Search Results (788)

Understanding the long-term impact of agricultural practices on soil parameters is essential for improving soil quality and sustainability. Soil Organic Carbon (SOC) and total Nitrogen (N) are key indicators due to their influence on crop productivity, nutrient cycling, and microbial activity. This study assesses the effects of tillage intensity (inversion vs. non-inversion) and organic amendments (manure vs. no manure) on SOC and total N dynamics in Mediterranean rain-fed arable systems. Data were collected over a ten-year field trial (2011–2020) in Catalonia, under cereal–legume rotation and organic management, focusing on two soil depths (0–10 and 10–20 cm). Fertilization was the main driver of SOC and N changes. Non-inversion tillage promoted topsoil accumulation and microbial colonization, especially during the first period (2011–2015). The combination of manure and reduced tillage led to faster and greater SOC increases. Moreover, initial SOC levels were negatively related to SOC changes in the topsoil. These results revealed the combination of manure and non-inversion tillage as the more suitable management practice to preserve soil quality in organic arable rain-fed systems, emphasizing the importance of understanding the impact of agricultural management in the long-term under Mediterranean conditions. Full article

Satellite Precipitation Products (SPPs) play a crucial role in hydrological modeling, particularly in data-scarce and climate-sensitive basins such as the Magat River Basin (MRB), Philippines—one of Southeast Asia’s most typhoon-prone and infrastructure-critical watersheds. This study presents the first full-cycle evaluation of nine widely used multi-source precipitation products (2000–2024), integrating raw validation against rain gauge observations, bias correction using quantile mapping, and post-correction re-ranking through an Entropy Weight Method–TOPSIS multi-criteria decision analysis (MCDA). Before correction, SM2RAIN-ASCAT demonstrated the strongest statistical performance, while CHIRPS and ClimGridPh-RR exhibited robust detection skills and spatial consistency. Following bias correction, substantial improvements were observed across all products, with CHIRPS markedly reducing systematic errors and ClimGridPh-RR showing enhanced correlation and volume reliability. Biases were decreased significantly, highlighting the effectiveness of quantile mapping in improving both seasonal and annual precipitation estimates. Beyond conventional validation, this framework explicitly aligns SPP evaluation with four critical hydrological applications: flood detection, drought monitoring, sediment yield modeling, and water balance estimation. The analysis revealed that SM2RAIN-ASCAT is most suitable for monitoring seasonal drought and dry periods, CHIRPS excels in detecting high-intensity and erosive rainfall events, and ClimGridPh-RR offers the most consistent long-term volume-based estimates. By integrating validation, correction, and application-specific ranking, this study provides a replicable blueprint for operational SPP assessment in monsoon-dominated, data-limited basins. The findings underscore the importance of tailoring product selection to hydrological purposes, supporting improved flood early warning, drought preparedness, sediment management, and water resources governance under intensifying climatic extremes. Full article

Rainfalls are the result of complex cloud microphysical processes. Trying to estimate their intensity and duration is a key task necessary for assessing precipitation magnitude. Across mountains, extreme rainfalls may cause several side effects on the ground, triggering severe geo-hydrological issues (floods and landslides) which impact people, human activities, buildings, and infrastructure. Therefore, having a tool able to reconstruct rainfall processes easily and understandably is advisable for non-expert stakeholders and researchers who deal with rainfall management. In this work, an evolution of the LUME (Linear Upslope Model Experiment), designed to simplify the study of the rainfall process, is presented. The main novelties of the new version, called LUME 2D, regard (1) the 2D domain extension, (2) the inclusion of warm-rain and cold-rain bulk-microphysical schemes (with snow and hail categories), and (3) the simulation of convective precipitations. The model was completely rewritten using Python (version 3.11) and was tested on a heavy rainfall event that occurred in Piedmont in April 2025. Using a 2D spatial and temporal interpolation of the radiosonde data, the model was able to reconstruct a realistic rainfall field of the event, reproducing rather accurately the rainfall intensity pattern. Applying the cold microphysics schemes, the snow and hail amounts were evaluated, while the rainfall intensity amplification due to the moist convection activation was detected within the results. The LUME 2D model has revealed itself to be an easy tool for carrying out further studies on intense rainfall events, improving understanding and highlighting their peculiarity in a straightforward way suitable for non-expert users. Full article

Erosion monitoring was carried out between 2003 and 2022 using a hydrological station with a Thomson overflow, a water gauge, and a limnigraph installed at the outlet of the Kolonia Celejów gully system. The study area is located in the north-western part of the Lublin Upland in the Nałęczów Plateau mesoregion (SE Poland). The total amount and intensity of precipitation were measured using an automatic station and water runoff and suspended sediment yield (SST) were also continuously measured. High variability in water runoff was observed during this period (max. of about 76,000 m³ and mean > 26,000 m³), and as a result of numerous heavy rains, a significant increase in SST (max. of about 95 Mg to about 1200 Mg and mean of 24 Mg to about 215 Mg) was noted in the second half of the measurement period. Most of the material removed at that time came from the cutting of the gully bottom and from the redeposition of material transported from the catchment used for agricultural purposes. In order to determine the volume of material delivered to the slope–gully cascade system in November 2012, a second station was installed at the gully head, which only operated until June 2013. However, the measurements covered all snowmelts and summer runoffs, as well as the June downpours. At the same time, these measurements represent the first unique attempt to quantify the delivery of material from the slope subcatchment to the gully system. The year 2013 was also important in terms of water runoff from the loess gully catchment area (about 40,000 m³) and was a record year (SST > 1197 Mg) for the total amount of suspended material runoff (7.6% and 33.5% of the 20-year total, respectively). During the cool half of the year, 16,490 m³ of water (i.e., 42% of the annual total) flowed out of the gully catchment area, and during the warm half of the year, 23,742 m³ of water (59% of the annual total) flowed out. In contrast, 24,076.7 m³ of water flowed out of the slope subcatchment area during the year, with slightly more flowing out in the cool half of the year (12,395.9 m³ or 51.5% of the annual total). In the slope and gully subcatchment areas, the suspended sediment discharge clearly dominated in the warm half of the year (98% and 97%). The record-breaking SST amount in June was over 1100 Mg of suspended sediment, which accounted for 93% of the annual SST from the gully catchment area and over 94% in the case of the slope subcatchment area. The relationships in the slope–gully cascade system in 2013 were considered representative of the entire measurement series, which were used to determine the degree of connectivity between the slope and gully subsystems. During summer downpours, the delivery of slope material from agricultural fields accounted for approx. 15% of the material removed from the catchment area, which confirms the predominance of transverse transport in the slope catchment area and longitudinal transport in the gully. The opposite situation occurs during thaws, with as much as 90% of the material removed coming from the slope catchment area. At that time, longitudinal transport dominates on the slope and transverse transport dominates in the gully. Full article

Intensity–duration–frequency (IDF) curves, which relate rainfall intensity (i), storm duration (d), and return period (T), are cornerstone tools for planning, designing, and operating hydraulic works. Since Sherman’s pioneering formulation in 1931, many modern implementations have systematically omitted the duration-shifting parameter C, causing predicted intensities to diverge to infinity as $d\to 0$. This mathematical paradox becomes especially problematic under extreme hydrological regimes and convective storms exceeding 300 mm/h, where an accurate curve fit is critical. Here, we first review conventional IDF curve fitting techniques and their limitations. We then introduce IDF-GtzLo, a novel, intuitive formulation that reinstates and calibrates C directly from observed storm statistics, ensuring finite intensities for all durations. Applied to 36 automatic weather stations across Mexico, our method reduces the root mean square error by 23 % compared to the classical model. By eliminating the infinite intensity paradox and improving statistical performance, IDF-GtzLo offers a more reliable foundation for hydrological risk assessment and the design of infrastructure resilient to climate-driven extremes. Full article

The intensification of global climate change has led to an increased frequency of extreme rainfall and temperature events, posing severe threats to China’s ecosystems and socio-economic systems. This study, based on multi-year daily precipitation, monthly surface air temperature, and daily near-surface temperature datasets, employs multi-year averaging, EOF mode analysis, Mann–Kendall testing, and R/S analysis. By selecting heavy-rain days, rainfall amount, rainfall intensity, and drought indices, it explores the spatiotemporal evolution and driving mechanisms of extreme rainfall, drought, and compound events across China. The analysis of extreme rainfall reveals that precipitation in China shows a “more in the southeast, less in the northwest; abundant in the southeast, sparse in the northwest” pattern. EOF analysis identifies two spatial modes for rainfall parameters, the “Eastern Coordination Mode” and the “North–South Antiphase Mode,” corresponding to heavy rainfall days, rainfall amount, and rainfall intensity. The Mann–Kendall test shows that some regions in the eastern monsoon zone have experienced a significant increase in heavy rainfall parameters, while certain areas in the northeast, southern China, and northwest have also undergone significant changes. By contrast, parts of the southwest have seen a decrease. R/S analysis reveals that the Hurst index is high in the eastern monsoon region, indicating a strong likelihood of continued upward trends in the future, while regions in the western arid and semi-arid zones and parts of the Tibetan Plateau exhibit stronger randomness in trends, leading to more alternating drought and flood events. The analysis of the drought index (SPI-3) reveals synchronized drought patterns in the central-eastern and northern regions, with “synergistic consistency,” “Northwest–Northeast Antiphase,” and “Northern–Central-South Antiphase” characteristics. The Mann–Kendall test indicates a “north-wet, south-dry” differentiation, with significant wetting in the northern regions and parts of the Tibetan Plateau, and significant drying in the central-eastern and southwestern regions. R/S analysis shows high Hurst indices across most of the northwest and northern regions, indicating stronger drought persistence, while coastal areas in the east are more prone to dry–wet transitions. In terms of compound events, high-temperature and heavy rainfall events have increased from northwest to southeast over the past 40 years, with southern China experiencing more than 200 days of such events. Significant changes have been observed in the eastern and southern coastal regions, with high Hurst indices and strong persistence in the eastern coastal areas. Low-temperature and heavy rainfall events are more frequent in the eastern coast and southwestern regions, with higher Hurst indices in the eastern and central regions, indicating strong persistence. Full article

This study investigates two extreme convective rainfall events that struck Poland in August 2024, affecting Warsaw (Okęcie) on 19 August and Zamość on 21 August. The aim is to evaluate the meteorological background, intensity, and spatial characteristics of these short-duration storms. We used high-resolution meteorological observations, radar imagery, and satellite data provided by the Institute of Meteorology and Water Management (IMGW-PIB). The storms were analyzed using temporal rainfall profiles, Chomicz α index classification, and comparison with World Meteorological Organization (WMO) thresholds for extreme precipitation. Both events exceeded national and international criteria for torrential rainfall. In Zamość, over 88.3 mm of rain fell within one hour, and 131.3 mm within three hours—ranking this episode among the most intense short-duration rainfall events in the region. Convective organization patterns, including multicellular clustering and convective training, were identified as key factors enhancing rainfall intensity. The results demonstrate the diagnostic value of combining national indices with global benchmarks in rainfall assessment. These findings support further integration of convection-permitting models and real-time nowcasting into urban hydrometeorological warning systems. Full article

The current research on light transmission under rainfall conditions primarily focuses on monochromatic converging light sources, and the related conclusions cannot be directly applied to spherical continuous-spectrum light sources (SCLSs). Based on the Lorenz–Mie scattering method, this study calculated the optical parameters of Gamma-distributed rainfall across three rainfall types and four intensity levels. A numerical algorithm model for radiative transfer under rainfall conditions was established for SCLSs. The effects of rainfall type, rainfall intensity, and light wavelength on radiative transfer were analyzed. Key conclusions include the following: when rainfall intensity is below moderate, the type of rainfall can be disregarded. However, for heavy to torrential rain, distinct differences between stratiform and non-stratiform rainfall must be considered. The attenuation caused by rainfall intensity does not increase linearly. Specifically, attenuation during moderate rain is lower than that in light rain, while heavy and torrential rain exhibit greater attenuation than both light and moderate rain. Wavelength bands significantly influence radiative transfer. Efforts to optimize the attenuation of radiative energy by rainfall should focus on the primary energy bands where most energy is concentrated. These findings highlight the importance of considering rainfall classification, nonlinear attenuation mechanisms, and wavelength-specific characteristics when evaluating radiative transfer under varying rainfall conditions. Full article

Meteorological and climatological trends are surely changing the way urban infrastructure systems need to be operated and maintained. Urban road traffic fluctuates more significantly under the interference of strong wind–rain weather, especially during tropical cyclones. Deep learning-based methods have significantly improved the accuracy of traffic prediction under extreme weather, but their robustness still has much room for improvement. As the frequency of extreme weather events increases due to climate change, accurately predicting spatiotemporal patterns of urban road traffic is crucial for a resilient transportation system. The compounding effects of the hazards, environments, and urban road network determine the spatiotemporal distribution of urban road traffic during an extreme weather event. In this paper, a novel Knowledge-driven Attribute-Augmented Attention Spatiotemporal Graph Convolutional Network (KA3STGCN) framework is proposed to predict urban road traffic under compound hazards. We design a disaster-knowledge attribute-augmented unit to enhance the model’s ability to perceive real-time hazard intensity and road vulnerability. The attribute-augmented unit includes the dynamic hazard attributes and static environment attributes besides the road traffic information. In addition, we improve feature extraction by combining Graph Convolutional Network, Gated Recurrent Unit, and the attention mechanism. A real-world dataset in Shenzhen City, China, was employed to validate the proposed framework. The findings show that the prediction accuracy of traffic speed can be significantly increased by 12.16%~31.67% with disaster information supplemented, and the framework performs robustly on different road vulnerabilities and hazard intensities. The framework can be migrated to other regions and disaster scenarios in order to strengthen city resilience. Full article

The aim of this study is to provide basic data on the yield and bioactive compound contents of the male asparagus cultivar ‘Avalim’ grown under two cultivation systems, i.e., an open field and a rain shelter house, in the Saemangeum reclaimed land. Spear sprouting, yield parameters, polyphenol and flavonoid contents, antioxidant enzyme activities (catalase, ascorbate peroxidase, peroxidase, and superoxide dismutase), and DPPH and ABTS radical scavenging activities of 22-month-old asparagus cultivated in each system were measured. Spear sprouting occurred approximately 10 days earlier in the rain shelter house than in the open field. The number of asparagus spears per 1000 m² was approximately 600 higher in the rain shelter house, and the total weight was 21% higher than that in the open field. Polyphenol and flavonoid contents, antioxidant enzyme activities, and DPPH and ABTS radical scavenging activities were higher in the open field than in the rain shelter house. The temperature in the rain shelter house during the cultivation period was 0.6 to 17.4 °C higher than that in the open field, while light intensity was 359.7 μmol·m⁻²·s⁻¹ higher in the open field. Consequently, cultivation in Saemangeum reclaimed land resulted in higher yields in the rain shelter house, whereas the bioactive compound levels were higher in the open field. Therefore, selecting an appropriate cultivation system based on the intended purpose, focusing on yield or functional quality, when cultivating asparagus on reclaimed land is important. Full article

Accurate estimation of path loss is essential for evaluating the impact of the propagation medium, determining transmission power requirements, and optimizing cell layouts for effective 5G millimetre wave coverage. At 28 GHz, rain attenuation is a critical factor, with its impact varying significantly based on environmental and regional characteristics. This study quantifies the degradation of 5G millimetre wave link budgets due to rainfall in South Africa and assesses the maximum coverage ranges for urban micro and urban macro deployments under varying rain intensities. The analysis focuses on Pretoria, a city characterized by diverse urban landscapes and seasonal thunderstorms. Urban micro cells are deployed on streetlights and building facades in dense zones such as Hatfield and Sunnyside to deliver high-capacity coverage. In contrast, urban macro cells target broader coverage from elevated structures, such as those in the Pretoria CBD. Using the Close-In path loss model for both line-of-sight and non-line-of-sight conditions, this study examines the relationships between link budget parameters, maximum path loss, and 5G millimetre wave link distances under rain-affected and clear-sky scenarios. The results highlight the significant influence of rainfall, particularly in non-line-of-sight conditions, and provide insights for designing efficient 5G networks tailored to South Africa’s unique climate. Full article

Despite significant progress, precipitation forecasting in West Africa remains challenging due to the complexity of atmospheric processes and the region’s climatic variability. This study aims to identify optimal configurations of the WRF model to improve precipitation forecasting. To evaluate the sensitivity of the model’s physical parameterizations, 15 configurations were tested by combining various cumulus parameterization schemes (CPSs) and planetary boundary layer (PBL) schemes. The analysis examines two contrasting rainfall events in Senegal: one characterized by widespread intense precipitation and another featuring localized moderate rainfall. Simulated rainfall, temperature, and humidity were validated against rain gauges, satellite products (ENACTS, ARC2, CHIRPS, and IMERG), and ERA5 reanalysis data. The results show that the WRF configurations achieve correlation coefficients (r) ranging from 0.27 to 0.62 against ENACTS and from 0.15 to 0.41 against rain gauges. The sensitivity analysis reveals that PBL schemes primarily influence temperature and humidity, while CPSs significantly affect precipitation. For the heavy rainfall event, several configurations accurately captured the observed patterns, particularly those using Tiedtke or Grell–Devenyi CPSs coupled with the Mellor–Yamada–Janjic (MYJ) PBL. However, the model showed limited skill in simulating localized convection during the moderate rainfall event. These findings highlight the importance of selecting appropriate parameterizations to enhance WRF-based precipitation forecasting, especially for extreme weather events in West Africa. Full article

The increasing frequency of extreme weather events presents serious challenges to both regional and global economies. This study focuses on quantifying the economic losses caused by three major types of extreme climate events (heatwaves, droughts, and heavy rain) in Hainan Island from 2001 to 2020. Moreover, a comprehensive dataset of related economic losses was developed. To support the analysis, we constructed an Extreme Climate Economic Loss Model (ECELM). Drought and heavy rain losses were estimated using a loss intensity index based on precipitation and typhoon landfall wind speeds. Heatwave-related losses were assessed through a threshold-based optimization approach. The results show that both heatwaves and heavy rain have exhibited increasing impacts from 2001 to 2020. Although heatwaves were the most frequent extreme event in more than half of the years, heavy rain caused the highest cumulative losses, reaching CNY 75 billion. Spatial analysis indicates that the southeastern coastal areas were the most severely affected. These findings provide valuable quantitative evidence for designing targeted regional climate adaptation strategies. Full article

Intense thunderstorms known as Nor’westers develop in the Eastern and North Eastern parts of India and Bangladesh before the monsoon season (March to May). The associated severe weather can cause extensive damage to property and livestock. This study uses the pre-monsoon volumetric data of S-band radar from 2013 to 2018 located in Kolkata to investigate the diurnal variation in the characteristics of the storms over Gangetic West Bengal. The cell initiation, echo top heights, maximum reflectivity, and core convective area are determined by using a flexible feature tracking algorithm (PyFLEXTRKR). The variation of the parameters in diurnal scale is examined from 211,503 individual cell tracks. The distribution of the severe weather phenomena based on radar based thresholds in spatial and temporal scale is also determined. The results show that new cell initiation peaks in the late evening and early morning, displaying bimodal variability. Most of these cells have a short lifespan of 0 to 3 h, with fewer than 5 percent of storms lasting beyond 3 h. The occurrence of hail is much greater in the afternoon due to intense surface heating than at other times. In contrast, the occurrence of lightning is higher in the late evening hours when the cell initiation reaches its peak. The convective rains are generally accompanied by lightning, exhibiting a similar diurnal temporal variability but are more widespread. The findings will assist operational weather forecasters in identifying locations that need targeted observation at certain times of the day to enhance the accuracy of severe weather nowcasting. Full article

Existing drainage systems have limited capacity to mitigate future climate change-induced flooding problems effectively. However, some studies have evaluated the effectiveness of integrating Water-Sensitive Urban Design (WSUD) with existing drainage systems in mitigating flooding in tropical regions. This study examined the performance of drainage systems and integrated WSUD options under current and future climate scenarios in a sub-catchment of Saltwater Creek, a tropical catchment located in Cairns, Australia. A combination of one-dimensional (1D) and two-dimensional (1D2D) runoff generation and routing models (RORB, storm injector, and MIKE+) is used for simulating runoff and inundation. Several types of WSUDs are tested alongside different climate change scenarios to assess the impact of WSUD in flood mitigation. The results indicate that the existing grey infrastructure is insufficient to address the anticipated increase in precipitation intensity and the resulting flooding caused by climate change in the Engineers Park sub-catchment. Under future climate change scenarios, moderate rainfall events contribute to a 25% increase in peak flow (95% confidence interval = [1.5%, 0.8%]) and total runoff volume (95% confidence interval = [1.05%, 6.5%]), as per the Representative Concentration Pathway 8.5 in the 2090 scenario. Integrating WSUD with existing grey infrastructure positively contributed to reducing the flooded area by 18–54% under RCP 8.5 in 2090. However, the efficiency of these combined systems is governed by several factors such as rainfall characteristics, the climate change scenario, rain barrel and porous pavement systems, and the size and physical characteristics of the study area. In the tropics, the flooding problem is estimated to increase under future climatic conditions, and the integration of WSUD with grey infrastructure can play a positive role in reducing floods and their impacts. However, careful interpretation of results is required with an additional assessment clarifying how these systems perform in large catchments and their economic viability for extensive applications. Full article