Search Results (616)

Hydrological behavior plays a critical role in seasonally dry forest ecosystems, as it underpins water availability for multiple productive activities, including forestry, agriculture, grazing, and urban supply. This study evaluated the hydrological effects of thinning treatments in a semi-arid oak–pine forest of Chihuahua, Mexico, using a Before–After–Control–Impact (BACI) design. Three Micro-catchments (MC) with initially comparable tree density and canopy cover were monitored during the rainy seasons of 2018 (pre-thinning) and 2019 (post-thinning). Thinning treatments were applied at 20% and 60% canopy cover in two MC, while a third remained unthinned as a 100% control. Precipitation and surface runoff were recorded at the event scale, and data were analyzed using Weibull probability models with a log link to capture the frequency and magnitude of runoff events. Precipitation patterns were broadly comparable across years, although 2018 included an extreme storm event (59 mm). In contrast, runoff volumes in 2019 were lower despite marginally higher seasonal rainfall, reflecting the absence of large storms. Statistical modeling indicated that for each additional millimeter of precipitation, mean runoff increased by approximately 12%, although thinning significantly altered baseline conditions. Relative to 2018, mean runoff ratios were 0.087 in the 100% canopy catchment, 0.296 in the 60% treatment, and 0.348 in the 20% treatment, suggesting that reduced canopy cover retained proportionally more runoff than the control. BACI contrasts confirmed that thinned catchments maintained higher proportions of runoff than the unthinned control, although statistical significance was marginal for the 20% canopy treatment. Overall, the study provides ecohydrological insights relevant to the management of semi-arid forest ecosystems. Full article

The vulnerability of reservoirs in Mediterranean regions to eutrophication is attributable to two key factors: strong seasonal hydrological variability and intensive agricultural activity. The present study evaluated the trophic state of 47 reservoirs in the Ebro Basin in Spain using two complementary approaches: the Organisation for Economic Co-operation and Development (OECD) classification system and the criteria set out in Royal Decree (RD) 47/2022. Chlorophyll-a, total phosphorus and transparency data were monitored from 2023 to 2024. While most of reservoirs were classified as oligotrophic to mesotrophic under the OECD thresholds, the RD 47/2022 identified 87% as being at risk of eutrophication. A significant variation in transparency was observed among the different reservoir types (p < 0.05), with high-altitude systems showing higher levels of water transparency. However, chlorophyll-a and total phosphorus had a significant spatial variability, exhibiting only modest correlations. Chlorophyll-a was weakly but significantly correlated to transparency (r = −0.21), while total phosphorus was not significantly associated with either variable, suggesting a decoupling between nutrient availability and phytoplankton biomass. The observed discrepancy between the two classification frameworks is indicative of divergent conceptual approaches (ecological condition versus management risk). It underscores the requirement for integrated monitoring that incorporates chemical, biological and catchment-scale indicators. These findings offer new insight into the trophic dynamics of Mediterranean reservoirs and highlights the importance of adapting regulatory assessment methods to region-specific climatic and hydrological contexts. Full article

Understanding hydrochemical evolution and apportioning pollution sources are prerequisites for effective groundwater protection at the regional scale; nevertheless, the governing processes and anthropogenic drivers in arid regions remain poorly constrained. Here, we present a comprehensive geochemical survey of the Datong River Basin, a representative arid catchment in north-western China. Thirty-seven groundwater samples were analyzed with hydrochemical methods and Positive-Matrix Factorization (PMF) to delineate natural controls and contaminant sources. Results showed that the aquifer is dominated by HCO₃–Ca(Mg) water controlled predominantly by silicate and carbonate weathering, modified locally by evapo-concentration and human activities. Water-quality indices classify 70.3% of the samples as excellent, but spatially restricted degradation is evident. PMF resolved three independent sources: a natural end-member enriched in Mn, Na⁺ and Cl⁻; a mixed source reflecting domestic wastewater, agricultural fertilizers and rock weathering; and an industrial source dominated by Fe. The mixed source contributes most major ions and chemical oxygen demand (COD), whereas the industrial source accounts for 75.7% of total Fe. These findings provide a robust scientific basis for groundwater management and pollution mitigation in arid regions under similar hydrogeological settings. Full article

Understanding how water-quality models perform across different hydrological and biogeochemical contexts is essential for managing nutrient losses in agricultural catchments. This study evaluated SimplyP, a parsimonious phosphorus model, adapted to better represent Irish agricultural catchments and implemented within the flexible Mobius2 framework. Long-term, high-frequency monitoring data from the Agricultural Catchments Programme (ACP) were used for two sites: Ballycanew, a grassland catchment dominated by surface runoff, and Castledockrell, an arable, groundwater-driven catchment. Model calibration and validation were performed for streamflow (Q), suspended sediment (SS), and multiple phosphorus (P) fractions, with performance assessed using Kling–Gupta efficiency (KGE). In Ballycanew, the model reproduced Q, SS, and total P load well, with weaker agreement for total reactive phosphorus (TRP), likely reflecting unaccounted point sources during low flows. In Castledockrell, performance was moderate for Q and SS, but TRP and other P fractions were not adequately captured, highlighting the need for more detailed representation of subsurface P pathways in groundwater-dominated systems. Overall, SimplyP is well-suited to surface-runoff-dominated catchments with conventional phosphorus mobilisation. Its flexible implementation in Mobius2 allows relatively straightforward modifications, such as including groundwater-mediated P processes, to extend applicability to more complex systems. High-resolution ACP datasets were crucial for identifying model strengths and limitations, supporting refinement for improved nutrient management across diverse agricultural landscapes. Full article

Landslides are among the most significant disasters that threaten communities worldwide. This study sampled 384 respondents, using standardized interviews and field observations, to analyze how they perceived the factors influencing the incidence of landslides in the Kivu catchment of Rwanda, especially in landslide-prone areas. This study employs a mixed-methods approach that combines household surveys and interviews with key informants to assess how residents perceive landslide causes, warning signs, and impacts, which were analyzed statistically using SPSS. For further analysis, a binary logistic regression model and chi-square tests were used. The chi-square test findings highlighted that heavy rainfall, inappropriate agricultural practices, steep slopes, deforestation, road construction, earthquakes, and climate change were strongly correlated with landslide occurrence, with a p < 0.05 level of significance, while mining activities were not correlated with landslides. On the other hand, a binary logistic regression model revealed that, among the selected factors influencing landslide occurrence in the Kivu catchment, road construction (B = −0.644; p = 0.014), inappropriate agriculturalpractices (−1.177; p = 0.000), steep slopes (B = −0.648; p = 0.018), deforestation (B = −0.854; p = 0.007), and earthquakes (B = −1.59; p = 0.008) were negatively correlated, while heavy rainfall (B = 1.686; p = 0.000) and climate change (B = 1.784; p = 0.001) were positively correlated, and this was statistically significant for landslide occurrence at a p-value < 0.05. In contrast, mining activities (B = −0.065; p = 0.917) showed a negative coefficient that was statistically insignificant with respect to landslide occurrence in the study area. Future studies should integrate surveys with landslide hazard modeling tools for better spatial prediction of vulnerability and economic losses. Therefore, the findings from this study will contribute to sustainable natural disaster management planning in the western region of Rwanda. Full article

Hydrological droughts represent a growing challenge for northern watersheds in Thailand, where climate change is projected to intensify seasonal water stress and destabilize agricultural productivity and water resource management. This study employed the Composite Hydrological Drought Index (CHDI) to evaluate the spatiotemporal characteristics of future droughts under representative concentration pathway (RCP) scenarios. The findings revealed a pronounced seasonal contrast: under RCP8.5, the CHDI values indicated more severe drought conditions during the dry season and greater flood potential during the wet season. Consequently, the region faces dual hydrological threats: prolonged water deficits and increased flood exposure within the same annual cycle. Drought persistence is expected to intensify, with maximum consecutive drought runs extending up to 10–11 months in future projections. The underlying mechanisms include increased actual evapotranspiration, which accelerates soil moisture depletion, enhanced rainfall variability, which drives the sequencing of floods and droughts, and catchment storage properties, which govern hydrological resilience. These interconnected processes alter the timing and clustering of drought events, concentrating hydrological stress during periods that are sensitive to agriculture. Overall, drought behavior in northern Thailand is projected to intensify in a spatially heterogeneous pattern, emphasizing the need for localized, integrated adaptation measures and flexible water management strategies to mitigate future risks of drought. Full article

Gully is the most visible sign of land degradation, but its effects on runoff and sediment dynamics during snowmelt conditions remain poorly understood. This study monitored a typical gully in the Mollisols region of Northeast China to investigate runoff and sediment transport at the Gully Head (GH) and Gully Tail (GT) during spring snowmelt. Results showed that gully significantly influenced snow distribution, with deeper snow accumulation than on slopes. Runoff at the GH lasted 9 days, while gully connectivity extended catchment runoff by 10 additional days. Runoff temporal variation at GH and GT was broadly consistent, with GH contributing 7.4% of the total runoff at GT. Peak runoff discharge and sediment concentration occurred on the sixth day after snowmelt onset, driven by snow cover and air temperature. Gully significantly increased the sediment concentration from the upslope runoff. Runoff responses to temperature varied by melt stage, with GT showing higher sensitivity, especially under high-runoff conditions. High sediment yield was linked not to snow depth, but to late-stage snowmelt and soil thawing, when erosion sensitivity peaked. Hysteresis analysis revealed dominant clockwise loops during this phase, contrasting with figure-eight and counterclockwise patterns in other stages. These findings highlight the importance of targeting erosion control during late snowmelt when runoff intensifies and soils thaw. Full article

This dataset presents field observations collected in the municipality of Goiatuba, Goiás State, Brazil, a consolidated and representative agricultural frontier of the Brazilian Cerrado biome. The region presents diverse land use dynamics, including annual cropping systems, irrigated fields with up to three harvests per year, and pasturelands. We conducted a field campaign from 3 to 7 November 2025, corresponding to the beginning of the 2025/2026 Brazilian crop season, when crops were at distinct early phenological stages. To ensure representativeness, we delineated 117 reference fields prior to the field campaign, and an additional 463 plots were surveyed during work. Geographic coordinates, crop types, and photographic records were obtained using the GPX Viewer application, a handheld GPS receiver, and the QField 3.7.9 mobile GIS application running on a tablet uploaded with Sentinel-2 true-color imagery and the municipal road network. Plot boundaries were subsequently digitized in QGIS Desktop 3.34.1 software, following a conservative mapping strategy to minimize edge effects and internal heterogeneity associated with trees and water catchment basins. In total, more than 26,000 hectares of agricultural fields were mapped, along with additional land use and land cover polygons representing water bodies, urban areas, and natural vegetation fragments. All reference fields were labeled based on in situ observations and linked to Sentinel-2 mosaics downloaded via the Google Earth Engine platform. This dataset is well-suited for training, testing, and validation of remote sensing classifiers, benchmarking studies, and agricultural mapping initiatives focused on the beginning of the agricultural season in the Brazilian Cerrado. Full article

Rain-on-snow (ROS) events significantly impact hydrological processes in snowy regions, yet their seasonal drivers remain poorly understood, particularly in low-elevation and low-gradient catchments. This study uses an XGBoost-SHAP explainable artificial intelligence (XAI) model to analyze meteorological and watershed controls on ROS runoff in the Laurentian Great Lakes region. We used daily discharge, precipitation, temperature, and snow depth data from 2000 to 2023, available from HYSETS, to identify ROS runoff. The XGBoost model’s performance for predicting ROS runoff was higher in winter (R² = 0.65, Nash–Sutcliffe = 0.59) than in spring (R² = 0.56, Nash–Sutcliffe = 0.49), indicating greater predictability in colder months. The results reveal that rainfall and temperature dominated ROS runoff generation, jointly explaining more than 60% of total model importance, while snow depth accounted for 8–12% depending on season. Winter runoff is predominantly governed by climatic factors—rainfall, air temperature, and their interactions—with soil permeability and slope orientation playing secondary roles. In contrast, spring runoff shows increased sensitivity to land cover characteristics, particularly agricultural and shrub cover, as vegetation-driven processes become more influential. Snow depth effects shift from predominantly negative in winter, where snow acts as storage, to positive contributions in spring at shallow to moderate depths. ROS runoff responded positively to air temperatures exceeding approximately 2.5 °C in both winter and spring. Land cover influences on ROS runoff differ by vegetation type and season. Agricultural areas consistently increase runoff in both seasons, likely due to limited infiltration, whereas shrub-dominated regions exhibit stronger runoff enhancement in spring. The seasonal shift in dominant controls underscores the importance of accounting for land–climate interactions in predicting ROS runoff under future climate scenarios. These insights are essential for improving flood forecasting, managing water resources, and developing adaptive strategies. Full article

Reservoirs are hotspots for the coupling of nutrients and heavy metals, and they substantially modify the compositions and spatiotemporal distributions of microorganisms in fluvial systems. However, relatively few studies have been performed that investigate the microbial mechanisms driving interactions among heavy metals and nutrients in reservoirs. The Goupitan Reservoir, a seasonal stratified reservoir located within the Wujiang River catchment, was chosen as the research subject. The temporal and spatial variations in heavy metals and nutrients, and the metagenomic composition of the reservoir water were analyzed in January, April, July, and October 2019. The results revealed that As, Ni, Co, and Mn were derived primarily from mine wastewater, whereas Zn, Pb, Cd, and Cr were related to domestic and agricultural wastewater discharge. The study area was dominated by Proteobacteria, Actinobacteria, Cyanobacteria, and Bacteroidetes, with the proportion of dominant phyla reaching 90%. Decreases in the dissolved oxygen (DO) concentration and pH in the bottom water during July and October were conducive to increases in the abundance of the anaerobic bacterial groups Planctomycetes and Acidobacteria. The functional genes norBC and nosZ associated with denitrification (DNF), the key gene nrfAH involved in the dissimilatory nitrate reduction to ammonium (DNRA) process, the functional genes aprAB and dsrAB responsible for sulfate reduction/sulfide oxidation, as well as the thiosulfate oxidation complex enzyme system SOX, all exhibit high abundance in hypoxic water bodies and peak in the redoxcline, highlighting the significance of related nitrogen (N) and sulfur (S) metabolic processes. In addition, the concentrations of heavy metals significantly affected the spatial differentiation of the planktonic bacterial community structure, with Mn, Co, Fe, Ni, As, and Cu making relatively high individual contributions (p < 0.01). This study is important for elucidating the sources and microbiological mechanisms influencing heavy metals and nutrients in seasonally stratified subtropical reservoirs. Full article

Nitrate (NO₃⁻) pollution in rivers within agricultural regions has become a global issue that cannot be ignored. Identifying the sources and transformation processes of NO₃⁻ is crucial for safeguarding water quality in agricultural catchment areas. This study traces the sources and transformation processes of NO₃⁻ in the Songhua River basin of Northeast China by analysing hydrochemical parameters and NO₃⁻ dual isotopes (δ¹⁵N and δ¹⁸O) in river water. It estimates the proportional contributions of NO₃⁻ sources using Bayesian modelling via the MixSIAR package (3.1.12) in the R programming language. (1) The relatively low NO₃⁻/Cl⁻ ratio and high chloride concentrations in the upstream section indicate that the primary sources of NO₃⁻ in this area are manure and sewage (M&S). (2) Dual isotope analysis of NO₃⁻ indicates that the primary sources of NO₃⁻ in the Songhua River basin are M&S, soil nitrogen (SN), and chemical fertilizers (CF). (3) Nitrification occurs throughout the entire watershed. (4) Model estimation results indicate that SN constitutes the primary source of NO₃⁻ throughout the entire watershed (48%), with no significant variation observed across the studied river sections. However, other major NO₃⁻ sources exhibit spatially significant differences, primarily manifested as follows: M&S constitute the primary upstream source of NO₃⁻ (39%), whilst downstream contributions are predominantly attributable to CF (20%). Intermediate regions experience combined impacts from both MS and CF sources. Full article

Agricultural pollution, such as contamination from manure storage or leaking livestock buildings, often spreads through the catchment, affecting groundwater and surface water. An effective solution is the construction of permeable organic barriers. This study evaluates the efficiency of an innovative bioactive barrier in removing nitrogen compounds (NO₃⁻ and NH₄⁺) and polychlorinated biphenyls (PCBs). Two types of barriers were tested: a horizontal deposit under a manure storage point and a vertical deposit in the leachate flow path. The bioactivity of the barrier was confirmed by the presence of bacterial genes involved in nitrogen transformation and PCB degradation. Results showed a 70% reduction in NO₃⁻ (368.4 mg·L⁻¹) and 43% reduction in NH₄⁺ (42.4 mg·L⁻¹). Genetic analysis identified bacteria capable of complete denitrification, resembling Pseudomonas stutzeri. The analysis also indicated that higher summer temperatures and pH levels fostered microbial communities capable of nitrogen transformation. Cluster analysis revealed that the vertical deposit zone was crucial for nitrogen removal. Additionally, the vertical barrier achieved a 53% reduction in PCBs, with Pseudomonas aeruginosa-like bacteria identified as PCB degraders. Full article

Severe floods such as in the Ahr valley in July 2021 are one of the leading causes of fatalities from natural disaster. Riverine and lacustrine floods are caused by a sudden flux of water masses from heavy rainfall or snowmelts. These surface water runoff events significantly enhance erosion of detrital material in the catchment, which is then deposited in natural sinks such as lakes. We reconstructed flood phases from Eifel maar lakes over the last 60,000 years and compared flood behavior with regional riverine flood data covering the past 1000 years. Multi-centennial flood cycles persisted throughout the Holocene with durations of flood-poor periods significantly decreasing around 3700 years ago due to human activity in the Eifel region. Holocene flood frequency peaked in the 13th and 14th centuries during the medieval agricultural revolution. Late Pleistocene flood phases occurred during the Younger Dryas and Heinrich stadials and represent surface runoff events in cold and dry climates. As flood behavior is strongly affected not only by increased water supply but also by soil stability and erosion processes in the catchment area, flood phases reflect shifts in the prevailing climate conditions and vegetation cover, either through natural steppe formation or human impact. Full article

In the São Brás de Alportel municipality, water scarcity poses a significant constraint on agricultural activities. This study utilises Remote Sensing (RS) and Geographical Information Systems (GISs) to identify existing irrigated areas, delineate catchment basins, and select the most suitable sites for the installation of new surface water reservoirs. First, the principal territorial components were characterised, including physical elements (climate, geology, soils, and hydrography) and anthropogenic infrastructure (road network and high-voltage power lines). Summer Sentinel-2 satellite imagery was then analysed to calculate the Normalised Difference Vegetation Index (NDVI), enabling the identification and classification of irrigated agricultural parcels. Flow directions and accumulations derived from Digital Elevation Models (DEMs) facilitated the characterisation of 38 micro-catchments and the extraction of 758 km of the drainage network. The siting criteria required a minimum setback of 100 m from roads and high-voltage lines, excluded farmland currently in use, and favoured mountainous areas with low permeability. Only 18.65% (2854 ha) of the municipality is agricultural land, of which just 4% (112 ha) currently benefits from irrigation. The NDVI-based classification achieved a Kappa coefficient of 0.88, indicating high reliability. Three sites demonstrated adequate storage capacity, with embankments measuring 8 m, 10 m, and 12 m in height. At one of these sites, two reservoirs arranged in a cascade were selected as an alternative to a single structure exceeding 12 m in height, thereby reducing environmental and landscape impact. The reservoirs fill between October and November in an average rainfall year and between October and January in a dry year, maintaining a positive annual water balance and allowing downstream plots to be irrigated by gravity. The methodology proved to be objective, replicable, and essential for the sustainable expansion of irrigation within the municipality. Full article

Karst aquifers, vital freshwater resources, are highly vulnerable to agricultural pollution, yet their hydro-geochemical responses remain poorly understood due to high spatial heterogeneity. This study aimed to unravel these complex responses in a subtropical karst agricultural catchment to provide a basis for its sustainable management. We employed high-frequency monitoring at a headwater spring (background), a depression well (hotspot), and the catchment outlet (integrated) in Southwest China. Using hydrological and geochemical data from 2017, we applied Principal Component Analysis (PCA) to apportion natural and anthropogenic sources. The main findings revealed significant spatial heterogeneity, with the depression well acting as a contamination hotspot characterized by rapid hydrological responses and elevated SO₄²⁻ and Cl⁻ concentrations. PCA successfully decoupled an “anthropogenic factor” (PC1, 40.5%) from a “natural weathering factor” (PC2, 25.2%). Critically, agricultural SO₄²⁻ at the hotspot was counter-intuitively higher during the wet season than the dry season, opposing the typical dilution pattern of background ions and revealing that depressions act as contaminant-concentrating pathways, whose risks are severely underestimated by traditional outlet monitoring. The anomalous sulfate dynamics reveal a cross-seasonal “storage-and-release” mechanism (legacy effect) within the karst Critical Zone, demonstrating that these systems can buffer and “remember” contaminants. Full article