Search Results (15,456)

Across Africa, drought seldom occurs alone. Rainfall deficits often coincide with heat, rapid soil moisture loss and reduced streamflow, producing compound events whose impacts exceed those of any single driver. This review synthesises station observations, satellite and reanalysis products, and climate model simulations to clarify where such events are most common, how they form, how they affect societies and ecosystems, and how risks are changing. A practical tiered definition tailored to African conditions is outlined and applied to identify five recurrent hotspots: the Sahel, the Greater Horn of Africa, southern Africa, the margins of the Congo Basin and the Guinea Coast. The review sets out a physically consistent sequence that links basin-scale sea surface temperature anomalies to shifts in monsoon circulation, and then to land processes that amplify and prolong heat and dryness through reduced evapotranspiration and soil-moisture memory. Documented impacts include lower crop and pasture productivity, pressure on rivers, reservoirs and groundwater, stress on hydropower and wider consequences for food and energy security. Compound drought frequency across these hotspots has risen by 18–55% since 1980, with the probability of the most severe events roughly doubling at 1.5 °C of global warming and tripling at 3 °C. The review highlights near-term priorities, including compound-aware monitoring, sub-seasonal-to-seasonal early warning and conjunctive water management. Full article

Land Use and Land Cover (LULC) changes significantly influence flood hazard, especially in rapidly urbanizing areas like the Wadi Ibrahim watershed in Makkah, Saudi Arabia. This study analyzed the impacts of historical (2001–2025) and projected (2037) LULC changes on floods using remote sensing, GIS, and hydrological modeling with 30 m DEM and Landsat data. Urban growth was assessed from 2001, 2013, and 2025 maps, and future scenarios were simulated with the MOLUSCE plugin in QGIS using Cellular Automata–Artificial Neural Network (CA-ANN) techniques. Hydrological simulations were used to examine changes in flood discharge and response to LULC transitions. The results revealed substantial urban expansion, with built-up areas increasing from 12 km² (11%) in 2001 to 28.7 km² (26%) in 2025 and projected to reach 31.9 km² (28.3%) by 2037. The corresponding impervious surface fraction rose from 11% to 28% over the same period. Hydrological modeling for 50-, 100-, and 200-year return periods reveals a significant escalation in flood response, with peak discharge (Q_p) increasing by up to 12% and runoff volume (V) by approximately 9% between 2001 and 2037. The LULC classification using the Random Forest algorithm demonstrated strong and reliable performance, achieving an average Kappa (κ) value of 0.86, indicating almost perfect agreement. Overall, the findings underscore the need for sustainable land management to reduce flood risk in rapidly growing arid regions. Full article

The mountainous southwest of Saudi Arabia exhibits complex, highly seasonal precipitation driven by Indian Ocean monsoon inflows and orographic lifting. To characterize storm hyetographs, cluster analysis was applied to 8972 rainfall events recorded at 151 gauges. Two primary clusters emerged: one with early, intense peaks and another with later peak intensities, broadly reflecting windward versus leeward storm behavior. A locally derived hyetograph profile (AI) was constructed from the cluster centroids and benchmarked against standard design-storm distributions (Uniform, SCS Type II, Huff quartiles). Across fit metrics—cumulative RMSE, Kolmogorov–Smirnov distance, and cosine-intensity similarity—the AI distribution provided the best match for ~46% of storms, markedly outperforming canonical profiles (Uniform and SCS Type II each best-fit only ~11–12%). These results indicate that region-specific rainfall distributions more accurately represent precipitation patterns than conventional profiles, and that tailored hyetographs can improve hydrologic modeling and water-resources assessments in this climatically heterogeneous region. Full article

The primary aim of this study is to identify the driving mechanisms behind long-term water-level changes and drought–flood transitions in Dongting Lake. To achieve this, we employed methods including the Improved Standardized Water Level Index (ISWI), Mann–Kendall test, Sen’s slope estimator, and a random forest–SHAP model to analyze hydro-meteorological data from 1992 to 2023. The results demonstrate a significant overall decline and spatial heterogeneity in water levels, alongside a systemic shift in the regional pattern from flood-dominated conditions to frequent droughts with intense drought–flood abrupt alternations. Crucially, during the critical autumn water recession period, runoff anomalies from the Yangtze River’s three outlets emerged as the dominant factor driving water-level changes, far exceeding the influence of local precipitation. Furthermore, a recent downward shift in the water level–discharge relationship indicates that under identical inflow conditions, water levels are now 1.5 to 2.0 m lower than in previous decades. These general findings highlight that critical-period inflow reductions and altered boundary hydrodynamic conditions mutually amplify low-water-level risks, providing a scientific reference for adaptive water resource management in complex river-connected lakes. Full article

Comano thermal water (CTW) is a hypotonic, bicarbonate–calcium–magnesium mineral water traditionally used to manage chronic inflammatory and relapsing skin diseases. This review summarizes and discusses the available clinical, experimental, and translational evidence on CTW, with a particular focus on dermatological indications. The physicochemical properties of CTW, along with the presence of a stable, non-pathogenic microbial community, are examined in relation to their potential biological activity. Clinical studies indicate that CTW-based balneotherapy, alone or in combination with narrowband Ultraviolet B (UVB) phototherapy, is associated with improvements in disease severity, symptom burden, and quality of life in patients with psoriasis and atopic dermatitis, and has a favorable safety and tolerability profile. Experimental data further suggest that CTW may exert anti-inflammatory and immunomodulatory effects, modulate keratinocyte function, support skin barrier restoration, and influence the cutaneous microenvironment, including microbiome-related pathways. The review also outlines emerging evidence for CTW in skin regeneration and in upper airway inflammatory conditions treated via inhalation-based approaches. Overall, this review suggests that CTW may serve as a biologically active therapeutic resource, warranting further investigation as a complementary approach within integrative management strategies for inflammatory and barrier-related conditions. Full article

Accurate estimation of river discharge is fundamental for water resources management, flood forecasting, and drought monitoring in the Amazon River Basin. Rating curves, which relate water level (stage) to discharge, are the primary tool for streamflow estimation. This study evaluates traditional curve-fitting methods and machine learning algorithms for modeling rating curves at the two largest gauging stations in the Amazon River: Itacoatiara and Óbidos. The analysis is based on 70 stage–discharge measurements at Itacoatiara (2008–2023) and 176 measurements at Óbidos (1968–2023). Five modeling approaches were compared: Power Law, Linear Regression, Decision Tree, Random Forest, XGBoost, and Multi-Layer Perceptron (MLP). Model performance was assessed against official baseline rating curves maintained by Brazil’s National Water Agency (ANA) and the Geological Survey of Brazil (SGB/CPRM) using Root Mean Square Error (RMSE), coefficient of determination (r²), Mean Bias Error (MBE), Nash–Sutcliffe Efficiency (NSE) and Kling–Gupta Efficiency (KGE). Results indicate that ensemble-based machine learning methods, particularly XGBoost (RMSE = 7463 m³/s, NSE = 0.973 at Itacoatiara; RMSE = 18,378 m³/s, NSE = 0.872 at Óbidos), outperformed traditional methods. However, the Decision Tree exhibited overfitting that could not be resolved through pruning, depth limitation, or other strategies given the sample size. Traditional methods such as the optimized Power Law remain practical and transparent alternatives for operational use. The findings suggest that machine learning can complement traditional approaches for improving rating curve accuracy in large tropical rivers, with K-fold cross-validation used to assess variability and performance. Full article

Transboundary river basins (TRBs) sustain billions of livelihoods, yet they face enduring systemic challenges of cooperative water governance. Although collaborative governance models consistently yield acceptable outcomes, adversarial dynamics and zero-sum approaches continue to dominate transboundary water management. This systematic review synthesizes the peer-reviewed literature (2000–2026) to evaluate how four major governance dimensions—and the cross-cutting integration of the water–energy–food (WEF) nexus—shape the effectiveness of water diplomacy in international basins. Socio-economic analysis reveals that benefit-sharing arrangements grounded in joint investment outperform zero-sum volumetric allocation, though implementation remains constrained by institutional fragmentation and governance lock-in. Power relations analysis demonstrates that material, institutional, knowledge-based, and narrative-framing asymmetries systematically define the range of achievable agreements and the reliability of cooperative commitments, with case analysis from the Nile, Mekong, Tigris–Euphrates, and Central Asian basins showing that comparable hydrological conditions yield divergent diplomatic outcomes depending on how power is distributed. Stakeholder engagement findings indicate that formal participatory mechanisms frequently produce symbolic rather than substantive inclusion, particularly where structural imbalances limit procedural access. Gender analysis provides that women’s inclusion improves agricultural productivity, water-use efficiency, and adaptive capacity—functioning as a governance variable with measurable system-performance effects rather than solely an equity objective. The WEF nexus operates as the integrative mechanism binding these dimensions, reframing diplomacy from volumetric allocation toward adaptive benefit arrangements that coordinate interdependent services across sectors. This review concludes that effective transboundary governance emerges from the concurrent integration of socio-economic benefit-sharing, power-responsive institutions, meaningful stakeholder participation, gender equity, and nexus-based coordination in global TRBs. Full article

This study investigates the geochemical behavior and transport mechanisms of Rare Earth Elements (REEs), Yttrium (Y), Zirconium (Zr), and Hafnium (Hf) in three natural water systems under reducing conditions: the Santa Barbara and Occhio dell’Abisso mud volcanoes and a sulphureous spring at Villafranca Sicula. A comprehensive fractionation approach was applied to isolate the truly dissolved fraction (TDF < 10 kDa), the colloidal fraction (10 kDa < CF < 450 nm), the suspended particulate matter (SPM > 450 nm), and the associated bottom sediments. Analytical results reveal that REE distribution is significantly influenced by redox conditions and solid–liquid interface processes. The absence of negative Cerium (Ce) anomalies and the presence of pronounced positive Europium (Eu) anomalies in the Santa Barbara and Occhio dell’Abisso waters suggest strongly reducing environments where Eu²⁺ stability is enhanced. Shale-normalized patterns indicate that, while SPM and sediment fractions often exhibit Middle REE (MREE) enrichment, linked to Mn-bearing and Fe-oxyhydroxide phases, the dissolved phase reflects dissolution processes governed by a non-CHARAC (CHarge-and-RAdius-Controlled) behavior. Furthermore, the study highlights a significant decoupling in the Zr/Hf and Y/Ho pairs. While these pairs remain coherent during magmatic processes, they undergo mutual fractionation in aqueous systems due to differential reactivity toward colloidal surfaces and organic ligands. Specifically, Zr/Hf ratios in the colloidal and dissolved fractions deviate from chondritic values, driven by the preferential scavenging of Hf onto mineral surfaces. These findings underscore the utility of REE and Zr-Hf systematics as high-resolution tracers for reconstructing water–rock interaction processes and elemental cycling in complex hydrological environments. Full article

Background/Objectives: Eleocharis ussuriensis Zinserl. is a perennial riparian sedge widely distributed in Northeast Asia and a dominant component of freshwater vegetation in South Korea. However, the intraspecific genetic structure of this species across contrasting hydrological habitats remains insufficiently understood. This study aimed to develop novel SSR markers from whole-genome data and investigate genetic variation and population structure among E. ussuriensis populations in South Korea. Methods: Twenty-one novel simple sequence repeat (SSR) markers were developed from whole-genome sequence data and applied to analyze genetic variation in 120 individuals from 6 populations. Genetic diversity, differentiation, and gene flow were estimated using allele-frequency-based metrics, and population genetic structure was further evaluated using spatial information derived from geographic coordinates. Results: A total of 201 alleles were detected, with a mean polymorphism information content (PIC) of 0.759, indicating high marker informativeness. Mean genetic diversity across populations showed observed heterozygosity (Ho = 0.360) and expected heterozygosity (He = 0.281), while multilocus genotype ratios (G/N) ranged from 0.30 to 1.00 among populations. Genetic differentiation was substantial (F_ST = 0.373–0.669; Jost’s D = 0.540–0.997). Mantel tests revealed that genetic differentiation was significantly correlated with geographic distance (r = 0.67, p < 0.001). Both allele-frequency-based and spatially explicit approaches suggested genetic structuring among populations. Conclusions: The results suggest spatial tendencies in genetic structure among populations, reflecting patterns of allele distribution across regions. These findings provide baseline information on genetic variation in E. ussuriensis and may contribute to a better understanding of its ecological dynamics. Full article

This study advances research on river extreme events by applying the peaks-over-threshold (POT) approach to Lithuanian rivers. Extreme flow regimes were analysed for three rivers representing distinct hydrological regions and one large river. Results from the annual maximum series and three POT samples (POT1, POT2, and POT3) demonstrated the added value of the POT approach, as it enabled substantially more information on flood magnitude, frequency, and seasonality to be extracted from a single daily discharge time series. Trend analysis and seasonal flood frequency assessment revealed pronounced differences among rivers in regions with contrasting runoff-generation processes. Overall, the POT approach provided a more comprehensive characterisation of extreme flow behaviour, particularly for rivers susceptible to frequent flash flooding. Full article

Slope aspect is the primary topographic factor controlling the surface thermal state in mountainous cold regions. By modulating the magnitude and timing of solar radiation on slopes, it systematically affects soil temperature, maximum frost depth, and freeze–thaw timing, and it drives differentiation of the coupled hydrothermal process between sunny and shady slopes. However, the quantitative patterns of slope aspect freeze–thaw dynamics in high-latitude seasonally frozen soils and their response mechanisms to climate warming have not been systematically revealed. Therefore, based on field monitoring, this study used the SHAW model to simulate the soil freeze–thaw process and designed multiple warming scenarios to evaluate the evolving trend of the aspect effect. The results showed that: (1) the SHAW model effectively simulated soil temperature dynamics (R² = 0.939, NSE = 0.913, RMSE = 1.71 °C); (2) the profile-mean soil temperature on sunny slopes was 3.10 °C higher than on shady slopes, with a maximum frost depth approximately 61.2 cm shallower, freezing onset about 18 days later, complete thawing 59–77 days earlier, and freezing and thawing rates approximately 28% and 50% higher, respectively; and (3) under the SSP2-4.5 scenario, various freeze–thaw differentiation metrics did not exhibit a systematic convergence trend, and the aspect effect remained robust against climate warming. These findings offer a quantitative basis for ecological and hydrological assessment, water-resource scheduling, and foundation-stability design in cold regions, thereby supporting ecosystem conservation, sustainable water-resource use, and climate-resilient infrastructure development, and informing sustainable development planning and policy-making in high-latitude regions under a warming climate. Full article

The impact of wind on disdrometer measurements has not yet been demonstrated through controlled reproducible physical experiments. This study aims to provide quantitative evidence of the deviation in raindrop trajectories approaching the sensing area of an optical disdrometer (the Thies Clima LPM) when immersed in a wind flow with a known velocity and direction relative to the sensor orientation. To this end, water drops with diameters between 0.9 mm and 1 mm were released in a wind tunnel and directed towards the instrument’s sensing area. Their trajectories were measured using a high-speed camera and compared with those expected in undisturbed conditions, as well as with the airflow field around the instrument body as measured in previous studies. This experiment provided the first direct measurement of the deviation in individual drop trajectories induced by wind near the Thies Clima LPM, a disdrometer commonly used in hydrological studies and applications. The effect of the non-radially symmetric geometry of the instrument on wind direction was observed, identifying the configuration most affected (parallel to the laser beam). The repeatability of the drop releasing system was checked by releasing multiple drops from the same position. This allowed attributing differences in the observed trajectories to a variation in the drop diameter. The collected dataset can be used to validate numerical models of the wind-induced bias of disdrometers and to develop adjustment functions for field measurements. Full article

Quantifying glacier contributions to river discharge is challenging because many land surface models (LSMs) lack glacier processes, whereas standalone glacier models are often disconnected from catchment hydrology. Here we develop the Conjunctive Surface–Subsurface Process model version 2-glacier coupled model (CSSPv2-GLC), and evaluate it over the Three-River Headwaters Region (TRHR) at 3 km during 1979–2017. The glacier coupling raises Nash–Sutcliffe Efficiency for monthly streamflow simulation at Tuotuohe station from 0.63 to 0.79 during calibration and from 0.61 to 0.76 during validation. CSSPv2-GLC reduces glacier surface temperature error to 1.85 K, compared with 3.09 K for the CSSPv2. Glacier meltwater contributions to total discharge reached 11.5% in July and 10.8% in August in the Yangtze headwaters. In contrast, the Lancang and Yellow headwaters contributed up to 4.5% and 1.8% in August. Dry-year contributions are 2–3 times higher than wet-year values, indicating a transient drought-buffering effect. These results demonstrate the value of integrating physically explicit glacier processes into land surface modeling frameworks for water resource assessment in glacierized headwater regions, and highlight the necessity of accounting for non-stationary glacier contributions to streamflow. Full article

Landslides are one of the most common natural hazards in China, and the efficient screening of important factors is crucial for landslide susceptibility mapping. Taking the Zigui–Badong section of the Three Gorges Reservoir Area (TGRA) as the study area, this research initially selected 25 evaluation factors based on topography, geology, hydrology, remote sensing images, and previous studies. Thirteen key factors were obtained through analysis. Three machine learning models—RF, DT, and XGBoost—were then used for landslide susceptibility mapping, with SHAP and LIME employed to interpret the models. Finally, a scoring method was used to rank the six sets of results and compare them with those from the traditional AUC-based Recursive Feature Elimination (AUC-RFE) method. The results showed that the core factor sets screened by interpretable methods outperformed those from AUC-RFE. To further obtain accurate core factor sets, two additional interpretable methods—PI and Explainable Boosting Machine (EBM)—were integrated, ultimately identifying a core factor set consisting of eight factors including Elevation, Slope Height, and Aspect. This set achieved an AUC value of 0.931, only 0.003 lower than that of the 13 filtered factors. The screening method proposed in this paper can significantly improve the efficiency of factor acquisition, reduce the difficulty of factor acquisition, and provide a new approach for the selection of key factors in landslide susceptibility assessment. Full article

Stochastic inputs are essential for incorporating hydrological variability in water resources assessment, planning, and management. However, most studies focus on the generation of precipitation and temperature, precipitation and streamflow, and precipitation and evaporation, with limited incorporation of groundwater levels. This study assessed the ability of the Variable Length Block (VLB) bootstrapping model for simultaneously generating stochastic sequences of rainfall, evaporation, and groundwater levels. The performance of the model was assessed by comparing single statistics of historical time series located within the box plots of 100 annual and monthly stochastically generated time series. The model preserved eight of the nine statistics adequately, except for skewness, across all variables, with historical values for evaporation and groundwater levels falling below and above the interquartile range for 12 months. All the historic statistics for rainfall, evaporation, and groundwater levels were within the interquartile ranges of the box plots for 83, 71, and 71% of the time, respectively. The historic statistics for rainfall, evaporation, and groundwater levels were within the box plot ranges for 100, 98, and 99% of the time, respectively. These findings indicated reasonably successful generation, and the VLB generator was therefore considered applicable for the stochastic generation of multiple hydrometric data types. Full article