Evaluation of urban flood susceptibility through integrated Bivariate statistics and Geospatial technology.

Flood disasters are frequent natural disasters that occur annually during the monsoon season and significantly impact urban areas. This area is characterized by impermeable concrete surfaces, which increase runoff and are particularly susceptible to flooding. Therefore, this study aims to adopt Bi-variate statistical methods such as frequency ratio (FR) and weight of evidence (WOE) to map flood susceptibility in an urbanized watershed. The study area encompasses an urbanized watershed surrounding the Chennai Metropolitan area in southern India. The essential parameters considered for flood susceptibility zonation include geomorphology, soil, land use/land cover (LU/LC), rainfall, drainage, slope, aspect, Topographic Wetness Index (TWI), and Normalized Difference Vegetation Index (NDVI). The flood susceptibility map was derived using 70% of randomly selected flood areas from the flood inventory database, and the other 30% was used for validation using the area under curve (AUC) method. The AUC method produced a frequency ratio of 0.806 and a weight of evidence value of 0.865 contributing to the zonation of the three classes. The study further investigates the impact of urbanization on flood susceptibility and is further classified into high, moderate, and low flood risk zones. With the abrupt change in climatic scenarios, there is an increase in the risk of flash floods. The results of this study can be used by policymakers and planners in developing a preparedness system to mitigate economic, human, and property losses due to floods in any urbanized watershed.

Mortality Associated with Priority Diseases in Flood-Affected Areas Using District Health Information System (DHIS2) During September-December 2022: Pakistan Experience.

OBJECTIVES: To quantify the burden of communicable diseases and characterize the most reported infections during public health emergency of floods in Pakistan. METHODS: The study's design is a descriptive trend analysis. The study utilized the disease data reported to District Health Information System (DHIS2) for the 12 most frequently reported priority diseases under the Integrated Disease Surveillance and Response (IDSR) system in Pakistan. RESULTS: In total, there were 1,532,963 suspected cases during August to December 2022 in flood-affected districts (n = 75) across Pakistan; Sindh Province reported the highest number of cases (n = 692,673) from 23 districts, followed by Khyber Pakhtunkhwa (KP) (n = 568,682) from 17 districts, Balochistan (n = 167,215) from 32 districts, and Punjab (n = 104,393) from 3 districts. High positivity was reported for malaria (79,622/201,901; 39.4%), followed by acute diarrhea (non-cholera) (23/62; 37.1%), hepatitis A and E (47/252; 18.7%), and dengue (603/3245; 18.6%). The crude mortality rate was 11.9 per 10 000 population (1824/1,532,963 [deaths/cases]). CONCLUSION: The study identified acute respiratory infection, acute diarrhea, malaria, and skin diseases as the most prevalent diseases. This suggests that preparedness efforts and interventions targeting these diseases should be prioritized in future flood response plans. The study highlights the importance of strengthening the IDSR as a Disease Early Warning System through the implementation of the DHIS2.

Combining multisensor images and social network data to assess the area flooded by a hurricane event.

In this study, multisensor remote sensing datasets were used to characterize the land use and land covers (LULC) flooded by Hurricane Willa which made landfall on October 24, 2018. The landscape characterization was done using an unsupervised K-means algorithm of a cloud-free Sentinel-2 MultiSpectral Instrument (MSI) image, acquired during the dry season before Hurricane Willa. A flood map was derived using the histogram thresholding technique over a Synthetic Aperture Radar (SAR) Sentinel-1 C-band and combined with a flood map derived from a Sentinel-2 MSI image. Both, the Sentinel-1 and Sentinel-2 images were obtained after Willa landfall. While the LULC map reached an accuracy of 92%, validated using data collected during field surveys, the flood map achieved 90% overall accuracy, validated using locations extracted from social network data, that were manually georeferenced. The agriculture class was the dominant land use (about 2,624 km2), followed by deciduous forest (1,591 km2) and sub-perennial forest (1,317 km2). About 1,608 km2 represents the permanent wetlands (mangrove, salt marsh, lagoon and estuaries, and littoral classes), but only 489 km2 of this area belongs to aquatic surfaces (lagoons and estuaries). The flooded area was 1,225 km2, with the agricultural class as the most impacted (735 km2). Our analysis detected the saltmarsh class occupied 541 km2in the LULC map, and around 328 km2 were flooded during Hurricane Willa. Since the water flow receded relatively quickly, obtaining representative imagery to assess the flood event was a challenge. Still, the high overall accuracies obtained in this study allow us to assume that the outputs are reliable and can be used in the implementation of effective strategies for the protection, restoration, and management of wetlands. In addition, they will improve the capacity of local governments and residents of Marismas Nacionales to make informed decisions for the protection of vulnerable areas to the different threats derived from climate change.

Health Consequences Management in a Multi-Hazard Context: A Systematic Review of the Coincidence of Flood and the COVID-19 Pandemic.

OBJECTIVES: The co-occurring flood and coronavirus disease (COVID-19) increase the consequences for health and life. This study examined the strategies to manage the health consequences of the co-occurring flood and COVID-19, with a specific focus on these 2 challenges. METHODS: This review included all the studies published in peer-reviewed journals between January 1980 and June 2021. Several electronic databases were searched, including Scopus, Web of Science, and PubMed. Mixed Methods Appraisal Tools (MMT), version 2018, assessed the articles retrieved through a comprehensive and systematic literature search. Descriptive and thematic analyses were carried out to derive strategies for managing the health consequences of the simultaneous flood and COVID-19. RESULTS: Among 4271 identified articles, 10 were eligible for inclusion. In total, 199 strategies were identified in this review for managing the multi-hazard health consequences of flooding and COVID-19, which were classified into 9 categories and 25 subcategories. The categories included policy making and decision making, coordination, risk communication, logistics, planning, preparedness measures, response measures, social and humanitarian support, and actions of local communities and non-governmental organizations. CONCLUSIONS: Managing a multi-hazard and reducing its health consequences requires various actions. Flood management must be needed, and flood-affected people and their health should be protected.

Disappearing cities on US coasts.

The sea level along the US coastlines is projected to rise by 0.25-0.3 m by 2050, increasing the probability of more destructive flooding and inundation in major cities1-3. However, these impacts may be exacerbated by coastal subsidence-the sinking of coastal land areas4-a factor that is often underrepresented in coastal-management policies and long-term urban planning2,5. In this study, we combine high-resolution vertical land motion (that is, raising or lowering of land) and elevation datasets with projections of sea-level rise to quantify the potential inundated areas in 32 major US coastal cities. Here we show that, even when considering the current coastal-defence structures, further land area of between 1,006 and 1,389 km2 is threatened by relative sea-level rise by 2050, posing a threat to a population of 55,000-273,000 people and 31,000-171,000 properties. Our analysis shows that not accounting for spatially variable land subsidence within the cities may lead to inaccurate projections of expected exposure. These potential consequences show the scale of the adaptation challenge, which is not appreciated in most US coastal cities.

Global evidence of rapid urban growth in flood zones since 1985.

Disaster losses are increasing and evidence is mounting that climate change is driving up the probability of extreme natural shocks1-3. Yet it has also proved politically expedient to invoke climate change as an exogenous force that supposedly places disasters beyond the influence of local and national authorities4,5. However, locally determined patterns of urbanization and spatial development are key factors to the exposure and vulnerability of people to climatic shocks6. Using high-resolution annual data, this study shows that, since 1985, human settlements around the world-from villages to megacities-have expanded continuously and rapidly into present-day flood zones. In many regions, growth in the most hazardous flood zones is outpacing growth in non-exposed zones by a large margin, particularly in East Asia, where high-hazard settlements have expanded 60% faster than flood-safe settlements. These results provide systematic evidence of a divergence in the exposure of countries to flood hazards. Instead of adapting their exposure, many countries continue to actively amplify their exposure to increasingly frequent climatic shocks.

A warming-induced reduction in snow fraction amplifies rainfall extremes.

The intensity of extreme precipitation events is projected to increase in a warmer climate1-5, posing a great challenge to water sustainability in natural and built environments. Of particular importance are rainfall (liquid precipitation) extremes owing to their instantaneous triggering of runoff and association with floods6, landslides7-9 and soil erosion10,11. However, so far, the body of literature on intensification of precipitation extremes has not examined the extremes of precipitation phase separately, namely liquid versus solid precipitation. Here we show that the increase in rainfall extremes in high-elevation regions of the Northern Hemisphere is amplified, averaging 15 per cent per degree Celsius of warming-double the rate expected from increases in atmospheric water vapour. We utilize both a climate reanalysis dataset and future model projections to show that the amplified increase is due to a warming-induced shift from snow to rain. Furthermore, we demonstrate that intermodel uncertainty in projections of rainfall extremes can be appreciably explained by changes in snow-rain partitioning (coefficient of determination 0.47). Our findings pinpoint high-altitude regions as 'hotspots' that are vulnerable to future risk of extreme-rainfall-related hazards, thereby requiring robust climate adaptation plans to alleviate potential risk. Moreover, our results offer a pathway towards reducing model uncertainty in projections of rainfall extremes.

Quantifying and improving flood resilience of urban drainage systems based on socio-ecological criteria.

In this paper, a new framework is developed for evaluating the resilience of urban drainage systems (UDSs) under floods by proposing and quantifying some technical and socio-ecological (SE) criteria. The proposed criteria are used to quantify the seven principles of building resilience in socio-ecological systems. The criteria mainly focus on preserving diversity and multiplicity in a UDS, managing variables that gradually change over time (slow variables), improving structural and functional connectivity, maintaining system adaptability, encouraging learning, broadening participation, and promoting polycentric governance systems. For evaluating the efficiency of the proposed framework, it is applied to a real-world case study of improving resilience of the UDS in the eastern part of Tehran metropolitan area. Three scenarios for flood management are proposed based on the Low Impact Development (LID) practices which are simulated using the Storm Water Management Model (SWMM). The Entropy method is used to consider the uncertainty in the relative importance of different criteria in estimating the flood resilience. The estimated values for the proposed criteria regarding the current drainage system in the study area show its undesirable condition in many sub-catchments. The results also show that using around 2.3 km2 of LID practices in this urban watershed can significantly improve the resilience in many sub-catchments (nearly, 30%) and reduce the total volume of the overflow (about 50%). The results also show that using the flood management scenarios, improving connectivity is the most influential factor that enhances the general resilience of the system.

The interaction of topographic slope with various geo-environmental flood-causing factors on flood prediction and susceptibility mapping.

This work integrates topographic slope with other geo-environmental flood-causing factors in order to improve the accuracy of flood prediction and susceptibility mapping using logistic regression (LR) model. The work was done for the eastern Jeddah watersheds in Saudi Arabia, where flash floods constitute a danger. A geospatial dataset with 140 historical flood records and twelve geo-environmental flood-causing factors was constructed. A number of significant statistical methods were also applied to provide reliable flood prediction and susceptibility mapping, including Jarque-Bera, Pearson's correlation, multicollinearity, heteroscedasticity, and heterogeneity analyses. The results of the models are validated using the area under curve (AUC) and other seven statistical measures. These statistical measures include accuracy (ACC), sensitivity (SST), specificity (SPF), negative predictive value (NPV), positive predictive value (PPV), root-mean-square error (RMSE), and Cohn's Kappa (K). Results showed that both in training and testing datasets, the LR model with the slope as a moderating variable (LR-SMV) outperformed the classical LR model. For both models (LR and LR-SMV), the adjusted R2 is 88.9 and 89.2%, respectively. The majority of the flood-causing factors in the LR-SMV model had lower Sig. R values than in the LR model. As compared to the LR model, the LR-SMV attained the highest values of PPV (90%), NPV (93%), SST (92%), SPF (90%), ACC (89%), and K (81%), for both training and testing data. Moreover, employing slope as a moderating variable demonstrated its viability and reliability for defining precisely flood-susceptibility zones in order to reduce flood risks.

The challenge of unprecedented floods and droughts in risk management.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Behavioral, health- related and demographic risk factors of death in floods: A case-control study.

During the first half of 2019, many provinces of Iran were affected by floods, which claimed the lives of 82 people. The present study aimed to investigate the behavioral, health related and demographic risk factors associated with deaths due to floods. We measured the odds ratio and investigated the contribution and significance of the factors in relation to mortality. This case-control study was conducted in the cities affected by flood in Iran. Data were collected on the flood victims using a questionnaire. Survivors, a member of the flood victim's family, were interviewed. In total, 77 subjects completed the survey in the case group, and 310 subjects completed the survey in the control group. The findings indicated that factors such as the age of less than 18 years, low literacy, being trapped in buildings/cars, and risky behaviors increased the risk of flood deaths. Regarding the behavioral factors, perceived/real swimming skills increased the risk of flood deaths although it may seem paradoxical. This increment is due to increased self confidence in time of flood. On the other hand, skills and abilities such as evacuation, requesting help, and escape decreased the risk of flood deaths. According to the results, the adoption of support strategies, protecting vulnerable groups, and improving the socioeconomic status of flood-prone areas could prevent and reduce the risk of flood deaths.

Satellite imaging reveals increased proportion of population exposed to floods.

Flooding affects more people than any other environmental hazard and hinders sustainable development1,2. Investing in flood adaptation strategies may reduce the loss of life and livelihood caused by floods3. Where and how floods occur and who is exposed are changing as a result of rapid urbanization4, flood mitigation infrastructure5 and increasing settlements in floodplains6. Previous estimates of the global flood-exposed population have been limited by a lack of observational data, relying instead on models, which have high uncertainty3,7-11. Here we use daily satellite imagery at 250-metre resolution to estimate flood extent and population exposure for 913 large flood events from 2000 to 2018. We determine a total inundation area of 2.23 million square kilometres, with 255-290 million people directly affected by floods. We estimate that the total population in locations with satellite-observed inundation grew by 58-86 million from 2000 to 2015. This represents an increase of 20 to 24 per cent in the proportion of the global population exposed to floods, ten times higher than previous estimates7. Climate change projections for 2030 indicate that the proportion of the population exposed to floods will increase further. The high spatial and temporal resolution of the satellite observations will improve our understanding of where floods are changing and how best to adapt. The global flood database generated from these observations will help to improve vulnerability assessments, the accuracy of global and local flood models, the efficacy of adaptation interventions and our understanding of the interactions between landcover change, climate and floods.

Geospatial Assessment of Floods in Western Nepal.

Floods are major problems, and their coexistence poses a potent threat, which cannot be eradicated but has to be managed. Extreme affects untold numbers of people, taxing economies, disrupting food production, creating unrest, and prompting migrations. There is much more that can be done to understand the effects of floods, particularly to help protect the poorest and most vulnerable. This research was carried out in the affected area of Bhimdatta municipality and aimed to find out the flood event of 2013 and present the scenario done for flood disaster management. The primary data were collected by direct observation and key informant survey. Landsat images were downloaded from USGS websites, and secondary information was collected through previous research and articles. The data were analyzed by using ArcGIS. It was found that the flood had created a negligible impact on the forest, high impact on the river itself, and average impact on land. 0.13% of forests, 17.38% of land, and 82.48% of river bodies were affected by the flood of 2013. Different governmental and nongovernmental organizations played an effective role for flood disaster management.

Relationship between flood severity and risk of hospitalisation in the Mekong River Delta of Vietnam.

OBJECTIVE: To examine the relationship between flood severity and risk of hospitalisation in the Vietnam Mekong River Delta (MRD). METHODS: We obtained data on hospitalisations and hydro-meteorological factors during 2011-2014 for seven MRD provinces. We classified each day into a flood-season exposure period: the 2011 extreme annual flood (EAF); 2012-2014 routine annual floods (RAF); dry season and non-flood wet season (reference period). We used province-specific Poisson regression models to calculate hospitalisation incidence rate ratios (IRRs). We pooled IRRs across provinces using random-effects meta-analysis. RESULTS: During the EAF, non-external cause hospitalisations increased 7.2% (95% CI 3.2% to 11.4%); infectious disease hospitalisations increased 16.4% (4.3% to 29.8%) and respiratory disease hospitalisations increased 25.5% (15.5% to 36.4%). During the RAF, respiratory disease hospitalisations increased 8.2% (3.2% to 13.5%). During the dry season, hospitalisations decreased for non-external causes and for each specific cause except injuries. CONCLUSIONS: We observed a gradient of decreasing risk of hospitalisation from EAF to RAF/non-flood wet season to dry season. Adaptation measures should be strengthened to prepare for the increased probability of more frequent extreme floods in the future, driven by climate change.

Fungi and their secondary metabolites in water-damaged indoors after a major flood event in eastern Croatia.

In winter and summer of 2016 and 2017, airborne fungi and house dust were collected in indoors of the village Gunja, which had been flooded, and the control village Gornji Stupnik (Croatia) in order to explore variations of fungal indoor levels, particularly Aspergilli section Nidulantes series Versicolores, as well as fungal metabolites in dust. Levels of airborne Aspergilli (Versicolores) were three times as high in winter and summer in Gunja than in the control village, while dustborne isolates were equally present in both locations. Sequencing of the calmodulin gene region revealed that among Aspergilli (Versicolores), A. jensenii and A. creber were dominant and together with A. puulaauensis, A. tennesseensis and A. venenatus produced sterigmatocystin and 5-methoxysterigmatocystin (HPLC coupled with mass spectrometry); A. amoenus, A. fructus, A. griseoaurantiacus, A. pepii, and A. protuberus produced sterigmatocystin but not 5-methoxysterigmatocystin; A. sydowii did not produce any of these toxins. A total of 75 metabolites related to Penicillium (29), Aspergillus (22), Fusarium (10), Alternaria (5), Stachybotrys (2), and other fungi (7) were detected in dust by liquid chromatography-tandem mass spectrometry. The majority of metabolites including sterigmatocystin and 5-methoxysterigmatocystin exhibited a higher prevalence in winter in Gunja.