Floods and cause-specific mortality in the UK: a nested case-control study.

BACKGROUND: Floods are the most frequent weather-related disaster, causing significant health impacts worldwide. Limited studies have examined the long-term consequences of flooding exposure. METHODS: Flood data were retrieved from the Dartmouth Flood Observatory and linked with health data from 499,487 UK Biobank participants. To calculate the annual cumulative flooding exposure, we multiplied the duration and severity of each flood event and then summed these values for each year. We conducted a nested case-control analysis to evaluate the long-term effect of flooding exposure on all-cause and cause-specific mortality. Each case was matched with eight controls. Flooding exposure was modelled using a distributed lag non-linear model to capture its nonlinear and lagged effects. RESULTS: The risk of all-cause mortality increased by 6.7% (odds ratio (OR): 1.067, 95% confidence interval (CI): 1.063-1.071) for every unit increase in flood index after confounders had been controlled for. The mortality risk from neurological and mental diseases was negligible in the current year, but strongest in the lag years 3 and 4. By contrast, the risk of mortality from suicide was the strongest in the current year (OR: 1.018, 95% CI: 1.008-1.028), and attenuated to lag year 5. Participants with higher levels of education and household income had a higher estimated risk of death from most causes whereas the risk of suicide-related mortality was higher among participants who were obese, had lower household income, engaged in less physical activity, were non-moderate alcohol consumers, and those living in more deprived areas. CONCLUSIONS: Long-term exposure to floods is associated with an increased risk of mortality. The health consequences of flooding exposure would vary across different periods after the event, with different profiles of vulnerable populations identified for different causes of death. These findings contribute to a better understanding of the long-term impacts of flooding exposure.

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.

Application of multi-criteria decision-making on low-impact development practice selection for the Kinyerezi River sub-catchments in Dar es Salaam, Tanzania.

The impermeable areas in catchments are proportional to peak flows that result in floods in river reaches where the flow-carrying capacity is inadequate. The high rate of urbanization witnessed in the Kinyerezi River catchment in Dar es Salaam city has been noted to contribute to floods and siltation in the Msimbazi River. The Low-Impact Development (LID) practices that includes bio-retention (BR) ponds, rain barrels (RBs), green roofs (GRs), etc. can be utilized to mitigate portion of the surface runoff. This study aims to propose suitable LID practices and their sizes for mitigating runoff floods in the Kinyerezi River catchment using the Multi-Criteria Decision-Making (MCDM) approach. The results indicated that the BR and RBs were ranked high in capturing the surface runoff while the sediment control fences were observed to be the best in reducing sediments flowing into the BR. The proposed BR ponds were greater than 800 m2 with 1.2 m depth while RB sizes for Kinyerezi and Kisungu secondary schools and Kinyerezi and Kifuru primary schools were 2,730; 2,748; 1,385; and 1,020 m3, respectively. The BR ponds and RBs are capable of promoting water-demanding economic activities such as horticulture, gardening, car washing while reducing the school expenses and runoff generation.

Transcriptome analysis of antioxidant system response in Styrax tonkinensis seedlings under flood-drought abrupt alternation.

BACKGROUND: Styrax tonkinensis (Pierre) Craib ex Hartwich faces challenges in expanding in the south provinces of Yangtze River region due to climate extremes like flood-drought abrupt alternation (FDAA) caused by global warming. Low tolerance to waterlogging and drought restricts its growth in this area. To study its antioxidant system and molecular response related to the peroxisome pathway under FDAA, we conducted experiments on two-year-old seedlings, measuring growth indexes, reactive oxygen species content, antioxidant enzyme activity, and analyzing transcriptomes under FDAA and drought (DT) conditions. RESULTS: The physiological results indicated a reduction in water content in roots, stems, and leaves under FDAA conditions. The most significant water loss, amounting to 15.53% was observed in the leaves. Also, ROS accumulation was predominantly observed in leaves rather than roots. Through transcriptome analysis, we assembled a total of 1,111,088 unigenes (with a total length of 1,111,628,179 bp). Generally, SOD1 and CAT genes in S. tonkinensis seedlings were up-regulated to scavenge ROS. Conversely, the MPV17 gene exhibited contrasting reaction with up-regulation in leaves and down-regulation in roots, leading to increased ROS accumulation in leaves. CHS and F3H were down-regulated, which did not play an essential role in scavenging ROS. Moreover, the down-regulation of PYL, CPK and CALM genes in leaves may not contribute to stomatal closure, thereby causing continuous water loss through transpiration. Whereas, the decreased root vigor during the waterlogging phase and up-regulated CPK and CALM in roots posed obstacles to water absorption by roots. Additionally, the DEGs related to energy metabolism, including LHCA and LHCB, were negatively regulated. CONCLUSIONS: The ROS generation triggered by MPV17 genes was not the main reason for the eventual mortality of the plant. Instead, plant mortality may be attributed to water loss during the waterlogging phase, decreased root water uptake capacity, and continued water loss during the subsequent drought period. This study establishes a scientific foundation for comprehending the morphological, physiological, and molecular facts of S. tonkinensis under FDAA conditions.

Rainfall analysis and deriving design storm for hydrological modelling of Koyna dam catchment area in Maharashtra state of India.

Rainfall is a key hydro meteorological variable. Climate change is disrupting the hydrological cycle and altering the usual cycle of rainfall, which frequently results in long-lasting storms with significant rainfall. A first step in hydrologic design of project is to determine the design storm or rainfall events to be used. For deriving design storm, researchers concluded that instead of using generalized readily available curves or maps, it is better to estimate design storm based on site specific historical rainfall data. The objective of the study is to analyze the rainfall data in the koyna watershed area in order to evaluate the design storm, which will be further used as an input data for HEC-HMS event based hydrological modelling of flood peak attenuation of design storm flow at koyna dam during extreme rainfall event. In this study, 40 years (1982-2021) of rainfall data from 8 rain gauge stations in Koyna Dam Catchment area is used initially for performing trend analysis through statistical and graphical techniques and then for Isopluvial analysis. The Sen's slope test and the Mann-Kendall test are the statistical techniques employed, and Innovative Trend Analysis is the graphical technique used. IDF approach is used for deriving design storm, and using Gumbel's frequency distribution method Isohyetal maps, IDF tables and curves are prepared for 2,10,25,50,75 and 100 year return periods and 6,12,24,48 and 96 h durations. Results obtained from statistical and graphical trend analysis of annual rainfall series are consistent. No statistically significant trend in annual rainfall series is observed, however there is rising and falling trend was observed in annual as well as monthly rainfall series. From the results of design storm study, the design storm hyetograph of 10 years return period and 96 h duration is selected, which gives the rainfall intensity of 10.88 mm/h for the koyna catchment. There are various dams nearby koyna catchment, The Isohyet maps, IDF curves and table output available from this study can be more reliably used during planning and design of hydraulic structure for other areas near by koyna catchment.

Dispersal and connectivity in increasingly extreme climatic conditions.

While climate change has been shown to impact several life-history traits of wild-living animal populations, little is known about its effects on dispersal and connectivity. Here, we capitalize on the highly variable flooding regime of the Okavango Delta to investigate the impacts of changing environmental conditions on the dispersal and connectivity of the endangered African wild dog (Lycaon pictus). Based on remote sensed flood extents observed over 20 years, we derive two extreme flood scenarios: a minimum and a maximum flood extent, representative of very dry and very wet environmental periods. These conditions are akin to those anticipated under increased climatic variability, as it is expected under climate change. Using a movement model parameterized with GPS data from dispersing individuals, we simulate 12,000 individual dispersal trajectories across the ecosystem under both scenarios and investigate patterns of connectivity. Across the entire ecosystem, surface water coverage during maximum flood extent reduces dispersal success (i.e., the propensity of individuals to disperse between adjacent subpopulations) by 12% and increases dispersal durations by 17%. Locally, however, dispersal success diminishes by as much as 78%. Depending on the flood extent, alternative dispersal corridors emerge, some of which in the immediate vicinity of human-dominated landscapes. Notably, under maximum flood extent, the number of dispersing trajectories moving into human-dominated landscapes decreases by 41% at the Okavango Delta's inflow, but increases by 126% at the Delta's distal end. This may drive the amplification of human-wildlife conflict. While predicting the impacts of climate change on environmental conditions on the ground remains challenging, our results highlight that environmental change may have significant consequences for dispersal patterns and connectivity, and ultimately, population viability. Acknowledging and anticipating such impacts will be key to effective conservation strategies and to preserve vital dispersal corridors in light of climate change and other human-related landscape alterations.

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.

Machine learning-based potential loss assessment of maize and rice production due to flash flood in Himachal Pradesh, India.

Flash floods in mountainous regions like the Himalayas are considered to be common natural calamities. Their consequences often are more dangerous than any flood event in the plains. These hazards not only put human lives at threat but also cause economic deflation due to the loss of lands, properties, and agricultural production. Hence, assessing the impact of such hazards in the existing agricultural system is of utmost importance to understand the probable crop loss. In this paper, we studied the efficiency of the remotely sensed microwave data to map the croplands affected by the flash flood that occurred in July 2023 in Himachal Pradesh, a mountainous state in the Indian Himalayan Region. The Una, Hamirpur, Kangra, and Sirmaur districts were identified as the most affected areas, with about 9%, 6%, 5.74%, and 3.61% of the respective districts' total geographical area under flood. Further, four machine learning algorithms (random forest, support vector regressor, k-nearest neighbor, and extreme gradient boosting) were evaluated to forecast maize and rice crop production and potential loss during the Kharif season in 2023. A regression algorithm with ten predictor variables consisting of the cropland area, two vegetation indices, and seven climatic parameters was applied to forecast the maize and rice production in the state. Amongst the four algorithms, random forest showed outstanding performance compared to others. The random forest regressor estimated the production of maize and rice with R2 more than 0.8 in most districts. The mean absolute error and the root mean squared error obtained from the random forest regressor were also minimal compared to the others. The maximum production loss of maize is estimated for Solan (54.13%), followed by Una (11.06%), and of rice in Kangra (19.1%), Una (18.8%) and Kinnaur (18.5%) districts. This indicated the utility of the proposed approach for a quick in-season forecast on crop production loss due to climatic hazards.

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.

Biodegradable microplastics pose greater risks than conventional microplastics to soil properties, microbial community and plant growth, especially under flooded conditions.

Biodegradable plastics (bio-plastics) are often viewed as viable option for mitigating plastic pollution. Nevertheless, the information regarding the potential risks of microplastics (MPs) released from bio-plastics in soil, particularly in flooded soils, is lacking. Here, our objective was to investigate the effect of polylactic acid MPs (PLA-MPs) and polyethylene MPs (PE-MPs) on soil properties, microbial community and plant growth under both non-flooded and flooded conditions. Our results demonstrated that PLA-MPs dramatically increased soil labile carbon (C) content and altered its composition and chemodiversity. The enrichment of labile C stimulated microbial N immobilization, resulting in a depletion of soil mineral nitrogen (N). This specialized environment created by PLA-MPs further filtered out specific microbial species, resulting in a low diversity and simplified microbial community. PLA-MPs caused an increase in denitrifiers (Noviherbaspirillum and Clostridium sensu stricto) and a decrease in nitrifiers (Nitrospira, MND1, and Ellin6067), potentially exacerbating the mineral N deficiency. The mineral N deficit caused by PLA-MPs inhibited wheatgrass growth. Conversely, PE-MPs had less effect on soil ecosystems, including soil properties, microbial community and wheatgrass growth. Overall, our study emphasizes that PLA-MPs cause more adverse effect on the ecosystem than PE-MPs in the short term, and that flooded conditions exacerbate and prolong these adverse effects. These results offer valuable insights for evaluating the potential threats of bio-MPs in both uplands and wetlands.

Analysing the outbreaks of leptospirosis after floods in Kerala, India.

A growing number of studies have linked the incidence of leptospirosis with the occurrence of flood events. Nevertheless, the interaction between flood and leptospirosis has not been extensively studied to understand the influence of flood attributes in inducing new cases. This study reviews leptospirosis cases in relation to multiple flood occurrences in Kerala, India. Leptospirosis data were obtained for three years: 2017 (non-flood year) and two years with flooding-2018 (heavy flooding) and 2019 (moderate flooding). We considered the severity of flood events using the discharge, duration and extent of each flooding event and compared them with the leptospirosis cases. The distribution of cases regarding flood discharge and duration was assessed through descriptive and spatiotemporal analyses, respectively. Furthermore, cluster analyses and spatial regression were completed to ascertain the relationship between flood extent and the postflood cases. This study found that postflood cases of leptospirosis can be associated with flood events in space and time. The total cases in both 2018 and 2019 increased in the post-flood phase, with the increase in 2018 being more evident. Unlike the 2019 flood, the flood of 2018 is a significant spatial indicator for postflood cases. Our study shows that flooding leads to an increase in leptospirosis cases, and there is stronger evidence for increased leptospirosis cases after a heavy flood event than after a moderate flooding event. Flood duration may be the most important factor in determining the increase in leptospirosis infections.

Manufactured housing communities and climate change: Understanding key vulnerabilities and recommendations for emergency managers.

Manufactured housing communities (MHCs), commonly referred to as mobile home parks, provide an estimated 2.7 million American households with largely unsubsidized, affordable housing. Climate change threatens those who call these communities home by exacerbating known structural and social vulnerabilities associated with this housing type-including but not limited to increased risks to flooding, extreme temperatures, high winds, and wildfires. Climate change requires emergency managers to understand the diverse, integrated, and complex vulnerabilities of MHCs that affect their exposure to climate change risk. This article presents findings from an integrative literature review focused on the climate-related vulnerabilities of these communities described at three levels of scale: household, housing structure, and park community. It then draws on 15 years of engagement and action research with MHC residents and stakeholders in Vermont, including several federally declared flooding disasters, to distill key recommendations for emergency managers for assisting MHCs to prepare for and respond to emergencies. As climate change accelerates, emergency managers can increase efficacy by learning about the MHCs in their jurisdictions by leveraging the best available data to characterize risks, integrating MHCs into planning and mitigation activities, and engaging in conversations with stakeholders, including MHC residents and their trusted partners.

Designing user-centered decision support systems for climate disasters: What information do communities and rescue responders need during floods?

Flooding events are the most common natural hazard globally, resulting in vast destruction and loss of life. An effective flood emergency response is necessary to lessen the negative impacts of flood disasters. However, disaster management and response efforts face a complex scenario. Simultaneously, regular citizens attempt to navigate the various sources of information being distributed and determine their best course of action. One thing is evident across all disaster scenarios: having accurate information and clear communication between citizens and rescue personnel is critical. This research aims to identify the diverse needs of two groups, rescue operators and citizens, during flood disaster events by investigating the sources and types of information they rely on and information that would improve their responses in the future. This information can improve the design and implementation of existing and future spatial decision support systems (SDSSs) during flooding events. This research identifies information characteristics crucial for rescue operators and everyday citizens' response and possible evacuation to flooding events by qualitatively coding survey responses from rescue responders and the public. The results show that including local input in SDSS development is crucial for improving higher-resolution flood risk quantification models. Doing so democratizes data collection and analysis, creates transparency and trust between people and governments, and leads to transformative solutions for the broader scientific community.

Impact of climate-induced floods and typhoons on geriatric disabling health among older Chinese and Filipinos: a cross-country systematic review.

BACKGROUND: Apart from both China and the Philippines continuing to be exposed to and affected by different climate-induced hazards, in particular floods and typhoons, they are also reported to be witnessing rapid ageing populations of 60 years and older. As such, this systematic review synthesized the existing evidence about the impacts aggravated by floods and typhoons on the geriatric disabling health of older Chinese and Filipinos, respectively. METHODS: Four (4) electronic databases were systematically searched to identify eligible studies published between 2000 and early 2023. This process had to confirm the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA), as well as the standard protocol registered with PROSPERO (CRD42023420549). RESULTS: Out of 317 and 216 initial records retrieved for China and the Philippines, respectively, 27 (China) and 25 (Philippines) studies were eligible for final review. The disabling conditions they reported to affect the health of older adults were grouped into 4 categories: cognitive and intellectual, physical, chronic and terminal illnesses, and mental and psychological, with the latter identified as the most prevalent condition to affect older Chinese and Filipinos. On a sub-category level, posttraumatic stress disorder (PTSD) was the most common condition reported in 27 flood-related studies in China, while injuries and wounds prevailed in the Philippines, according to 25 typhoon-related studies. CONCLUSION: The increasing occurrence of extreme climate hazards, especially floods and typhoons in China and the Philippines, respectively, impacted the health of their older adults with various disabling effects or conditions. Therefore, this calls for appropriate geriatric-informed interventions in the context of climate change and rapidly ageing settings beyond China and the Philippines to others that are also prone to floods and typhoons.

Understanding Challenges Women Face in Flood-Affected Areas to Access Sexual and Reproductive Health Services: A Rapid Assessment from a Disaster-Torn Pakistan.

Introduction: According to the Global Climate Risk Index, Pakistan is ranked as the fifth-most vulnerable country to climate change. Most recently, during June-August 2022, heavy torrential rains coupled with riverine, urban, and flash flooding led to an unprecedented disaster in Pakistan. Around thirty-three million people were affected by the floods. More than 2 million houses were damaged, leaving approximately 8 million displaced and approximately 600,000 people in relief camps. Among those, 8.2 million women and 16 million children are the worst affected, with many requiring urgent medical and reproductive healthcare. To plan an efficient healthcare program and a climate-resilient health system, it is crucial to understand the issues that the affected people face during floods. Methodology. This rapid assessment included the population in the most severely affected districts across the four provinces of Pakistan. A mixed methods approach using qualitative and quantitative techniques was utilized. A total of 52 qualitative, in-depth interviews were conducted with community-level healthcare providers, national and provincial government departments, and development partners involved in relief activities. Using a structured questionnaire, the quantitative cross-sectional survey was conducted with a final sample of 422 women, married and unmarried (15-49 years old), residing in the relief camps in the flood-affected areas. The outcome variable of the survey was the access to sexual and reproductive health services faced by the women in the flood-affected districts. Data collection took place four months postfloods during Nov-Dec 2022, while the data analysis was conducted between Dec 2022 and Jan 2023. The quantitative data was analyzed using SPSS (Statistical Package for the Social Sciences) version 20, and qualitative data was analyzed using NVivo 12. Ethical consent was sought from all the participants. Ethical approval was also sought from the ethics committee of the Health Services Academy, Government of Pakistan. Results: The findings indicated that, overall, all the provinces were unprepared for a calamity of such a large magnitude. Access to services and health data reporting from the flood-affected areas was challenging mainly due to a shortage of trained health workforce because of the displacement of a large volume of the health workforce. Overall, equipment, medicines, supplies, and food were scarce. Women residing in the camps were markedly affected, and 84% (375) were not satisfied with the flood relief services provided to them. The floods impacted their monthly income as 30% (132) of respondents started depending on charity postfloods. Almost 77% (344) reported limited access to sexual and reproductive health services and had yet to receive sanitary, hygiene, and delivery kits, while 69% (107 out of 154) of girls stopped schooling postfloods. Almost 77% (112) of the married women reported having a child less than one year of age. Yet, only 30% (44 out of 144 currently married women) were using any form of family planning method-damage to the health facilities affected access to overall maternal care services. Conclusion: The findings concluded that there was no planning for sexual and reproductive health services in the flood-affected areas. Several barriers were identified. The government and development partners needed to prepare to cater to women's needs during the floods. The findings highlight the need for collaborative efforts between the government, civil society, and development partners to address the challenges faced in disaster management and strengthen disaster management capacity.

Exploring optimal deep tunnel sewer systems to enhance urban pluvial flood resilience in the gangnam region, South Korea.

Urban pluvial flooding is becoming a global concern, exacerbated by urbanization and climate change, especially in rapidly developing areas where existing sewer systems lag behind growth. In order to minimize a system's functional failures during extreme rainfalls, localized engineering solutions are required for urban areas chronically suffering from pluvial floods. This study critically evaluates the Deep Tunnel Sewer System (DTSS) as a robust grey infrastructure solution for enhancing urban flood resilience, with a case study in the Gangnam region of Seoul, South Korea. To do so, we integrated a one-dimensional sewer model with a rapid flood spreading model to identify optimal routes and conduit diameters for the DTSS, focusing on four flood-related metrics: the total flood volume, the flood duration, the peak flooding rate, and the number of flooded nodes. Results indicate that, had the DTSS been in place, it could have reduced historical flood volumes over the last decade by 50.1-99.3%, depending on the DTSS route. Regarding the conduit diameter, an 8 m diameter was found to be optimal for minimizing all flood-related metrics. Our research also developed the Intensity-Duration-Frequency (IDF) surfaces in three dimensions, providing a correlation between simulated flood-related metrics and design rainfall characteristics to distinguish the effect of DTSS on flood risk reduction. Our findings demonstrate how highly engineered solutions can enhance urban flood resilience, but they may still face challenges during extreme heavy rainfalls with a 80-year frequency or above. This study contributes to rational decision-making and emergency management in the face of increasing urban pluvial flood risks.

Multi-hazard assessment of climate-related hazards for European coastal cities.

The assessment of risk posed by climate change in coastal cities encompasses multiple climate-related hazards. Sea-level rise, coastal flooding and coastal erosion are important hazards, but they are not the only ones. The varying availability and quality of data across cities hinders the ability to conduct holistic and standardized multi-hazard assessments. Indeed, there are far fewer studies on multiple hazards than on single hazards. Also, the comparability of existing methodologies becomes challenging, making it difficult to establish a cohesive understanding of the overall vulnerability and resilience of coastal cities. The use of indicators allows for a standardized and systematic evaluation of baseline hazards across different cities. The methodology developed in this work establishes a framework to assess a wide variety of climate-related hazards across diverse coastal cities, including sea-level rise, coastal flooding, coastal erosion, heavy rainfall, land flooding, droughts, extreme temperatures, heatwaves, cold spells, strong winds and landslides. Indicators are produced and results are compared and mapped for ten European coastal cities. The indicators are meticulously designed to be applicable across different geographical contexts in Europe. In this manner, the proposed approach allows interventions to be prioritized based on the severity and urgency of the specific risks faced by each city.

Coupling simulation of pipeline nodes - Storage tank linkage in urban high-density built-up areas using optimization model.

Climate change and urbanization contribute to the increased frequency of short-duration intense rainstorms. Traditional solutions often involve multiple scenarios for cost-effectiveness comparison, neglecting the rationality of placement conditions. The effective coupling and coordination of the location, number, size, and cost of storage tanks are crucial to addressing this issue. A three-phase approach is proposed to enhance the dynamic link between drainage pipeline and storage tanks in urban high-density built-up areas, integrating Python language, SWMM, the Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-III), and the Analytic Hierarchy Process (AHP) methods. In the first stage, each node within the pipeline network is considered as a potential storage tank location. In the second stage, factors such as the length and diameter of the upstream connecting pipeline, as well as the suitability of the storage tank location, are assessed. In the third stage, the length and diameter of the downstream connecting pipeline node are evaluated. The results show that the 90 overflow nodes (overflow time >0.5h) have been cleared using the three-phase approach with a 50a (duration = 3h) return period as the rainfall scenario, which meets the flooding limitations. After the completion of the three-phase method configuration, the total overflow and SS loads were reduced by 96.45% and 49.30%, respectively, compared to the status quo conditions. These two indicators have decreased by 48.16 and 9.05%, respectively, compared to the first phase (the traditional method of only replacing all overflow nodes with storage tanks). The proposed framework enables decision-makers to evaluate the acceptability and reliability of the optimal management plan, taking into account their preferences and uncertainties.