Search Results (3,547)

Glacier mass loss driven by climate change has increased glacier-related hazards, including glacier debris flows, and poses growing threats to downstream communities. The Badswat Basin in northern Karakoram has experienced repeated glacier debris flows in recent years but lacks systematic disaster analysis and detailed monitoring. This study reconstructs and analyzes three glacier debris flows from 2015, 2018, and 2021 using multi-source remote sensing data and high-resolution DEMs. Results show that three events were triggered by tributary glaciers, with the 2015 event creating the initial dammed lake, and the 2018 and 2021 events further enlarging it (up to 0.72 km² and 40 million m³). These events transported glacier mass downstream, expanded alluvial fans, and caused net glacier erosion. The 2018 event was the most destructive, damaging 75 buildings, flooding 0.28 km² of farmland, and destroying 4.95 km of roads. Analysis suggests that topography influences environmental vulnerability and glacier stability. High temperatures, which accelerate glacier melting, are the primary drivers of the hazard. The bidirectional link between glacier movement and debris flows is a key factor in triggering or intensifying events. Under future climate scenarios, both tributary and main glaciers are expected to continue losing mass, further increasing downstream risks. This study details the evolutionary process of recurring periodic debris flows in the Badswat Basin, providing scientific insights into glacier–landform interactions and hazard management in high-mountain socio-ecological systems. Full article

Autophagy is an evolutionarily conserved cellular process that maintains homeostasis by degrading intracellular materials. Numerous studies have investigated the role of autophagy-related genes (ATGs) in plant adaptation to abiotic stresses. In plants, hypoxia (e.g., flooding events, oxygen supply during growth) rapidly activates the autophagy pathway as a protective mechanism for cell survival. Considering the moisture-loving yet waterlogging-sensitive nature of tea plants, this study explored the role of CsATG8f in the tea plant’s response to submergence. We found that overexpression of CsATG8f formed more autophagosomes than controls under submergence. Furthermore, CsATG8f was confirmed to physically interact with CsRAP2.12. Co-overexpression of both genes partially suppressed transcription of hypoxia-response genes while activating the antioxidant system, thereby enhancing tea plants’ resistance to submergence. Consistent with this, the opposite trend was observed in silenced plants, which attempted to mitigate stress damage by increasing GABA levels in vivo. In conclusion, our study reveals the crucial roles of CsATG8f and CsRAP2.12 in tea plant tolerance to submergence and provides new insights into potential regulatory networks governing tea plant adaptation to flooding. Full article

Against the backdrop of increasingly evident climate change and frequent extreme weather events, flash floods have emerged as a major challenge for flood disaster prevention and mitigation in China. Flash flood early warning systems are crucial means to address this challenge, primarily comprising rainfall-based warnings (RW) and discharge-based warnings (DW). To support precise flash flood warnings, this study compares the effectiveness of RW and DW and summarizes their applicable scenarios through both case study analysis and model simulations. The results demonstrate that DW outperforms RW under the following scenarios: ① During persistent moderate-intensity rainfall events when antecedent soil moisture is moderate to high, RW is prone to missed or delayed warnings. ② When rainfall exhibits significant spatial heterogeneity, RW tends to produce false alarms. Conversely, RW outperforms DW in the following scenarios: ① For localized short-duration heavy rainfall events, DW is prone to missed or delayed warnings. ② In basins where numerous small- and medium-sized reservoirs exist upstream without operational data, DW is prone to false alarms. ③ When sparse or unevenly distributed rain gauges result in poor representativeness of areal rainfall, DW is prone to missed warnings. To enhance flash flood disaster management, future warning systems should integrate both RW and DW approaches to deliver more timely, reliable, and scientifically grounded warning information for local authorities. Full article

In arid regions, rainfall is scarce, summer-concentrated, and prone to extreme events, while evaporation exceeds precipitation, creating fragile ecosystems that need scientific stormwater management for flood resilience. Sponge cities, through the implementation of green infrastructure, can alleviate urban flooding, improve rainwater utilization, and enhance the urban ecological environment. Under the “dual carbon” target, sponge city construction has gained new developmental significance. It must not only ensure core functions and minimize construction costs but also fully leverage its carbon reduction potential, thereby serving as a crucial pathway for promoting urban green and low-carbon development. Therefore, this study focused on Xining, a typical arid city in Northwest China, and couples the Non-dominated Sorting Genetic Algorithm-III (NSGA-III) with the Storm Water Management Model (SWMM) to construct a multi-objective optimization model for Low Impact Development (LID) facilities. The layout optimization design of LID facilities is conducted from three dimensions: life cycle cost (LCC), rainwater utilization rate (K), and carbon emission intensity (CI). Hydrological simulations and scheme optimizations were performed under different design rainfall events. Subsequently, the entropy-weighted TOPSIS method was utilized to evaluate and compare these optimized schemes. It is shown by the results that: (1) The optimized LID schemes achieved a K of 76.2–80.43%, an LCC of 2.413–3.019 billion yuan, and a CI of −2.8 to 0.19 kg/m²; (2) Compared with the no-LID scenario, the optimized scheme significantly enhanced hydrological regulation, flood mitigation, and pollutant removal. Under different rainfall return periods, the annual runoff control rate increased from 64.97% to 80.66–82.23%, with total runoff reduction rates reaching 46.41–49.26% and peak flow reductions of 45–47.62%. Under the rainfall event with a 10-year return period, the total number of waterlogging nodes decreased from 108 to 82, and the number of nodes with a ponding duration exceeding 1 h was reduced by 62.5%. The removal efficiency of total suspended solids (TSS) under the optimized scheme remained stable above 60%. The optimized scheme is highly adaptable to the rainwater management needs of arid areas by prioritizing “infiltration and retention”. Vegetative swales emerge as the primary facility due to their low cost and high carbon sink capacity. This study provides a feasible pathway and decision-making support for the low-carbon layout of LID facilities in arid regions. Full article

Understanding extreme precipitation (EP) evolution is crucial for global climate adaptation and hazardous disasters prevention. However, spatial non-stationarity of urbanization relationships with EP variations has been rarely discussed in a complex topographic context. Taking the city Liuzhou in China as the example, this study separately quantified the evolution of EP intensity, magnitude, duration, and frequency on different temporal scales with Innovative Trend Analysis (ITA). Based on a finer spatial (5 km grid) scale and multiple temporal (daily, daytime, nighttime, and 14 h) scale analyses, it innovatively identified spatially varying urbanization effects on EP with more details in different elevations. Our results indicate that: (1) from 2009 to 2023, EP events became more intense, persistent, and frequent, particularly for higher-grade EPs and in the steeper north of Liuzhou; (2) despite the globally negative correlations, spatial correlations between comprehensive urbanization (CUB) and each EP index on individual temporal scales were still explicitly categorized into four types using LISA maps—high-high, high-low, low-low, and low-high; (3) Geographically Weighted Regression (GWR) was demonstrated to precisely explain the response of most EP characteristics to multiple manifestation of urbanization with respect to population (POP), economy (GDP), and urban area (URP) expansion (adjusted R²: 0.5–0.8). The predictive accuracy of GWR on urbanization and EPs was spatially non-stationary and variable with temporal scales. The local influential strength and direction varied significantly with elevations. The most significant and positive influences of three urbanization predictors on EPs occurred at different elevation grades, respectively. Compared with POP and GDP, urban area percent (URP) was indicated to positively relate to EP changes in more areas of Liuzhou. The spatial and quantitative relationships between urbanization and EPs can help to guide effective urban planning and location-specific management of flood risks. Full article

Flash floods are among the most destructive hazards in northeastern Bangladesh, particularly in Sylhet district, where intense rainfall from the Meghalaya hills generates rapid inundation of low-lying areas. This study applies the Delft3D Flexible Mesh (FM) Suite to simulate flash flood inundation in the Surma River catchment and assess its potential for hazard mapping. Hydrological inputs were obtained from Bangladesh Water Development Board (BWDB) stations, combined with bathymetric surveys and a 10 m resolution DEM derived from remote sensing data. Model calibration and validation were performed using observed discharge and water level data at SW267 for the years 2019–2020 and verified for flood events in 2012, 2016, and 2017. The model achieved strong agreement with observed flows (R² > 0.9, NSE = 0.75–0.93), and the simulated inundation extent corresponded well with Sentinel-1A satellite-derived flood maps. Validation indicated that Delft3D FM can reasonably capture flash flood propagation and floodplain inundation patterns, including frequently affected areas, e.g., Sylhet Uposhohor. The results demonstrate the value of integrating hydrodynamic modeling with satellite-based validation for improved flood risk management. Findings highlight the potential of Delft3D FM to support early warning, urban planning, and disaster preparedness in flash flood-prone regions of Bangladesh. Full article

Urban catchments are increasingly vulnerable to hydrologic extremes driven by land-use change and climate variability, challenging the traditional assumption of stationarity. This study develops a computational framework to assess the nonstationary behavior of peak flow, volume, and duration in an urban catchment in the Philippines using 39 years of daily flow records (June 1984–November 2022). Missing observations (~8% of the series) were reconstructed using multiple linear regression (MLR) and artificial neural networks (ANNs) with four predictors: daily rainfall, antecedent rainfall, antecedent flow, and built-up area index. MLR with all predictors yielded the most accurate reconstructions. Nonstationarity was detected using the Mann–Kendall test, Sen slope estimator, Pettitt test, and variance change test. Flood events were extracted using block maxima (BM) and peak-over-threshold (POT) methods. BM-based results showed stationary peak flow and volume, while duration increased by 1.78 h/year. POT analyses revealed nonstationarity across all variables, without significant shifts in variance. These findings demonstrate that methodological choices strongly influence nonstationary detection. The framework underscores the importance of reliable data reconstruction and robust statistical testing for nonstationary analysis of flood events. POT-based approaches more effectively capture evolving trends in peak flow, volume, and duration. These can be used in designing resilient infrastructure and flood risk management in urbanizing catchments. Full article

Intensity–Frequency–Duration Curves (IDF curves) are a tool applied in hydraulic and hydrology engineering to design infrastructure for rainfall management. They express how precipitation, with a defined duration (D) and intensity (I), is frequent in a certain area. They are built from past recorded rainfall series, applying the extreme value statistics, and they are considered invariant in time. However, the current climate change projections are showing a detectable positive trend in temperatures, which, according to Clausius–Clapeyron, is expected to intensify extreme precipitation (higher temperatures bring more water vapour available for precipitation). According to the IPCC (Intergovernmental Panel on Climate Change) reports, rainfall events are projected to intensify their magnitude and frequency, becoming more extreme, especially across “climatic hot-spot” areas such as the Mediterranean basin. Therefore, a sensible modification of IDF curves is expected, posing some challenges for future hydraulic infrastructure design (i.e., sewage networks), which may experience damage and failure due to extreme intensification. In this paper, a methodology for reconstructing IDF curves by analysing the EURO-CORDEX climate model outputs is presented. The methodology consists of the analysis of climatic rainfall series (that cover a future period up to 2100) using GEV (Generalised Extreme Value) techniques. The future anomalies of rainfall height (H) and their return period (RP) have been evaluated and then compared to the currently adopted IDF curves. The study is applied in Lombardy (Italy), a region characterised by strong orographic precipitation gradients due to the influence of Alpine complex orography. The future anomalies of H evaluated in the study show an increase of 20–30 mm (2071–2100 ensemble median, RCP 8.5) in rainfall depth. Conversely, a significant reduction in the return period by 40–60% (i.e., the current 100-year event becomes a ≈40–60-year event by 2071–2100 under RCP 8.5) is reported, leading to an intensification of extreme events. The former have been considered to correct the currently adopted IDF curves, taking into account climate change drivers. A series of applications in the field of hydraulic infrastructure (a stormwater retention tank and a sewage pipe) have demonstrated how the influence of IDF curve modification may change their design. The latter have shown how future RP modification (i.e., reduction) of the design rainfall may lead to systematic under-design and increased flood risk if not addressed properly. Full article

A macrotidal estuary with mountain-stream inputs (MEMSs) is characterized by strong hydrodynamic forcing, high turbidity, and complex channel morphology. This study combines field measurements (2005–2020) with a 2D hydrodynamic–sediment model to examine estuarine turbidity maximum (ETM) dynamics, erosion–deposition patterns, and the effects of engineering interventions in the Jiaojiang Estuary (JJE). Results show that the coupled influence of upstream floods and downstream macrotides produces highly seasonal and spatially variable water–sediment processes: mountain-stream floods exhibit sharp hydrodynamic fluctuations, and the estuary displays pronounced tidal-wave deformation. Over the 15-year observation period, the riverbed experienced alternating erosion (up to −3.5 m) and deposition (up to +4.2 m), with net erosion of 0.5–1.2 m occurring in most Ling River sections during high-discharge years. The ETM migrated about 30 km during spring tides, with near-bed suspended sediment concentrations reaching 50–60 kg/m³. Human activities—particularly historical sand mining—modified channel geometry and sediment composition, intensifying the exchange between bed material and suspended sediment and facilitating the formation and migration of the ETM. Extreme events further enhanced geomorphic adjustment: the post-Lekima (2019) flood produced maximum scour of −5.8 m in the upper Ling River and deposition of +3.2 m in the Jiaojiang main channel within weeks. Channel curvature and junction morphology strongly controlled flood-level distribution. Model experiments indicate that lowering shoal elevations and widening the cross-section at key constrictions can effectively reduce flood levels. Collectively, these findings clarify the morphodynamic evolution mechanisms of a MEMS system and provide quantitative guidance for flood-mitigation and estuarine-management strategies. Full article

This study presents a framework for assessing the resilience of steel special moment-resisting frame (SMRF) buildings under sequential earthquake–flood hazards. Surrogate models, including a stacked attention-based LSTM network (Stack-AttenLSTM) and CatBoost, are developed to predict key engineering demand parameters (EDPs), particularly maximum inter-storey drift ratios (MIDRs), avoiding the need for computationally expensive nonlinear time history analysis (NLTHA). The predicted EDPs are integrated with the FEMA P-58 methodology to estimate repair costs and durations, while the REDi framework is used to capture recovery delays and functionality loss. A two-storey code-compliant SMRF building is evaluated under a design-basis earthquake (DBE) with and without a subsequent 4.0 m flood. Results show that the combined hazard nearly doubles repair costs (from 0.33 to 0.77 of replacement value), increases downtime from 194 to over 411 days, and reduces the resilience index (R_i) from 0.873 to 0.265. These findings highlight the severe impacts of cascading multi-hazard events and the need to extend performance-based design toward resilience-focused strategies. The proposed surrogate-based framework provides a practical tool for evaluating multi-hazard risks and guiding the design of more resilient structures. Full article

Torrential flows are hazardous hydro-geomorphological phenomena characterized by sudden water discharge and intense sediment transport. They occur in mountainous areas where hydrometeorological monitoring is often limited or absent. The lack of such data hinders the identification of flow types and sediment transport conditions, reducing the effectiveness of mitigation measures. To address this issue, the current study focuses on geomorphic characteristics of torrential watersheds and identifies indirect indicators of torrential activity. The sedimentological and geomorphic signatures of torrential flows in the lower Damdere River catchment (Eastern Rhodopes Mountains, southern Bulgaria) were characterized. To capture inter-annual variability in torrential activity and differences between the Damdere and its tributary the Duandere, we sampled riverbed deposits. We also sampled areas upstream and downstream of the check dam to assess its influence. Samples were analyzed for grain size distribution, petrography, and mineralogy (X-ray diffraction). Results show contrasting controls on sediment supply and transport: the Duandere delivers relatively coarse material, whereas the Damdere attains higher transport capacity during torrential events. The check dam is largely infilled and exerts only local effects by trapping finer sediments upstream. Downstream, the channel retains its torrential character. Inter-annual comparison upstream of the structure shows sediment fining linked to lower flows. Petrographic and XRD data point to mechanically driven erosion and rapid sediment transfer. The results underline the importance of geological–geomorphological indicators in the lack of long-term monitoring in similar mountain catchments and can support flood risk management. Full article

Wildfires are among the most severe disturbances in Mediterranean ecosystems, altering vegetation structure, soil properties, and hydrological functioning. Understanding post-fire hydrological dynamics is crucial for predicting flood and erosion risks and vegetation restoration in fire-prone regions. This study investigates the hydrological responses of Mediterranean watersheds following a wildfire event by integrating WiMMed (Watershed Integrated Management in Mediterranean Environments), a distributed, physically based hydrological model, with high-resolution vegetation data derived from LiDAR and Landsat imagery. A Priority Post-Fire Restoration Index (PPRI) was calculated as the weighted sum of the six parameters runoff (mm), flow accumulation (mm), distance to drainage network (m), slope (%), erodibility (K), lithology, and LiDAR index under a sediment reduction and runoff peak reduction scenario. The post-fire hydrological processes modeled with WiMMed described the dynamics of surface runoff and soil moisture redistribution across the upper soil layers after fire, and their gradual attenuation with vegetation regrowth. The spatial distribution of the PPRI identified specific zones within the burned watershed that require urgent restoration measures (10% and 4.55% under sediment reduction and peak reduction scenarios, respectively). The combined use of process-based modeling and remote sensing offers valuable insights into watershed-scale hydrological resilience and supports the design of post-fire restoration strategies in Mediterranean landscapes. Full article

Urban floods are becoming increasingly frequent and severe, highlighting the need for real-time information that supports safe evacuation decision-making. This study proposes and validates an unmanned aerial vehicle (UAV)-based methodology for real-time urban flood monitoring using an actual flood event caused by Typhoon Hinnamnor at the Seondeok Intersection in Gyeongju, Republic of Korea. The method comprises three simple steps: (1) collecting UAV images and data; (2) generating spatial and terrain information through photogrammetry; and (3) estimating flood extent, depth, and volume using GIS-based analysis. A total of 796 UAV images were processed, yielding a flooded area of 3847.36 m², a flood volume of 13,895.13 m³, and a maximum depth of 0.75 m. To assess performance, UAV-derived results were compared with XP-SWMM simulation outputs. Significant discrepancies were observed in flood extent, inundation volume, and flood persistence, indicating that hydrological models may not fully capture localized drainage failures or site-specific conditions in urban environments. These findings demonstrate that UAV-based monitoring provides a more accurate representation of actual flood and can supply high-resolution, rapidly obtainable information essential for real-time evacuation. This study provides empirical evidence of UAV applicability during the flood event itself and highlights its potential to enhance disaster-response capability, improve decision-making, and strengthen the resilience and sustainability of flood-prone urban areas. Full article

Against the backdrop of rapid urbanization and an increase in extreme rainfall, the impermeable expansion caused by land use changes is significantly altering the urban property convergence process and intensifying the risk of waterlogging. To reveal the impact of land use change on the urban flooding processes, this study takes the main urban area of Wuhan (MUAW) as an example. Based on land use data from 2006 and 2020, it designs rainfall events with return periods of 5, 50, and 100 years. The NewFlood two-dimensional hydrodynamic model is employed to simulate flood evolution, with results validated against flood-prone locations. Flow velocity changes at typical flood-prone points are grouped and statistically analyzed according to land use conversion types. The results showed the following: (1) Between 2006 and 2020, land use transfer in MUAW is primarily influenced by urban sprawl and cropland reduction. (2) Urban expansion led to an increase in the area and depth of rainwater accumulation during rainstorms, which was highly aligned with the direction of urban sprawl, thereby increasing the risk of urban flooding during rainstorms. (3) Land use transfer has a limited impact on the maximum water depth and flow direction in MUAW. However, it can increase peak flow velocity or shift the peak time earlier, reducing the city’s available emergency response time and increasing the difficulty of emergency response. The contribution of this paper lies in quantifying the waterlogging effect of land use change from dynamic dimensions such as “flow velocity—peak occurrence time”, providing process evidence for the assessment of urban early warning advance, the allocation of drainage capacity and land use control, and offering a reference for prioritizing the layout of nature-based solutions and green infrastructure in low-lying catchment areas and key catchment channels to reduce flood risks. Full article

Floods rank among the most destructive natural hazards worldwide. In Canada’s capital region—Ottawa and its surrounding areas—flood prediction is crucial, especially in flood-prone zones, to improve flood mitigation strategies, given its historical record-breaking events in 2017 and 2019, which resulted in substantial damage to homes and infrastructure in the region. Previous studies in these regions typically did not use remote sensing techniques or advanced methods to enhance flood susceptibility prediction and extent mapping. This study addressed the gap by incorporating 18 flood conditioning factors and integrating high-performance machine learning algorithms such as Random Forest, Support Vector Machines and XGBoost to develop ensemble flood susceptibility models. The HEC-RAS 2D model was used to simulate hydrodynamic variables based on a 100-year flood scenario. The developed ensemble model for flood susceptibility prediction achieved strong performance (Kappa, F1-score, and AUC all above 0.979) and demonstrated model transferability, maintaining high accuracy (Kappa > 0.850, F1-score > 0.920, AUC > 0.990) when applied to other sub-regions. The hydraulic model reveals that flood velocity and depth differ across sub-regions, reaching maximums of 15 m/s and 15 m, respectively. SHAP analysis indicates Elevation, Handmodel, MNDWI, NDWI, and Aspect are key factors influencing floods. These findings and methods help Natural Resources Canada develop tools and policies for effective flood risk reduction in the Ottawa River watershed and similar regions. Full article