interactions with floodwater spreading and built environment features influence the users’ reaction to the emergency, especially during immediate disaster phases (i.e., evacuation). Recent studies tried to define simulation models to evaluate such exposure-related criticalities, assess individuals’ flood risk, and propose risk-mitigation strategies aimed at supporting the community’s proper response. Although they generally include safety issues (e.g., human body stability), such tools usually adopt a simplified approach to individuals’ motion representation in floodwaters, i.e., using input from non-specialized databases and models. This study provides general modelling approaches to estimate evacuation speed variations depending on individual’s excitement (walking, running), floodwaters depths and individuals’ features (age, gender, height, average speed on dry surfaces). The proposed models prefer a normalized evacuation speeds approach in respect of minimum motion constraint conditions to extend their applicability depending on the individuals’ characteristics. Speed data from previous experiments are organized using linear regression models. Results confirm how individuals’ speed reduces when depth and age increase. The most significant models are discussed to be implemented in evacuation simulation models to describe the evacuees’ motion in floodwaters with different confidence degree levels and then assess the community’s flood risk and risk-reduction strategies effectiveness.

Possibilities of Controlling the River Outlets by Weirs on the Example of Noteć Bystra River

The possibility of effective control of selected dams in the Noteć Bystra river is analyzed. Such a control is expected to permit inundation of selected arable areas, e.g., peat grasslands, to avoid flooding of the city of Czarnków and the terrains located downstream. The chosen case study is the reach of the Noteć River between the dams Pianowka–Mikolajewo–Rosko. The analysis was made on the basis of simulations of the flow and regulation of dams in flood conditions. The flow peaks of hypothetical flood waves were designed according to the directions of the ISOK project (Informatyczny System Osłony Kraju przed nadzwyczajnymi zagrożeniami—IT System of the Country’s Protection Against Extreme Hazards) as the maximum flows over 10-years (p = 10%), 100-years (p = 1%), and 500-years (p = 0.2%). The obtained results are presented as longitudinal profiles of the water surface, maps of inundated areas and maps of inundated soils. The main conclusion is that the robust control of dams reduces the peak of flow during flood wave propagation and forces inundation of the a priori selected areas. It helps to decrease the spatial range of the flood hazard and significantly reduces risk related to floods.

Coastal flood risks in China through the 21st century - An application of DIVA

China experiences frequent coastal flooding, with nearly US$ 77 billion of direct economic losses and over 7,000 fatalities reported from 1989 to 2014. Flood damages are likely to grow due to climate change induced sea-level rise and increasing exposure if no further adaptation measures are taken. This paper quantifies potential damage and adaptation costs of coastal flooding in China over the 21st Century, including the effects of sea-level rise. It develops and utilises a new, detailed coastal database of China developed within the Dynamic Interactive Vulnerability Assessment (DIVA) model framework. The refined database provides a more realistic spatial representation of coasts, with more than 2700 coastal segments, covering 28,966 km of coastline. Over 50% of China's coast is artificial, representing defended coast and/or claimed land. Coastal flood damage and adaptation costs for China are assessed for different Representative Concentration Pathway (RCP) and Shared Socio-economic Pathways (SSP) combinations representing climate change and socio-economic change and two adaptation strategies: no upgrade of currently existing defences and maintaining current protection levels. By 2100, 0.7-20.0 million people may be flooded/yr and US$ 67-3,308 billion damages/yr are projected without upgrade to defences. In contrast, maintaining the current protection level would reduce those numbers to 0.2-0.4 million people flooded/yr and US$ 22-60 billion/yr flood costs by 2100, with protection investment costs of US$ 8-17 billion/yr. In 2100, maintaining current protection levels, dikes costs are two orders of magnitude smaller than flood costs across all scenarios, even without accounting for indirect damages. This research improves on earlier national assessments of China by generating a wider range of projections, based on improved datasets. The information delivered in this study will help governments, policy-makers, insurance companies and local communities in China understand risks and design appropriate strategies to adapt to increasing coastal flood risk in an uncertain world.

Influence of Microtopography and Alluvial Lowland Characteristics on Location and Development of Residential Areas in the Kuji River Basin of Japan

Adopting a comprehensive, basin-wide method for preventing flood disasters would be effective to deflect the climate-change-induced intensified water-related disasters. This study considers the land use and settlement patterns based on microtopography and flood risks. The influence of the microtopography and alluvial lowland characteristics on the location and development of residential areas in the Kuji River basin, Japan, is a fundamental aspect of historical knowledge. Investigating the relation between the microtopography and the location of antiquities shows that most of the relics dating to or before the third century were situated in the terraces near the lowlands. The development of lowlands near the mainstream of the Kuji River began around the third century. Furthermore, the relation between the microtopography and development of residential areas is investigated using building density as the development indicator. The results confirm the increase in building density in the alluvial surface, proving a history of flood damage and delayed development compared to other regions. This investigation reveals land development in areas, including the former river bed on the mouth of the Kuji River and the flood plain on the margins of the Hitachiota urban distinct, with no confirmed inhabitation before modern times because of elevated flooding risk.

Differential Mental Health Impact Six Months After Extensive River Flooding in Rural Australia: A Cross-Sectional Analysis Through an Equity Lens

Background: Northern New South Wales in Australia is a “hotspot” for natural disaster declarations with recent extensive flooding in early 2017. With limited knowledge about how climate change affects mental health and resilience, robust local assessments are required to better understand long-term impact, particularly in communities prone to extreme weather events.

Methods: Six months post-flood, a cross-sectional survey of adults living in the region during the flood was conducted to quantify associations between flood impact and psychological morbidity (post-traumatic stress (PTSD), anxiety, depression, suicidal ideation) for different exposure scenarios, and respondent groups. We adopted a community-academic partnership approach and purposive recruitment to increase participation from marginalized groups.

Results: Of 2,180 respondents, almost all (91%) were affected by some degree of flood-related exposure at an individual and community level (ranging from suburb damage to home or business inundated). Socio-economically marginalized respondents were more likely to have their homes inundated and to be displaced. Mental health risk was significantly elevated for respondents: whose home/business/farm was inundated [e.g., home inundation: PTSD adjusted odds ratio (AOR) 13.72 (99% CI 4.53–41.56)]; who reported multiple exposures [e.g., three exposures: PTSD AOR 6.43 (99% CI 2.11–19.60)]; and who were still displaced after 6 months [e.g., PTSD AOR 24.43 (99% CI 7.05–84.69)].

Conclusion: The 2017 flood had profound impact, particularly for respondents still displaced and for socio-economically marginalized groups. Our community-academic partnership approach builds community cohesion, informs targeted mental health disaster preparedness and response policies for different sectors of the community and longer-term interventions aimed at improving community adaptability to climate change.

Terrestrial Water Storage in China: Spatiotemporal Pattern and Driving Factors

China is the largest agricultural country with the largest population and booming socio-economy, and hence, remarkably increasing water demand. In this sense, it is practically critical to obtain knowledge about spatiotemporal variations of the territorial water storage (TWS) and relevant driving factors. In this study, we attempted to investigate TWS changes in both space and time using the monthly GRACE (Gravity Recovery and Climate Experiment) data during 2003–2015. Impacts of four climate indices on TWS were explored, and these four climate indices are, respectively, El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), North Atlantic Oscillation (NAO), and Pacific decadal oscillation (PDO). In addition, we also considered the impacts of precipitation changes on TWS. We found significant correlations between climatic variations and TWS changes across China. Meanwhile, the impacts of climate indices on TWS changes were shifting from one region to another across China with different time lags ranging from 0 to 12 months. ENSO, IOD and PDO exerted significant impacts on TWS over 80% of the regions across China, while NAO affected TWS changes over around 40% of the regions across China. Moreover, we also detected significant relations between TWS and precipitation changes within 9 out of the 10 largest river basins across China. These results highlight the management of TWS across China in a changing environment and also provide a theoretical ground for TWS management in other regions of the globe.

Mapping Flood-Related Mortality in the Mediterranean Basin. Results from the MEFF v2.0 DB

Recent events in Western Attica in Greece (24 deaths in November 2017), in the Balearic Islands (13 deaths in October 2018), and in southern France (15 deaths in October 2018) show that flood-related mortality remains a major concern in Mediterranean countries facing flash floods. Over the past several years, many initiatives have arisen to create databases on flood-related mortality. An international initiative started in 2011 pooling regional and national databases on flood mortality from region and/or countries bordering the Mediterranean Sea. The MEditerranean Flood Fatality Database (MEFF DB) brings together, in 2018, six Mediterranean regions/countries: Catalonia (Spain), Balearic Islands (Spain), Southern France, Calabria (Italy), Greece, and Turkey, and covers the period 1980–2018. MEFF DB is on progress and, every year, new data are included, but for this study, we kept only the preliminary data that were geolocated and validated on 31st of December 2018. This research introduces a new step in the analysis of flood-related mortality and follows the statistical description of the MEFF DB already published. The goals of this paper are to draw the spatial distribution of flood mortality through a geographical information system (GIS) at different spatial scales: country, NUTS 3 (Nomenclature of Territorial Units for Statistics. Level 3) regions, catchment areas, and grid. A fatality rate (F: number of deaths/year/million of inhabitants) is created to help this analysis. Then, we try to relate mortality to basic (human or physical) drivers such as population density, rainfall seasonality, or rainfall frequency across the Mediterranean Basin. The mapping of F shows a negative mortality gradient between the western and the eastern parts of the Mediterranean Sea. The south of France appears to be the most affected region. The maps also highlight the seasonality of flood-related deaths with the same west–east gradient. It confirms that flood mortality follows the climatological seasonal patterns across the Mediterranean Basin. Flood-related fatalities mainly occur during the early fall season in the western part of the Mediterranean area, while the Easter Basin is affected later, in November or during the winter season. Eastern Turkey introduces another pattern, as mortality is more severe in summer. Mortality maps are then compared with factors that potentially contribute to the occurrence of flood fatalities, such as precipitation intensity (rainfall hazard), to explain geographical differences in the fatality rate. The density of a fatal event is correlated to the population density and the rainfall frequency. Conversely, the average number of deaths per event depends on other factors such as prevention or crisis management.

Rationale and methods for a cross-sectional study of mental health and wellbeing following river flooding in rural Australia, using a community-academic partnership approach

BACKGROUND

Climate change is associated with greater frequency, duration, intensity and unpredictability of certain weather-related events, including floods. Floods harm mental health. There is limited understanding of the mental health and well-being effects from river flooding, particularly over the longer term and in rural contexts. This paper describes the rationale, aims, objectives, study design and socio-demographic characteristics of the sample for a study measuring associations between flood experience and mental health and wellbeing of residents (particularly those most likely to be negatively impacted and hard to reach) in rural NSW Australia 6 months following a devastating flood in 2017. To our knowledge, the study is the first of its kind within Australia in a rural community and is an important initiative given the likelihood of an increasing frequency of severe flooding in Australia given climate change.

METHODS

A conceptual framework (The Flood Impact Framework) drawing on social ecological approaches was developed by the research team. It was based on the literature and feedback from the community. The Framework describes putative relationships between flood exposure and mental health and wellbeing outcomes. Within a community-academic partnership approach, a cross-sectional survey was then undertaken to quantify and further explore these relationships.

RESULTS

The cross-sectional survey was conducted online (including on mobile phone) and on paper between September and November 2017 and recruited 2530 respondents. Of those, 2180 provided complete demographic data, among whom 69% were women, 91% were aged 25-74, 4% identified as Aboriginal and/or Torres Strait Islander, 9% were farmers and 33% were business owners.

CONCLUSIONS

The study recruited a wide range of respondents and the partnership facilitated the community's engagement with the design and implementation of the study. The study will provide a basis for a follow-up study, that will aim to improve the understanding of mental health and wellbeing effects over the longer term. It will provide an important and original contribution to understanding river flooding and mental health in rural Australia, a topic that will grow in importance in the context of human-induced climate change, and identify critical opportunities to strengthen services, emergency planning and resilience to future flooding.

Modified Palmer Drought Severity Index: Model improvement and application

Monitoring of droughts is the first step into human adaptation and related management of drought hazards. Therefore, drought index is critical in drought monitoring practice. However, the standing drought indices include no information about agricultural irrigation. In this case, based on the Palmer Drought Severity Index (PDSI) and the Self-Calibrating Palmer Drought Severity Index (sc-PDSI), here we proposed the Modified Palmer Drought Severity Index (MPDSI) by considering agricultural irrigation such as irrigation quotas and soil water deficits. We compared changes of droughts monitored by MPDSI and other drought indices considered in this study, and found that MPDSI can well monitor drought conditions in irrigated regions. In this sense, MPDSI can monitor the actual drought conditions under human influences such as irrigation. Besides, we also found that MPDSI can well lessen overestimation of drought conditions by PDSI in terms of drought duration and drought intensity. Therefore, we can conclude that MPDSI can be accepted in drought monitoring practice across China. It should be noted here that the idea behind development of MPDSI and also the MDPSI proposed in this study can be well referenced in drought monitoring in other regions of the globe.

Time-Series Study of Associations between Rates of People Affected by Disasters and the El Niño Southern Oscillation (ENSO) Cycle

The El Niño Southern Oscillation (ENSO) is a major driver of climatic variability that can have far reaching consequences for public health globally. We explored whether global, regional and country-level rates of people affected by natural disasters (PAD) are linked to ENSO. Annual numbers of PAD between 1964–2017 recorded on the EM-DAT disaster database were combined with UN population data to create PAD rates. Time-series regression was used to assess de-trended associations between PAD and 2 ENSO indices: Oceanic Niño Index (ONI) and multivariate El Niño Index (MEI). Over 95% of PAD were caused by floods, droughts or storms, with over 75% of people affected by these three disasters residing in Asia. Globally, drought-related PAD rate increased sharply in El Niño years (versus neutral years). Flood events were the disaster type most strongly associated with El Niño regionally: in South Asia, flood-related PAD increased by 40.5% (95% CI 19.3% to 65.6%) for each boundary point increase in ONI (p = 0.002). India was found to be the country with the largest increase in flood-related PAD rates following an El Niño event, with the Philippines experiencing the largest increase following La Niña. Multivariate ENSO Index (MEI)-analyses showed consistent results. These findings can be used to inform disaster preparedness strategies.

Evaluation of Manning’s n Roughness Coefficient in Arid Environments by Using SAR Backscatter

The prediction of arid region flash floods (magnitude and frequency) is essential to ensure the safety of human life and infrastructures and is commonly based on hydrological models. Traditionally, catchment characteristics are extracted using point-based measurements. A considerable improvement of point-based observations is offered by remote sensing technologies, which enables the determination of continuous spatial hydrological parameters and variables, such as surface roughness, which significantly influence runoff velocity and depth. Hydrological models commonly express the surface roughness using Manning’s roughness coefficient (n) as a key variable. The objectives were thus to determine surface roughness by exploiting a new high spatial resolution spaceborne synthetic aperture radar (SAR) technology and to examine the correlation between radar backscatter and Manning’s roughness coefficient in an arid environment. A very strong correlation (R2 = 0.97) was found between the constellation of small satellites for Mediterranean basin observation (COSMO)-SkyMed SAR backscatter and surface roughness. The results of this research demonstrate the feasibility of using an X-band spaceborne sensor with high spatial resolution for the evaluation of surface roughness in flat arid environments. The innovative method proposed to evaluate Manning’s n roughness coefficient in arid environments with sparse vegetation cover using radar backscatter may lead to improvements in the performance of hydrological models.