Estimating sediment volumes from fossil fluvial overbank deposits remains challenging, particularly at fine spatial and temporal scales in complex morphologies. This study focuses on a ~7 km 2 concave bank of the Grande Ponche palaeomeander (Rhône Delta, France), where rapid overbank deposition occurred over ~20 years during the Little Ice Age (LIA). Two modelling approaches are evaluated for reconstructing deposit thickness with sinuous geometry from sparse datasets: Discrete Smooth Interpolation (DSI), and kriging applied on a complex grid allowing curvilinear anisotropy to be reproduced. Both approaches yielded similar volume estimates (~0.009–0.01 km 3 ), showing overbank deposits (~0.004 km 3 , ~3.15 mm/yr) and floodplain aggradation (~0.006 km 3 , ~1.43 mm/yr). Compared to conventional techniques, DSI and kriging provided more realistic 3D models capturing spatial anisotropy and proximo-distal thickness gradients, hence prefiguring better sediment volume estimation. Bootstrapping results show volume estimates less sensitive to spatial distribution of sparse data. DSI enabled the reconstruction of levee and crevasse splay within overbank deposits from a minimal dataset. Kriging requires denser data to obtain suitable variograms and then did not achieve these detailed models. However, when applicable, it allows for volume estimate uncertainty that DSI does not provide. The fine-scale sediment volumes at the Grande Ponche reveal the disproportionate geomorphological impact of short-term LIA flood, with aggradation rates far exceeding Holocene and modern Rhône delta averages. These results show that brief intense climatic phases can generate important but spatially localised sediment storage. Improved quantification of such short-term sedimentary pulses strengthens source-to-sink analyses and refines our understanding of sedimentary responses to climatic variability in fluvial-deltaic systems. • Fine-scale sediment volumes estimated for Little Ice Age overbank deposits • Discrete Smooth Interpolation and kriging used to model sediment thickness from sparse data • Curvilinear grid improves kriging performance in sinuous palaeochannels • Overbank deposition during the LIA reached up to 3.15 cm/yr locally • LIA sedimentation rates greatly exceed both Holocene and modern Rhône Delta records

The online version contains supplementary material available at 10.1007/s11111-026-00523-z.

Every year, floods disrupt the lives of hundreds of millions of people worldwide. Their impacts are further intensified by climate change, rapid urbanization, and land-use changes, making it crucial to identify areas most susceptible to flooding. While machine learning (ML) models have proven effective in identifying flood susceptibility, their validity and the integration of human risk remain underexplored in geomorphologically complex and highly flood-prone regions. This study developed an ensemble ML framework for flood susceptibility mapping in the Kosi Megafan, located in Nepal and India. We compared its performance with established ML models and a one-dimensional convolutional neural network (1D-CNN), validated results using Dartmouth Flood Observatory (DFO) and Sentinel-1 SAR (Synthetic Aperture Radar) data, and assessed the population exposed to high-risk zones. A total of 13 (8 retained) flood conditioning factors (FCFs) were derived from remote sensing datasets, and a flood inventory was created to train multiple ML models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), Support Vector Machine (SVM), 1D-CNN, and a Stacked Ensemble model. Among these, the stacked ensemble model achieved the highest performance (AUC = 0.76, accuracy = 0.70, precision = 0.69, recall = 0.72, F1-score = 0.70). The resulting susceptibility map identified high-risk zones mainly in the southern and southwestern Megafan, showing strong spatial agreement with the Sentinel-1-derived flood inventory and the DFO flood data (1992–2022). This study highlights the effectiveness of combining SAR-derived flood evidence with ensemble ML approaches for accurate and scalable flood susceptibility mapping in data-scarce, hazard-prone basins. Ultimately, the research supports efforts to build resilience and mitigate the long-term impact of flooding in the region.

Hurricanes can disrupt healthcare delivery and patients' access to timely cancer care. Such disruptions may contribute to adverse cancer outcomes, yet few studies have examined hurricane-related delays in treatment initiation. We conducted a quasi-experimental, observational study using a CITS to evaluate the association between hurricane exposure and time to initial treatment among patients diagnosed with breast, colorectal, or lung cancer in North Carolina following Hurricanes Matthew (2016) and Florence (2018). The analysis included 59,406 patients between November 2015 and August 2019 in the NC Central Cancer Registry. Hurricane-exposed areas was defined using (1) presidential disaster declarations (county level) and (2) flood extent data (FLDEX) at county and ZIP-code levels. Monthly median time to initial cancer-directed treatment within 12 months of diagnosis was modeled using ARIMA to estimate immediate (level) and sustained (trend) effects. No significant immediate or sustained changes in median time to treatment were observed using FEMA-based exposure definitions. However, using ZIP- code level FLDEX data, colorectal cancer patients in high-flood exposure areas (0.1% and 0.5% flooded) experienced significant immediate median delays of 10.39 (2.8, 18.0) and 10.97 days (95% CI: 2.1, 19.9), respectively. While no significant effects on time to treatment were observed using traditional measures of hurricane hazards, more granular flood extent data revealed treatment delays among colorectal patients living in areas with greater flooding extent. These findings provide support for further investigation of the use of ZIP code-level flood extent data to evaluate hurricane impacts on continuity of cancer care.

Impacts of major floods on new human respiratory health symptoms in indoor environments

This study investigates the impact of flooding on maternal health outcomes among pregnant women in rural Hyderabad, Pakistan, using a mixed-methods approach combining retrospective facility record analysis (pre- and post-flood data), quantitative surveys (n=400), and qualitative interviews (n=10). Pre- and post-flood comparisons of facility records revealed severe healthcare disruptions, with antenatal care visits declining by 60% (120±25 to 48±18/month, p<0.001) and cesarean section availability dropping from 90% to 35% post-flood. Neonatal mortality nearly tripled (12 to 34 deaths/1,000 live births, p=0.002) based on health facility data. Flood-exposed women showed significantly higher stress levels (β=3.8, p<0.001), food insecurity (β=2.3, p<0.001), and reduced satisfaction with healthcare access (2.1±1.0 vs 8.3±1.3, p<0.001). Effect sizes (Cohen's d) and β coefficients were derived from multivariate regression and between-group comparisons, with models adjusted for confounders such as income, education, and access to transport. Qualitative findings identified three key themes: (1) transportation and infrastructure barriers, (2) profound psychological distress, and (3) reliance on traditional midwives due to system failures. The study highlights critical gaps in emergency preparedness and maternal health knowledge, with flood-affected women scoring significantly lower on measures of health awareness (e.g., 3.2±1.5 vs 7.5±1.4 for water purification knowledge, p<0.001). These findings demonstrate the urgent need for flood-resilient maternal health services and targeted community education programs in vulnerable regions.

The 2022 and 2025 floods in Pakistan forced more than 33 million people to flee from their homes, destroyed medical facilities across a large portion of Punjab, Khyber-Pakhtunkhwa, Sindh, and Balochistan, and revealed major deficiencies in government management, healthcare systems, environmental protection, and climate preparedness. Pakistan emits <1% of worldwide greenhouse gases, yet remains among the most climate-sensitive nations, reflecting global inequities in climate impact. Floods destroyed basic health determinants, thus contributing to infectious disease epidemics, malnutrition, and mental health problems. To evaluate the short- and long-term flood impacts, this article applies the Disaster Management Cycle, along with the One Health, Planetary Health, and Doughnut Economy frameworks. The framework demonstrates the impact of floods on the health and healthcare system while simultaneously eroding the ecosystem and making the population more susceptible. The article identifies priorities for climate-adaptive health care infrastructure, environmental recovery, equity-centered disaster preparedness, and integration of One Health principles into medical education.

Glacial Lake Outburst Floods (GLOFs) are an increasing hydro-meteorological hazard in the high-altitude areas of northern Pakistan, which is enhanced due to the increased glacial melt under human-induced climate change. This paper examines the spatial-temporal occurrence of GLOFs and assesses the socio-economic impact of GLOFs on down-stream communities in Gilgit-Baltistan (GB) and Chitral District, in the Hindu Kush-Karakoram ranges. The study is based on multi-temporal satellite imagery (Landsat and Sentinel series), historical inventory of the Pakistan Meteorological Department (PMD) and International Centre for Integrated Mountains Development (ICIMOD) highly-resolution digital elevation models, and field-based measurements in 12 high-risk valleys, showing a striking 38% increase in GLOF events over the 35-year period, with intense acceleration since Out of 3,044 glacial lakes identified over GB and neighboring Khyber Pakhtunkhwa, 33 are considered to be potentially dangerous, exposing over 7 million people to increased risk. Socio-economic effects were measured using 450 household surveys, semi-structured interviews with 85 key informants, and a geospatial combination of flood inundation maps and census, agricultural and infrastructure data. Notable disasters, such as the Gupis GLOF in Ghizer in August 2025 (destroying more than 300 houses, the Ghizer River, and displacing hundreds), demonstrate an average direct loss of USD 45 million per major outburst, mainly by destroying irrigated agricultural land (42%), road and bridge networks (31%), hydropower and irrigation systems (18% The indirect impacts (livelihood disruption, temporary migration, food insecurity, and increased poverty) lasted 4-8 years after the event, and they were disproportionately on agrarian households, women and indigenous populations with a low adaptive capacity. Vulnerability mapping identifies hotspots that are a combination of physical exposure and socio-economic marginalization. This analysis places GLOF risk as a deep-rooted socio-economic amplifier in GB and Chitral by moving beyond glaciological drivers to pre-empt human dimensions. Results highlight the necessity of combined, community-based adaptation plans, such as more effective early-warning systems, nature-based response, and transboundary risk-financing framework, to achieve resilience in current cryospheric change.

We develop a micro-level climate stress testing framework to evaluate the financial performance of small business loans under diverse climate scenarios. Focusing on European small and medium-sized enterprises (SMEs), we estimate the impact of coastal, flash, and river floods on loan default risk using a discrete-time survival model. Our analysis reveals that flood events significantly increase SME loan default probabilities in countries such as Spain and France. However, this effect is notably reduced in regions with strong infrastructure or effective support mechanisms. To complement the empirical findings, we conduct a forward-looking stress testing exercise that projects default probability trajectories under varying flood severity scenarios. This approach enables financial institutions and regulators to quantify the loan-level credit risk associated with climate-related flooding, offering valuable insights for risk management and policy design. • Climate stress test of SME loans in Europe using micro-level survival modelling. • Floods significantly raise SME loan default risk in Spain and France. • The impact of flooding is lower where structural defences and aid support are high. • Granular spatial and climate data are key for accurate SME stress testing.

Introduction: Floods are among the most frequent and destructive disasters globally, posing significant threats to human life, infrastructure, cultural and environmental heritage, and economic activities. The impact of floods is expected to grow due to climate change, population growth, and economic factors. Effective flood risk management involves assessing three key components: the hazard, exposure, and vulnerability. While understanding of hazards and exposure has improved, the terminology and methodologies for assessing vulnerability remain in development. Methods: This study focuses on evaluating the flood vulnerability level in municipalities of Mazovia Province, Poland, using a flood vulnerability index and open-access data. Research was conducted in municipalities identified as flood hazard areas (fluvial floods) with a 1% probability of occurrence. Results: The total flood vulnerability index of municipalities showed that the municipality of Wyszków had the greatest vulnerability, which stems from its highest exposure indicator, its high lack of resilience level, and its low level of susceptibility. The proportion of individuals with non-Polish nationality is relatively low in this area. Additionally, the percentages of people living in hardship, older individuals, and women are moderate compared to other municipalities. Conclusion: Municipalities, where vulnerability is mainly influenced by exposure, should implement spatial policies that limit land use within flood hazard areas. In areas where susceptibility significantly influences flood vulnerability, it is crucial to educate residents on how to protect themselves from flooding and to inform them about appropriate behaviors during a flood. Municipalities with low resilience should invest in the necessary manpower and equipment for effective rescue operations, facilitate a swift return to normalcy, and increase funding for civil protection efforts. Additionally, they should assess whether the number and availability of emergency services (such as firefighters) align with the population size and distribution. Acknowledgment: This research was funded by the National Science Centre, Poland, under the OPUS call in the Weave programme [2023/51/I/HS4/00255].

Differentiated Hydrodynamic Assessment of Pluvial and Fluvial Flooding in the Downstream Periyar Catchment Under Return Period Based Scenarios

Introduction: Increase in temperature and natural disasters may have impacts on individual behavior and cause social destabilization; however, there is no clear evidence regarding the impact of flash flooding. The study sought to evaluate the impact of flash floods on rates of violent trauma in Texas. Methods: Data from the Texas EMS Registry between 2018-2022 following 16 flash floods was used. Violent trauma totals were calculated within the county of the flash flood incidence. The baseline rate was established two weeks prior to the flash flood, and the post period extended two weeks post flood. Multivariable linear regression was performed to compare changes in violent trauma rates and county level covariables. Analyses were adjusted for county median income, county population, county social vulnerability index (SVI), total cost of damaged property, and the county baseline rate. Results: The baseline and post-flood median rate of violent trauma per county was 14.5 and 13.5 cases per week, respectively. Baseline violent trauma rates were positively correlated with county population (r=0.76), and increased SVI (r=0.53), and negatively correlated with increased income (r=-0.30). Testing showed no significant difference in the rates of violent trauma in the post-flash flood group compared to baseline (z=0.547, p=0.5843). Further analysis showed that for every $10,000 decrease in median income, there was an increase in weekly violent trauma by 2.67 cases (95% CI -0.87, 6.21; p=0.12) post flash flood. Conclusion: The findings demonstrate a positive correlation between the social vulnerability index and baseline rates, and a negative correlation between county median income and baseline rates. The findings also show a potential reduction in violent trauma in counties with higher income, indicating potential disparities in community resilience. Research with a larger population of flash floods is needed to further evaluate the impacts of flash floods and the potential protective factors against fluctuations in violence rates.

Flooding is one of the biggest challenges reported by small to medium-sized businesses (SMEs) in the UK, and flood insurance is an important tool for reducing SMEs’ future flood risks. Flood insurance helps small businesses manage increasing risks and, if priced and designed right, serves as a powerful incentive to better prepare for and reduce the impact of future floods. However, flood insurance uptake by SMEs is low and expensive. Insurance pricing depends on knowing an SME’s risks and level of resilience with confidence. However, SMEs exhibit diverse risk profiles and levels of vulnerability due to their heterogeneous business characteristics. Such complexity makes it difficult for the insurance industry to commodify SMEs’ risk and provide affordable insurance. As flood risk is on the rise, it is paramount to identify which factors influence insurers’ decisions to grant insurance to SMEs or deny it. This study uses a mixed-method approach were through online surveys, semi-structured interviews, focus group discussions, and workshops with lenders, insurers, surveyors, brokers, and SMEs, pursue threefold objectives: 1) identify factors that influence SMEs resilience and insurers decision making; 2) assess SMEs’ losses, flood risk mitigation strategies and insurance needs; and 3) collaborate with the insurance industry and SMEs to design and pilot a tool to unlock affordable insurance coverage. Results show that while critical, professional flood risk assessment and flood depth damages are not sufficient on their own. Well-kept descriptive and photographic evidence, along with the positive attitude associated with SMEs’ behaviour, makes the evidence much more compelling and convincing when they are deciding whether to insure or lend to specific businesses. The tool also encouraged SMEs to initiate or improve resilient behaviour and to facilitate communication and knowledge exchange between SMEs and insurance providers. Overall, this research offers policy and practice recommendations that have the potential to increase mutual understanding and drive a positive behavioural change among SMEs and the insurance industry.

Explainable flood damage assessment using multi-atrous self-attention and vision-language integration

Green mussel species Perna viridis is commonly occurring in coastal zone of Sindh. It is a fact that this species is growing fast. It is widely used in food. This edible species of mussel occurring in mudflats of Indus River creeks which relate to Arabian sea in Sindh Pakistan. Research study was done at mudflat of Ambra creek at Gharho shrimp farm situated at taluka Keti Bandar district Thatta, Sindh, Pakistan during period of 2023-2024. Water quality parameters of Ambar creek were examined with temperature of water 23.14286 ± 9.281318 °C; turbidity of water was found 40.28571 ± 8.4599918 cm; pH values observed 7.708571 ± 0.214975; hardness (CaCO3) 706.7143 ± 111.6538 mg/l; salinity of water 27.57143 ± 4.157609 ppt; TDS 86934.43 ± 13616.28 mg/l in both saline and freshwater environment. Dissolved oxygen 10.34857 ± 13616.28 mg/l and depth of water was observed 14.78571 ± 3.43823 fts. Water quality parameters of the experimental sites were found suitable for growth and dispersal of bivalve mussels. Ambra creek water is rich in micro biomass which consists of micro live food items. Various sized samples of the species were collected from mudflats in the creek during study period having size from 1.2 to 7.3 cm length and weight 0.179 to 50.23g. The reproductive system and maturation of gonads along with reproductive cycle of the animal were studied and found suitable as per environmental conditions of the habitat. It usually depends on the seasonal variation of temperature and turbidity of water. The effects of rainfall and floods have shown a significant change in maturation. It was observed that heavy flood in the river Indus brings lot of silt and clay which plays a positive role in the growth, production and reproduction of the Perna viridis.

This study aims to examine the impact of flash floods and landslides in Sumatra on the income of Micro, Small, and Medium Enterprises (MSMEs) in Aceh, using a literature review. Flash floods and landslides can significantly reduce business income, especially in the agricultural and MSME sectors, through land damage, asset loss, and decreased productivity. Studies in similar regions show that household and business income can drop dramatically during and after a disaster, by as much as 80% compared to normal conditions. In addition, MSMEs face further challenges, including higher operating costs due to limited electricity supply, infrastructure damage, and restricted access to raw materials and markets. Factors such as income diversification, educational levels, and membership in social organizations can affect SMEs' vulnerability and their ability to adapt to disasters. The results of this review emphasize the importance of mitigation efforts, improving disaster literacy, and government policy support and access to financing to strengthen the resilience of SMEs in Aceh to the risks of flash floods and landslides. Keywords: Aceh, Flash Floods and Landslides, Income, MSMEs

Abstract Anthropogenically induced climate change is expected to increase the intensity and frequency of natural disturbances like floods and droughts, with serious potential consequences for wetlands. While there have been some studies that have investigated the impact of hurricanes (tropical cyclones) on coastal wetlands, there are gaps in spatially quantifying the impacts of other extreme meteorological events on inland wetlands. We addressed this gap by studying the impacts of severe flooding, caused by a deep cut-off low system in September 2023, on wetlands in southern Africa. This study aimed to spatially quantify biogeomorphic changes in the wetlands following the flood event, using freely available remote sensing data from before and after the event, and to establish the best method for this analysis. Three methods were applied to detect changes, namely digitization, index analysis and change detection. For the index analysis, the effectiveness of the Normalized Difference Vegetation Index (NDVI) and Bare Soil Index (BSI) was explored. From the results of all methods, we found that bare ground increased significantly (t=-6.35, df = 8, p &lt; 0.01) by a mean of 70 000 m 2 (8%) per wetland, while greenness significantly decreased (t = 5.61, df = 8, p &lt; 0.01) with a mean loss of vegetation of 40 000 m 2 following the floods. The most accurate of the automated approaches to mapping post-flood impact on palmiet wetland systems was change detection (89%). Leveraging applications in remote sensing using freely available imagery presents a critical opportunity to study and interrogate tipping points in wetlands in data-constrained regions.

The study delivers a deep analysis to scrutinise essential notions regarding causes, impacts, and challenges of climate change. Pakistan is considered one of the top five countries vulnerable to climate-related problems. Climate change has become one of the major reasons worldwide. The worse metrological conditions include various natural disasters such as abrupt increases in temperature, deteriorating precipitation patterns, and rapid glacier melting. One of the greatest dilemmas is that climate-induced floods have escalated in regularity and intensity, paving the way for massive complications to the social, governmental, and economic systems of Pakistan. Frequent torrents led to loss of human lives and grievous harm to infrastructure. The qualitative research is used to conduct this research. In conclusion, floods are unrestrained, but their effects can be overcome through resilient planning and strategies, good infrastructure, and reforms. The government of Pakistan must associate national advancement with meteorological dimensions and mitigate the impact of climate change.

Abstract The loss of potential storage space due to vegetation succession is a significant issue, particularly in unmanaged farmlands connected to drainage channels, reducing the effectiveness of the land in mitigating flood risk. This study aimed to discover unmanaged spaces within the alluvial plain of the Lower Tone River Basin, Japan, that have undergone vegetation succession. By monitoring the distribution of vegetation succession, the aim was to develop a technical method to identify and repurpose vegetation succession sites as storage spaces through proposed interventions to mitigate inland flooding within the alluvial plain of the Lower Tone River Basin. The analytical framework involved extracting alluvial plain areas, monitoring vegetation succession by integrating optical and synthetic aperture radar satellite images over the 2017–2024 period, analyzing the relationship between land-use types and vegetation succession patterns, extracting targeted vegetation succession sites, and classifying targeted vegetation succession patches based on height above the nearest drainage, distance to the nearest drainage channel, and other parameters. The classification resulted in three functional classes. Class 1 spaces were closely linked to water channels, making them critical areas for immediate floodwater storage. Class 2 spaces served as intermediate storage areas, situated at moderate distances from the water channels. Class 3 spaces provided final storage spaces for dispersed floodwater at the highest elevation and the furthest distance from the drainage channels. The sequential impact of inland flooding characterizes the functional hierarchy among Classes 1, 2, and 3, considering the on-site conditions. Overflowing from the drainage channels first impacts the Class 1 spaces. As the floodwater dispersed, it reached Class 2 spaces. Finally, Class 3 spaces served as the last line of mitigation, storing floodwater spread widely across the landscape. By identifying and categorizing vegetation succession patches for conversion into storage spaces, this study provides a basis for prioritizing areas for intervention and developing targeted flood mitigation strategies.

Rapid, objective, and accurate crop damage assessment is essential to minimizing farmers’ financial loss and enabling early settlement of crop insurance. The present study proposes a framework for assessing the impact of heavy rainfall-induced flood on Kharif rice over West Bengal under a satellite-based crop insurance program. Daily actual and normal rainfall data from India Meteorological Department (IMD) were used to study the pattern and magnitude of rainfall to confirm the heavy rainfall incidence over affected districts of West Bengal. The Sentinel-1-derived temporal VH backscatter validated using ground observations was utilized to identify the rice crop areas. The backscatter difference images between pre-and post-peril periods, along with threshold and histogram approaches, were adopted to discriminate the inundated areas from non-inundated areas. The information on the inundated rice crop was derived by intersecting the rice layer with the inundated area. The behavior of temporal backscatter profiles, i.e., pre- and post-peril periods, was analyzed to ascertain the impacts of flood-induced inundation on rice crop health. Further, the phenological information during floods was identified from transplanting periods in backscatter profiles, and damage severity was assessed by integrating inundation, the affected area, and rice crop stage information. The outcomes, validated with ~1500 crop loss surveys (CLSs), show that the framework is effective and useful for crop insurance.