Search Results (65)

Under global warming, compound extreme events such as Drought–Flood Abrupt Alternation (DFAA) are becoming increasingly common, yet the structural asymmetry and spatial dynamic evolution between Drought to Flood (D–F) and Flood to Drought (F–D) processes remain under-researched. Using high-resolution daily precipitation data spanning 1961 to 2022 from nine major river basins in China, DFAA events were identified via the Standardized Weighted Average Precipitation (SWAP) index coupled with run theory, and their evolution was analyzed using multidimensional spatiotemporal metrics. Our results reveal a spatial frequency and severity mismatch, where southern basins exhibit high frequency occurrences dominated by slight to moderate events, whereas northern and inland basins experience lower overall frequency but a significantly higher proportion of severe events. Spatial polarity asymmetry is evident, with D–F events dominating nationwide and exceeding 74% in northern and inland basins, while southern humid basins exhibit a more balanced D–F/F–D structure. Temporally, D–F processes involve prolonged moisture accumulation, whereas F–D processes manifest as short-lived post-rainfall moisture deficits. Based on risk trajectories, basins were categorized into four impact patterns: highly oscillatory pattern, intensifying pattern, long-cycle accumulative pattern, and baseline pattern. Ultimately, regional DFAA risks are governed by polarity asymmetry and non-stationary evolution rather than absolute frequency alone, providing a critical scientific basis for basin-specific disaster mitigation strategies under climate change. Full article

This study established a refined, distributed SWAT modeling framework that integrates elevation-band and snowmelt modules to reconstruct the alpine hydrological and sediment cycles of the Koshi River Basin (KRB) over the period 1990–2024, with climate scenarios constructed using the delta change approach. The KRB, a major transboundary watershed traversing China, Nepal, and India, was selected owing to its critical hydro-climatic role under the destabilizing “Asian Water Tower”; it generates substantial sediment yield, hosts the densest concentration of hydropower potential within the Ganges system, and spans an extreme vertical gradient from Mount Everest to the southern alluvial plains. Results reveal accelerated warming at a rate of 0.21 °C per decade and an overall warming–wetting trend, punctuated by an abrupt interdecadal shift around 2015. Precipitation dominated interannual streamflow variability, with enhanced rainfall triggering basin-wide sediment surges that overwhelmed the natural buffering capacity of the land surface. Conversely, rising temperatures intensified actual evapotranspiration, markedly depleting soil water and reducing total water yield and monsoon runoff, although sustained snow and glacier melt effectively elevated the dry-season low-flow baseline. The integrated climate forcing reshaped the disparity between hydrological extremes, imposing severe seasonal eco-hydrological stress that manifested as a pre-monsoon deficit in terrestrial green water and acute summer sediment outbursts for aquatic habitats. Furthermore, the flood regime exhibited an altered distribution, with mid-to-high frequency floods enhanced while low-frequency extreme flood peaks declined. The hydro-sedimentological regime consequently exhibits pronounced nonlinear responses to climate change, providing a critical, threshold-based scientific foundation for adaptive transboundary water resource management. Full article

Introduction: Estuaries are among the most productive ecosystems in the world, holding great ecological and economic importance. As transitional zones between rivers and the sea, they experience abrupt abiotic changes linked to the tidal cycle, as well as seasonal changes related to greater river discharge during periods of higher rainfall. Therefore, salinity and temperature are key factors in structuring communities. These estuarine areas are recognized as nursery grounds, offering an abundance of food and shelter from predators, which creates ideal conditions for juvenile growth. Objective: Intense heatwaves were recorded in northern Spain during 2021 and 2022. This study aimed to understand how environmental factors influence the daily and seasonal dynamics of epibenthic communities and to compare these results with those obtained 40 years ago. Methodology: The epibenthic community in the Minho River estuary was assessed between September 2021 and August 2022 during spring tides at both low tide and high tide. Five trawls were carried out at each tide using a 2-meter-wide beam trawl. Several physical and chemical parameters were evaluated during the sampling process. Results: A total of 10,527 demersal fish and epibenthic crustaceans belonging to 21 species were caught in the sampling area. The structure of epibenthic assemblages was heavily influenced by tidal regimes. Assemblages at low tide had a greater number of taxa. In contrast, high-tide assemblages exhibited significantly higher diversity and evenness. Significant differences were observed between the spring/summer and winter assemblages. A SIMPER analysis revealed that Carcinus maenas contributed most to assemblage dissimilarity, both seasonally and by tide. Furthermore, Echiichthys vipera and Platichthys flesus were the species that contributed most to assemblage dissimilarity in both 1982 and 2021–2022. Conclusions: Compared with historical data, the rise in temperature and salinity, coupled with reduced water flow, has caused a profound restructuring of benthopelagic communities. This is driven by a significant increase in the marine character of the habitat. Substantial taxonomic turnover is evident, characterized by reductions in abundance and increases in the number of taxa sampled, as well as in diversity and evenness. Full article

This study presents an integrated framework for agricultural drought monitoring in data-scarce regions, utilizing the Google Earth Engine (GEE) platform to analyze multisource Earth observation data over the South Wollo highlands, Ethiopia, from 2001 to 2024. The analysis was complemented by Mann–Kendall trend testing, Sen’s slope estimation, and Pettitt change-point detection to identify and quantify long-term trends and abrupt shifts in drought dynamics. The methodology integrates climatic and satellite-derived indicators within a hybrid analytical framework. It incorporates the standardized precipitation evapotranspiration index (SPEI), vegetation condition index (VCI), vegetation health index (VHI), temperature condition index (TCI), and land surface temperature (LST), which are derived from MODIS (NDVI, LST, PET) and CHIRPS precipitation datasets. The analysis focused on the main growing season (June–September) to capture critical crop growth and moisture-sensitive periods for agricultural production in the study area. The findings reveal pronounced interannual variability in drought occurrence and intensity across the study period. Severe agricultural drought conditions were most extensive in 2009 and 2014, with VHIs indicating 15% and 4% of the area under severe and extreme drought in 2009, respectively, and 2.6% and 2% in 2014, respectively. In contrast, 2001, 2005, 2020, and particularly 2024 were characterized by predominantly no-drought to mild-drought conditions, with no-drought coverage increasing from 86.7% (2009) to 98.0% (2024). Vegetation-based indices demonstrate that drought impacts are episodic rather than persistent and strongly controlled by rainfall timing and early-season moisture availability. The LST exhibited marked year-to-year variability (28.8 °C to 33.8 °C), with elevated temperatures coinciding with drought periods and suppressed evaporative cooling. Correlation analysis confirmed a strong positive relationship between the SPEI and VHI (r = 0.77), with moderate correlations for the VCI (r = 0.40) and TCI (r = 0.36), underscoring the sensitivity of integrated vegetation health to the climatic water balance. The study concludes that combining the SPEI with satellite-derived vegetation and thermal indices provides a robust, scalable approach for agricultural drought assessment in regions with limited ground-based observations. The integrated framework effectively captures both moisture deficits and thermal stress components, offering a scientific basis for improving drought early warning systems and climate-resilient agricultural planning in Ethiopia and similar environments. Full article

Human-induced climate change has rendered urban areas highly vulnerable to extreme events such as heatwaves, droughts, and floods. This study conducts a scoping review of extreme and compound climate hazards in Iranian urban areas under global warming conditions. Mapping the available literature, 92 authoritative scientific works published between 1999 and 2025 were analyzed. The review synthesizes evidence on the spatiotemporal patterns of heatwaves, drought, torrential rainfall, sea-level rise, and compound hazards across Iran. The results indicate that central, northwestern, eastern, and southern Iran experience the highest heatwave intensity and frequency, with short-duration heatwaves being more common than prolonged ones. Western Iran faces a high risk of torrential rainfall, but urbanization amplifies flood consequences by expanding impervious surfaces and accelerating surface runoff. Coastal areas show high vulnerability to compound flooding due to sea-level rise and storms. The review further reveals that Iran is experiencing hydroclimate whiplash (abrupt transitions between drought and flood) driven by global warming. The study concludes by presenting management suggestions and future research directions for integrated compound hazard management in Iran. Full article

The northern part of the state of Mato Grosso is located at the intersection of large-scale agricultural production and the Amazon, a tropical biome of great importance for ecosystem services and biodiversity. Agricultural production activities interact with natural capital, among other factors, in land use and in biogeochemical cycles of water and carbon. In this study, we sought to use remote sensing at the regional level to diagnose and spatialize the contribution of agricultural activity to dry areas. Using carbon dioxide orbital models, land use classification techniques, the Standardized Precipitation Index (SPI), and Pettitt and Mann–Kendall statistics, the variables were compared spatially for the biogeographic boundary of the Amazon in Mato Grosso in two distinct time frames: (i) over the crop years of the CO₂ efflux model (2020 to 2023), and (ii) over the years 2008 to 2023, with consolidated data from the MODIS sensor system. The hot and cold spots analysis reinforces the correlation of carbon variables to land use; the drought index suggests a spatial correlation to forest loss, where more intense agricultural activity favors drought and inhibits moderate rainfall, and in turn is linked to the amount of forest in the context of intense continentality. Temporally, the statistical diagnosis highlights abrupt changes in 2011, 2013, and 2019, restate the complex relation of tropical forest and biogeochemical cycles, above all with carbon dioxide. Full article

Accurate forecasting of local weather patterns is essential for climate resilience and sustainable planning. This study analysed 35 years (1990–2025) of hourly temperature and precipitation data from Thohoyandou, South Africa, to assess the impacts of climate change and improve anomaly prediction. Exploratory analysis and Bayesian Estimator of Abrupt change, Seasonal change, and Trend (BEAST) decomposition revealed accelerated warming trends of 0.025 °C per year in temperature anomalies, alongside highly irregular rainfall patterns characterised by extreme events rather than systematic changes. Three models, Artificial Neural Networks (ANN), Long Short-Term Memory (LSTM) networks, and a Generalised Additive Model (GAM), were evaluated for anomaly forecasting, with feature selection guided by LASSO regression. For temperature, the LSTM performed better than the ANN and GAM, with MSE = 0.458, MAE = 0.457, MBE = 0.087, and MASE = 0.510. For temperature anomalies, the LSTM model performed best, followed by the GAM and ANN models. For precipitation anomalies, the LSTM model also achieved the lowest prediction error, with MSE = 0.187, MAE = 0.111, MBE = −0.009, and MASE = 1.873; however, MASE values above 1 indicate that rainfall forecasting remains challenging. These results show the LSTM model’s ability to handle temperature anomalies and the difficulty of modelling rainfall. GAM performed less accurately but steadily in modelling precipitation. Full article

Rainfall and streamflow analyses have long been central to hydrological research, yet traditional approaches often overlook the complexity introduced by changing climate signals, land-use dynamics, and human infrastructure. This study applies an integrated, data-driven framework to explore emerging hydroclimatic shifts in the Navasota River Watershed of east-central Texas. By combining autocorrelation analysis, Mann–Kendall and modified Mann–Kendall trend tests, and Pettitt’s change-point detection, we examine more than a century of precipitation and streamflow records alongside post-1978 reservoir operations. Results reveal an accelerating wetting tendency, particularly evident in decadal rolling averages and early-summer precipitation, accompanied by a statistically significant increase in 10-year moving averages of annual peak streamflow. While abrupt regime shifts were not detected, subtle but persistent changes point to evolving watershed memory and heightened flood risk in the post-dam era. This study reframes rainfall and streamflow trend analysis as a dynamic tool for anticipating hydrologic regime shifts, highlighting the urgent need for adaptive water infrastructure and flood management strategies in rapidly urbanizing and climate-sensitive watersheds. Full article

The response mechanisms of reinforced soil retaining wall structures under rainfall infiltration are not fully understood, leading to insufficient design guidelines. This study investigates a modular reinforced soil retaining wall model employing concrete blocks as the facing panel, standard sand as backfill, and a biaxial geogrid as reinforcement. Three sets of tests with varying rainfall intensities (150 mm/h, 300 mm/h, and 450 mm/h) were conducted to analyse and compare the response patterns of rainwater infiltration, earth pressure distribution, reinforcement strain, and displacement characteristics. The results indicate that with increasing rainfall intensity, the depth of infiltration influence extends across the entire wall section, with significant water accumulation at the base under heavy rainstorm conditions. The distribution pattern of static earth pressure is generally consistent across tests; however, a notable abrupt change reaching 8.59 kPa was observed at mid-height under rainstorm conditions. The strain increment distribution in the reinforcement is non-uniform, with increments under heavy rain and heavy rainstorm conditions being less than those under rainstorm conditions. The displacement of the wall panel is greatest in the middle and upper sections, with the smallest displacement occurring under rainstorm conditions. The displacement pattern shows a negative correlation with both the static earth pressure and the reinforcement strain patterns. These findings provide theoretical support for drainage design and stability control of reinforced soil retaining walls in regions experiencing heavy rainfall. Full article

This study focuses on a rapidly urbanizing coastal plain where river networks serve as critical pathways for pollutant transport to nearshore waters. Under frequent sluice control and sluggish hydrodynamics, pollutants accumulate in channels and are subsequently flushed during intense rainfall or sluice-opening events, increasing pollutant loads in downstream estuaries. Based on 2017–2024 water quality monitoring data, integrated multi-source environmental factor analysis and unmanned patrol boat technology, systematic water quality assessment and pollution source identification were conducted. Significant spatial heterogeneity was observed: phosphorus and nitrogen pollution dominated in the eastern region, whereas the permanganate index was more prominent in the western part of the network. Identification of abrupt water quality change sections revealed industrial wastewater as the primary contributor to phosphorus and nitrogen, whereas permanganate index pollution originated widely from aquaculture, agriculture, and industrial discharges. Atmospheric deposition likely provides a non-negligible contribution to phosphorus and nitrogen input, with fluxes strongly correlated to rainfall. Sediment release posed internal risks of carbon and phosphorus, with intensity positively linked to pollution levels. This study elucidates the water quality characteristics and multi-source pollution mechanisms in typical coastal river networks under rapid economic development. Therefore, it provides a scientific basis for precise regional water environment management and coastal water quality protection. Full article

For runoff-generated debris flow continuum mechanics-based early warning models, the computational unit must satisfy the homogeneity assumption of continuum mechanics. Although traditional grid cells meet the homogeneity assumption as computational units, they segment channel geomorphological functional reaches, weaken the clustered mobilization of sediment sources, and constrain efficiency due to grid-by-grid calculations. To address these limitations, we construct a Froude number ($Fr$) calculation model constrained by key factors such as the channel cross-sectional geometry and topographic parameters. The absolute deviation of $Fr$ is used as a criterion for homogeneity within the computational unit. By combining critical shear stress theory and velocity perturbation, physical thresholds for the criteria are derived. A physical model-based method for automatically delineating homogeneous channel units (${CU}_j$) is proposed, ensuring that the geometric features and hydrodynamic parameters within ${CU}_j$ are homogeneous, while ensuring heterogeneity between adjacent ${CU}_j$. Comprehensive multi-scale validation in Yeniu Gully, a typical debris flow catchment in Wenchuan County, demonstrates that parameters such as longitudinal gradient, cross-sectional area, flow depth, and shear stress remain relatively homogeneous within each ${CU}_j$ but differ significantly between adjacent ${CU}_j$. Furthermore, the proposed method can stably characterize key channel geomorphological functional units, such as bends, confluences, abrupt width changes, longitudinal gradient changes, erosion segments, and deposition segments. Sensitivity analysis demonstrates that the method satisfies both robustness and universality under various conditions of rainfall intensity, runoff coefficient, and Manning’s roughness coefficient. Even under the most unfavorable extreme conditions, the accuracy of ${CU}_j$ delineation exceeds 88.64%, indicating high reliability and suitability for deployment in various debris flow catchments. The proposed framework for defining ${CU}_j$ resolves the conflict in traditional computational units between the “continuum model homogeneity requirement” and “geomorphological functional unit continuity,” providing a more rational and efficient computational environment for runoff-generated debris flow continuum mechanics-based early warning models. Full article

Hamatocaulis vernicosus is a pleurocarpous moss of conservation concern, listed in Annex II of the EU Habitats Directive due to its significant and ongoing decline across Europe. H. vernicosus is also listed as ‘Vulnerable’ on the Red List of Romanian Bryophytes. Despite its protected status, the species remains under-recorded in Romania, where many potentially suitable habitats have yet to be surveyed. The ecosystems, classified as Transition mire and quaking bog (NATURA 2000 code: 7140), are wet peatlands with oligo- to mesotrophic conditions and a pH of 5.0–7.5 H. vernicosus is recorded in 58 Romanian locations (10 confirmed by us, 5 new), spanning the Continental and Alpine bioregions. Models showed good performance (AUC 0.79–0.83; TSS 0.54–0.59), with distribution mainly shaped by mean annual temperature and temperature range, and secondarily by precipitation. The species favors cold, stable climates with high seasonal rainfall. Even though the number of localities reported for this species has increased in recent years, this does not indicate an improvement in its conservation status, but rather is an effect of recent recording efforts. To support targeted conservation planning, an ensemble species distribution model was developed in order to predict the suitable habitats of H. vernicosus across Romania. Both climate models project major range losses for the varnished hook-moss: ~30% by 2050 and ~40–60% by 2100, depending on the scenario. Losses are gradual under SSP245 but more abrupt under SSP585, with increased fragmentation, especially between the Eastern and Southern Carpathians. By integrating field observations with predictive climate change modeling, our study brings critical insights applicable to the conservation of H. vernicosus and the unique peatland ecosystems it relies on. Full article

Creep through mainly vertical displacement along en echelon ground ruptures within the creeping segment of the West Valley Fault (WVF) in the Luzon Island, Philippines, has been occurring since first documented in the 90s. It is believed to have been triggered by excessive groundwater withdrawal, mainly because of the high rates of slip recorded in the 90s. Near-field displacements measured by locally fabricated linear variable differential transformer (LVDT) and ultrasonic creepmeters are compared with near-field long-term displacements as measured by precise leveling surveys. Though the ultrasonic creepmeter is less accurate in measuring short-term displacement than the LVDT creepmeter, both are reliable in measuring longer-term displacements. Data from creepmeters can reveal association of displacement with seasonal precipitation and correlation between short-term displacement and episodic rainfall. In the case of the WVF’s creeping segment, rainfall episodes and wet seasons do not always result in immediate abrupt displacement changes. Nevertheless, the results of our monitoring with creepmeters underscores the contribution of precipitation in triggering creep, through its effect on the ground and by releasing stored tectonic strain, in the southern region of the WVF’s creeping zone where groundwater withdrawal remains largely unregulated. Continuous monitoring and periodic leveling surveys should continue as creep continues to cause damage and the potential for induced seismicity remains. Full article

Precipitation concentration reflects the uneven temporal distribution of rainfall. It plays a critical role in water resource management and flood–drought risk under climate change. However, its long-term trends, associations with atmospheric teleconnections as potential drivers, and links to extreme heavy precipitation events remain poorly understood in complex basins like the Yangtze River Basin. This study analyzes these aspects using ground station data from 1960 to 2019 and conducts a comparison using the Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM (GPM IMERG) satellite product. We calculated three indices—Daily Precipitation Concentration Index (PCID), Monthly Precipitation Concentration Index (PCIM), and Seasonal Precipitation Concentration Index (SPCI)—to quantify rainfall unevenness, selected for their ability to capture multi-scale variability and associations with extremes. Key methods include Mann–Kendall trend tests for detecting changes, Hurst exponents for persistence, Pettitt detection for abrupt shifts, random forest modeling to assess atmospheric teleconnections, and hot spot analysis for spatial clustering. Results show a significant basin-wide decrease in PCID, driven by increased frequency of small-to-moderate rainfall events, with strong spatial synchrony to extreme heavy precipitation indices. PCIM is most strongly associated with El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). GPM IMERG captures PCIM patterns well but underestimates PCID trends and magnitudes, highlighting limitations in daily-scale resolution. These findings provide a benchmark for satellite product improvement and support adaptive strategies for extreme precipitation risks in changing climates. Full article

How to solve the contradiction between coal mining and soil and water conservation is a key scientific issue in the achievement of high-quality development in the middle reaches of the Yellow River. In this paper, the northern Shaanxi mining area in the middle reaches of the Yellow River is taken as the research area, and the surface loess micro-topography is taken as the entry point. The numerical simulation test and soil loss model calculation are used to reveal the different types of loess natural slope morphology (straight slope, concave slope, convex slope, and composite slope) and the natural slopes (5°, 15°, 25°, 35°, 45°). The influence characteristics and laws of the same mining on the surface loess slope morphology in the coal mining subsidence area are analyzed, and the soil erosion effect on the slope scale is analyzed. The results show that: (1) Coal mining subsidence will lead to an increase in the slope of the loess slope, and the smaller the natural slope, the greater the increase in slope. Among them, the influence of coal mining subsidence on the ‘concave loess slope with natural slope of 15°’ is the most significant, and the natural slope of 15° is the key dividing point for the transformation of the sensitive slope shape of the loess slope in the coal mining subsidence area of northern Shaanxi. (2) Coal mining subsidence will lead to the decrease in slope length of a loess natural slope, and the smaller the natural slope, the greater the decrease in slope length. Among them, coal mining subsidence has the most significant impact on the ‘concave loess slope with a natural slope of 25°’. The natural slope of 25° is the key point of the sudden change rate of the slope length of the loess slope in the coal mining subsidence area of northern Shaanxi. (3) Coal mining subsidence will lead to the increase in the soil erosion modulus on the surface loess slope under the scale of ‘annual erosion rainfall’ and ‘typical field erosion rainfall’, and the smaller the natural slope, the greater the increase in the soil erosion modulus. The natural slopes of 15° and 25° are the key points of the abrupt change in soil erosion intensity on the loess slope in the coal mining subsidence area of northern Shaanxi under the scales of ‘annual erosion rainfall’ and ‘typical erosion rainfall’, respectively. Under the scale of annual erosion rainfall, the increment of the 15° slope was 1.65 times, 1.12 times, 1.11 times, and 1.02 times that of the 5°, 25°, 35°, and 45° slopes, respectively. Under the typical erosion rainfall scale, the increment of the 25° slope was 4.22 times, 1.32 times, 1.04 times, and 1.15 times that of the 5°, 15°, 35°, and 45° slopes, respectively. (4) For the loess subsidence slope with any slope shape, the increase in slope gradient is the main factor for the increase in the soil erosion modulus. Under the annual erosion rainfall scale, the contribution of slope increase was 92.9%. Under the typical erosion rainfall scale, the contribution of slope increase was 79.1%. The research results can provide scientific guidance for soil erosion and control in the northern Shaanxi mining area in the middle reaches of the Yellow River Basin. Full article