Search Results (1,175)

Climate change can alter both the amount and timing of inflows to water supply reservoirs while also increasing heat-driven demand and the likelihood of stressful warm-season conditions. Climate-driven changes in inflow to Eagle Mountain Lake Reservoir (Texas, USA) were quantified by integrating (i) a calibrated SWAT model evaluated at four USGS stream gauges, (ii) statistically downscaled CMIP6 daily precipitation and minimum/maximum temperature at seven stations/grid points for a historical baseline (2003–2022) and two future windows (2031–2050 and 2081–2100) under SSP1-2.6, SSP2-4.5, and SSP5-8.5, and (iii) observed reservoir operations (lake level, water supply releases, and flood discharge; 1990–2022). A standard watershed climate workflow is reframed through an operations-focused lens, wherein projected inflow changes are translated into decision-relevant indicators via the utilization of observed thresholds and operating mode signals. Included within this framework are spring refill-season inflow shifts, a hot–dry month metric, and storage threshold performance measures, which are coupled with screening-level probabilities linked to multi-year inflow deficits. Across models and stations, mean annual temperature increases by 0.7–1.9 °C in the 2030s and by 0.7–6.1 °C in the 2080s, while annual precipitation changes remain uncertain (−24% to +55%). Daily projections show a strong increase in extreme heat days (daily Tmax above the historical 95th percentile), from about 18 days yr⁻¹ historically to about 30–33 days yr⁻¹ in the 2030s and about 34–82 days yr⁻¹ by the 2080s. Hot–dry months (monthly mean Tmax above the historical 90th percentile and monthly precipitation below the historical median) increase modestly by mid-century and rise to about 1.5 months yr⁻¹ on average by the 2080s under SSP5-8.5. SWAT simulations indicate that the mean annual inflow declines by 17–20% across scenarios, with the largest reductions during the spring refill period (March–June). Historical operations show that hot–dry months are associated with approximately double the mean water supply release (7.2 vs. 3.5 m³/s) and a lower monthly minimum lake level (about 0.30 m; about 1.0 ft lower on average). Flood discharges occur almost exclusively when lake elevation is at or above about 197.8 m and follow multi-day rainfall clusters (cross-validated AUC = 0.99). Together, these results indicate that earlier-season inflow reductions and more frequent hot–dry stress will tighten the operational margin between refill, summer demand, and flood management, underscoring the need for adaptive drought response triggers and integrated drought–flood planning for the Dallas–Fort Worth region. Full article

This study, conducted in the framework of the LIAISE field campaign in NE Spain (May–September 2021), investigates how near-surface relative humidity influences early-stage rainfall characteristics when precipitation is most affected by temperature and relative humidity before rainfall onset. Two instrumented sites were examined, using disdrometers, Micro Rain Radar (MRR), C-band weather radar data, and automatic weather stations. Rainfall events were first classified as stratiform or convective using weather radar data based on a texture analysis of the reflectivity field. Then, only stratiform events were selected and further classified into dry and moist categories according to the upper and lower terciles of near-surface (2 m) relative humidity at the rainfall onset (dry < 54%; moist > 72%). Results show that during dry events, the time delay between the detection of precipitation at ~750 m above ground level (AGL) (by MRR or C-band radar) and its arrival at the surface (measured by the disdrometer) is consistently longer than during moist events, indicating possible evaporation of raindrops during their descent. Surface drop size distributions also differ: dry cases have generally fewer small drops (with diameters < 0.8 mm) but relatively more large drops, leading to higher radar reflectivity values despite similar surface rainfall amounts. However, reflectivity observed aloft by C-band radar and MRR does not present the dependence on relative humidity found at ground level. Findings reported here increase our understanding of the impact of low-level conditions on precipitation characteristics and microphysical associated processes and may contribute to improve correction schemes in operational weather radar quantitative precipitation estimates. Full article

It is known that rainfall leads to a reduction in driving speed. However, the results of various studies are inconsistent regarding the amount of speed reduction. In this study, we combine high-resolution radar-based rainfall estimates for three days with heavy rainfall with driving speeds derived from floating car data on 1.5 million road sections in Germany. Using linear regression models, we investigate the functional relationship between rainfall and driving speeds depending on road section characteristics like speed limit and number of lanes. We find that the speed reduction due to rainfall is higher at road section with higher speed limits and on multi-lane roads. On highway road section with speed limits of 130 km/h, for example, heavy rainfall of more than 8 L/m${}^2$ in five minutes leads to an average speed reduction of more than 30%, although estimates at very high rainfall intensities are subject to increased uncertainty due to data sparsity. Cross-validation shows that including rainfall as a predictor for driving speed reduces mean squared errors by up 14% in general and up to 50% in heavy rainfall conditions. Furthermore, rainfall as a continuous variable should be preferred over categorical variables for a parsimonious model. Our results demonstrate that parsimonious, interpretable models combining radar rainfall data with floating car data can capture systematic rainfall-related speed reductions across a wide range of road types. However, the analysis should be interpreted strictly as a descriptive, event-specific study. It does not support generalizable inference across time, seasons, or broader traffic conditions. To make this approach suitable for operational applications such as real-time speed prediction, route planning, and traffic management, larger multi-event datasets and the consideration of effects like weekday structure and diurnal demand patterns are required to better constrain effects under heavy rainfall conditions. Full article

Rainfall-induced failures in red clay slopes are common, yet the coupled influence of soil structure degradation and rainfall temporal patterns on slope hydromechanical behavior remains poorly understood. This study advances the understanding by investigating a cut slope failure in Yunnan through integrated field monitoring, laboratory testing, and numerical modeling. Key advancements include: (1) elucidating the coupled effect of structure degradation on both shear strength reduction and hydraulic conductivity alteration; (2) systematically quantifying the impact of rainfall temporal patterns beyond total rainfall; and (3) providing a mechanistic explanation for the critical role of early-peak rainfall. Mechanical and hydrological parameters were obtained from intact and remolded samples, with soil-water retention estimated via pedotransfer functions. A hydro-mechanical finite element model of the slope was constructed and calibrated using recorded rainfall, displacement data and failure surface. Six simulation scenarios were designed by combining three strength conditions (intact at natural water content, intact at saturation, remolded at natural water content) with two hydraulic conductivity values (intact vs. remolded). Additionally, four synthetic rainfall patterns, including uniform, peak-increasing, peak-decaying and bell-shaped rainfall, were simulated to evaluate their influence on pore water pressure development and slope stability. Results show remolding reduced hydraulic conductivity 4.7-fold, slowing wetting front advance and increasing shallow pore water pressure. Intact soil facilitated deeper drainage, elevating pressure near the soil-rock interface. Strength reduction induced by structure degradation (water saturating and remolding) enlarged the slope deformation zone by 1.5 times under same hydraulic conductivity. Simulations using saturated intact strength best matched field observations. The results from this specific slope indicate that strength parameters primarily control stability, while permeability affects deformation depth. Simulations considering different rainfall patterns indicate that slope stability depends more critically on the temporal distribution of rainfall intensity than on the total amount. Overall, peak-decaying rainfall led to the most rapid rise in pore water pressure, earliest instability and lowest failure rainfall threshold, whereas peak-increasing rainfall showed the opposite trends. Our findings outline a practical framework for assessing red clay slope stability during rainfall. This framework recommends using saturated intact strength parameters in stability analysis. It highlights the important influence of rainfall temporal patterns, especially those with an early peak, on failure timing and rainfall threshold. Full article

This study aims to investigate the effects of Chan-Hom (2015) typhoon-induced variations in enthalpy flux (EF) and moisture flux (MF) on intensity variations and rainfall. Chan-Hom (2015) made landfall at Zhoushan, then changed its direction and moved towards Korea. This analysis used ERA5 reanalyzed data, encompassing daily surface latent and sensible heat flux, along with wind measurements at a height of 10 m. Furthermore, wind components and specific humidity data from the 1000–200 hPa level in ERA5 were utilized to compute the MF and MF convergence, in accordance with the equations outlined in the methodology. This study examines the correlation among typhoon intensity, precipitation, MF, and EF. The mechanism by which Typhoon Chan-Hom has caused a decline in sea surface temperature (SST) was analyzed. Typhoons need a higher EF that can affect them before landfall to maintain their intensity. The highest LHF was observed (340 W/m²) prior to typhoon landfall, indicating that LHF responds to intensity-induced wind during Chan-Hom. Typhoon-induced rainfall is mainly controlled by the MF convergence, rather than the typhoon intensity. The spatial and temporal distributions of MF and MF convergence (MFC) during typhoon formation to landfall reveal that the symmetric MFC is dominated by typhoon intensity; a symmetrical structure is observed when the intensity is high. MFC includes wind convergence and moisture advection. Wind convergence dominates the MFC during typhoons, but moisture advection forms at the eyewall. MF during the typhoon’s landfall can relate to the amount of rainfall that occurred over the land. However, the rainfall pattern changed after landfall, and the typhoon changed its direction. SST cooling observed in the study area is mainly due to the upwelling process with strong cyclonic winds. Full article

East Africa’s March–April–May (MAM) rainfall exhibits pronounced variability that strongly influences agriculture, water security, and livelihoods. This study analyzes consecutive wet day (CWD) events using CHIRPS precipitation, GridSat infrared cold-cloud brightness temperature, and ERA5 reanalysis for 1982–2023 to examine rainfall variability and its relationship with atmospheric circulation and convection. CWDs are classified into short (3–5 days), medium (6–10 days), and long (>10 days) events. Results reveal three regional activity centers: the Eastern Congo Basin, Lake Victoria, and Southwest Ethiopia. The Congo Basin emerges as the most convectively active region, sustaining frequent events across all categories and supporting long-duration rainfall through persistent moisture flow and mesoscale convection. On average, CWDs contribute 43% of total MAM rainfall across East Africa, ranging from negligible amounts in arid areas to over 90% in equatorial regions. Short-duration events dominate the seasonal total, while long-duration events, though spatially restricted, contribute up to 52% locally. Composite convection analysis shows a transition from widespread moderate activity during short events to highly localized, intense convection in long events, particularly over the equatorial Congo and Lake Victoria regions. These findings highlight the critical contribution of organized synoptic-scale systems to East Africa’s hydrological cycle, which will have implications for improving sub-seasonal rainfall forecasts. Full article

Dry climate regions face heightened risks of flooding and infrastructure damage even with minimal rainfall. Climate change is intensifying this vulnerability by increasing the duration, frequency, and intensity of precipitation events in areas that have historically experienced arid conditions. As a result, accurate precipitation estimation in these regions is critical for effective planning, risk mitigation, and infrastructure resilience. This study evaluates the performance of five satellite- and model-based precipitation products by comparing them against in situ rain gauge observations in a dry-climate region: The fifth generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) (analyzing maximum and minimum precipitation rates separately), the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), the Western Land Data Assimilation System (WLDAS), and the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG). The analysis focuses on both average daily rainfall and extreme precipitation events, with particular attention to precipitation magnitude and the accuracy of event detection, using a combination of statistical metrics—including bias ratio, mean error, and correlation coefficient—as well as contingency statistics such as probability of detection, false alarm rate, missed precipitation fraction, and false precipitation fraction. The study area is Palm Desert, a mountainous, arid, and urban region in Southern California, which exemplifies the challenges faced by dry regions under changing climate conditions. Among the products assessed, WLDAS ranked highest in measuring total precipitation and extreme rainfall amounts but performed the worst in detecting the occurrence of both average and extreme rainfall events. In contrast, IMERG and ERA5-MIN demonstrated the strongest ability to detect the timing of precipitation, though they were less accurate in estimating the magnitude of rainfall per event. Overall, this study provides valuable insights into the reliability and limitations of different precipitation estimation products in dry regions, where even small amounts of rainfall can have disproportionately large impacts on infrastructure and public safety. Full article

Wetlands store large amounts of soil organic carbon stock (SOCS), making them crucial for global climate regulation. However, climate change, poor management, and weak protection policies threaten these stocks. To assess the contribution of different wetland types for national and international climate targets and to monitor the effectiveness of protection measures, additional research is required. Therefore, we assessed SOCS and disturbances from climate change, land use/land cover (LULC), and soil chemical composition in saline and eutrophic Ramsar sites in Serbia. Analyzing a total of 96 samples, we accounted for soil depth, reference soil group (RSG), and habitat/vegetation type. Mean SOCS in the saline site ranged from approximately 36 t·ha⁻¹ at 0–30 cm to 26 t·ha⁻¹ at 30–60 cm, whereas values were much higher for the eutrophic sites, ranging from 81 to 82 t·ha⁻¹ at 0–30 cm and 47–63 t·ha⁻¹ at 30–60 cm. Differences between groups for the whole soil columns (0–60 cm) were significant at the 0.1% level. While SOCS generally decreases with depth, it showed notable local variability, including occasional instances at deeper layers, indicating complex environmental and anthropogenic influences. Spatial mapping of soil chemistry parameters (pH, humus, P₂O₅, and K₂O) along with land use/land cover (LULC) data revealed nutrient dynamics influenced by agricultural activities. An analysis of regional climate data revealed temperature increases relative to the reference period of 1971–2000 by 0.5 °C for the decade 2001–2010 and of 1.5 °C for 2011–2020. Climate projections under the RCP4.5 and 8.5 scenarios predict further warming trends, as well as increased rainfall variability and drought risks. The results of our study contribute to quantifying the important, though variable, contribution of wetland sites to global climate regulation and show the influence of geogenic, pedogenic, and anthropogenic factors on SOCS. National policies should be adapted to safeguard these stocks and to limit negative effects from surrounding agricultural areas, as well as to develop strategies to cope with expected regional climate change effects. Full article

The SCS-CN (Soil Conservation Service Curve Number) model is important for flood forecasting as it provides a relatively simple and widely used methodology for estimating the amount of surface runoff from a rainfall event, which is a crucial input in predicting flood volumes and peaks in ungauged or data-scarce watersheds. Thus, the authors developed a hydrological model based on the SCS-CN curve methodology and GIS (Geographic Information Systems) to estimate the flood hydrograph in the upper parts of the Biała Lądecka River basin in Poland. The numerical model was calibrated based on the data available from the Polish Institute of Meteorology and Water Management (IMGW). The output of the model demonstrates the effect in the flood hydrograph at the town of Lądek-Zdrój. Additionally, hydraulic routing calculations were included to analyze the possible causes of the dam failure of the Stronie Śląskie reservoir in the year 2024. The main purpose of this study is to corroborate the influence of climate change on flood events and their consequences, as well as to assist in forecasting future catastrophic hydrological events and thus earlier adaptation and reinforce the infrastructure in our territories against future flooding. Full article

Savanna ecosystems of the Sahel are heavily affected by climate change, leading to drier subtropical regions. These ecosystems play a fundamental role in food security of the region, so that an improved understanding of how these ecosystems are affected by these weather events is thereby critical. Several studies have assessed the herbaceous production level, dynamics during the rainy season, and biotic and abiotic factors that could impact this production. Some authors argue that rain is the main factor positively influencing the biomass production in semi-arid areas where the rainfall ranges between 200 and 750 mm. This study aims to assess the contribution of some meteorological variables to biomass production in a Sahelian semiarid savannah. From 2008 to 2018, rainfall (mm), soil moisture (%), soil temperature (°C) at 5 cm depth, number of times there was no rain (NTNR), number of rainy days, and the herbaceous biomass were monitored. The contributions of meteorological variables to biomass production were calculated using the XGBoost regression model. The most influential meteorological parameters on herbaceous biomass production are soil temperature, amount, and distribution of rainfall. Full article

Dew, a key component of Non-Rainfall Water Inputs (NRWIs), plays a disproportionately significant role in land–atmosphere interactions. This review synthesizes advances in understanding its ecological, hydrological, and environmental effects, quantification methods, and spatiotemporal variations. A key finding is the regional dichotomy of dew effects: in arid regions, it is a crucial hydrological source, whereas in humid/alpine regions, its energy-balance regulation via latent heat release often outweighs its hydrological contribution. Significant challenges persist, including methodological inconsistencies, an overreliance on point-scale data from arid zones, and an underappreciation of dew’s energy impacts, particularly in cold regions. Recent studies suggest a general declining trend in dew frequency and amount in many arid regions, which could exacerbate water stress for dependent ecosystems. However, regional heterogeneities and interactions with other NRWIs remain poorly constrained. Future research must overcome observational bottlenecks, deepen energy–water coupling studies, quantify climate change impacts, expand research to underrepresented regions, and integrate multi-method approaches to improve model predictability, thereby supporting ecosystem resilience and water security under global change. Full article

When it rains or snows over a city, water droplets capture airborne pollutants and transport them to the ground. Prolonged precipitation over the same area can remove a larger amount of pollution; however, rainfall systems vary in duration and tend to move rapidly across regions. Wet deposition sprinklers replicate this natural scavenging process. They can operate for extended periods as needed and can be installed at specific locations where pollution mitigation is most necessary. Despite encouraging experimental results and the widespread use of similar technologies in industrial sectors—such as mining, the construction industry, and waste management—very limited scientific research has focused on their application in urban environments. In particular, their use as an emergency measure during severe pollution episodes as a protective intervention for sensitive subjects, while awaiting the effects of long-term structural solutions, remain largely unexplored. In the present work, we systematically discuss the key elements required to design and implement a network of anti-smog cannons (ASC) to protect sensitive receptors from severe air pollution events in large cities. Based on this analysis, we established a generalized framework that can be applied to any urban context worldwide. We also examine the potential application of the proposed method to the city of Turin (≈850,000 inhabitants, north-western Italy), which is considered a representative case study for other cities in Western Europe. Our findings indicate that such a network is both technically feasible and economically sustainable for local government authorities. Full article

Agricultural non-point source pollution (AGNPSP) is one of the core challenges facing global water environment management. Existing research mainly focuses on post-event estimation of pollution loads and source analysis, while studies on proactive risk warning for watershed non-point source pollution are relatively limited, especially those that integrate with agricultural production practices. Therefore, this study takes the River Tongyang Watershed as the research object and establishes a fertilization warning and regulation model based on short-term meteorological data. First, it simulates the migration and transformation processes of pollutants within the watershed under different meteorological conditions and analyzes their spatiotemporal evolution characteristics. Then, combined with real-time water quality monitoring data at the lake inlet, it calculates the residual environmental capacity for pollutants in the river water. Finally, based on this environmental capacity and the farmland area, it back-calculates the maximum safe fertilization amount for each plot under different meteorological scenarios to achieve precise fertilization management. When the planned fertilization amount does not exceed this maximum safe value, environmental risks are within a controllable range; if exceeded, fertilization should be proportionally reduced to prevent non-point source pollution. The results indicate that this model can accurately predict the concentration trends of non-point source pollutants and can develop differentiated fertilization strategies based on rainfall scenarios. The “fertilization determined by water” decision-making framework established in this study provides a technically significant pathway for shifting watershed agricultural non-point source pollution management from passive treatment to active prevention. Full article

Hydroclimatic and geomorphological prerequisites for mudflow hazard were studied using data on several of the largest flood events in the Khamar-Daban mountain area (Lake Baikal, East Siberia) for the period from 1966 to 2022. The data include flood-forming precipitation and atmospheric circulation patterns, the amount of related suspended sediment discharge in the years of high floods, as well as terrain features favorable for the formation of catastrophic floods and mudflows. Floods and mudflows in the area can arise under conditions of extremely high daily precipitation (up to 200 mm or more) after the territory becomes moistened by prolonged rainfall under meridional air transport. The maximum water discharge correlates with a multifold increase in the suspended sediment discharge and turbidity. The increase in sediment discharge associated with maximum water discharge (floods) of ≤10% probability is apparently due to 4–9 times higher flow rates. On the other hand, the formation of the solid runoff component in the area is controlled geomorphologically by slope processes depending on slope steepness, elevation contrasts, and the thickness of soft sediments subject to denudation and transport. The geomorphological conditions are most favorable for the development of mudflows and catastrophic floods in the catchments of the Bezymyannaya, Slyudyanka, Khara-Murin, and Utulik rivers. Floods and mudflows are especially hazardous on the southern shore of Lake Baikal, encircled by the Khamar-Daban Range, where active mudflow processes pose risks to the towns of Slyudyanka and Baikalsk, as well as to the sludge storage facilities of the abandoned Baikal Pulp and Paper Mill. Full article

This study conducts a diagnostic analysis of an extremely heavy rainfall event and its causative factors that occurred in Libya, North Africa on 10 September 2023. The Weather Research and Forecasting (WRF) model was also employed to perform some sensitivity experiments for this heavy rainfall event and further reveal its causes. Results indicate that the primary synoptic system responsible for this extreme precipitation event was an extratropical cyclone (storm) named “Daniel”. During the formation and development of this cyclone, the circulation at the 500 hPa level from the eastern Atlantic to western Asia exhibited a stable “two troughs and one ridge” pattern, with a upper-level cold vortex over the eastern Atlantic, a high-pressure ridge over central Europe, and a cut-off low over western Asia, collectively facilitating the formation and development of this cyclone. As this cyclone moved southward, it absorbed substantial energy from the Mediterranean Sea; following landfall, the intrusion of weak cold air enabled the cyclone to continue intensifying. Meanwhile, the northwest low-level jet stream to the west of the extratropical cyclone moved alongside the cyclone to the coastal regions of northeastern Libya, where it converged with water vapor transport belts originating from the Ionian Sea, the Aegean Sea, and the coastal waters of northeastern Libya. This convergence provided abundant water vapor for the rainstorm event, and under the combined effects of convergence and orographic lifting on the windward slopes of the coastal mountains, extreme precipitation was generated. In addition, the atmosphere over the coastal regions of northeastern Libya exhibited strong stratification instability, which was conducive to the occurrence of extreme heavy precipitation. Although WRF successfully reproduced the precipitation process, the precipitation amount was underestimated. Sensitivity experiments revealed that both the topography in the precipitation area and the sea surface temperature (SST) of the Mediterranean Sea contributed to this extreme heavy precipitation event. Full article