Search Results (263)

The growing complexity of human systems and the increasing frequency of climate-driven hazards have transformed some disasters from isolated events into cascading phenomena which propagate through critical infrastructure networks, disrupting essential services and amplifying systemic risk. This work examines the impacts of extreme storms and subsequent flooding on critical entities as defined under the new EU Directive (Critical Entities Resilience, CER). This study introduces a structured Critical Entities Disruption Database—Greece (CEDD-GR), as a methodological framework for systematically recording and analysing disruptions to critical entities, and applies it to the case of Storm Daniel (2023), one of the most severe flood events recorded in Greece. The analysis identified direct impacts across eight of the eleven sectors defined in the CER Directive, namely, energy, transport, health, drinking water, wastewater, public administration, digital infrastructure and food production, processing and distribution. A total of 21 different types of critical entities were documented, revealing the mechanisms through which failures affected different subsectors. The results underscore the systemic fragility of critical entities when exposed to extreme storms, compound flooding, and mass wasting processes (landslides, ground subsidence) and highlight the need for integrated resilience planning in line with the CER framework. Full article

The Sichuan Basin is a high-incidence area for China’s drought–flood abrupt alternation (DFAA) events. To reveal the spatiotemporal evolution characteristics and driving factors of drought–flood abrupt alternation (DFAA) compound disasters in the Sichuan Basin, this study identified drought-to-flood (DF) and flood-to-drought (FD) events using the Standardized Precipitation Evapotranspiration Index based on meteorological data and circulation factors from 1963 to 2022. By constructing a standardized drought–flood abrupt alternation magnitude index to classify event grades, combined with methods such as trend analysis, Morlet wavelet and Random Forest, the study explored the trend variation laws, spatial distribution patterns, and core driving factors of DFAA events in the basin. The results showed that on the interannual scale, the upward trend of FD events was more obvious than that of DF events, with a significant increase in the proportion of moderate and severe events; both the frequency and intensity of summer FD events increased significantly, and the intensity of winter FD events also exhibited a marked upward trend. Spatially, DF events occurred frequently in Guang’an and Chongqing, while FD events were concentrated in the western edge of the basin, as well as Yibin and Luzhou. Moderate and severe events were more prominent in the edge areas of the basin. The occurrence of DFAA events was generally jointly driven by the meteorological factors and regulation of large-scale sea surface temperature-circulation factors: the triggering factors of DF events showed a diversified and decentralized characteristic, while FD events were mainly driven by the subtropical high, and tropical sea surface temperature anomalies were the common precursor signal for both types of events. This study provides a scientific basis and technical support for the formulation of disaster prevention and mitigation strategies and the optimal management of water resources for compound extreme meteorological disasters in the Sichuan Basin. Full article

To improve the degradation rate of sulfamethoxazole (SMX) under hypoxic conditions in paddy fields during the flooding period, a laboratory microcosm experiment was established in this study to investigate the regulatory effect of straw return on the hypoxic degradation of SMX and its underlying microbial mechanisms. The results demonstrated that straw addition significantly promoted the hypoxic degradation of SMX. By the 10th day of the experiment, the residual SMX content in the straw-amended group was only 11.3% of that in the non-straw control group, and the average degradation rate throughout the experimental period was increased by 85.7%. Straw provided complex carbon sources, including organic carbon (e.g., starch, sugars, and humus) and cellulose, which not only reshaped the microbial community structure and created new ecological niches but also increased the microbial network density under SMX stress from 0.010 to 0.024. Acinetobacter, Bacillus, and Pseudomonas, which possess both straw decomposition and SMX degradation capabilities, sequentially became the dominant bacterial taxa. These dominant taxa can adapt to hypoxic fermentation in the flooded environment and co-metabolize SMX by activating the metabolic pathways of aromatic compounds and sugars. This study is expected to open up a novel approach for the remediation of SMX-contaminated flooded paddy fields and provide valuable innovative insights for technological breakthroughs and practical applications in related fields. Full article

Urban socio-economic resilience to climate change has emerged as a central research theme as cities increasingly confront interconnected environmental, economic, and social risks. Despite the rapidly expanding body of literature, the conceptual boundaries, thematic evolution, and analytical priorities of this field remain fragmented across disciplines, and no prior study has systematically mapped the socio-economic dimension of urban resilience through a combined bibliometric and thematic analysis over a multi-decadal horizon. This study addresses that gap by providing a systematic review of global research on urban socio-economic resilience to climate change, integrating bibliometric and thematic analyses of peer-reviewed publications from 1990 to 2025. Following the PRISMA 2020 guidelines, records were retrieved from the Web of Science Core Collection and subjected to a multi-stage screening procedure that combined automated relevance scoring with mandatory manual validation of the socio-economic dimension, resulting in a final dataset of 5076 publications. The analysis examines conceptual interpretations of socio-economic resilience, dominant climate hazards affecting urban systems, methodological approaches and assessment indicators, adaptation strategies and governance responses, and emerging research gaps. The results reveal a marked acceleration of scientific output after 2015, driven by the Paris Agreement and the IPCC Special Report on Global Warming of 1.5 °C (2018). The bibliometric network analyses identify adaptation, vulnerability, flooding, and sustainability transitions as the core thematic clusters. The findings trace a paradigmatic trajectory from equilibrist recovery frameworks toward transformative, socio-economically grounded resilience models and reveal persistent gaps in the operationalization of governance, equity measurement, and geographic representation. By synthesizing three-and-a-half decades of scholarship, this review clarifies the intellectual structure of the field and proposes four specific post-2026 research pathways that emphasize longitudinal cross-city comparisons, mixed-methods assessments, sector-specific compound hazard analyses, and governance mechanism studies. Full article

Extreme hydrometeorological events are occurring more often under climate change, increasing the risk for cities in coastal zones and lower river reaches. Such areas are prone to compound flooding (CF), where flood duration and magnitude are amplified by the combined effects of storm surges, onshore winds, long-term sea-level rise, and increasingly frequent rainfall-driven floods. This study assesses the socio-economic risk of residential neighbourhoods (RNs) along the lower reach of the Danė River in the city of Klaipėda, Lithuania, using a composite socio-economic risk index (CSERI) developed in this study under an extreme flood scenario, if the sea level in the south-eastern Baltic Sea rises by 1 m by the end of the century. The results show a strong relationship between water levels in the Klaipėda Strait and the lower reach of the Danė River, confirming a CF regime, where flood magnitude is driven by the interaction between strait water level and river discharge. The CSERI is based on five risk sub-indices (SIs): the building risk SI, road infrastructure risk SI, population risk SI, economic entities risk SI, and cultural heritage risk SI. The assessment identifies RNs at greatest risk under climate change and anthropogenic pressure and indicates priority areas for adaptation measures to reduce potential socio-economic losses. The proposed CSERI provides a practical decision-support tool for sustainable and climate-resilient urban development in coastal cities. Full article

The chemical agent injection modes and displacement characteristics of chemical compound flooding, consisting of a plugging agent, an oil displacement agent, and a viscosity reducer, were investigated by laboratory experiments for target heavy oil reservoirs after multiple cycles of huff-and-puff. The performances of the oil displacement agent, viscosity reducer and plugging agent were evaluated, and the formulation and concentration were optimized. The oil displacement effects and displacement characteristics of different injection modes were studied by sand-filled two-pipe models. The experiment results showed that alternating injections of the oil displacement agent and viscosity reducer yielded better results than their mixed injection, and small segments alternating injections achieved the highest recovery. The larger the dosage of the oil displacement agent, the larger the maximum liquid production ratio between the high- and low-permeability layers, but with the smaller the liquid production reverse duration. The larger the dosage of the viscosity reducer, the greater the water cut decrease but the smaller the maximum liquid production ratio. For chemical compound flooding in the Zhong’er block in the Gudao oilfield, the recommended injection mode was 0.1 PV plugging agent + 2000 mg/L of oil displacement agent + 0.5% viscosity reducer, with small segments of the oil displacement agent being followed by a viscosity reducer at an injection slug ratio of 6:4. However, the injection mode depends on the prices of oil and the chemical agent. When prices fluctuate, the chemical agent concentration should be adjusted accordingly. Full article

The northeast monsoon prevailing over southeastern China in late seasons, generally from October to March, frequently generates water level anomalies upstream of the Taiwan Strait (TWS) that reach the coastal waters of Guangdong in South China, and, with compounding astronomical high tides, elevate coastal flood risk over the region. The risk of coastal flooding or sea inundation is further heightened when monsoon forcing co-occurs with storm surge brought by late-season tropical cyclones (TCs). This study integrates tide gauge observations from Hong Kong (HK) and its vicinity together with Delft3D Flexible Mesh simulations to diagnose a tide-modulated anomaly wave mechanism. Observations show that anomalies originating in or near TWS arrive in HK with station-dependent phasing. These water level anomalies exhibit a characteristic ~6 h periodicity west of the Taiwan Shoal, and display peaks that systematically align with the astronomical high tide. Time–frequency analysis reveals a wave period transformation from ~12 h north of Dongshandao over the coast of southeastern China to ~6 h west of the Taiwan Shoal. We test the hypothesis that wind-forced water anomalies generated in or near TWS undergo shoal-modulated nonlinear tide–wind interaction and tidal-current advection that transform their dominant period and phase-lock them to the tide, producing four anomaly peaks per day downstream and station-dependent phasing in HK. Hindcasts of the November 2024 monsoon episode reproduce the observed timing, periodicity, and spatial transition, while constituent experiments demonstrate that semi-diurnal forcing entering via the TWS is the primary driver of the ~6 h signal, with the Taiwan Shoal acting as the modulation locus. Accurate water level forecasts for the Guangdong coast, therefore, need to incorporate upstream wind forcing over the TWS and bathymetric controls around the Taiwan Shoal, with practical implications for compound flood risk during spring tides and co-occurring monsoon and/or TC events. Full article

Hurricanes create compound hazards such as storm surge, flooding, and wind-driven debris that can degrade roadway capacity, fragment network connectivity, and hinder evacuation and shelter operations. From a sustainability perspective, improving evacuation planning is essential for reducing disaster-related losses, protecting vulnerable populations, and strengthening the resilience of coastal communities facing intensifying climate-driven hazards. This paper develops a micro-scale, agent-based evacuation modeling framework to assess evacuation performance under baseline and compound-hazard conditions, with emphasis on municipal decision support. The framework is demonstrated for Westbrook, Connecticut, at the census block-group scale in AnyLogic by integrating household locations, vehicle availability, road-network connectivity, and shelter capacities from publicly available datasets. Evacuation propensity and destination choice are parameterized using survey data, enabling empirically grounded decisions for in-town versus out-of-town evacuation among household-vehicle agents. Compound disruptions are represented through flood-related road closures derived from SLOSH storm-surge outputs and stochastic wind-related disruptions that dynamically constrain accessibility during the simulation. Scenarios are evaluated for Saffir–Simpson Category 1–2 and Category 3–4 hurricanes under baseline and compound conditions. Model outputs quantify normalized evacuation time, congestion and critical intersections, shelter demand and unmet capacity, evacuation failure, and spatial heterogeneity across block groups. Results indicate that compound flooding substantially increases evacuation times and failure rates, with the largest performance degradation concentrated in higher-vulnerability areas. Optimization experiments further compare the effectiveness of behavioral shifts, shelter-capacity expansion, and earlier departure timing in reducing delays and unmet shelter demand. Overall, the proposed framework provides transparent, reproducible, and scalable analytics that town engineers and emergency planners can use to evaluate evacuation readiness under compound hurricane impacts. Full article

The combined impacts of urban pluvial flooding and traffic congestion can severely delay emergency response. However, existing studies often focus on isolated scenarios, failing to systematically quantify the reduction in overall service capability and specific route disruptions to critical functional nodes under compound hazards. To address this problem, this study proposes a three-tier analytical framework to systematically evaluate the resilience of emergency services under compound hazards. The framework first utilizes spatial network analysis to simulate the overall spatial evolution of service capabilities for Emergency Medical Service (EMS) and Fire and Rescue Service (FRS) across various return periods and traffic conditions. It then delves into the emergency response coverage for vulnerable population places. Finally, the fastest-route analysis is employed to identify variations in rescue routing. The study reveals several critical insights. (1) As rainfall intensity and traffic congestion intensify, the coverage areas of EMS and FRS exhibit significant contraction and boundary erosion. Notably, the service areas of FRS show a distinct fragmentation pattern. (2) The protection levels for vulnerable population places (e.g., kindergartens, primary and secondary schools, and nursing homes) show a pronounced stepwise decline. Under extreme rainfall and the heaviest congestion, the 5 min coverage for these sites drops from 89.9% to 23.6% for EMS, and from 72.4% to only 15.1% for FRS, revealing a severe risk exposure for vulnerable groups. (3) Road inundation leads to a substantial extension of rescue routes and even results in the complete isolation of 141 primary and secondary schools. Overall, the framework provides actionable decision support to enhance urban emergency response under compound hazards. Full article

This study presents a two-dimensional hydraulic modelling framework for the simulation of flash and compound flooding in coastal urban areas with non-perennial river systems. The model employs a rain-on-grid approach within HEC-RAS v6.7 beta5 (2D solver) to simulate rainfall-driven runoff and explicitly incorporates coastal water-level forcing to represent storm tides. The framework is applied to an ungauged coastal basin in northern Greece using a 50-year return period design storm. Model results show good agreement with official Flood Risk Management Plan maps while identifying additional inundated areas linked to lower-order streams. Compound flooding simulations indicate a 21% increase in flooded areas, highlighting the importance of integrated modelling for operational flood forecasting. Full article

Drought–flood abrupt alternation (DFAA) events have emerged as a critical type of compound climate extreme under ongoing climate change, posing increasing risks to water resources and ecosystems in Southwest China. This study investigated the spatiotemporal evolution of DFAA events during the historical period (1995–2024) and the future period (2025–2064), as well as their relationships with evapotranspiration. Daily precipitation was simulated using a CMIP6 multi-model ensemble mean (MME) combined with Delta downscaling, while station observations were used to identify DFAA events and evapotranspiration. Model performance was evaluated using Taylor diagrams and simulation relative bias. The results showed that the downscaled MME substantially improved the simulation of precipitation, evapotranspiration, and cumulative DFAA event occurrences, with relative bias in most regions controlled within ±3%. Compared with the historical period, both drought-to-flood (DTF) and flood-to-drought (FTD) events showed overall increases during 2025–2064. Specifically, under the four SSP scenarios, DTF events increased by 165, 133, 180, and 140 occurrences, respectively, while FTD events increased by 130, 147, 114, and 79 occurrences, respectively. The regional mean trends of DTF events during the near-term period were −0.21, 0.16, −0.45, and 1.24 times·5a⁻¹, whereas the corresponding trends of FTD events were 1.82, 1.17, 0.05, and −1.03 times·5a⁻¹ under the four scenarios. Spatial analyses revealed pronounced regional heterogeneity, with enhanced signals mainly concentrated in eastern Sichuan, Chongqing, and parts of Guizhou. Lagged correlation analyses further indicated significant monthly lag effects between DFAA events and evapotranspiration during the flood season; DTF events generally showed positive correlations with subsequent evapotranspiration, whereas FTD events exhibited predominantly negative correlations. Overall, this study clarifies the future spatiotemporal evolution of DFAA events in Southwest China and highlights the important role of land–atmosphere hydrothermal processes in regulating compound drought–flood extremes. Full article

In 2024, an abrupt drought-to-flood transition (ADFT) event occurred in Henan Province, China, causing severe losses to agriculture and the economy. Predicting the spatiotemporal evolution of such compound extremes remains challenging at the subseasonal scale. This study employs soil moisture percentiles to identify local droughts and floods, connects them into coherent patches, and detects an ADFT event spatiotemporally. The proposed three-dimensional identification method is further applied to evaluate the ECMWF S2S reforecasts of the 2024 ADFT event. At a 1-week lead, the ECMWF ensemble mean successfully captures the transition. However, the spatial extent is underpredicted substantially at a 2-week lead. In terms of probabilistic forecast, the Brier skill scores for drought, transition, and flood stages are 0.38, 0.57, and 0.38 at a 1-week lead, respectively. However, these scores drop sharply at a 2-week lead, particularly for the transition and flood stages. The decreased forecast skill is jointly influenced by internal dynamical errors in the model and biases in the positions of the subtropical high- and low-pressure systems at long lead. This study assesses the capability of a numerical model to predict a compound extreme from both deterministic and probabilistic perspectives, and highlights the critical role of atmospheric circulation in achieving skillful prediction. Full article

Compound geological disaster chains pose major challenges for disaster prevention in mountainous regions due to their complex mechanisms and cascading impacts. This study investigates a landslide–debris flow–flash flood hazard chain that occurred on 21 July 2024 in the Xujia River catchment, Mianning County, Sichuan Province, China. This event is used as a representative case to improve the understanding of the formation and amplification mechanisms of breach-type debris flows through dynamic inversion constrained by sedimentary records. The objective is to reconstruct the evolution of the event and assess its downstream hazard extent. Post-disaster sedimentary and geomorphological records, including deposit distribution, channel aggradation, and flow traces, were systematically analyzed based on remote sensing interpretation, unmanned aerial vehicle surveys, and detailed field investigations. These sedimentary data were used as key constraints to estimate debris flow magnitude and mobility under different rainfall scenarios. A rainfall flood scenario-based estimation method was applied to quantify debris flow magnitude, and numerical simulations were conducted using the Rapid Mass Movement Simulation model to reproduce debris flow propagation and deposition processes. The results indicate that prolonged antecedent rainfall triggered slope failure in a tributary, leading to the accumulation of landslide-derived material and the formation of a temporary channel blockage. The subsequent breach of this blockage significantly amplified debris flow discharge, velocity, and sediment outflow, resulting in downstream hazard expansion. Simulation results constrained by sedimentary evidence show that peak discharge and solid material output under breach conditions were approximately three times higher than those of rainfall-driven scenarios under comparable rainfall frequencies. These findings demonstrate that sedimentary records provide critical constraints for the inversion of landslide debris flow disaster chain dynamics and highlight the effectiveness of post-disaster evidence based numerical assessment for hazard analysis and risk mitigation in debris flow-prone mountainous catchments. Full article

Precise modeling of narrow gorges is challenging due to extreme confinement, hindering visibility and accessibility. These environments often render Global Navigation Satellite Systems (GNSS)-based positioning unfeasible, a difficulty compounded by water and dense vegetation. Consequently, multi-technique data fusion is required. This study proposes a robust methodology to generate high-resolution 3D models of such complex environments by integrating multiple aerial (e.g., Unmanned Aerial Vehicles, UAVs) and terrestrial techniques. A multi-sensor approach combined UAV-Light Detection and Ranging (LiDAR) and UAV-photogrammetry for external areas with Terrestrial laser scanning (TLS), Mobile Mapping System (MMS), and Spherical Photogrammetry (SP) for the canyon floor. Furthermore, the representativeness of these 3D models was analyzed against standard Digital Terrain Models (DTMs) for determining water height levels during flood events. A one-dimensional hydraulic (1DH) model compared the 3D mesh approach with the traditional 2.5D perspective in a challenging, narrow canyon prone to flooding. Our results show that traditional 2.5D DTMs significantly over- or underestimate water levels in narrow sections—failing to account for overhangs and vertical wall irregularities—whereas high-resolution 3D meshes provide a more realistic representation of hydraulic behavior. This work demonstrates that multi-sensor data fusion is essential for accurate flood risk management and infrastructure planning in complex fluvial environments. Full article

Purple rice contains beneficial bioactive compounds, but the concentrations can be influenced by the growing conditions. This study investigated the interactive effects of water regime, biochar amendment, and nitrogen (N) sources on the yield and grain quality of purple rice. Purple rice grown under flooded conditions combined with biochar and urea or ammonium demonstrated significant increases in grain yield and yield components such as plant height, number of spikelets per panicle, and the percentage of filled grains compared to non-flooded conditions. Nitrate consistently resulted in the lowest yields and grain quality, especially under non-flooded conditions and with no added biochar. Grain anthocyanin concentration was highest under flooded conditions, with the maximum observed with biochar and nitrate application and with ammonium application without biochar. In contrast, the grain phenol content and antioxidant capacity were maximized by the biochar and water applications. The findings indicate that rice husk biochar can improve productivity without altering the color shade of purple rice. Combining flooding, biochar, and ammonium or urea improves the agronomic performance of purple rice, though the impact on nutritional qualities is more complex. Full article