Search Results (593)

Tropical cyclones can rapidly alter watershed chemistry by shifting hydrologic pathways and mobilizing stored nutrients, yet these disturbances often remain undetected when storms cause little visible flooding or geomorphic damage. During Hurricane Helene 2024, intense rainfall across the Oconee River watershed in Georgia generated sharp increases in discharge that triggered substantial nutrient export despite minimal physical alteration to the landscape. High-frequency measurements of nitrate, phosphate, and sulfate in urban, forested, and recreational settings revealed pronounced and synchronous post-storm increases in all three solutes. Nitrate showed the strongest and most persistent response, with mean concentrations increasing from approximately 1–3 mg/L during pre-storm conditions to 6–14 mg/L post-storm across sites, and remaining elevated for several months after hydrologic conditions returned to baseline. Phosphate concentrations increased sharply during the post-storm period, rising from pre-storm means of ≤0.3 mg/L to a post-storm average of 1.5 mg/L, but declined more rapidly during recovery, consistent with sediment-associated mobilization and subsequent attenuation. Sulfate concentrations also increased substantially across the watershed, with post-storm mean values commonly exceeding 20 mg/L and maximum concentrations reaching 41 mg/L, indicating sustained dissolved-phase release and enhanced temporal variability. Recovery trajectories differed by solute: phosphate returned to baseline within weeks, nitrate declined gradually, and sulfate remained elevated throughout the winter. These findings demonstrate that substantial chemical perturbations can occur even in the absence of visible storm impacts, underscoring the importance of event-based, high-resolution monitoring to detect transient but consequential shifts in watershed biogeochemistry. They also highlight the need to better resolve solute-specific pathways that govern nutrient mobilization during extreme rainfall in mixed-use watersheds with legacy nutrient stores and engineered drainage networks. Full article

In regions lacking sufficient data, remote sensing (RS) offers a reliable alternative for precipitation estimation, enabling more effective drought management. This study comprehensively evaluates four commonly used RS datasets—Climate Hazards Center InfraRed Precipitation with Station data (CHIRPS), Tropical Applications of Meteorology using Satellite data (TAMSAT), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), and Multi-Source Weighted-Ensemble Precipitation (MSWEP) against ground-based data—with respect to their performance in detecting precipitation and drought patterns in the Great Ruaha River Basin (GRRB), Tanzania (1983–2020). Statistical metrics including the Pearson correlation coefficient (r), mean error (ME), root mean square error (RMSE), and bias were employed to assess the performance at daily, monthly, seasonal (wet/dry), and annual timescales. Most of the RS products exhibited lower correlations (r < 0.5) at daily timestep and low RMSE, bias, and ME. Monthly performance improved substantially (r > 0.8 at most stations) particularly during the wet season (r = 0.52–0.82) while annual and dry-season performance declined (r < 0.5 and r < 0.3, respectively). Performance under RMSE, bias, and ME declined at higher timescales, particularly during the wet season and annually. CHIRPS, MSWEP, and PERSIANN generally overestimated precipitation while TAMSAT consistently underestimated it. Spatially, CHIRPS and MSWEP reproduced coherent basin-scale patterns of drought persistence, with longer dry-spells concentrated in the northern, central, and western parts of the basin and shorter dry-spells in the eastern and southern regions. Trend analysis further revealed that most products captured consistent large-scale changes in dry-spell characteristics, although localized drought events were more variably detected. CHIRPS and MSWEP showed superior performance especially in capturing monthly precipitation patterns and major drought events in the basin. Most products struggled to detect extreme dry conditions with the exception of CHIRPS and MSWEP at certain stations and periods. Based on these findings, CHIRPS and MSWEP are recommended for drought monitoring and water resource planning in the GRRB. Their appropriate use can help water managers make informed decisions, promote sustainable resource use, and strengthen resilience to extreme weather events. Full article

The Mun River Basin, the largest Mekong tributary in Northeast Thailand, has experienced extensive agricultural expansion and forest decline, raising concerns over increasing soil erosion and sediment transfer. This study provides an integrated assessment of soil loss, sediment yield (SY), and sediment delivery ratio (SDR) across 19 sub-watersheds using the Universal Soil Loss Equation (USLE), field-based SY data, and multivariate statistical analyses in 2024. Basinwide soil loss was estimated at ~35 million t y⁻¹ (mean 4.96 t ha⁻¹ y⁻¹), with more than 80% of the basin classified in the no erosion to very low erosion classes. Despite substantial hillslope erosion, only 402,405 t y⁻¹ of sediment reaches the river network, corresponding to a low SDR of 1.15%, which falls within the range reported for large tropical watersheds with significant reservoir infrastructure. Soil loss is most strongly influenced by slope and forested terrain, while SY responds primarily to rainfall and tree plantations; urban land, croplands, and reservoirs act as sediment sinks. Principal Component Analysis (PCA) resolved multicollinearity and produced six components explaining over 90% of predictor variance. A PCA-based regression model predicted SY per unit area with high accuracy (r = 0.81). The results highlight the dominant roles of hydroclimate and land-use structure in shaping sediment connectivity, supporting targeted soil and watershed-management strategies. Full article

This study evaluated the water supply and regulation of the San Pedro River basin, located in the municipality of Puerto Libertador (Córdoba, Colombia), under climate change scenarios, using the SWAT (Soil and Water Assessment Tool) hydrological model. The model was calibrated and validated in SWAT-CUP using the SUFI-2 algorithm, based on observed streamflow series and sensitive hydrological parameters. Observed and satellite climate data, CHIRPS for precipitation and ERA5-Land for temperature, radiation, humidity, and wind, were employed. Climatic data were integrated along with spatial information on soils, land use, and topography, allowing for an adequate representation of the basin’s heterogeneity. The model showed acceptable performance (NSE > 0.6; PBIAS < ±15%), reproducing the seasonal variability and the average flow behavior. Climate projections under RCP 4.5 and RCP 8.5 scenarios, derived from the MIROC5 model (CMIP5), indicated a slight decrease in mean streamflow and an increase in interannual variability for the period 2040–2070, suggesting a potential reduction in surface water availability and natural hydrological regulation by mid-century. The Water Regulation Index (WRI) exhibited a downward trend in most sub-basins, particularly in areas affected by forest loss and agricultural expansion. The WRI showed a downward trend in most sub-basins, especially those with loss of forest cover and a predominance of agricultural uses. These findings provide basin-specific evidence on how climate change and land-use pressures may jointly affect hydrological regulation in tropical Andean–Caribbean basins. These results highlight the usefulness of the SWAT model as a decision-support tool for integrated water resources management in the San Pedro River basin and similar tropical Andean–Caribbean catchments, supporting basin-scale climate adaptation planning. They also emphasize the importance of conserving headwater ecosystems and forest cover to sustain hydrological regulation, reduce vulnerability to flow extremes, and enhance long-term regional water security. Full article

The Philippines experiences intense rainfall but has limited ground-based monitoring infrastructure for flood prediction. Satellite rainfall products provide broad coverage but contain systematic biases that reduce operational usefulness. This study evaluated whether three correction methods—Quantile Mapping (QM), Random Forest (RF), and Hybrid Ensemble—maintain accuracy when applied to future periods with substantially different rainfall characteristics. Using the Cagayan de Oro River Basin in Northern Mindanao as a case study, models were trained on 2019–2020 data and tested on an independent 2021 period exhibiting 120% higher mean rainfall and 33% increased rainy-day frequency. During training, Random Forest and Hybrid Ensemble substantially outperformed Quantile Mapping (R² = 0.71 and 0.76 versus R² = 0.25 for QM). However, when tested under realistic operational constraints using seasonally incomplete calibration data (January–April only), performance rankings reversed completely. Quantile Mapping maintained operational reliability (R² = 0.53, RMSE = 5.23 mm), while Random Forest and Hybrid Ensemble failed dramatically (R² dropping to 0.46 and 0.41, respectively). This demonstrates that training accuracy poorly predicts operational reliability under changing rainfall regimes. Quantile Mapping’s percentile-based correction naturally adapts when rainfall patterns shift without requiring recalibration, while machine learning methods learned magnitude-specific patterns that failed when conditions changed. For flood early warning in data-limited basins with equipment failures and variable rainfall, only Quantile Mapping proved operationally reliable. This has practical implications for disaster risk reduction across the Philippines and similar tropical regions where standard validation approaches may systematically mislead model selection by measuring calibration performance rather than operational transferability. Full article

Parametric tropical cyclone models are widely used to generate large wind field ensembles for assessing extreme storm tides and wave heights. The radius of maximum wind (RMW) is a key model parameter and is commonly estimated using empirical formulas. This study shows that uncertainty introduced by the choice of RMW formulas has been largely overlooked in tropical cyclone risk assessments. Using the Pearl River Estuary as a case study, historical wind fields (1981–2024) were generated with a parametric tropical cyclone model combined with eight empirical RMW formulas. Storm tides and wave heights during tropical cyclone events were simulated using a coupled wave–current model (ROMS–SWAN) and analyzed with extreme value theory. The results indicate that, for estuarine nearshore zones, the 100-year return period of water level and significant wave height vary by up to 1.26 m and 1.54 m, respectively, across all the selected RMW formulas. Joint probability analysis further shows that RMW uncertainty can shift the joint return period of the same compound storm tide and wave event from 100 years to 10 years. For an individual extreme event, differences in the RMW formula alone can produce deviations up to 2.11 m in peak storm tide levels and 3.8 m in significant wave heights. Such differences can also change the duration of extreme sea states by 13 h. These results highlight that RMW formula selection is a critical uncertainty factor, and related uncertainty should be considered in large-sample tropical cyclone hazard assessment and engineering design. Full article

Under concurrent global warming and multi-scale climate anomalies, regional precipitation has become more uneven and less stable, and extreme events occur more frequently, amplifying water scarcity and ecological risk. Focusing on mainland China, we analyze nearly 70 years of monthly station precipitation records together with eight climate drivers—the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), Multivariate ENSO Index (MEI), Arctic Oscillation (AO), surface air pressure (AP), wind speed (WS), relative humidity (RH), and surface solar radiation (SR)—and precipitation outputs from eight CMIP6 models. Using wavelet analysis and partial redundancy analysis, we systematically evaluate the qualitative relationships between climate drivers and precipitation and quantify the contribution of each driver. The results show that seasonal precipitation decreases stepwise from the southeast toward the northwest, and that stability is markedly lower in the northern arid and semi-arid regions than in the humid south, with widespread declines near the boundary between the second and third topographic steps of China. During the cold season, and in the northern arid and semi-arid zones and along the margins of the Tibetan Plateau, precipitation varies mainly with interdecadal swings of North Atlantic sea surface temperature and with the strength of polar and midlatitude circulation, and it is further amplified by variability in near-surface winds; the combined contribution reaches about 32% across the Northeast Plain, the Junggar Basin, and areas north of the Loess Plateau. During the warm season, and in the eastern and southern monsoon regions, precipitation is modulated primarily by tropical Pacific sea surface temperature and convection anomalies and by related changes in the position and strength of the subtropical high, moisture transport pathways, and relative humidity; the combined contribution is about 22% south of the Yangtze River and in adjacent areas. Our findings reveal the spatiotemporal variability of precipitation in China and its responses to multiple climate drivers and their relative contributions, providing a quantitative basis for water allocation and disaster risk management under climate change. Full article

Three ageing reservoirs in Ekiti State, Nigeria (Ureje constructed in 1958, Egbe in 1982, and Ero in 1989), were comparatively assessed to evaluate fish assemblages and their conservation relevance. Despite the absence of formal fisheries governance, all three reservoirs supported temporally stable fish communities with low overall diversity. A core assemblage of six species dominated across sites, while species richness increased from seven species in the small urban Ureje reservoir to nine species in the larger and more rural Ero reservoir. Four native species that have become locally scarce in surrounding river systems (Heterotis niloticus, Parachanna obscura, Hepsetus odoe, and Hyperopisus bebe) persisted at low but consistent abundance. Aquatic environmental variables remained within suitable limits for freshwater fishes, and trophic structure appeared intact across the reservoirs. Catch density was substantially higher in the urban reservoir compared to the rural systems, reflecting spatial differences in fishing intensity. Overall, the findings demonstrate that small tropical reservoirs can function as important freshwater habitats that sustain fish biodiversity and fisheries production in modified landscapes. Full article

This study investigates spatial and seasonal variation in the assemblages of benthic microgastropods (snails < 5–10 mm in length) within a poorly studied tropical bay. As these organisms are abundant, diverse and relatively easy to sample, with well-established taxonomy, they may prove a highly suitable group for ecological studies in such areas. Sediment samples were collected from three river basins in Camamu Bay, Brazil, during the wet and dry seasons. A total of 132 microgastropod species was recorded, demonstrating high diversity. The most abundant species were Eulithidium affine, Bittiolum varium, Cerithium atratum, Vitta virginea and Schwartziella bryerea. The least abundant species were Tenaturris gemma, Turbinella laevigata, Petaloconchus erectus, Parviturboides interruptus and Vitrinella cupidinensis. Statistical analysis revealed significant seasonal and spatial differences in diversity and assemblage composition, which correlated with environmental gradients. The results suggest that microgastropods are a suitable component of the biota for ecological and applied studies in marine sediments, particularly in remote tropical locations where full macrofaunal analysis may be challenging. Whilst further testing across impact gradients is needed, this approach offers a practical solution for ecological investigations in remote regions with limited taxonomic expertise and highlights microgastropods as a useful indicator taxon for impact biomonitoring in tropical marine sediments. Full article

This study investigates the impact of eddy viscosity on equatorially trapped waves and the instability of the background shear in a simple barotropic–baroclinic model. It is the first study to include eddy viscosity in the study of tropical wave dynamics. This study also unifies the study of baroclinic and barotropic instabilities by using a coupled barotopic and baroclinic model of the tropical atmosphere. Linear wave theory is combined with a systematic Galerkin projection of the baroclinic dynamical fields onto parabolic cylinder functions. This study investigates varying shear strengths, eddy viscosities, and their combined effects. In the absence of shear, baroclinic and barotropic waves decouple. The baroclinic waves themselves separate into triads, forming the equatorially trapped wave modes known as Matsuno waves. However, when a strong eddy viscosity is included, the structure and propagation characteristics of these equatorial waves are significantly altered. Different wave types interact, leading to strong mixing in the meridional direction and coupling between meridional modes. This coupling destroys the Matsuno mode separation and offers pathways for these waves to couple and interact with one another. These results suggest that viscosity does not simply suppress growth; it may also reshape the propagation characteristics of unstable modes. In the presence of a background shear, some wave modes become unstable, and barotropic and baroclinic waves are coupled. Without eddy viscosity, instability begins with small scale and slowly propagating modes, at arbitrary small shear strengths. This instability manifests as an ultra-violet catastrophe. As the shear strength increases, the catastrophic instability at small scales expands to high-frequency waves. Meanwhile, instability peaks emerge at synoptic and planetary scales along several Rossby mode branches. When a small eddy viscosity is reintroduced, the catastrophic small-scale instabilities disappear, while the large-scale Rossby wave instabilities persist. These westward-moving modes exhibit a mixed barotropic–baroclinic structure with signature vortices straddling the equator. Some vortices are centered close to the equator, while others are far away. Some waves resemble synoptic-scale monsoon depressions and tropical easterly waves, while others operate on the planetary scale and present elongated shapes reminiscent of atmospheric-river flow patterns. Full article

Groundwater is one of the main sources of water supply in tropical developing countries; however, its integrated management is often constrained by limited hydrogeological information and increasing anthropogenic pressures on aquifer systems. This study presents the numerical modeling of groundwater flow in the Neogene–Quaternary aquifer system of the Middle Magdalena Valley (Colombia), focusing on the rural area of Puerto Wilches, which is characterized by strong surface–groundwater interactions, particularly with the Yarirí wetland and the Magdalena River. A three-dimensional model was implemented and calibrated in FEFLOW v.8.1 under steady-state and transient conditions, integrating both primary and secondary data. The dataset included piezometric levels measured with water level meters and automatic loggers, hydrometeorological records, 21 physicochemical and microbiological parameters analyzed in 45 samples collected during three field campaigns under contrasting hydrological conditions, 79 pumping tests, detailed lithological columns from drilled wells, and complementary geological and geophysical models. The results indicate a predominant east–west groundwater flow from the Eastern Cordillera toward the Magdalena River, with seasonal recharge and discharge patterns controlled by the bimodal rainfall regime. Microbiological contamination (total coliforms in 69% of groundwater samples) and nitrate concentrations above 10 mg/L in 21% of wells were detected, mainly due to agricultural fertilizers and domestic wastewater infiltration. Particle tracking revealed predominantly horizontal flow paths, with transit times of up to 800 years in intermediate units of the Real Group and around 60 years in shallow Quaternary deposits, highlighting the differential vulnerability of the system to contamination. These findings provide scientific foundations for strengthening integrated groundwater management in tropical regions under agroindustrial and hydrocarbon pressures and emphasize the need to consolidate monitoring networks, promote sustainable agricultural practices, and establish preventive measures to protect groundwater quality. Full article

Understanding the processes that shape parasite community structure across spatial scales is essential for linking ecological theory with host–parasite dynamics. Using a metacommunity framework, we examined the metacommunity of helminth parasites infecting the freshwater fish Pseudoxiphophorus bimaculatus across 11 sites along the La Antigua River basin (Veracruz, Mexico). We combined β-diversity partitioning, local and species contributions to diversity, elements of metacommunity structure (EMS), and variance partitioning to identify the mechanisms underlying spatial variation in parasite composition. Helminth metacommunity was dominated by a few widespread taxa, with balanced variation in species abundances—indicative of turnover—emerging as the main driver of β-diversity at both host and site levels. Both rare and common species contributed disproportionately to regional diversity. EMS analyses revealed coherent, non-random community structures that varied from nested to quasi-Gleasonian and quasi-Clementsian types among sites and guilds, suggesting that species respond individually to shared environmental gradients. Variance partitioning indicated that environmental filtering, particularly through habitat structure, explained most of the variation in community composition, exceeding the effects of water quality and host size. Overall, our results demonstrate that turnover, species uniqueness, and environmental filtering interact to shape helminth parasite metacommunities in tropical freshwater systems, highlighting the integrative role of environmental heterogeneity and dispersal limitation in parasite community assembly. Full article

Soil organic carbon (SOC) plays a crucial role in climate change mitigation by regulating atmospheric CO₂ and maintaining ecosystem balance; however, its stability is influenced by land use in anthropized areas such as the tropical Andes. This study developed a dynamic compartmental model based on ordinary differential equations to simulate carbon fluxes among litter, humus, and microbial biomass under four land uses in the Las-Piedras River basin (Popayán, Colombia): riparian forest (RF), ecological restoration (ER), natural-regeneration (NR), and livestock (LS). The model includes two decomposition rate constants: k₁, for the transformation of fresh organic matter, and k₂, for the turnover of humified organic matter. It was calibrated using field data on soil physicochemical and biological properties, as well as carbon inputs and outputs. The results showed clear differences in SOC dynamics among land uses: RF had the highest SOC stocks (148.7 Mg ha⁻¹) and microbial biomass, while LS showed the lowest values and the greatest deviation due to compaction and low residue input. The humus fraction remained the most stable pool (k₂ ≈ 10⁻⁴ month⁻¹), confirming its recalcitrant nature. Overall, the model reproduced SOC behavior accurately (MAE = 0.01–0.30 Mg ha⁻¹) and provides a framework for improving soil carbon management in mountain ecosystems. Full article

The Tarim Basin is currently the largest petroliferous basin in China, with hydrocarbons primarily hosted in Ordovician marine carbonate paleokarst fracture–vug reservoirs—a typical example being the Tahe Oilfield located in the northern structural uplift of the basin. The principle of “the present is the key to the past” serves as a core method for studying paleokarst fracture–vug reservoirs in the Tahe Oilfield. The deep and ultra-deep carbonate fracture–vug reservoirs in the Tahe Oilfield formed under humid tropical to subtropical paleoclimates during the Paleozoic Era, belonging to a humid tropical–subtropical paleoepikarst dynamic system. Modern karst types in China are diverse, providing abundant modern karst analogs for paleokarst research in the Tarim Basin. Carbonate regions in Eastern China can be divided into two major zones from north to south: the arid to semiarid north karst and the humid tropical–subtropical south karst. Karst in Northern China is characterized by large karst spring systems, with fissure–conduit networks as the primary aquifers; in contrast, karst in Southern China features underground river networks dominated by conduits and caves. From the perspective of karst hydrodynamic conditions, the paleokarst environment of deep fracture–vug reservoirs in the Tarim Basin exhibits high similarity to the modern karst environment in Southern China. The development patterns of karst underground rivers and caves in Southern China can be applied to comparative studies of carbonate fracture–vug reservoir structures in the Tarim Basin. Research on modern and paleokarst systems complements and advances each other, jointly promoting the development of karstology from different perspectives. Full article

Microbial communities play a crucial role in coastal ecosystem function, yet their seasonal and spatial dynamics in response to environmental change remain underexplored in tropical and subtropical regions. This yearlong study investigated microbial composition in water, sinking particles, and sediments along an inshore–offshore gradient influenced by the Caloosahatchee River Estuary in southwest Florida. The region has been altered by rapid coastal development and was struck by Hurricane Ian in September 2022. Environmental parameters exhibited significant spatiotemporal variation, shaping microbial beta diversity in all habitats. Sediment communities showed the greatest hurricane-induced disruption but returned to pre-disturbance conditions within six months. Dominant microbial classes included Alphaproteobacteria, Bacteroidia, and Gammaproteobacteria. Biogeochemical cycling taxa displayed strong habitat specificity, such as Desulfobulbia which dominated sinking particles, Desulfobacteria which was abundant in sediments, and Nitrosomonadaceae and Nitrosopumilaceae which were key nitrifiers in water and sediments, respectively. Particle–sediment taxonomic overlap suggests resuspension processes. Several inshore microbial indicators were consistently present across microbial habitats, especially at estuarine sites, suggesting the estuary as a microbial diversity reservoir for the coastal zone. These results highlight the value of long-term microbial monitoring to understand ecosystem change and resilience in dynamic coastal environments. Full article