Natural Disasters and Rehabilitation: Post‐Disaster Aid, Corruption, Misallocation, and Mistargeting - Ahmad, Muhammad Irshad; Shen, Qiong; Boota, Muhammad Waseem; Liu, Ruifeng; Ma, Hengyun (Sustainable Development, 2025)
ABSTRACT The increasing frequency of natural disasters, such as floods, droughts, and tsunamis, has made vulnerable communities less resilient, pushing them toward long‐term poverty and food insecurity. Effective post‐disaster rehabilitation is critical to restoring livelihoods, infrastructure, and food security. However, challenges such as corruption, misallocation, and mistargeting undermine post‐disaster aid programs. This study systematically reviews 86 peer‐reviewed articles (1990–2023) using the preferred reporting items for systematic reviews and meta‐analyses (PRISMA) protocol to investigate aid inefficiencies in disaster recovery. The findings reveal that aid often fails to reach the most affected communities, being diverted to unaffected areas due to political influence and local elites, exacerbating inequalities. Corruption further hampers institutional performance and long‐term disaster resilience efforts. The study calls for transparent, accountable, and inclusive strategies for aid distribution, aligning with SDG 10 (reduced inequalities) and SDG 11 (sustainable cities and communities). Future research should focus on gender‐sensitive strategies, local governance, and technological innovations to enhance aid transparency and effectiveness.
Keywords: Scopus_Alert_12_Septembre_2025

Predicting current habitat suitability for intermediate snail hosts of urogenital and intestinal schistosomiasis in the Lower Shire Valley floodplain of southern Malawi - Nkolokosa, Clinton; Chirombo, James; Jones, Christopher M.; Mbewe, Rex B.; Kambewa, Eggrey Aisha; Makaula, Peter; Tangena, Julie-Anne Akiko; Stothard, J. Russell (Parasites & Vectors, 2025)
Abstract Background Relating the geographical distribution of intermediate freshwater snail hosts (viz. vectors of schistosomes) to local environmental attributes offers value for understanding the epidemiological landscape of schistosomiasis transmission in a changing aquatic environment. Schistosomiasis—both urogenital and intestinal—causes significant human suffering, affecting approximately 240 million people globally and grouped within the neglected tropical disease (NTD) umbrella. This study addresses the following questions: 1. Where are the most suitable habitats for intermediate host snails in the Lower Shire Valley (LSV) in Malawi? 2. Which environmental factors are strongly associated with the geographical distribution of such snails in the LSV? Methods This paper presents the first species distribution models (SDMs) for intermediate snail hosts for urogenital and intestinal schistosomiasis in Chikwawa and Nsanje Districts, which together form the LSV). The SDMs developed for this study are ensemble machine learning approaches based on Random Forest (RF), Support Vector Machines (SVM), and multilayer perceptron (MLP) and are specific to the Bulinus africanus group and Biomphalaria pfeifferi . The former transmits urogenital schistosomiasis ( Schistosoma haematobium ), while the latter transmits intestinal schistosomiasis ( Schistosoma mansoni ). Results The SDMs reveal the following: 1) currently, Bu. africanus group not only has a wide distribution across central Chikwawa and eastern Nsanje but is also concentrated in floodplains, and the LSV has few habitats that can support Bi. pfeifferi , and 2) vegetation cover is the most important predictor of Bu. africanus group distribution, whereas precipitation variables are most important for Bi. pfeifferi in the LSV. Thus, Bu. africanus group habitat is the most dominant and abundant, while Bi. pfeifferi suitable habitat is patchy and scarce. Conclusion The distribution of suitable habitats for potential urogenital and intestinal schistosomiasis transmission across LSV is not uniform and typically non-overlapping. Understanding the spatial and temporal distributions of these snails is important for controlling and eliminating schistosomiasis. Graphical Abstract
Keywords: Scopus_Alert_12_Septembre_2025

Market-based instruments to fund nature-based solutions for flood risk management can disproportionately benefit affluent areas - Hill, Bartholomew; Marjoribanks, Tim; Moore, Harriet; Bosher, Lee; Gussy, Mark (Communications Earth & Environment, 2025)
Abstract Market-based instruments, including competitive tenders, are central to funding global environmental restoration and management projects. Recently, tenders have been utilised to fund Nature-based Solutions schemes for Natural Flood Management, with the explicit purpose of achieving co-benefits; flood management and reducing inequities. While multiple studies consider the efficacy of Nature-based Solutions for tackling inequities, no prior research has quantified whether the resource allocation for these projects has been conducted equitably. We analyse two national natural flood management programmes funded through competitive tenders in England to explore who benefits by considering the characteristics of projects, including socio-economic, geographical (e.g. rurality) and flood risk dynamics. Our results suggest that inequity occurs at both the application and funding stages of Nature-based Solutions projects for flood risk management. This reflects wider international challenges of using market-based instruments for environmental resource allocation. Competitive tenders have the potential to undermine the equitable benefits of Nature-based Solutions.
Keywords: Scopus_Alert_12_Septembre_2025

Research on Extreme Precipitation Risk Considering Physical-social-environmental Attributes - Zhang, Jianlei; Chu, Chenkun; Wang, Peng (Journal of Disaster Prevention and Mitigation Engineering, 2025)
This study aims to conduct a grid-scale extreme precipitation risk assessment in Xuanwu District, Nanjing, so as to fill the gaps in existing indicator systems and improve the precision of risk characterization. By integrating physical, social, and environmental indicators, a risk assessment framework was constructed to comprehensively represent the characteristics of extreme precipitation risk. This study applied the entropy weight method to calculate indicator weights, combined with ArcGIS technology and the K-means clustering algorithm, to analyze the spatial distribution characteristics of risk under a 100-year extreme precipitation scenario and to identify key influencing indicators across different risk levels. The results showed that extreme precipitation risk levels in Xuanwu District exhibited significant spatial heterogeneity, with an overall distribution pattern of low risk in the central area and high risk in the surrounding areas. The influence mechanisms of key indicators showed tiered response characteristics: the low-risk areas were mainly controlled by the submerged areas of urban and rural, industrial and mining, and residential lands, water body area, soil erosion level, and normalized difference vegetation index (NDVI). The medium-risk areas were influenced by the submerged areas of urban and rural, industrial and mining, residential lands, the submerged areas of forest land, emergency service response time to disaster-affected areas, soil erosion level, and NDVI. The high-risk areas were jointly dominated by the submerged areas of urban and rural, industrial and mining, residential lands, the submerged areas of forest land, and NDVI. The extremely high-risk areas were driven by three factors—the submerged areas of forest land, emergency service response time to disaster-affected areas, and the proportion of the largest patch to the landscape area. This study improves the indicator system for extreme precipitation risk assessment and clarifies the tiered response patterns of risk-driving indicators, providing a scientific basis for developing differentiated flood control strategies in Xuanwu District while offering important theoretical support for improving regional flood disaster resilience. © 2025 Editorial Office of Journal of Disaster Prevention and Mitigation Engineering. All rights reserved.
Publisher: Editorial Office of Journal of Disaster Prevention and Mitigation Engineering
Keywords: Scopus_Alert_5_Septembre_2025

Integrative strategies for urban flood resilience and risk: A meta-analysis of policy, infrastructural, and ecosystem-based interventions - Wang, Shitao; Bi, Xuehao (Physics and Chemistry of the Earth, 2025)
Urban flooding, intensified by climate change and rapid urbanization, demands robust and operationally effective resilience strategies. However, empirical evidence on the comparative effectiveness of such strategies remains limited. This study presents the first meta-analytic synthesis evaluating urban flood resilience interventions across institutional, infrastructural, and socio-ecological domains. By synthesizing data from 29 peer-reviewed studies (2000–2024), this study applies standardized effect sizes (Cohen's d) and meta-regression models to assess the effectiveness of different strategies. Results reveal a substantial overall effect (pooled d = 2.96, 95 % CI: [1.92, 3.99]) with high heterogeneity (I2 = 93.8 %). Institutional mechanisms, such as policy coordination, regulatory frameworks, and risk governance, consistently show the strongest and most statistically significant impacts (d ≈ 2.96). Low Impact Development (LID) demonstrates limited, non-significant effects (d ≈ 0.08). The study introduces a novel hierarchical resilience framework spanning different dimensions and establishes an evidence-based typology of urban flood resilience strategies. These findings highlight the importance of integrated, multi-level governance and context-specific planning in enhancing urban flood resilience. The study findings provides critical insights for implementing resilience strategies in flood-prone urban areas, and support the formulation of adaptive and sustainable urban policies. © 2025
Publisher: Elsevier Ltd
Keywords: Scopus_Alert_5_Septembre_2025

Impact of Land Use Patterns on Flood Risk in the Chang-Zhu-Tan Urban Agglomeration, China - Zhang, Ting; Wu, Kai; Wang, Xiulian; Li, Xinai; Li, Long; Chen, Longqian (Remote Sensing, 2025)
Flood risk assessment is an effective tool for disaster prevention and mitigation. As land use is a key factor influencing flood disasters, studying the impact of different land use patterns on flood risk is crucial. This study evaluates flood risk in the Chang-Zhu-Tan (CZT) urban agglomeration by selecting 17 socioeconomic and natural environmental factors within a risk assessment framework encompassing hazard, exposure, vulnerability, and resilience. Additionally, the Patch-Generating Land Use Simulation (PLUS) and multilayer perceptron (MLP)/Bayesian network (BN) models were coupled to predict flood risks under three future land use scenarios: natural development, urban construction, and ecological protection. This integrated modeling framework combines MLP’s high-precision nonlinear fitting with BN’s probabilistic inference, effectively mitigating prediction uncertainty in traditional single-model approaches while preserving predictive accuracy and enhancing causal interpretability. The results indicate that high-risk flood zones are predominantly concentrated along the Xiang River, while medium-high- and medium-risk areas are mainly distributed on the periphery of high-risk zones, exhibiting a gradient decline. Low-risk areas are scattered in mountainous regions far from socioeconomic activities. Simulating future land use using the PLUS model with a Kappa coefficient of 0.78 and an overall accuracy of 0.87. Under all future scenarios, cropland decreases while construction land increases. Forestland decreases in all scenarios except for ecological protection, where it expands. In future risk predictions, the MLP model achieved a high accuracy of 97.83%, while the BN model reached 87.14%. Both models consistently indicated that the flood risk was minimized under the ecological protection scenario and maximized under the urban construction scenario. Therefore, adopting ecological protection measures can effectively mitigate flood risks, offering valuable guidance for future disaster prevention and mitigation strategies. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Enhanced Urban Flood Hazard Assessment by Stochastic Event Catalog - Yan, Haochen; Guo, Kaihua; Guan, Mingfu (Water Resources Research, 2025)
Assessing flood severity in urban areas is a pivotal task for urban resilience and climate adaptation. However, the lack of in situ measurements hinders direct spatial estimation of flood return periods, while conventional assumptions about rainstorm-flood consistency introduce significant uncertainties due to rainstorm spatiotemporal variability (STV). This study proposes a novel framework that utilizes multivariate frequency analysis of flood variables at the street level (50 m) through a stochastic rainstorm-flood event catalog. The rainstorm events in the catalog are generated by a random field generator and resampled to match the joint distribution of STV variables consistent with radar observations. Urban flood processes are then simulated by a hydrodynamic model for flood hazard assessment (FHA). We applied the framework to a rural-urban watershed using 3,000 cases randomly resampled from the catalog. Results reveal that inundation characteristics respond more rapidly to increasing rainfall intensities than downstream flood peaks, particularly during the early stages of rainstorms. The complex joint probability structures of rainstorm severity and STV variables obscure the mechanistic control of individual factors on flood response. A significant underestimation of street-level flood hazards occurs when assuming the same return periods (RPs) as those for watershed-level hazards. The inconsistency between rainstorm and flood severities results in widespread underestimation of street-level flood hazards in upstream regions, while traditional storm designs that neglect STV lead to overestimations in mid- and downstream areas. This study highlights the complex probabilistic behavior of spatially distributed flood hazards across multiple scales, enhancing the insights and methodologies for street-level FHA. © 2025 The Author(s).
Publisher: John Wiley and Sons Inc
Keywords: Scopus_Alert_5_Septembre_2025

Spatial–Temporal Characteristics and Drivers of Summer Extreme Precipitation in the Poyang Lake City Group (PLCG) from 1971 to 2022 - Liu, Hua; Zhang, Ziqing; Liu, Bo (Remote Sensing, 2025)
Global warming has intensified the hydrological cycle, resulting in more frequent extreme precipitation events and altered spatiotemporal precipitation patterns in urban areas, thereby increasing the risk of urban flooding and threatening socio-economic and ecological security. This study investigates the characteristics of summer extreme precipitation in the Poyang Lake City Group (PLCG) from 1971 to 2022, utilizing the China Daily Precipitation Dataset and NCEP/NCAR reanalysis data. Nine extreme precipitation indices were examined through linear trend analysis, Mann–Kendall tests, wavelet transforms, and correlation methods to quantify trends, periodicity, and atmospheric drivers. The key findings include: (1) All indices exhibited increasing trends, with RX1Day and R95p exhibiting significant rises (p < 0.05). PRCPTOT, R20, and SDII also increased, indicating heightened precipitation intensity and frequency. (2) R50, RX1Day, and SDII demonstrated east-high-to-west-low spatial gradients, whereas PRCPTOT and R20 peaked in the eastern and western PLCG. More than over 88% of stations recorded rising trends in PRCPTOT and R95p. (3) Abrupt changes occurred during 1993–2009 for PRCPTOT, R50, and SDII. Wavelet analysis revealed dominant periodicities of 26–39 years, linked to atmospheric oscillations. (4) Strong subtropical highs, moisture convergence, and negative OLR anomalies were closely associated with extreme precipitation. Warmer SSTs in the eastern equatorial Pacific amplified precipitation in preceding seasons. This study provides a scientific basis for flood prevention and climate adaptation in the PLCG and highlighting the region’s vulnerability to monsoonal shifts under global warming. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Producing Hydrological Projections Under Climate Change: A Groundwater-Inclusive Practical Guide - Mourot, Frédérique M.; Irvine, Dylan J.; Remenyi, Tomas A.; Hutley, Lindsay B.; Crosbie, Russell S.; Moore, Catherine R. (Earth's Future, 2025)
With global warming, the hydrological cycle is intensifying with more frequent and severe droughts and floods, placing water resources and their dependent communities under increasing stress. Guidance and insights into the projection of future water conditions are, therefore, increasingly needed to inform climate change adaptation. Hydrological projections can provide such insights when suitably designed for user needs, produced from the best available climate knowledge, and leverage appropriate hydrological models. However, producing such hydrological projections is a complex process that requires skills and knowledge spanning from the often-siloed disciplines of climate, hydrology, communication, and decision-making. Groundwater projections are still underrepresented compared to surface water projections, despite the importance of groundwater to sustain society and the environment. Accordingly, this paper bridges these silos and fills a gap by providing detailed guidance on the important steps and best practices to develop groundwater-inclusive hydrological projections that can effectively support decision-making. Using an extensive literature review and our practical experience as climate scientists, hydro(geo)logists, numerical modelers, uncertainty experts and decision-makers, here we provide: (a) an overview of climate change hydrological impacts as background knowledge; (b) a step-by-step guide to produce groundwater-inclusive hydrological projections under climate change, targeted to both scientists and water practitioners; (c) a summary of important considerations related to hydrological projection uncertainty; and (d) insights to use hydrological projections and their associated uncertainty for impactful communication and decision-making. By providing this practical guide, our paper addresses a critical interdisciplinary knowledge gap and supports enhanced decision-making and resilience to climate change threats. © 2025 Commonwealth of Australia. Earth Science New Zealand. Acclimatised Pty Ltd and The Author(s). Earth's Future published by Wiley Periodicals LLC on behalf of American Geophysical Union.
Publisher: John Wiley and Sons Inc
Keywords: Scopus_Alert_5_Septembre_2025

Interest Flooding Attacks in Named Data Networking and Mitigations: Recent Advances and Challenges - Ogunbunmi, Simeon; Chen, Yu; Zhao, Qi; Nagothu, Deeraj; Wei, Sixiao; Chen, Genshe; Blasch, Erik (Future Internet, 2025)
Named Data Networking (NDN) represents a promising Information-Centric Networking architecture that addresses limitations of traditional host-centric Internet protocols by emphasizing content names rather than host addresses for communication. While NDN offers advantages in content distribution, mobility support, and built-in security features, its stateful forwarding plane introduces significant vulnerabilities, particularly Interest Flooding Attacks (IFAs). These IFA attacks exploit the Pending Interest Table (PIT) by injecting malicious interest packets for non-existent or unsatisfiable content, leading to resource exhaustion and denial-of-service attacks against legitimate users. This survey examines research advances in IFA detection and mitigation from 2013 to 2024, analyzing seven relevant published detection and mitigation strategies to provide current insights into this evolving security challenge. We establish a taxonomy of attack variants, including Fake Interest, Unsatisfiable Interest, Interest Loop, and Collusive models, while examining their operational characteristics and network performance impacts. Our analysis categorizes defense mechanisms into five primary approaches: rate-limiting strategies, PIT management techniques, machine learning and artificial intelligence methods, reputation-based systems, and blockchain-enabled solutions. These approaches are evaluated for their effectiveness, computational requirements, and deployment feasibility. The survey extends to domain-specific implementations in resource-constrained environments, examining adaptations for Internet of Things deployments, wireless sensor networks, and high-mobility vehicular scenarios. Five critical research directions are proposed: adaptive defense mechanisms against sophisticated attackers, privacy-preserving detection techniques, real-time optimization for edge computing environments, standardized evaluation frameworks, and hybrid approaches combining multiple mitigation strategies. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Injectivity, Potential Wettability Alteration, and Mineral Dissolution in Low-Salinity Waterflood Applications: The Role of Salinity, Surfactants, Polymers, Nanomaterials, and Mineral Dissolution - Sarma, Hemanta K.; Awolayo, Adedapo N.; Olayiwola, Saheed O.; Fakir, Shasanowar H.; Belhaj, Ahmed F. (Processes, 2025)
Waterflooding, a key method for secondary hydrocarbon recovery, has been employed since the early 20th century. Over time, the role of water chemistry and ions in recovery has been studied extensively. Low-salinity water (LSW) injection, a common technique since the 1930s, improves oil recovery by altering the wettability of reservoir rocks and reducing residual oil saturation. Recent developments emphasize the integration of LSW with various recovery methods such as CO2 injections, surfactants, alkali, polymers, and nanoparticles (NPs). This article offers a comprehensive perspective on how LSW injection is combined with these enhanced oil recovery (EOR) techniques, with a focus on improving oil displacement and recovery efficiency. Surfactants enhance the effectiveness of LSW by lowering interfacial tension (IFT) and improving wettability, while ASP flooding helps reduce surfactant loss and promotes in situ soap formation. Polymer injections boost oil recovery by increasing fluid viscosity and improving sweep efficiency. Nevertheless, challenges such as fine migration and unstable flow persist, requiring additional optimization. The combination of LSW with nanoparticles has shown potential in modifying wettability, adjusting viscosity, and stabilizing emulsions through careful concentration management to prevent or reduce formation damage. Finally, building on discussions around the underlying mechanisms involved in improved oil recovery and the challenges associated with each approach, this article highlights their prospects for future research and field implementation. By combining LSW with advanced EOR techniques, the oil industry can improve recovery efficiency while addressing both environmental and operational challenges. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_5_Septembre_2025

Copula-based joint distribution modelling of precipitation, temperature and humidity events in the assessments of agricultural risks, with a case study in Morocco - Latif, Shahid; El Ouadi, Ihssan; Ouarda, Taha B. M. J. (Stochastic Environmental Research and Risk Assessment, 2025)
The agriculture sector is profoundly impacted by the abiotic stresses in arid or semi-arid regions that experience extreme weather patterns related to temperature (T), precipitation (P), humidity (H), and other factors. This study adopts a flexible approach that incorporates the D-vine copula density to analyze trivariate (and bivariate) joint and conditional hazard risk. The methodology was applied to a case study in the Ait Ben Yacoub region of Morocco. Monthly series for T, H, and P were modeled using the Weibull-2P and Weibull-3P models, selected based on fitness statistics. The survival BB8 copula was best described as joint dependence for pair T–P, rotated BB8 270 degrees copula for T–H, while rotated Joe 270 degrees copula for P–H. The analysis of joint probability stress focused on both primary joint scenarios (for OR and AND-hazard conditions) and conditional return periods (RPs) for trivariate and bivariate case. Lower univariate RPs resulted in higher marginal quantiles for T and lower for H and P events. Lower trivariate (and bivariate) AND-joint RPs (or higher concurrence probabilities) were associated with higher T with lower P and H quantiles. The occurrence of trivariate (and bivariate) events was less frequent in the AND-joint case compared to the OR-joint case. The conditional joint RP of T (or T with P, or T with H) was significantly affected by different P (at 10th and 25th percentile) and H (at 5th and 25th percentile) (or P, or H) conditions. Lower conditional RPs of T (or T with H, or T with P) had resulted at given low P and H (or low P, or low H levels). In conclusion, the estimated risk statistics are vital for the study region, highlighting the need for effective adaptation and resilience planning in agriculture crop management.
Keywords: Infolettre_Septembre_2025

High-Resolution Daily XCH4 Prediction Using New Convolutional Neural Network Autoencoder Model and Remote Sensing Data - Awad, Mohamad M.; Homayouni, Saeid (Atmosphere, 2025)
Atmospheric methane (CH4) concentrations have increased to 2.5 times their pre-industrial levels, with a marked acceleration in recent decades. CH4 is responsible for approximately 30% of the global temperature rise since the Industrial Revolution. This growing concentration contributes to environmental degradation, including ocean acidification, accelerated climate change, and a rise in natural disasters. The column-averaged dry-air mole fraction of methane (XCH4) is a crucial indicator for assessing atmospheric CH4 levels. In this study, the Sentinel-5P TROPOMI instrument was employed to monitor, map, and estimate CH4 concentrations on both regional and global scales. However, TROPOMI data exhibits limitations such as spatial gaps and relatively coarse resolution, particularly at regional scales or over small areas. To mitigate these limitations, a novel Convolutional Neural Network Autoencoder (CNN-AE) model was developed. Validation was performed using the Total Carbon Column Observing Network (TCCON), providing a benchmark for evaluating the accuracy of various interpolation and prediction models. The CNN-AE model demonstrated the highest accuracy in regional-scale analysis, achieving a Mean Absolute Error (MAE) of 28.48 ppb and a Root Mean Square Error (RMSE) of 30.07 ppb. This was followed by the Random Forest (RF) regressor (MAE: 29.07 ppb; RMSE: 36.89 ppb), GridData Nearest Neighbor Interpolator (NNI) (MAE: 30.06 ppb; RMSE: 32.14 ppb), and the Radial Basis Function (RBF) Interpolator (MAE: 80.23 ppb; RMSE: 90.54 ppb). On a global scale, the CNN-AE again outperformed other methods, yielding the lowest MAE and RMSE (19.78 and 24.7 ppb, respectively), followed by RF (21.46 and 27.23 ppb), GridData NNI (25.3 and 32.62 ppb), and RBF (43.08 and 54.93 ppb).
Publisher: Multidisciplinary Digital Publishing Institute
Keywords: Infolettre_Septembre_2025

Optimizing ensemble learning for satellite-based multi-hazard monitoring and susceptibility assessment of landslides, land subsidence, floods, and wildfires - Razavi-Termeh, Seyed Vahid; Sadeghi-Niaraki, Abolghasem; Ali, Farman; Pradhan, Biswajeet; Choi, Soo-Mi (Scientific Reports, 2025)
The preparation of accurate multi-hazard susceptibility maps is essential to effective disaster risk management. Past studies have relied mainly on traditional machine learning models, but these models do not perform well for complex spatial patterns. To address this gap, this study uses two meta-heuristic algorithms (Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)) to provide an optimized Random Forest (RF) model with better predictive ability. We focus on four significant hazards—landslides, land subsidence, wildfires, and floods—in Kurdistan Province, Iran, using Sentinel-1 and Sentinel-2 satellite imagery collected between 2015 and 2022. Furthermore, two models of RF-GA and RF-PSO were utilized to create multi-hazard susceptibility, which were evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). The RF-GA algorithm achieved 91.1% accuracy for flood hazards, 83.8% for wildfires, and 99.1% for landslide hazards. In contrast, utilizing RF-PSO resulted in a 95.9% accuracy for land subsidence hazards. The combined RF-GA algorithm demonstrated superior accuracy to individual RF modeling techniques. Furthermore, eastern regions are more prone to floods and land subsidence, whereas western areas face more significant risks from landslides and wildfires. Additionally, floods and land subsidence exhibit a considerable correlation, impacting each other’s occurrence, while wildfires and landslides demonstrate interacting dynamics, influencing each other’s likelihood of occurrence. © The Author(s) 2025.
Publisher: Nature Research

A novel and scalable flood risk assessment framework for cultural heritage based on unmanned aerial vehicle photogrammetry and multi-scale rain-on-grid hydraulic modeling - Alexopoulos, M.J.; Iliopoulou, T.; Modé, P.; Istrati, D.; Spyrakos, C.C.; Soile, S.; Verykokou, S.; Ioannidis, C.; Koutsoyiannis, D. (Science of the Total Environment, 2025)
This study presents a novel multi-scale flood risk assessment framework for cultural heritage sites, applied to the Temple of Apollo, Aegina Island, Greece. Three modeling configurations were developed and compared: (i) an island-wide Rain-on-Grid (RoG) hydraulic model at 5 m resolution, (ii) a site-only model driven by inflows from the island-scale simulation, and (iii) a high-resolution nested model coupling island-scale outputs with centimeter-scale site RoG simulations enabled by UAV photogrammetry. Simulations for 100-, 1000-, and 2000-year return periods revealed strong scale-dependent differences: island-wide inundation extents of 7.3–10.3 km2, site-specific inundation of 2–24 %, and water volumes of 92–1483 m3 depending on the model configuration and return period. Flow velocities remained below 1.0 m/s, indicating low erosive potential but possible material degradation. Limestone deterioration analysis showed 4–10 % compressive strength reduction, 3–9 % elastic modulus decrease, and mass losses of 0.64–26.08 kg after 24-h inundations. The nested approach provided more realistic water volume accumulation over the single-scale model and revealed critical micro-topographic controls on flood behavior. This scalable, built on readily accessible tools (HEC-RAS and UAV), framework supports rapid deployment to heritage sites globally, enabling quantitative risk assessments for adaptation planning and conservation prioritization. © 2025 The Authors
Publisher: Elsevier B.V.

Editorial preface to special issue: Temporal and spatial patterns in Holocene floods under the influence of past global change, and their implications for forecasting “unpredecented” future events - Schulte, Lothar; Santisteban, Juan I.; Fuller, Ian C.; Ballesteros-Cánovas, Juan Antonio (Global and Planetary Change, 2025)
Floods constitute the most significant natural hazard to societies worldwide. Population growth and unchecked development have led to floodplain encroachment. Modelling suggests that climate change will regionally intensify the threat posed by future floods, with more people in harm's way. From a global change perspective, past flood events and their spatial-temporal patterns are of particular interest because they can be linked to former climate patterns, which can be used to guide future climate predictions. Millennial and centennial time series contain evidence of very rare extreme events, which are often considered by society as ‘unprecedented’. By understanding their timing, magnitude and frequency in conjunction with prevailing climate regime, we can better forecast their future occurrence. This Virtual Special Issue (VSI) entitled Temporal and spatial patterns in Holocene floods under the influence of past global change, and their implications for forecasting “unpredecented” future events comprises 14 papers that focus on how centennial and millennia-scale natural and documentary flood archives help improve future flood science. Specifically, documentation of large and very rare flood episodes challenges society's lack of imagination regarding the scale of flood disasters that are possible (what we term here, the “unknown unknowns”). Temporal and spatial flood behaviour and related climate patterns as well as the reconstruction of flood propagation in river systems are important foci of this VSI. These reconstructions are crucial for the provision of robust and reliable data sets, knowledge and baseline information for future flood scenarios and forecasting. We argue that it remains difficult to establish analogies for understanding flood risk during the current period of global warming. Most studies in this VSI suggest that the most severe flooding occurred during relatively cool climate periods, such as the Little Ice Age. However, flood patterns have been significantly altered by land use and river management in many catchments and floodplains over the last two centuries, thereby obscuring the climate signal. When the largest floods in instrumental records are compared with paleoflood records reconstructed from natural and documentary archives, it becomes clear that precedent floods should have been considered in many cases of flood frequency analysis and flood risk modelling in hydraulic infrastructure. Finally, numerical geomorphological analysis and hydrological simulations show great potential for testing and improving our understanding of the processes and factors involved in the temporal and spatial behaviour of floods. © 2025 The Authors
Publisher: Elsevier B.V.

Reservoir Potential Unlocked: Synergies Between Low-Salinity Water Flooding, Nanoparticles and Surfactants in Enhanced Oil Recovery─A Review - Mumbere, Walidi; Sagala, Farad; Gupta, Uttam; Bbosa, Denis (ACS Omega, 2025)
This review explores the synergistic application of low-salinity water flooding (LSWF), nanoparticles, and surfactants in enhanced oil recovery (EOR), emphasizing their combined potential to address modern oil production challenges. It highlights the ability of LSWF to alter reservoir wettability, improve sweep efficiency, nanoparticles to enhance fluid mobility, and reduce interfacial tension, and surfactants to lower the interfacial tension and promote emulsification. All of this aim to provide practical, easy-to-use, and sustainable solutions for oil recovery. The review discusses existing research gaps in the long-term stability of nanoparticle-surfactant complexes, site-specific differences in rock-fluid interactions, and economic viability across diverse reservoirs. The review summarizes experimental findings, demonstrating recovery rates of 45–55% for nanoparticles, 50–60% for surfactants, and 40–50% for LSWF with improvements of 75–82% through this integrated approach. Additionally, the review addresses technological advancements, environmental considerations, and economic feasibility, highlighting challenges such as nanoparticle agglomeration and surfactant adsorption. A bibliographic analysis of global research trends, mechanisms, and field applications underscores the importance of interdisciplinary collaboration in optimizing this strategy for sustainable and efficient EOR processes. The findings aim to guide researchers and industry professionals in leveraging the synergistic effects of these methods to maximize oil recovery and reduce environmental footprints with a proposition to develop advanced characterization techniques, and verifying practicality through field implementation studies © 2025 The Authors. Published by American Chemical Society
Publisher: American Chemical Society

Impact of Climate Change on Human Health in Thailand: A Literature Review - Ratanawong, Pitcha; Nunthaitaweekul, Pachanat; Huynh, Phuong Trang; Weesakul, Uruya (Journal of Disaster Research, 2025)
This study aims to find and summarize published studies that examined the effects of climate change on human health and diseases in Thailand by conducting aliterature review using the preferred reporting items for systematic reviews and meta-analysis guidelines between October 17, 2023, and January 31, 2024. We earched PubMed and OvidSP for relevant research. We included studies that were written in English orThai; primary research focused on climate change or its subsets (natural disasters or climate issues, such as rising temperatures and altered weather patterns that increase the frequency, intensity, and severity of manynatural disasters and climate issues); focused on human health; indexed by PubMed or OvidSP; available as published research with full-text journal articles; and published in 2013 or later. Our search yielded 53 relevant articles. These articles identified five main categories of climate issues: temperature, rainfall/precipitation, humidity, wind speed, and flooding. We identified five categories of health issues: dengue, respiratory diseases and infections, malaria, skin diseases/symptoms, and other health issues. The most studied relationship is between temperature and dengue. Most articles reported the harmful effects of climate issues on health, although four reported opposite effects, and seven reported no significant associations. Among the 53 articles, ten utilized prediction models. The main goal of this review is to summarize current research to guide future studies and assist policymakers in prioritizing climate-related health policies in Thailand. Study limitations include the use of only two databases, the restriction to articles from 2013 onwards, and the inclusion of only articles in English and Thai, which may have limited the number of articles found for this literature review. © 2025, Fuji Technology Press. All rights reserved.
Publisher: Fuji Technology Press

Non-Aquatic Fauna of Amazonian Floodplain Forests and its Responses to Seasonal Flooding - Pedroza, Diego; Cohn-Haft, Mario; Haugaasen, Torbjørn (Wetlands, 2025)
The non-aquatic fauna (e.g. insects, birds, mammals) that occupies seasonally flooded floodplain forests in the Amazon is a major component of the region’s biodiversity, and the responses portrayed to cope with this inundation are varied. However, no systematic review of these species, including specialist species (exclusive to this environment), and their responses to seasonal inundation has yet been performed. Here, we provide an up-to-date and thorough examination of research on non-aquatic fauna that utilize Amazonian floodplain forests and their responses to seasonal flooding. We conducted a survey of published and unpublished studies from 1853 to 2023 through the Web of Science and Google Scholar platforms. We found a total of 445 studies, including 11,513 species of non-aquatic animals that inhabit floodplain forests. We identified ten main types of responses to flooding, the three most common being vertical migration, occupation of floating substrates and eggs submerged in a dormant state. Results suggest great behavioral, morphological and physiological plasticity among non-aquatic species, including those that are not floodplain forest specialists. Several types of responses occur independently in widely distinct taxonomic groups, emphasizing convergent strategies to deal with seasonal flooding. Our findings underline the uniqueness of the floodplain fauna and its importance for the regional biodiversity conservation agenda. © The Author(s), under exclusive licence to Society of Wetland Scientists 2025.
Publisher: Springer Science and Business Media B.V.

Managing floods and droughts synergistically: A transformative governance approach - Sánchez, Ana Núñez; Koehler, Johanna; Van Loon, Anne F. (PLOS Water, 2025)
Floods and droughts cause large economic and environmental impacts and incalculable human suffering. Despite growing evidence of important synergies in their management, floods and droughts tend to be mostly managed in silos. The synergistic management of flood and drought risk is limited by the inability of current governance systems to change at the scope, depth and speed required to address the emerging challenges of climate change induced hydroclimatic risks. Building on the concept of continuous transformational change and combining key elements across sectoral governance frameworks, this paper proposes a transformative governance conceptual framework that enables national governments to work across silos in a whole of government approach to lead a whole of society effort to manage the whole hydroclimatic spectrum. Spain, a country with an advanced hydroclimatic risk management system, is presented as an illustrative example to explore the possible idiosyncrasies of implementing the proposed changes on the ground. © 2025 Núñez Sánchez et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Publisher: Public Library of Science

Extreme and compound events in lakes - Woolway, R. Iestyn; Zhang, Yunlin; Jennings, Eleanor; Zohary, Tamar; Jane, Stephen F.; Jansen, Joachim; Weyhenmeyer, Gesa A.; Long, Di; Fleischmann, Ayan; Feng, Lian; Qin, Boqiang; Shi, Kun; et al. (Nature Reviews Earth and Environment, 2025)
Extreme and compound events disrupt lake ecosystems worldwide, with their frequency, intensity and duration increasing in response to climate change. In this Review we outline evidence of the occurrence, drivers and impact of extreme and compound events in lakes. Univariate extremes, which include lake heatwaves, droughts and floods, underwater dimming episodes and hypoxia, can occur concurrently, sequentially or simultaneously at different locations to form multivariate, temporal or spatial compound events, respectively. The probability of extreme and compound events is increasing owing to climate warming, declining lake water levels in half of lakes globally, and basin-scale anthropogenic stressors, such as nutrient pollution. Most in-lake extreme events are inherently compound in nature owing to tightly coupled physical, chemical and biological underlying processes. The cascading effects of compound events propagate or dissipate through lakes. For example, a heatwave might trigger stratification and oxygen depletion, subsequently leading to fish mortality or the proliferation of harmful algal blooms. Interactions between extremes are increasingly observed and can trigger feedback loops that exacerbate harmful algal blooms and fishery declines, leading to severe ecological and socio-economic consequences. Managing the increasing risk of compound events requires integrated models, coordinated monitoring and proactive adaptation strategies tailored to the vulnerabilities of lake ecosystems. © Springer Nature Limited 2025.
Publisher: Springer Nature

Research on the Comprehensive Evaluation Model of Risk in Flood Disaster Environments - Yu, Yan; Zhou, Tianhua (Water (Switzerland), 2025)
Losses from floods and the wide range of impacts have been at the forefront of hazard-triggered disasters in China. Affected by large-scale human activities and the environmental evolution, China’s defense flood situation is undergoing significant changes. This paper constructs a comprehensive flood disaster risk assessment model through systematic analysis of four key factors—hazard (H), exposure (E), susceptibility/sensitivity (S), and disaster prevention capabilities (C)—and establishes an evaluation index system. Using the Analytic Hierarchy Process (AHP), we determined indicator weights and quantified flood risk via the following formula R = H × E × V × C. After we applied this model to 16 towns in coastal Zhejiang Province, the results reveal three distinct risk tiers: low (R < 0.04), medium (0.04 ≤ R ≤ 0.1), and high (R > 0.1). High-risk areas (e.g., Longxi and Shitang towns) are primarily constrained by natural hazards and socioeconomic vulnerability, while low-risk towns benefit from a robust disaster mitigation capacity. Risk typology analysis further classifies towns into natural, social–structural, capacity-driven, or mixed profiles, providing granular insights for targeted flood management. The spatial risk distribution offers a scientific basis for optimizing flood control planning and resource allocation in the district. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Assessing Community Perception, Preparedness, and Adaptation to Urban Flood Risks in Malaysia - Kumaresen, Maniyammai; Teo, Fang Yenn; Selvarajoo, Anurita; Sivapalan, Subarna; Falconer, Roger A. (Water (Switzerland), 2025)
Urban flooding has significantly impacted the livelihoods of households and communities worldwide. It highlights the urgency of focusing on both flood preparedness and adaptation strategies to understand the community’s perception and adaptive capacity. This study investigates the levels of risk perception, flood preparedness, and adaptive capacity, while also exploring the inter-relationships among these factors within the context of urban flooding in Malaysia. A quantitative approach was employed, involving a structured questionnaire administered to residents in flood-prone urban areas across Greater Kuala Lumpur, Malaysia. A total of 212 responses were analysed using descriptive statistics, categorical index classification, and Spearman correlation analysis. The findings indicate that residents generally reported high levels of risk perception and preparedness, although adaptive capacity exhibited greater variability, with a mean score of 3.97 (SD = 0.64). Positive associations were found among risk perception, flood preparedness, and adaptive capacity. This study contributes to the existing knowledge by providing evidence on community resilience and highlighting key factors that can guide flood management policies and encourage adaptive planning at the community level. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

The Impact of Land Use Change on Improving Surface Runoff, Peak Flood Discharge, and Sedimentation in the Maros Watershed - Mansida, Amrullah; Gaffar, Farida; Zainuddin, Muh Amir; Syamsuri, Andi Makbul (Engineering, Technology and Applied Science Research, 2025)
The present study aims to analyze how land use changes affect surface runoff, flood peak discharge, and sedimentation. Moreover, it aims to assess the specific impact of these changes on the flood peak discharge and to propose effective strategies for reducing flood risks. Visual interpretation of the land use changes was utilized based on Landsat imagery from 2010, 2017, and 2021, along with SPOT 4 satellite data. Soil samples were collected to measure the erosion rates, water discharge, and sediment loads (both suspended and bedload). The findings showed a significant reduction in the secondary dryland forest, which shrank by 52.71 km² (a 7.99% decrease), while shrub and agricultural areas expanded by 51.03 km² (a 7.73% increase). This shift contributed to a greater surface runoff and an increased erosion, especially in dryland-shrubland areas, where erosion reached 4,248.33 tons/ha/year. The flood peak discharges rose sharply in areas converted to agriculture and settlements, halving the flood return period from 50 years to just 25 years. During the wet season, the sediment loads peaked at 782.17 tons/day (equivalent to 377,293.48 m³ per year), while the dry season sedimentation—mostly driven by quarrying—reached 10.45 tons/day. To address these issues, the current study proposes adopting adaptive spatial planning, restoring the watershed, and applying nature-based solutions, such as Biopore Absorption Holes (BAH), Rainwater Infiltration Wells (RIW), and similar technologies. © by the authors.
Publisher: Dr D. Pylarinos
Keywords: Scopus_Alert_22_Aout_2025

Identification of Critical Exposed Elements and Strategies for Mitigating Secondary Hazards in Flood-Induced Coal Mine Accidents - Yang, Xue; Liu, Chen; Pan, Langxuan; Su, Xiaona; He, Ke; Mao, Ziyu (Water (Switzerland), 2025)
Natech events, involving multi-hazard coupling and cascading effects, pose serious threats to coal mine safety. This paper addresses flood-induced Natech scenarios in coal mining and introduces a two-stage cascading analysis framework based on hazard systems theory. A tri-layered network—comprising natural hazards, exposed elements, and secondary hazards—models hazard propagation. In Stage 1, an improved adjacency information entropy algorithm with multi-hazard coupling coefficients identifies critical exposed elements. In Stage 2, Dijkstra’s algorithm extracts key risk transmission paths. A dual-dimensional classification method, based on entropy and transmission risk, is then applied to prioritize emergency responses. This method integrates the criticality of exposed elements with the risk levels associated with secondary disaster propagation paths. Case studies validate the framework, revealing: (1) Hierarchical heterogeneity in the network, with surface facilities and surrounding hydrological systems as central hubs; shaft and tunnel systems and surrounding geological systems are significantly affected by propagation from these core nodes, exhibiting marked instability. (2) Strong risk polarization in secondary hazard propagation, with core-node-originated paths being more efficient and urgent. (3) The entropy-risk classification enables targeted hazard control, improving efficiency. The study proposes chain-breaking strategies for precise, hierarchical, and timely emergency management, enhancing coal mine resilience to flood-induced Natech events. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Response of Grain Yield to Extreme Precipitation in Major Grain-Producing Areas of China Against the Background of Climate Change—A Case Study of Henan Province - Sheng, Keding; Li, Rui; Zhang, Fengqiuli; Chen, Tongde; Liu, Peng; Hu, Yanan; Li, Bingyin; Song, Zhiyuan (Water (Switzerland), 2025)
Based on the panel data of daily meteorological stations and winter wheat yield in Henan Province from 2000 to 2023, this study comprehensively used the Mann–Kendall trend test, wavelet coherence analysis (WTC), and other methods to reveal the temporal and spatial evolution of extreme precipitation and its multi-scale stress mechanism on grain yield. The results showed the following: (1) Extreme precipitation showed the characteristics of ‘frequent fluctuation-gentle trend-strong spatial heterogeneity’, and the maximum daily precipitation in spring (RX1DAY) showed a significant uplift. The increase in rainstorm events (R95p/R99p) in the southern region during the summer is particularly prominent; at the same time, the number of consecutive drought days (CDDs > 15 d) in the middle of autumn was significantly prolonged. It was also found that 2010 is a significant mutation node. Since then, the synergistic effect of ‘increasing drought days–increasing rainstorm frequency’ has begun to appear, and the short-period coherence of super-strong precipitation (R99p) has risen to more than 0.8. (2) The spatial pattern of winter wheat in Henan is characterized by the three-level differentiation of ‘stable core area, sensitive transition zone and shrinking suburban area’, and the stability of winter wheat has improved but there are still local risks. (3) There is a multi-scale stress mechanism of extreme precipitation on winter wheat yield. The long-period (4–8 years) drought and flood events drive the system risk through a 1–2-year lag effect (short-period (0.5–2 years) medium rainstorm intensity directly impacted the production system). This study proposes a ‘sub-scale governance’ strategy, using a 1–2-year lag window to establish a rainstorm warning mechanism, and optimizing drainage facilities for high-risk areas of floods in the south to improve the climate resilience of the agricultural system against the background of climate change. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Empirical Modelling of Ice-Jam Flood Hazards Along the Mackenzie River in a Changing Climate - Lindenschmidt, Karl-Erich; Gomez, Sergio; Saade, Jad; Perry, Brian; Das, Apurba (Water (Switzerland), 2025)
This study introduces a novel methodology for assessing ice-jam flood hazards along river channels. It employs empirical equations that relate non-dimensional ice-jam stage to discharge, enabling the generation of an ensemble of longitudinal profiles of ice-jam backwater levels through Monte-Carlo simulations. These simulations produce non-exceedance probability profiles, which indicate the likelihood of various flood levels occurring due to ice jams. The flood levels associated with specific return periods were validated using historical gauge records. The empirical equations require input parameters such as channel width, slope, and thalweg elevation, which were obtained from bathymetric surveys. This approach is applied to assess ice-jam flood hazards by extrapolating data from a gauged reach at Fort Simpson to an ungauged reach at Jean Marie River along the Mackenzie River in Canada’s Northwest Territories. The analysis further suggests that climate change is likely to increase the severity of ice-jam flood hazards in both reaches by the end of the century. This methodology is applicable to other cold-region rivers in Canada and northern Europe, provided similar fluvial geomorphological and hydro-meteorological data are available, making it a valuable tool for ice-jam flood risk assessment in other ungauged areas. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Analysis of the Availability of Residential Locations Based on Flood Mitigation in Momunu District, Buol Regency - Assiddiqi, Moh. Hasbi; Lanuru, Mahatma; Tumpu, Miswar (Engineering, Technology and Applied Science Research, 2025)
The population growth and limited land availability for housing have forced some communities to reside in disaster-prone areas, particularly those vulnerable to flooding. This study, presents a spatial-based assessment that integrates physical and regulatory criteria to identify safe and appropriate residential zones. Using spatial analysis through map overlays, scoring, and weighting techniques, the research evaluates seven key physical variables: land slope, drainage, erosion, land use, road accessibility, access to essential facilities, and flood hazard vulnerability. The novelty of this study lies in the integration of flood mitigation into residential suitability mapping that is aligned with the Regional Spatial Plan (RTRW), offering a comprehensive and policy-relevant framework. The findings reveal that 20.85% of the study area is suitable for housing, 61.83% is conditionally suitable, and 17.32% is unsuitable. Based on the land availability and RTRW compliance, residential land is categorized into Available Location I (47 hectares) and Available Location II (423 hectares). These results provide not only a technical basis for guiding safe settlement, but also a strategic reference for planners and policymakers. The study proposes that future research incorporates socio-economic variables and real-time flood data for dynamic risk assessment. Furthermore, stakeholder engagement and community-based mapping are proposed to enhance the local resilience and ensure participatory planning. Ultimately, this research contributes to sustainable urban development by supporting informed decision-making for safer, flood-resilient settlements. © by the authors.
Publisher: Dr D. Pylarinos
Keywords: Scopus_Alert_22_Aout_2025

Assessing Flooding from Changes in Extreme Rainfall: Using the Design Rainfall Approach in Hydrologic Modeling - Jalowska, Anna M.; Line, Daniel E.; Spero, Tanya L.; Kurki-Fox, J. Jack; Doll, Barbara A.; Bowden, Jared H.; Gray, Geneva M. E. (Water (Switzerland), 2025)
Quantifying future changes in extreme events and associated flooding is challenging yet fundamental for stormwater managers. Along the U.S. Atlantic Coast, Eastern North Carolina (ENC) is frequently exposed to catastrophic floods from extreme rainfall that is typically associated with tropical cyclones. This study presents a novel approach that uses rainfall data from five dynamically and statistically downscaled (DD and SD) global climate models under two scenarios to visualize a potential future extent of flooding in ENC. Here, we use DD data (at 36-km grid spacing) to compute future changes in precipitation intensity–duration–frequency (PIDF) curves at the end of the 21st century. These PIDF curves are further applied to observed rainfall from Hurricane Matthew—a landfalling storm that created widespread flooding across ENC in 2016—to project versions of “Matthew 2100” that reflect changes in extreme precipitation under those scenarios. Each Matthew-2100 rainfall distribution was then used in hydrologic models (HEC-HMS and HEC-RAS) to simulate “2100” discharges and flooding extents in the Neuse River Basin (4686 km2) in ENC. The results show that DD datasets better represented historical changes in extreme rainfall than SD datasets. The projected changes in ENC rainfall (up to 112%) exceed values published for the U.S. but do not exceed historical values. The peak discharges for Matthew-2100 could increase by 23–69%, with 0.4–3 m increases in water surface elevation and 8–57% increases in flooded area. The projected increases in flooding would threaten people, ecosystems, agriculture, infrastructure, and the economy throughout ENC. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Machine learning-based ensemble of Global climate models and trend analysis for projecting extreme precipitation indices under future climate scenarios - Kumar, G. Praveen; Dwarakish, G.S. (Environmental Monitoring and Assessment, 2025)
Monitoring changes in climatic extremes is vital, as they influence current and future climate while significantly impacting ecosystems and society. This study examines trends in extreme precipitation indices over an Indian tropical river basin, analyzing and ranking 28 Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs) based on their performance against India Meteorological Department (IMD) data. The top five performing GCMs were selected to construct multi-model ensembles (MMEs) using Machine Learning (ML) algorithms, Random Forest (RF), Support Vector Machine (SVM), Multiple Linear Regression (MLR), and the Arithmetic Mean. Statistical metrics reveal that the application of an RF model for ensembling performs better than other models. The analysis focused on six IMD-convention indices and eight indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). Future projections were examined for three timeframes: near future (2025–2050), mid-future (2051–2075), and far future (2076–2100) for SSP245 and SSP585 scenarios. Statistical trend analysis, the Mann-Kendall test, Sen’s Slope estimator, and Innovative Trend Analysis (ITA), were applied to the MME to assess variability and detect changes in extreme precipitation trends. Compared to SSP245, in the SSP585 scenario, Total Precipitation (PRCPTOT) shows a significant decreasing trend in the near future, mid-future, and far future and Moderate Rain (MR) shows a decreasing trend in the near future and far future of monsoon season. The findings reveal significant future trends in extreme precipitation, impacting Sustainable Development Goals (SDGs) achievement and providing crucial insights for sustainable water resource management and policy planning in the Kali River basin. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.
Publisher: Springer Science and Business Media Deutschland GmbH
Keywords: Scopus_Alert_22_Aout_2025

Multi-Sensor Flood Mapping in Urban and Agricultural Landscapes of the Netherlands Using SAR and Optical Data with Random Forest Classifier - Narin, Omer Gokberk; Sekertekin, Aliihsan; Bayik, Caglar; Bektas Balcik, Filiz; Arıkan, Mahmut; Sanli, Fusun Balik; Abdikan, Saygin (Remote Sensing, 2025)
Floods stand as one of the most harmful natural disasters, which have become more dangerous because of climate change effects on urban structures and agricultural fields. This research presents a comprehensive flood mapping approach that combines multi-sensor satellite data with a machine learning method to evaluate the July 2021 flood in the Netherlands. The research developed 25 different feature scenarios through the combination of Sentinel-1, Landsat-8, and Radarsat-2 imagery data by using backscattering coefficients together with optical Normalized Difference Water Index (NDWI) and Hue, Saturation, and Value (HSV) images and Synthetic Aperture Radar (SAR)-derived Grey Level Co-occurrence Matrix (GLCM) texture features. The Random Forest (RF) classifier was optimized before its application based on two different flood-prone regions, which included Zutphen’s urban area and Heijen’s agricultural land. Results demonstrated that the multi-sensor fusion scenarios (S18, S20, and S25) achieved the highest classification performance, with overall accuracy reaching 96.4% (Kappa = 0.906–0.949) in Zutphen and 87.5% (Kappa = 0.754–0.833) in Heijen. For the flood class F1 scores of all scenarios, they varied from 0.742 to 0.969 in Zutphen and from 0.626 to 0.969 in Heijen. Eventually, the addition of SAR texture metrics enhanced flood boundary identification throughout both urban and agricultural settings. Radarsat-2 provided limited benefits to the overall results, since Sentinel-1 and Landsat-8 data proved more effective despite being freely available. This study demonstrates that using SAR and optical features together with texture information creates a powerful and expandable flood mapping system, and RF classification performs well in diverse landscape settings. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

Predictive Flood Uncertainty Associated with the Overtopping Rates of Vertical Seawall on Coral Reef Topography - Zhang, Hongqian; Lu, Bin; Geng, Yumei; Liu, Ye (Water (Switzerland), 2025)
Accurate prediction of wave overtopping rates is essential for flood risk assessment along coral reef coastlines. This study quantifies the uncertainty sources affecting overtopping rates for vertical seawalls on reef flats, using ensemble simulations with a validated non-hydrostatic SWASH model. By generating extensive random wave sequences, we identify spectral resolution, wave spectral width, and wave groupiness as the dominant controls on the uncertainty. Statistical metrics, including the Coefficient of Variation ((Formula presented.)) and Range Uncertainty Level ((Formula presented.)), demonstrate that overtopping rates exhibit substantial variability under randomized wave conditions, with (Formula presented.) exceeding 40% for low spectral resolutions (50–100 bins), while achieving statistical convergence ((Formula presented.) around 20%) requires at least 700 frequency bins, far surpassing conventional standards. The (Formula presented.), which describes the ratio of extreme to minimal overtopping rates, also decreases markedly as the number of frequency bins increases from 50 to 700. It is found that the overtopping rate follows a normal distribution with 700 frequency bins in wave generation. Simulations further demonstrate that overtopping rates increase by a factor of 2–4 as the JONSWAP spectrum peak enhancement factor ((Formula presented.)) increases from 1 to 7. The wave groupiness factor ((Formula presented.)) emerges as a predictor of overtopping variability, enabling a more efficient experimental design through reduction in groupiness-guided replication. These findings establish practical thresholds for experimental design and highlight the critical role of spectral parameters in hazard assessment. © 2025 by the authors.
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Keywords: Scopus_Alert_22_Aout_2025

A multi-hazard assessment approach to reveal and compare heat- and flood-related risks and inequalities in London, Boston, and Sydney - Longato, Davide; Maragno, Denis (International Journal of Disaster Risk Reduction, 2025)
Keywords: Scopus_Alert_22_Aout_2025

Floods, land loss, and gendered vulnerability: Assessing the social impacts of small hydropower in Vietnam - Swe, Khin Nilar; Phuong, Ho Thi; Thinh, Tran Duc; Chan, Nyien (Environmental Development, 2025)
Keywords: Scopus_Alert_22_Aout_2025

The Paradigm Shift in Scientific Interest on Flood Risk: From Hydraulic Analysis to Integrated Land Use Planning Approaches - Franco, Ángela; García-Ayllón, Salvador (Water, 2025)
Floods are natural hazards that have the greatest socioeconomic impact worldwide, given that 23% of the global population live in urban areas at risk of flooding. In this field of research, the analysis of flood risk has traditionally been studied based mainly on approaches specific to civil engineering such as hydraulics and hydrology. However, these patterns of approaching the problem in research seem to be changing in recent years. During the last few years, a growing trend has been observed towards the use of methodology-based approaches oriented towards urban planning and land use management. In this context, this study analyzes the evolution of these research patterns in the field by developing a bibliometric meta-analysis of 2694 scientific publications on this topic published in recent decades. Evaluating keyword co-occurrence using VOSviewer software version 1.6.20, we analyzed how phenomena such as climate change have modified the way of addressing the study of this problem, giving growing weight to the use of integrated approaches improving territorial planning or implementing adaptive strategies, as opposed to the more traditional vision of previous decades, which only focused on the construction of hydraulic infrastructures for flood control.
Keywords: Scopus_Alert_22_Aout_2025

Exploring Waterlogging Challenges, Causes and Mitigating Strategies in Maize ( Zea mays L.) - Behera, Supriya; Kar, Ipsita; Yadav, Ashok; Sahu, Ankita (Journal of Agronomy and Crop Science, 2025)
ABSTRACT Waterlogging is a critical abiotic stress factor severely affecting maize, one of the World's most widely cultivated cereal crops. Globally, maize is a crucial food crop, grown in diverse agro‐climatic zones, from subtropical to temperate climates. Waterlogging, resulting from flooding, intense rainfall and inefficient drainage systems, continues to be a major abiotic stress factor influencing crop productivity globally. Prolonged exposure to excess soil moisture leads to oxygen depletion in the root zone, resulting in restricted aerobic respiration, impaired nutrient uptake and disruption of physiological processes. This review aims to provide a comprehensive overview of the morphological, physiological and biochemical changes maize undergoes in response to waterlogging stress. Key aspects such as root system adaptation, reduction in photosynthetic efficiency, accumulation of reactive oxygen species (ROS) and hormonal imbalances are systematically examined. Furthermore, we delve into the metabolic shifts that enable maize to survive under anaerobic conditions, including alterations in energy metabolism, carbohydrate partitioning, and activating antioxidant defence mechanisms. The role of key signalling molecules such as ethylene is explored, highlighting their involvement in regulating stress responses. Additionally, the review discusses agronomic and genetic approaches for improving waterlogging tolerance in maize, including the development of stress‐resilient cultivars through breeding and biotechnological interventions. By synthesising recent advances in understanding maize's response to waterlogging, this paper identifies gaps and proposes future research directions, focusing on the integration of molecular and field‐based strategies. The insights from this review are crucial for developing sustainable agricultural practices aimed at mitigating the adverse impacts of waterlogging on maize productivity, particularly in flood‐prone areas. Breeding for waterlogging resilience integrates the creation of robust varieties, plant morphology optimisation, and utilisation of tolerant secondary traits through combined conventional and biotechnological breeding strategies.
Keywords: Scopus_Alert_22_Aout_2025

Quantifying the spatiotemporal dynamics of urban flooding susceptibility in the greater bay area under shared socio-economic pathways using the SD-PLUS-LightGBM framework - Zhou, Shiqi; Jia, Weiyi; Geng, Xiwen; Xu, Haowen; Diao, Haifeng; Liu, Zhiyu; Wang, Mo; Fu, Xiaoping; Wu, Yuwei; Qiao, Renlu; Wu, Zhiqiang (Resources, Conservation and Recycling, 2025)
Urbanization and climate change keep intensifying extreme rainfall events. Previous studies have explored urban flood susceptibility, yet a comprehensive approach that unifies these perspectives has remained underdeveloped. This study established a holistic framework using the SD-PLUS-LightGBM model with multiple variables under three SSP-RCP scenarios to predict spatial-temporal dynamics of flood susceptibility in the Greater Bay Area between 2030 and 2050. Compared with traditional models, LightGBM established superior predictive accuracy and operational reliability for urban flood susceptibility mapping. The results indicated a non-linear expansion of high-susceptibility zones, with SSP5–8.5 projections showing a two-fold increase in vulnerable areas by 2050 relative to 2020 baselines. Regions experiencing pronounced susceptibility transitions were expected to grow significantly (0.23 % of the total area), concentrated in historic urban cores and peri‑urban interfaces. This study offered an in-depth approach to stormwater management along with targeted recommendations for sustainable urban planning and design. © 2025
Publisher: Elsevier B.V.
Keywords: Scopus_Alert_15_Aout_2025

Seasonal Influences of Precipitation and River Stage on Groundwater Levels in Platte River Watersheds Vulnerable to Spring Floods - Kim, Incheol; Koya, Sinan Rasiya; Roy, Tirthankar; Eun, Jongwan (Journal of Hydrologic Engineering, 2025)
Spring floods occurring in the Midwest US are often aggravated by meteorological and hydrological conditions. In this study, the seasonal influences of precipitation (PRCP) and river stage (RS) on groundwater level (GWL) fluctuations were analyzed for the Middle and Lower Platte watersheds along the Platte River in a Midwestern catchment that is vulnerable to spring floods. Statistical analysis was conducted to simulate GWL with a moving average-based time lag consideration approach by using multiple hydrological data sets for 25 study sites. The results showed that the time lag consideration approach appropriately provided the regional information of water infiltration characteristics among GWL, PRCP, and RS for each study site. Also, the correlations of GWL with PRCP and RS were found to vary depending on the season. Especially in the early spring season, the correlation of GWL with PRCP is very weak (correlation coefficient=0.001 to 0.198). This may be due to entirely or partially frozen ground, which prevents rainwater from penetrating into the aquifer, causing large amounts of runoff and contributing to frequent flooding in early spring. In addition, statistical analysis showed that accounting for the time lag of PRCP and RS improved GWL simulation performance, and their influence varied by season. © 2025 American Society of Civil Engineers.
Publisher: American Society of Civil Engineers (ASCE)
Keywords: Scopus_Alert_15_Aout_2025

Comparative assessment of flood risk to critical infrastructure: The case of Utah, USA - Clark, Austin S.; Collins, Tim (International Journal of Disaster Risk Reduction, 2025)
During and after a disaster, selected services and systems are needed to recover and maintain important functions of society. These are deemed critical infrastructure (CI). When these services are disrupted due to the impacts of a disaster, response and recovery may be slowed or halted. As flooding events are occurring more often across larger geographic extents, advancing methods for assessing risks of flooding to CI is vital. We use Utah, USA as a case study to demonstrate a novel, transferable approach for assessing fine-scale flood risks to CI across large geographic areas. Specifically, our assessment approach integrates high-resolution building footprints of schools, first responder facilities, and hospitals, and flood risk maps from a state-of-the-art big data flood model and the U.S. Federal Emergency Management Agency (FEMA). We show that 94 CI facilities across Utah are at risk of severe flooding, and that those risks to CI are almost entirely overlooked by FEMA flood risk maps. Though nearly every CI building is located outside of FEMA flood zones, FEMA maps inaccurately and incompletely represent flood risks, indicating that future flood risk assessment approaches should use flood risk maps from other sources. The approach we introduce can be used to assess flood risks to CI elsewhere, and case study results can be applied to inform flood risk reduction efforts in Utah. © 2025 Elsevier Ltd
Publisher: Elsevier Ltd
Keywords: Scopus_Alert_15_Aout_2025

Impact of climate change scenario on sea level rise and future coastal flooding in major coastal cities of India - Chakrabortty, Rabin; Ali, Tarig; Atabay, Serter; Roy, Paramita; Pande, Chaitanya Baliram (Scientific Reports, 2025)
This study evaluates the impacts of projected sea level rise (SLR) on coastal flooding across major Indian cities: Mumbai, Kolkata, Chennai, Visakhapatnam, Surat, Kochi, Thiruvananthapuram, and Mangaluru. Machine learning models, including Long Short-Term Memory (LSTM), Random Forest (RF), and Gradient Boosting (GB), has been employed to assess flood risks under four Shared Socioeconomic Pathways (SSP 126, 245, 370, and 585) emission scenarios. The research utilized these models because they demonstrate high performance in handling difficult data relationships and both temporal patterns and sophisticated environmental data. SLR projections provided by computers generate forecasts that combine with digital elevation models (DEMs) to determine coastal flooding risks and locate flood-prone areas. Results reveal that Mumbai and Kolkata face the highest flood risks, particularly under high emission scenarios, while Kochi and Mangaluru exhibit moderate exposure. Model performance is validated using residual analysis and Receiver Operating Characteristic (ROC) curves, confirming reliable predictive accuracy. These findings provide essential information for urban planners and policymakers to prioritize climate adaptation strategies in vulnerable coastal cities. © The Author(s) 2025.
Publisher: Nature Research
Keywords: Scopus_Alert_15_Aout_2025

Multi-Criteria Decision Analysis for Managed Aquifer Recharge (MAR): A Flood-Responsive Approach in Milpa Alta, Mexico City - Areu-Rangel, Omar S.; Singh, Amrie; Bonasia, Rosanna (Environmental Quality Management, 2025)
Milpa Alta, located southeast of Mexico City, is a key region for environmental sustainability due to its volcanic soil, biodiversity, and critical role in aquifer recharge, which supports the city's water supply. However, rapid urbanization has severely impacted the area, causing reduced vegetation cover, increased runoff, and diminished groundwater recharge, which intensify flooding, soil erosion, and water scarcity. This study aims to identify optimal sites for managed aquifer recharge (MAR) structures in Milpa Alta through a multi-criteria analysis incorporating criteria such as topography, land use, proximity to urban areas, and drainage networks. Uniquely, hydraulic simulations of flood scenarios were integrated into the analysis to improve the precision of site selection. Geographic information systems (GIS) were used to assess and combine these criteria, providing a spatial evaluation of suitability. Results indicate that the central and northern regions of Milpa Alta, particularly around San Francisco Tecoxpa and San Antonio Tecómitl, are most suitable for MAR implementation due to their permeable soils, gentle slopes, and proximity to agricultural lands and drainage networks. These MAR structures can enhance groundwater recharge and mitigate flood risks during extreme rainfall events, with the potential to capture up to 300,000 m3 of surface runoff during a single high-intensity storm event. Despite its strengths, the study acknowledges limitations such as the absence of detailed water quality analyses and the need for sensitivity testing of the criteria weighting. This research provides an innovative approach to MAR site selection by integrating flood simulations, offering a replicable model for similar regions. Successful implementation of MAR in Milpa Alta requires addressing water quality concerns, engaging stakeholders, and ensuring compliance with regulatory frameworks. The findings emphasize MAR's potential to balance urbanization pressures with sustainable water management and flood mitigation strategies in Mexico City's rapidly developing areas. © 2025 Wiley Periodicals LLC.
Publisher: John Wiley and Sons Inc
Keywords: Scopus_Alert_15_Aout_2025

HyEco: A hybrid hydrodynamic-cum-ecological modelling framework to demystify flood and human-health risks over flood-prone metropolis - Deopa, Rahul; Mohanty, Mohit Prakash (Water Research X, 2025)
Urban flooding, exacerbated by climate change and unregulated urbanization, poses significant risks to the built environment. In addition to physical damage, floodwaters often mobilize a hazardous mix of untreated sewage, industrial effluents, and undesirable pollutants, leading to severe microbial contamination in the floodwaters. This study introduces “HyEco”-an integrated framework comprising high-fidelity 3-way coupled hydrodynamic and ecological modelling with an aim to capture the “unhidden tangible flood risks” and “hidden intangible public-health risks” in tandem. Focusing on Delhi, India, a densely populated metropolis prone to recurrent urban flooding and associated health crises, the framework simulates the 2023 mega-flood event. Results show that approximately 63.5 % of the region is categorized under ‘high’ to ‘very high’ flood risk zones, with over 20 % of these areas housing around 15 % of the city's dense population. The hydrodynamic model outputs were forced into the ecological model to simulate the fate and transport of microbial contamination in floodwaters. Escherichia coli concentrations ranged from 772,868 to 790,000 MPN/100 mL, far exceeding established safety thresholds. A Quantitative Microbial Risk Assessment (QMRA) reveals elevated infection probabilities, particularly among children, with risks up to 2.60×10⁻³ under repeated exposure and 8.38×10⁻⁴ to 8.57×10⁻⁴ for pedestrian splash exposures. Unlike prior approaches that examine flood and microbial risks in isolation or depend on static datasets, HyEco overcomes key methodological gaps by dynamically integrating flood and microbial processes at high spatio-temporal resolution. The HyEco framework offers a scalable and actionable tool for integrated flood risk management and climate-resilient public health planning. © 2025
Publisher: Elsevier Ltd
Keywords: Scopus_Alert_15_Aout_2025

Pedestrian vulnerability assessment of underground staircases in urban flooding - Wu, Wenqi; Zhu, Zhongfan; Zheng, Xinyu; Liu, Shuyou; Zhang, Dawei (Sustainable Cities and Society, 2025)
Urban underground flooding occurs frequently worldwide in the context of climate change and rapid urbanization, posing a serious threat to the travel safety of urban populations; in particular, staircases play an important role in the emergency evacuation of pedestrians in floodwater. Previous studies have identified the staircase configuration as a crucial factor influencing the evacuation difficulty of pedestrians in floodwater. However, the correlation between the geometric characteristics of staircase structures and pedestrian vulnerability is not fully understood, and few parametric studies have focused on the effects of wind intrusion into underground spaces and the effects of various engineering measures. This study thereby aims to assess pedestrian vulnerability in underground staircase floodwater as the width of the lower segment of the staircase increases, the effect of wind in the staircase is incorporated, and several flood prevention and/or windproof measures are implemented. Computational fluid dynamics (CFD) simulations were performed to reproduce the mean floodwater flow field and wind flow field on underground staircases. The findings show that (i) a variation in the width of the lower staircase after the rest platform affects pedestrian vulnerability, i.e., an increasing lower staircase width decreases the pedestrian risk to a certain degree; however, the jet behind the rest platform intensifies it; (ii) the incorporation of the wind effect when it intrudes the staircase obviously deteriorates the pedestrian vulnerability, and a discrepancy exists in the evacuation speeds of different pedestrian groups under a joint effect of wind and floodwater; and (iii) some engineering measures, especially windproof measures, have the potential to mitigate pedestrian vulnerability. These findings can serve as a reference for policymakers and stakeholders in coping with urban underground flooding hazards and guiding the emergency evacuation of people trapped in floodwater in the context of resilient city construction. © 2025 Elsevier Ltd
Publisher: Elsevier Ltd
Keywords: Scopus_Alert_15_Aout_2025

Extreme precipitation risk assessment with improved WOA-Optimized copula model under composite conditions - Wang, Zhaocai; Ma, Chao; Wu, Junhao; Wu, Tunhua (Theoretical and Applied Climatology, 2025)
An accurate study of extreme precipitation risk events is crucial for flood control, urban planning, and engineering design. The Copula function effectively handles uncertainties and nonlinear interactions among multiple hydrological variables, capturing complex correlations in extreme precipitation events for more precise risk assessments. Selecting the parameters of the Copula function is critical, as it defines the function’s shape and the dependence structure between variables, influencing its application. Traditional parameterization methods, like maximum likelihood estimation and least squares, often require large datasets and distribution assumptions, making them cumbersome for high-dimensional data. This research presents a model using an enhanced whale optimization algorithm to estimate Copula parameters (CLCWOA-Copula), aiming to assess return period (RP) and failure probability associated with extreme precipitation risk events. Monthly precipitation data from Zhengzhou, China, from 1950 to 2024 is analyzed, using the 90th percentile as the extreme precipitation threshold. Marginal distributions are fitted using the P-III and gamma distributions, etc., which are then combined using CLCWOA-Copula to analyze coincident RP, joint RP, Kendall RP, and failure probability under composite conditions. The results demonstrate that this optimization method possesses strong global search capabilities and parallel computing abilities, yielding optimal Copula parameter values within few iterations and selecting the best-fit Copula function based on AIC, R², and RMSE. The Kendall RP and failure probability offer more accurate tools for extreme precipitation risk analysis; when Pmax reaches 540 mm, P90 reaches 1080 mm, or R90 reaches 0.83, a one-in-a-century extreme precipitation event is indicated. This study provides important insights for risk metrics applicable to extreme weather. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2025.
Publisher: Springer
Keywords: Scopus_Alert_15_Aout_2025

Projections of extreme weather events according to climate change scenarios and populations at-risk in Brazil - Dantas, Leydson Galvíncio; Ferreira, Andrêa Jacqueline Fortes; Pinto Junior, Jony Arrais; Cortes, Taísa Rodrigues; Neves, Danielson Jorge Delgado; de Oliveira, Beatriz Fátima Alves; da Silveira, Ismael Henrique (Climatic Change, 2025)
Extreme weather events, such as heat waves, heavy rainfall and droughts, have become more frequent and intense in Brazil. According to climate change scenarios, this trend, which has a negative impact on people’s health and living conditions, will continue. Here, we analysed indicators for extreme weather events resulting from climate change, projected for the 21st century, alongside socio-demographic indicators for Brazilian municipalities, in an attempt to identify populations exposed to the risks of the climate crisis. We calculated the values of indicators for extreme air temperature and precipitation events, based on NEX-GDDP-CMIP6 data, for a reference period and for the future, as well as socio-demographic indicators based on recent census data. Using Spearman’s coefficient, we then calculated anomaly indicators for the future time intervals and analysed correlations with the socio-demographic indicators. Our results indicate a reduction in cold days and an increase in hot days and heat waves in both scenarios (SSP2-4.5 and SSP5-8.5), with the most changes occurring in the highest emission scenario. The extreme precipitation indicators suggest both an increase and a reduction in intense precipitation and droughts in a number of the country’s regions. The projected changes are more intense in the highest emission scenario, and in the North and Northeast regions. We noted a trend for greatest occurrence of extreme events in locations with a higher proportion of Black, Parda/Brown, Indigenous and Quilombola populations, and the socially vulnerable. We recommend that policies to adapt and mitigate the impacts of climate change focus on reducing inequalities and promoting climate justice. © The Author(s) 2025.
Publisher: Springer Science and Business Media B.V.
Keywords: Scopus_Alert_15_Aout_2025

Future Projection of Rainstorm and Flood Disaster Risk in Sichuan-Chongqing Region under CMIP6 Different Climate Change Scenarios - Yao, Ying; Li, Xiehui; Wang, Lei; Li, Hongying (Plateau Meteorology, 2025)
In recent years，rapid urbanization and global warming have led to frequent and severe rainstorm and flood disasters in the Sichuan-Chongqing region. This change will not only have a serious impact on the ecological environment and socio-economic development of the area，but also significantly increase the pressure on urban infrastructure and threaten the safety of people's lives and property. Therefore，it is particularly important to scientifically and accurately analyze the disaster risk of rainstorm and flood in Sichuan-Chongqing region in the past and future. This paper utilized daily precipitation data from 50 selected meteorological stations in the Sichuan-Chongqing region，precipitation data from 5 CMIP6 models，gridded population and economic data under Shared Socioeconomic Pathways（SSPs），as well as DEM and land use remote sensing data. Firstly，using Taylor diagrams，quantitative indices（S），and standardized anomaly sequences，the study evaluated the simulation performance of 5 individual CMIP6 models，an equal-weighted aggregation of 5 models（EWA-5），and unequally-weighted aggregations of 5 models（UEWA-5）for five selected extreme precipitation indices. Then，by building a comprehensive risk assessment model of rainstorm and flood disaster based on disaster risk and vulnerability of disaster bearing body，the study conducted risk assessments，future projections，and comparative analyses of rainstorm and flood disasters during baseline（1995-2014）and future near-term（2025-2044）and long-term （2045-2064）periods under three different climate change scenarios（SSP1-2. 6，SSP2-4. 5，SSP5-8. 5）. Results indicated：（1）The EC-Earth3 model performed best in simulating the five extreme precipitation indices，with correlation coefficients between simulated and observed values of 0. 78 for R95p，0. 90 for RX1day，and 0. 77 for RX5day. Overall，the simulation performance of UEWA-5 exceeded that of EWA-5.（2）During the baseline period，central Sichuan exhibited high values for the five extreme precipitation indices，followed by eastern Sichuan and Chongqing，while western Sichuan showed lower values. The year 1998 recorded peak values for all five indices，with a maximum single-day precipitation of 86 mm for RX1day and an intensity（SDII）value of 11. 3 mm·d-1.（3）In future periods，the five extreme precipitation indices display a spatial distribution characterized by higher values in central regions and lower values around the periphery. Higher levels of social vulnerability and radiative forcing correlate with larger values of extreme precipitation indices. Comparing the two future periods，values of the indices are larger in the long term，notably with R95p averaging 846. 8 mm，an increase of 169. 2 mm compared to the near term.（4）During historical periods，areas with higher comprehensive risk of rainstorm and flood disasters were concentrated in central Sichuan and downtown Chongqing. In the two future periods，the high and moderately high-risk areas in central Sichuan are expected to expand，while the moderate-risk areas will shrink. The range of low-risk areas in the western Sichuan Plateau will also decrease，and the risk levels in southern Sichuan and eastern Sichuan-Chongqing border areas will respectively decrease to moderate-low and low-risk zones. Comparing the two future periods，the range of moderately high and moderate-risk areas in central Sichuan is expected to expand，while southwestern Chongqing will transition to a moderate-risk area in the long term. Other regions will generally maintain their original risk levels. Changes in disaster risk levels in the Sichuan-Chongqing region are less pronounced with increasing social vulnerability and radiative forcing，especially in the western Sichuan Plateau and northeastern Sichuan，where changes in disaster risk levels are minimal. The study results can provide important references for reducing disaster risks，enhancing emergency response capabilities，and making scientifically informed decisions for disaster prevention in the Sichuan-Chongqing region. © Editorial Department of Plateau Meteorology.
Publisher: Science China Press
Keywords: Scopus_Alert_15_Aout_2025

Interactive Effects of Climate Change and Contaminants in Aquatic Ecosystems on Environmental-Human Health - Yu, Kaifeng; Mohapatra, Sanjeeb; Chen, Yihan; Jiang, Peng; Tong, Xuneng (Current Pollution Reports, 2025)
Purpose of the Review: Climate change is intensifying the pressures on aquatic ecosystems by altering the dynamics of contaminants, with cascading effects on ecological and human health. This review synthesizes recent evidence on how rising temperatures, altered precipitation patterns, and extreme weather events influence chemical and microbial contaminant dynamics in aquatic environments. Recent Findings: Key findings reveal that elevated temperatures enhance phosphorus pollution and algal blooms, increase heavy metal release from sediments, and promote the mobilization of organic pollutants. Concurrently, climate change exacerbates microbial contamination by facilitating the spread of waterborne microbial contaminants, especially posing more pressure to antimicrobial resistance-related contaminants through temperature-driven horizontal gene transfer and extreme precipitation events. Complex interactions between chemical and microbial contaminants like heavy metals co-selecting for antibiotic resistance further amplify risks. The compounded effects of climate change and contaminants threaten water quality, ecosystem resilience, and public health, particularly through increased toxicant exposure via seafood and waterborne disease outbreaks. Despite growing recognition of these interactions, critical gaps remain in understanding their synergistic mechanisms, especially in data-scarce regions. Summary: This review highlights the urgent need for integrated monitoring, predictive modeling, and adaptive policies under a One Health framework to mitigate the multifaceted impacts of climate-driven contamination. Future research should prioritize real-world assessments of temperature effects, urban overflow dynamics during extreme weather, and the socio-behavioral dimensions of contaminant spread to inform effective mitigation strategies. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.
Publisher: Springer Science and Business Media Deutschland GmbH
Keywords: Scopus_Alert_15_Aout_2025

The Needs, Challenges, and Priorities for Advancing Global Flood Research - Samadi, Vidya; Fowler, Hayley J.; Lamond, Jessica; Wagener, Thorsten; Brunner, Manuela; Gourley, Jonathan; Moradkhani, Hamid; Popescu, Ioana; Wasko, Conrad; Wright, Daniel; Wu, Huan; Zhang, Ke; et al. (WIREs Water, 2025)
ABSTRACT In recent years, numerous flood events have caused loss of life, widespread disruption, and damage across the globe. These devastating impacts highlight the importance of a better understanding of flood generating processes, their impacts, and their variability under climate and landscape changes. Here, we argue that the ability to better model flooding is underpinned by the grand challenge of understanding flood generation mechanisms and potential impacts. To address this challenge, the World Meteorological Organization‐Global Energy and Water Exchanges (GEWEX) Hydrometeorology Panel (GHP) aims to establish a Global Flood Crosscutting project to propagate flood modeling and research knowledge across regions and to synthesize results at the global scale. This paper outlines a framework for understanding the dynamics and impacts of runoff generation processes and a rationale for the role of a Global Flood Crosscutting project to address these challenges. Within this Global Flood Crosscutting project, we will establish a common terminology and methods to enable the global research community to exchange knowledge and experiences, and to design experiments toward developing actionable recommendations for more effective flood management practices and policies for improved resilience. This harmonization of rich perspectives across disciplines will foster the co‐production of knowledge primed to advance flood research, particularly in the current period of heightened climate variability and rapid change. It will create a new transdisciplinary paradigm for flood science, wherein different dimensions of mechanistic understanding and processes are rigorously considered alongside socioeconomic impacts, early warning communications, and longer‐term adaptation to alleviate flood risks in society.
Keywords: Infolettre_Ete_2025

Projecting climate and socioeconomic contributions to global flood-induced displacements using a data-driven approach - Del Rio Amador, Lenin; Boudreault, Mathieu; Carozza, David A. (Natural Hazards, 2025)
Keywords: Infolettre_Ete_2025

Full-scale characterization of the effects of a bioretention system on water quality and quantity following the replacement of a mixed stormwater and combined sewer system - Le Cauchois, Pia; Doucet, Samuel; Bouattour, Ons; McQuaid, Natasha; Beral, Henry; Kõiv-Vainik, Margit; Bichai, Françoise; McCarthy, David; St-Laurent, Julien; Dagenais, Danielle; Bennekrela, Nesrine; Guerra, Juan; et al. (Blue-Green Systems, 2025)
ABSTRACT Urbanization is leading to more frequent flooding as cities have more impervious surfaces and runoff exceeds the capacity of combined sewer systems. In heavy rainfall, contaminated excess water is discharged into the natural environment, damaging ecosystems and threatening drinking water sources. To address these challenges aggravated by climate change, urban blue-green water management systems, such as bioretention cells, are increasingly being adopted. Bioretention cells use substrate and plants adapted to the climate to manage rainwater. They form shallow depressions, allowing infiltration, storage, and gradual evacuation of runoff. In 2018, the City of Trois-Rivières (Québec, Canada) installed 54 bioretention cells along a residential street, several of which were equipped with access points to monitor performance. Groundwater quality was monitored through the installation of piezometers to detect potential contamination. This large-scale project aimed to improve stormwater quality and reduce sewer flows. The studied bioretention cells reduced the flow and generally improved water quality entering the sewer system, as well as the quality of stormwater, with some exceptions. Higher outflow concentrations were observed for contaminants such as manganese and nitrate. The results of this initiative provide useful recommendations for similar projects for urban climate change adaptation.
Keywords: Infolettre_Ete_2025

Societal drivers for the integration of hydrogeomorphology and human benefits in river restoration projects - Gariépy‐Girouard, Étienne; Buffin‐Bélanger, Thomas; Biron, Pascale M. (River Research and Applications, 2025)
Abstract Integrating hydrogeomorphological (HGM) principles into the restoration of degraded rivers can achieve sustainable results and provide various human benefits. HGM principles mainly involve understanding the context and processes that shape a fluvial system before any intervention, in order to support its dynamism and to align with its potential functioning and uses. Despite recent management approaches inspired by HGM principles, most restoration projects carried out in Quebec (Canada) are not process‐based and target specific one‐dimensional objectives. Although there is an overall lack of post‐project monitoring, several projects appear to have failed or had mixed success. This research aims to shed light on the diversity of societal drivers behind river restoration projects and to examine how they influence the integration of HGM principles and human benefits. Four restoration projects were characterized through participant observation and interviews with the organizations running them. Representatives of two ministries involved in river restoration and management were also interviewed. The results show that projects were mainly shaped by public acceptance disregarding HGM principles, which can lead to poorly‐informed action. Project funding and stakeholders' expertise have also challenged project implementation and played a key role in defining their objectives. The addition of these components improve the current analytical frameworks for identifying river restoration objectives. Depending on specific sociocultural, political and legislative contexts, funding programs and stakeholders' expertise may either facilitate or restrict the integration of HGM principles and human benefits in the projects. Recognizing these key drivers reframes river restoration as a fundamentally social activity and enlightens how they could impel innovative approaches towards more sustainable results.

Developing an ensemble machine learning framework for enhanced climate projections using CMIP6 data in the Middle East - Khosravi, Younes; Ouarda, Taha B.M.J.; Homayouni, Saeid (npj Climate and Atmospheric Science, 2025)
Abstract Climate change in the Middle East has intensified with rising temperatures, shifting rainfall patterns, and more frequent extreme events. This study introduces the Stacking-EML framework, which merges five machine learning models three meta-learners to predict maximum temperature, minimum temperature, and precipitation using CMIP6 data under SSP1-2.6, SSP2-4.5, and SSP5-8.5. The results indicate that Stacking-EML not only significantly improves prediction accuracy compared to individual models and traditional CMIP6 outputs but also enhances climate projections by integrating multiple ML models, offering more reliable, regionally refined forecasts. Findings show R² improvements to 0.99 for maximum temperature, 0.98 for minimum temperature, and 0.82 for precipitation. Under SSP5-8.5, summer temperatures in southern regions are expected to exceed 45 °C, exacerbating drought conditions due to reduced rainfall. Spatial analysis reveals that Saudi Arabia, Oman, Yemen, and Iran face the greatest heat and drought impacts, while Turkey and northern Iran may experience increased precipitation and flood risks.
Keywords: Infolettre; Infolettre_Mai_2025

Beyond fear: The role of emotions in disaster risk reduction in the face of climate change - Lizarralde, Gonzalo; Lajoie, Steffen; Gould, Kevin; Araneda, Claudio; Cruz-Panesso, Ilian; Diaz, Julia Helena; Monsalve, Elsa; Burdiles, Roberto; Herazo, Benjamin; Páez, Holmes; Valladares, Arturo; Bornstein, Lisa; et al. (Emotion, Space and Society, 2025)
Keywords: Infolettre; Infolettre_Decembre_2024

Turkmen women’s traditional craft skills in post-disaster recovery: the case of the 2019 Northeast floods in Iran - Hassani, Atoosa; Fayazi, Mahmood; Mottaki, Zoheir; Adib, Morteza; Dehbandi, Ramin; Khalili Gheidari, Yasamam; Seraji, Fatemeh (Disaster Prevention and Management: An International Journal, 2025)
Purpose This study investigates why Turkmen women’s traditional handicraft skills have declined and explains how the local, traditional craft skills accelerated the post-flood recovery of Turkmen women in the aftermath of the 2019 Northeast floods in Iran. Design/methodology/approach The research adopts a case study approach, employing reflective thematic analysis. Findings Post-disaster recovery spurred a shift from traditional to modern lifestyles through new housing designs, enhanced female literacy and greater economic participation. However, this transition devalued traditional crafts due to heightened household chores, material scarcity and reduced market demand. Nonetheless, women with craft skills played a pivotal role in household recovery by repairing damaged items and crafting dowries for their daughters, illustrating their contribution to social and economic resilience. Social implications These research findings shed light on the importance of traditional craft skills in enabling the female household member, in particular, to recover from disasters and contribute to the recovery of their households and communities. Originality/value The originality of this study lies in its focus on the specific context of Turkmen women’s traditional craft skills and their role in post-disaster recovery, particularly after the 2019 Northeast floods in Iran. While there is existing research on post-disaster recovery mechanisms, this study uniquely examines the under-researched impact of traditional craft skills on the recovery process, specifically for female household members.
Keywords: Infolettre; Infolettre_Fevrier_2025

Use of digital elevation models for flood susceptibility assessment via a hydrogeomorphic approach: A case study of the Basento River in Italy - Albano, Raffaele; Adamowski, Jan (Natural Hazards, 2025)
Abstract Floods are the most common and threatening natural risk for many countries in the world. Flood risk mapping is therefore of great importance for managing socio-economic and environmental impacts. Several researchers have proposed low-complexity and cost-effective flood mapping solutions that are useful for data scarce environments or at large-scale. Among these approaches, a line of recent research focuses on hydrogeomorphic methods that, due to digital elevation models (DEMs), exploit the causality between past flood events and the hydraulic geometry of floodplains. This study aims to compare the use of freely-available DEMs to support an advanced hydrogeomorphic method, Geomorphic Flood Index (GFI), to map flood-prone areas of the Basento River basin (Italy). The five selected DEMs are obtained from different sources, are characterized by different resolutions, spatial coverage, acquisition process, processing and validation, etc., and include: (i) HydroSHEDS v.1.1 (resolution 3 arc-seconds), hydrologically conditioned, derived primarily from STRM (NASA) and characterized by global coverage; (ii) ASTER GDEM v.3 with a res. of around 30 m (source: METI and NASA) and global coverage; (iii) EU-DEM v. 1.1 (res. 1 arc-second), Pan-European and combining SRTM and ASTER GDEM, customized to obtain a consistency with the EU-Hydro and screened to remove artefacts (source: Copernicus Land Monitoring Service); (iv) TinItaly DEM v. 1.1, (res. 10 m-cell size grid) and produced and distributed by INGV with coverage of the entire Italian territory; (v) Laser Scanner DEM with high resolution (5 m cell size grid) produced on the basis of Ground e Model Keypoint and available as part of the RSDI geoportal of the Basilicata Region with coverage at the regional administrative level. The effects of DEMs on the performance of the GFI calibration on the main reach of the Basento River, and its validation on one of its mountain tributaries (Gallitello Creek), were evaluated with widely accepted statistical metrics, i.e., the Area Under the Receiver Operating Characteristics (ROC) curve (AUC), Accuracy, Sensitivity and Specificity. Results confirmed the merits of the GFI in flood mapping using simple watershed characteristics and showed high Accuracy (AUC reached a value over 0.9 in all simulations) and low dependency on changes in the adopted DEMs and standard flood maps (1D and 2D hydraulic models or three return periods). The EU-DEM was identified as the most suitable data source for supporting GFI mapping with an AUC > 0.97 in the calibration phase for the main river reach. This may be due in part to its appropriate resolution for hydrological application but was also due to its customized pre-processing that supported an optimal description of the river network morphology. Indeed, EU-DEM obtained the highest performances (e.g., Accuracy around 98%) even in the validation phase where better results were expected from the high-resolution DEM (due to the very small size of Gallitello Creek cross-sections). For other DEMs, GFI generally showed an increase in metrics performance when, in the calibration phase, it neglected the floodplains of the river delta, where the standard flood map is produced using a 2D hydraulic model. However, if the DEMs were hydrologically conditioned with a relatively simple algorithm that forced the stream flow in the main river network, the GFI could be applied to the whole Basento watershed, including the delta, with a similar performance.
Keywords: Infolettre; Infolettre_Fevrier_2025

Four core principles to reconcile sociocultural conditions and disaster risk reduction in pursuit of community resilience - Graveline, Marie-Hélène; Germain, Daniel; Boyer-Villemaire, Ursule; Guimond, Laurie (Environmental Hazards, 2025)
Keywords: Infolettre; Infolettre_Fevrier_2025