Search Results (316)

The rising global temperature and changing climate patterns have increased the frequency and intensity of extreme heat events, droughts, and heavy precipitation, significantly affecting agriculture, water resources, and ecosystems. Solar radiation management (SRM) has been proposed as a geoengineering strategy to mitigate these effects by reducing incoming solar radiation. This study evaluated future trends and variability in rainfall and temperature extremes in the Philippines under GeoMIP (G6Solar and G6Sulfur) and ScenarioMIP (SSP2-4.5 and SSP5-8.5) projections. Using five General Circulation Models (GCMs) and a suite of 10 climate indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI), changes in extreme precipitation and temperature across different climate zones in the Philippines were assessed. Climate projections for the future (2041–2070) scenario were analyzed using bias correction, downscaling, and spatial interpolation techniques. Trend analysis was evaluated using the Mann–Kendall test and Sen’s slope estimator, while variability was assessed through statistical methods. The results show widespread warming and increased extreme precipitation, but these trends vary significantly across regions. Non-uniform responses emerge across scenarios, with some northern regions experiencing decreases in specific precipitation indices despite the broader warming trend under SRM and non-SRM conditions. These findings provide critical insights into the potential impacts of SRM on future climate extremes in the Philippines and guidance on climate policy recommendations for decision-makers and stakeholders. Full article

Urban transportation systems face increasing sustainability and resilience challenges due to the growing frequency and intensity of weather extremes. Weather-related congestion may increase travel delays, fuel consumption, and unequal economic costs, thereby undermining urban sustainability. Although previous studies have examined the relationship between weather conditions and traffic congestion, limited attention has been paid to whether street-network design can enhance transportation resilience under extreme weather conditions. This study investigates the relationships among extreme weather, traffic congestion, and street density using daily congestion and meteorological data from 35 major Chinese cities between 2018 and 2024. Fixed-effects regressions estimate the associations between multiple weather extremes and congestion and examine the moderating role of street density. Heavy rainfall, extreme cold, and low visibility are associated with increased congestion, whereas extreme heat is associated with reduced congestion. Street density could buffer congestion under extreme cold and heavy snow cover, suggesting that denser networks may improve resilience to localized road-surface disruptions. Heterogeneity analyses reveal weaker weather-related congestion responses in megacities and clustered cities, and during the COVID-19 period. These findings highlight the potential role of street-network design in supporting sustainable and climate-resilient transportation by reducing vulnerability to weather-related congestion. Full article

Rain gardens are widely used for stormwater treatment; however, the performance of alternative sorbent materials under varying rainfall conditions remains insufficiently understood. In this study, the removal of nutrients and heavy metals was evaluated in laboratory-scale rain gardens amended with halloysite of two grain size fractions (1–2 mm and 2–4 mm) under rainfall events lasting 30 and 120 min. Three column systems were tested: a reference column containing dolomite, sand, and gravel (C1), and two halloysite-amended columns (C2 and C3). Synthetic stormwater containing N–NH₄⁺, N–NO₃^–, P–PO₄^3–, Cu, Zn, and Pb was applied. Halloysite improved nutrient removal in all rainfall scenarios compared with the reference column. Dissolved inorganic nitrogen (DIN) removal reached 84% in column C3, whereas soluble reactive phosphorus (SRP) removal reached 85% in column C2. Complete removal of Cu, Zn, and Pb was observed in all columns, highlighting the dominant role of dolomite in heavy metal retention. These findings demonstrate the potential of halloysite as a nutrient-removing amendment in rain garden. Full article

This study evaluated the effects of placing wood chips (F-Wood chip) or pumice (F-Pumice) at the bottom of poultry feather compost on open-field ginger soilless media production. Root control bags were prepared with 10 L of wood chips or pumice overlain by 20 L of feather compost, with three ginger rhizomes planted. Crops were drip-irrigated without synthetic fertilization and replenished with compost three times. Results indicated that bottom-placed wood chips or pumice improved water infiltration. Ginger yield was significantly higher in the F-Wood chip treatment than in the F-Pumice, with fresh weights of 3.4 and 2.5 kg, and dry weights of 451.8 and 332.7 g, respectively. Furthermore, F-Wood chip significantly increased rhizome calcium levels. Although no significant differences were observed between treatments regarding leaf and post-harvest media nutrient contents, the F-Wood chip group exhibited higher microbial abundance (9.5 ± 4.5 × 10⁵ CFU ⁻¹) and greater endophytic diversity, spanning 7 genera and 11 species with potential plant growth-promoting and stress-resistance functions. Overall, this innovative integrated crop management strategy demonstrates great potential to substitute for fossil-fuel-based chemical fertilizers, this innovative production mode eliminates the need for fossil-fuel-based chemical fertilizers, offering an applicable and sustainable soilless cultivation solution for open-field ginger production under extreme weather conditions like typhoons and heavy rainfall. Full article

Quarry waste piles are heterogeneous engineered embankments that are susceptible to slope instability, yet early detection of pre-failure surface changes remains challenging due to complex surface conditions and measurement uncertainty. This study presents an integrated remote sensing-based framework for monitoring quarry waste pile instability by combining multi-temporal change detection with scale-dependent surface roughness analysis. The original contribution of the proposed framework lies in linking displacement-based change detection with multi-scale characterization of surface roughness, enabling both observed surface movement and topographical conditions associated with developing instability to be evaluated within a unified monitoring approach. Multi-epoch Unmanned Aerial Vehicle (UAV)-mounted Light Detection and Ranging (LiDAR) and photogrammetric point clouds were acquired before and after documented failure events at an active quarry site at active quarry sites located northeast of Montreal, Quebec, Canada. The regional climatic conditions, characterized by seasonal freeze–thaw cycles, rapid snowmelt, and periods of heavy rainfall, can promote water infiltration and elevated pore-water pressures, thereby increasing the susceptibility of these heterogeneous waste piles to slope instability. A standardized workflow was implemented, including precision alignment using a Recursive Iterative Closest Point (R-ICP) registration strategy, vegetation filtering with a multiscale CANUPO classifier, and uncertainty quantification through a Level of Detection (LoD) analysis. The resulting LoD thresholds were 10–15 cm for LiDAR-to-LiDAR comparisons and 34–36 cm for mixed-sensor datasets. Multi-scale roughness analysis revealed that zones which later experienced instability exhibited consistently higher and more heterogeneous roughness than adjacent stable areas within a well-defined linear scale range. A roughness-based A/D indicator enabled objective delineation of hazardous zones prior to failure. Post-failure monitoring showed surface smoothing following major displacement, followed by renewed roughness increases associated with secondary movements. These results demonstrate that scale-dependent roughness provides complementary information to displacement-based change detection, enabling potentially unstable areas to be identified and prioritized before substantial displacement becomes evident. The integrated framework can assist quarry managers in targeting field inspections and monitoring efforts toward higher-risk areas and support earlier preventive actions to reduce slope-failure risk. Full article

Although metal-modified biochar demonstrates high efficacy for phosphorus (P) removal in aqueous systems, its soil-scale mechanisms and ecological consequences under extreme rainfall remain largely unknown. In this study, we investigated how iron-modified biochar (BC+Fe) regulates P leaching and soil microbial communities in acidic soils using adsorption assays and column leaching experiments under simulated prolonged heavy rainfall. Mechanistically, BC+Fe exhibited adsorption kinetics that were better described by the pseudo-second-order model, consistent with a chemisorption-dominated P retention mechanism. Across six consecutive leaching events, BC+Fe significantly increased soil pH from 4.1 to 4.5 and reduced cumulative P loss by 37.7% compared to unmodified biochar (BC), with the most pronounced mitigation occurring during the initial leaching events when P losses were greatest. After leaching, soil total and available P concentrations under BC+Fe were approximately 3.4- and 3.7-fold higher, respectively, than under BC. Crucially, while both biochar types shifted bacterial community composition, BC+Fe maintained bacterial Shannon diversity and network complexity at levels comparable to the unamended soil and significantly higher than those under BC. Further analysis revealed that P leaching loss and soil pH were the primary environmental drivers shaping these microbial responses, and specifically, severe P loss was directly associated with simplified network complexity and intensified microbial competition (reflected by increased negative cohesion). Functional profiles inferred using Tax4Fun2 further showed that BC+Fe supported higher predicted microbial functional redundancy than both BC and the unamended control. Collectively, these findings demonstrate that iron-modified biochar mitigates P leaching through robust chemisorption and pH stabilization, while concurrently safeguarding microbial network complexity and functional redundancy. This dual benefit highlights the potential of iron-modified biochar as a sustainable amendment for maintaining soil ecosystem buffering capacity against severe hydrological stress. Full article

In order to mitigate the negative effects of heavy rainfall events, natural water retention measures (NWRM)—such as hedges, erosion control strips, vegetated drainage channels, wooded strips, retention basins and ditch pockets—have gained renewed attention as an effective climate adaptation strategy. To identify potential areas for NWRM, this study applied and methodologically expanded an existing approach for identifying dominant runoff processes (DRPs) to an agricultural sub-catchment in the Weserbergland region of Germany. The DRP were determined using a Geographic Information System (GIS) and validated through field surveys. Potential areas for water retention within the same runoff process classes were identified for three defined objectives: improving infiltration, extending flow paths, and redirecting runoff to surrounding areas. Spatial differentiation was achieved using accumulated catchment area and overland flow distance. The watershed is predominantly characterized by surface runoff (Hortonian Overland Flow). Field validation confirmed the DRP classification for around two-thirds of the study area, with deviations occurring predominantly on arable land. Supplementing the DRP approach with a topographic analysis allowed for further differentiation, focusing on small, topographically defined sub-watersheds. The identified areas offer significant potential for interventions. Combined with supplementary data, analyses of the water network and the involvement of local stakeholders, the resulting potential map provides a solid basis for planning smaller-scale water retention measures. Full article

Polar-orbiting microwave radiometers provide indispensable all-weather measurements of the atmospheric state, yet revisit intervals of many hours leave critical gaps during rapidly evolving weather events. To address this limitation, we developed MIDAS (Microwave Inference via Diffusion Across Satellites), a probabilistic framework that estimates microwave brightness temperature (BT) fields across the geostationary full-disk domain from infrared observations at 10 min intervals. This study focuses on the five Microwave Humidity Sounder-2 (MWHS-2) humidity-sounding channels near 183 GHz, which provide vertically resolved water vapor information. MIDAS achieves relative errors below 0.5% for the majority of cases, with a channel-averaged mean absolute error of 1.15 K, outperforming a deterministic U-Net baseline (1.43 K). Beyond per-sample evaluation, MIDAS reproduces large-scale climatological patterns across the full-disk domain over a three-month summer period, consistent with Radiative Transfer for TOVS–Scattering (RTTOV-SCATT) simulations. In deep convective scenes where reconstruction is most difficult, the ensemble spread naturally tracks reconstruction difficulty, providing a built-in indicator of prediction confidence. Notably, MIDAS incorporates real-time polar-orbiting observations as physical constraints via a merge-sampling mechanism, reducing ensemble RMSE by over 20% and improving probabilistic calibration by more than 30%. Proof-of-concept assimilation experiments for two high-impact weather cases show that MIDAS-generated fields yield forecast improvements comparable to those from real satellite observations, reducing tropical cyclone track errors from approximately 110 km to 40 km and improving heavy precipitation forecasts at extreme rainfall thresholds where direct infrared assimilation shows no benefit. Overall, our framework demonstrates the potential of generative models to supplement sparse observational coverage and provide physically plausible microwave humidity fields for downstream applications. Full article

This study investigated short-duration heavy-rainfall events in Sichuan during 2023–2025. A 35 km × 35 km cloud window centered on heavy-rainfall stations was constructed. Multiple cloud parameters in the window were statistically analyzed to examine their responses to heavy rainfall under different rainfall-intensity classes. Representative cases were also examined. The results showed that: (1) Eight major cloud parameters, including minimum cloud-top brightness temperature and deep convection index, showed clear responses to heavy rainfall in both rainfall-intensity classes. (2) Heavy-rainfall locations were mainly found in large-gradient zones near the edges of low cloud-top brightness temperature regions (<220 K) and high cloud-top height regions (>12 km). Cloud-parameter extrema generally appeared before the end of peak rainfall. Samples with rainfall intensity > 50 mm·h⁻¹ were mainly associated with ice-phase cold cloud-tops. These cloud-tops had brightness temperatures below 200 K, heights above 15 km, and pressures below 100 hPa, indicating stronger convective activity. In contrast, the 20–50 mm·h⁻¹ samples showed relatively weaker convective activity. (3) When cloud-top brightness temperature < 220 K, deep convection index ≥ 40, cloud-top height ≥ 15 km, DTB13 ≤ −1 K, and cloud-top pressure ≤ 130 hPa occurred simultaneously or successively, the cloud window indicated potential for short-duration heavy rainfall. Full article

Climate-induced natural hazards can result in disruptions and failures of railway routes which are associated with high economic costs. Hence, the mechanisms of climate impacts posing a threat to rail transport must be identified, analysed and localised in railway networks. This study aims at assessing heavy rainfall hazards on the railway network of the federal state Nordrhein-Westfalen (NRW) in Germany and presents a GIS-based flooding indicator. A rule-based classification and aggregation approach with a hazard matrix was developed using potential flooding depths and flow velocities, resulting in five hazard classes. The approach was applied to the railway network in NRW for two heavy rainfall scenarios (N₁₀₀, N_ext). The results show that the clear majority of route kilometres are classified as at least moderate hazard in both precipitation scenarios considered (N_ext 81%, N₁₀₀ 72%). On railway routes in low mountain range regions, more sections are assigned higher hazard classes than in flat landscapes. The plausibility of the indicator was explored through scenario, structural and conceptual parameter analyses, which support robustness of the results. The maps can serve as a tool for making qualitative statements on the potential impact on the German railway network and localising these impacts spatially. Full article

Large-scale urbanization in China has altered land surface characteristics, affected climate and hydrological cycles, and changed the spatial and temporal distribution of precipitation. The combined effects of global warming and the urban heat island effect have further intensified changes in urban rainfall patterns. Therefore, it is essential to clarify the spatiotemporal evolution of precipitation under China’s rapid urbanization process in order to reduce multiple disaster risks. To achieve this, historical precipitation data and multisource remote sensing imagery were integrated to construct a spatiotemporal coupling model for analyzing the relationship between urbanization patterns and precipitation distribution in China. In addition, combined with the background of global climate change, the spatiotemporal evolution characteristics of annual, monthly, and seasonal precipitation were investigated. The main conclusions are as follows: (1) China still has great potential for urbanization and economic development and is currently in a new stage of rapid growth; (2) During 1992–2020, the national area proportion receiving annual precipitation of (200, 400] mm decreased by approximately 0.12 percentage points per year, whereas the area proportion receiving (400, 800] mm increased by approximately 0.11 percentage points per year, indicating a measurable shift toward wetter precipitation conditions; (3) Heavy rainfall events in China are expected to increase in the future, mainly occurring from June to August, with a maximum monthly precipitation reaching 1137.9 mm; (4) Urbanization may be one of the important factors associated with precipitation changes in China, with 2008 identified as a key turning point, when the urbanization rate approached 50% and began to exhibit a preliminary scale effect. Full article

Quantifying the impact of land use changes on the threat of flash-floods is a critical consideration in flood hazard planning and risk reduction, and is an area of active research. Here, a coupled Weather Research and Forecasting model hydrological extension package (i.e., WRF-Hydro) modeling approach is applied to simulate flash-flooding processes for short-duration, localized, intense precipitation events. To better understand the effect of urbanization on flash floods, a series of numerical experiments is performed surrounding Ellicott City, Maryland, a location which has experienced both significant heavy rainfall events and suburban development over the past several decades. Two intense rainfall events occurring on 30 July 2016 and 27 May 2018 are investigated, respectively, to first calibrate the hydrologic model performance and then quantify the sensitivity of flash flooding to varying degrees of urbanization. Performing the same experiments using observed historical land use states is of more limited insight, as the thrust of suburban development in the Ellicott City region significantly predates satellite-derived land use datasets. Results confirm that urbanization produces larger river streamflow, higher water stages, faster hydrologic responses to achieve peak flow discharge, and shorter recession limbs, even for very intense, short-duration events. The collective findings suggest that WRF-Hydro is applicable for both watershed flash flood prediction and hypothesis testing, and demonstrates potential utility to urban development decision-makers in locations such as Ellicott City, which could face future increases in catastrophic flooding. Full article

Urban separate sewer systems face significant challenges from rainfall-derived infiltration and inflow (RDII) during the wet season. To achieve the integrated optimization of operational safety, energy consumption, and carbon emissions, this study proposes a dynamic optimal control method. A real-time regulation framework was developed by coupling a Storm Water Management Model (SWMM) hydraulic model with a Non-dominated Sorting Genetic Algorithm II (NSGA-II) multi-objective optimization algorithm within a Model Predictive Control (MPC) structure. Based on real-time water level risks, the framework adaptively adjusts the priority among three objectives: overflow reduction, pumping station energy consumption, and methane emission potential. Using a real separate sewer network in CZ city as a case study, the method was evaluated under light, moderate, and heavy rainfall scenarios. Results show that, compared with traditional rule-based control (RBC) and fixed-weight static model predictive control (SMPC), the proposed dynamic model predictive control (DMPC) strategy reduces overflow by 37.2% during heavy rain, and achieves 16.5% energy savings and a 15.8% reduction in methane emission potential during light rain. The strategy also balances network storage utilization, mitigates local overload, and demonstrates enhanced robustness to rainfall forecast errors, providing an effective technical solution for safe, energy-efficient, and low-carbon urban drainage operation. Full article

Membrane roofs with saddle geometry are widely used in stadiums and public facilities that are highly exposed to rainfall. However, current design practice typically considers rainfall only in terms of seepage effects, drainage requirements, or static stability checks, while the influence of extreme rainfall on dynamic behavior and prestress loss has not been comprehensively quantified. In this study, the behavior of a restored engineering-scale saddle-shaped membrane roof under three representative rainfall intensities (50, 300, and 550 mm/h) is investigated through combined laboratory experiments (span L = 2.52 m) and numerical simulations, with particular emphasis on how supporting conditions and pretension levels affect vertical displacement, vibration propagation, and rainfall-induced edge-cable pretension loss. The findings are intended to reveal response mechanisms and trends, while quantitative extrapolation to full-size roofs should be conducted with scaling considerations. The numerical model is validated against the experimental results through comparisons of cable forces and vertical displacements. The results indicate that while the maximum vertical displacement induced by heavy rainfall is small (millimeter-level) and does not cause immediate failure, the rainfall event induces a significant permanent loss of pretension (a maximum observed relaxation of 10.4% in the edge cables for the tested specimen) in the edge cables. This relaxation degrades the structural stiffness, potentially compromising aerodynamic stability under subsequent wind events. Consequently, for the tested configuration, post-rainfall pretension inspection is recommended for events exceeding 300 mm/h, with retensioning suggested if significant tension loss is detected. This recommendation should be interpreted as an indicative engineering reference for the present specimen rather than a universal criterion for all saddle membrane roofs. Full article

The goatpox virus (GPV) is a highly contagious pathogen primarily affecting domestic small ruminants in endemic regions of Northern Africa, the Middle East, and Asia. This study reports the first confirmed outbreak of GPV in captive wild ruminants in the United Arab Emirates (UAE). The outbreak occurred in a fenced 900-hectare mountainous reserve following a period of heavy rainfall, and Barbary sheep (Ammotragus lervia), Nubian ibex (Capra nubiana), Arabian oryx (Oryx leucoryx), and Scimitar oryx (Oryx dammah) were affected. Clinical signs included generalized cutaneous nodules, mucopurulent nasal discharge, respiratory distress, weakness, and emaciation. Over a three-month period, 71 animals died or were euthanized. Histopathological findings were consistent with GPV infection in goats, although typical inclusion bodies were missing. Real-time PCR confirmed GPV DNA in multiple tissues with a high viral genome load. Virus isolation was successful only in lamb testis cells. Whole-genome sequencing demonstrated that the isolates were genetically identical and clustered within the Central and Western Asia lineage, showing closest similarity to a Turkish field strain. The finding highlights the potential for cross-species transmission of GPV into wildlife and emphasizes the importance of surveillance, as well as molecular diagnostic and preventative vaccination strategies at the wildlife–livestock interface. Full article