Search Results (6,780)

Building height is a key indicator of vertical urbanization and urban morphological complexity, yet accurately mapping building height at fine spatial resolution and large spatial scales remains challenging. This study proposes an attention-based deep learning framework (ABHNet) for building height estimation at a 10 m spatial resolution by integrating multi-source remote sensing data and socioeconomic information. The model jointly exploits Sentinel-1 synthetic aperture radar data, Sentinel-2 multispectral imagery, and point of interest (POI) data. The proposed framework is evaluated in Shanghai, a megacity with dense and vertically complex urban structures, using Baidu Maps-derived building height data as reference information. The results demonstrate that the proposed method achieves accurate building height estimation, with a root mean squared error (RMSE) of 3.81 m and a mean absolute error (MAE) of 0.96 m for 2023, and an RMSE of 3.30 m and an MAE of 0.78 m for 2019, indicating robust performance across different time periods. Also, this model is applied in two other cities (Changzhou and Guiyang) and the results indicate good performance. In addition, the expandability of the framework is examined by incorporating higher-resolution ZY-3 imagery, for which the spatial resolution was increased to 2.5 m, highlighting the potential extension of the model to heterogeneous data sources. Overall, this study demonstrates the effectiveness of attention-based deep learning and multimodal data fusion for large-scale and fine-resolution building height estimation using open-source data. Full article

This research investigates the relationships between the parameters of the GR4J hydrological model and a set of morphometric descriptors, climatic indices, land-cover characteristics, and soil properties across the Caquetá River Basin (Colombia). Twelve limnimetric–limnographic gauges with consistent records for the period 2001–2022 were selected for model calibration and validation. The corresponding sub-watersheds were delineated and characterized in terms of geomorphometry, vegetation cover, and soil permeability. According to that, the morphometric assessment focused on estimating key geomorphometric parameters, while land-cover descriptions utilized NDVI data. Soil type identification was based on the average approximate permeability across each analyzed sub-watershed. Model calibration was performed using the Differential Evolution Markov Chain (DE-MC) algorithm with 8000 simulations, forced by CHIRPS satellite precipitation and ERA5 potential evaporation data. Relationships between GR4J parameters and watershed attributes were assessed using Spearman’s rank correlation and curve-fitting analyses. The results reveal strong and consistent relationships between GR4J parameters (X1–X4) and key morphometric variables, including basin perimeter, circularity ratio, main channel length, and channel slope. Coefficients of determination ranged from 0.80 to 0.98, highlighting the potential for parameter regionalization based on physiographic and environmental descriptors. Full article

Lubricating oil (LO) is manufactured in various formulations for different applications. The inappropriate disposal of petroleum hydrocarbons can increase soil contamination, promoting deleterious environmental and human health impacts. More specifically, following prolonged exposure, LO contaminants are known to have carcinogenic and neurotoxic effects in humans. Bioremediation provides an effective and attractive strategy to expedite the clean-up processes of LO contaminants. We isolated and identified environmentally adapted strains of Pseudomonas aeruginosa, Pseudomonas putida, and Proteus vulgaris from Houston watershed bayou soils. Interestingly, all three exhibited increased resistance, vis-a-vis surrogate strains, to various antibiotic challenges (of chloramphenicol, tetracycline, kanamycin, penicillin, streptomycin, etc.) and increased biofilm formation ranging from 1.6 to 6.7-fold. In fact, all three environmental strains were significantly better at producing enhanced biofilm formation in the presence of spent LO rather than clean LO as well as outproducing biofilm made by the surrogate strains. Finally, the environmental isolates P. aeruginosa, P. putida, and P. vulgaris demonstrated an enhanced ability to sequester clean (2-, 2.5- and 1.14-fold) and spent (1.4-, 1.5, and 1.2-fold) LO when compared to their commercially acquired surrogate reference strains. Our three environmentally isolated organisms from Houston watershed soils appeared to be environmentally adapted to tolerate LO exposures. In the presence of LOs, all three environmentally isolated strains exhibited enhanced growth, enhanced biofilm production, and improved bioaccumulation of LOs relative to commercial reference strains. Taken together, environmentally adapted organisms can promote the bioremediation of contaminants threatening our environment and, potentially, human health. Full article

Identifying the specific sources of heavy metal accumulation in intensive agricultural landscapes is essential for ensuring soil sustainability and food security. In this study, we independently carried out a high-density regional geochemical survey and high-resolution field sampling in the Yangtze–Huaihe Watershed, Eastern China, and used the original sample dataset to distinguish between geogenic backgrounds and anthropogenic enrichments. By employing the APCS-MLR model, four distinct pollution sources were quantitatively identified: natural pedogenesis, agricultural activities, traffic emissions, and industrial inputs. Results demonstrated that while most heavy metal concentrations remained below national safety thresholds, Cd and Hg exhibited significant topsoil enrichment, signaling potential ecological risks. Source apportionment revealed that natural sources primarily controlled As, Cr, Ni, and Pb, with the contribution ranging from 41% to 70%. In contrast, traffic emissions (e.g., tire wear and fuel combustion) emerged as the dominant source for Cd (68%), Zn (55%), and Cu (34%), while industrial activities accounted for a substantial 89% of Hg accumulation via atmospheric deposition. Notably, despite the region’s intensive cultivation, agricultural practices played a surprisingly minor role in heavy metal accumulation. These findings highlight that the accumulations from traffic and industry now account for approximately 50% of the total heavy metal load in the region. Our results underscore the critical importance of high-resolution spatial data for precise source identification and suggest that implementing vegetative buffer zones and stricter industrial emission controls are imperative to mitigate further soil degradation in similar agricultural watersheds. Full article

In this work, iron–phosphorus-based composite biochar (FPBC) was prepared by modification with the leachate of spent LiFePO₄ batteries. The effects of solution pH, dosage, adsorption time, initial concentration, and temperature on the adsorption performance of FPBC were investigated by batch adsorption experiments with Pb(II) and Sb(III) as the target pollutants, and the adsorption mechanism was explored using SEM, BET, XPS, FTIR and XRD characterization. The results indicated that as the initial pH of the solution increased, the removal efficiency of FPBC for Pb(II) gradually increased, while the removal efficiency for Sb(III) remained largely unchanged. The removal of Pb(II) and Sb(III) by FPBC fitted the pseudo-second-order kinetic model and the three-step intraparticle diffusion model, indicating that their removal was primarily controlled by chemical adsorption. Isothermal adsorption studies revealed that FPBC adsorption of Pb(II) better fitted the Langmuir and D-R models, suggesting a monolayer-dominated adsorption process. In contrast, adsorption of Sb(III) fitted the Langmuir, Freundlich, and Temkin models, suggesting a combination of monolayer and multilayer adsorption characteristics. The maximum adsorption capacities of FPBC for Pb(II) and Sb(III) were 312.54 mg·g⁻¹ and 219.20 mg·g⁻¹ at 30 °C, which were approximately 12.85 and 3.37 times those of commercial corn stalk biochar (BC). Thermodynamic analysis confirmed that the removal of Pb(II) and Sb(III) by FPBC was a spontaneous and endothermic process. In addition, FPBC demonstrated strong selective adsorption of Pb(II) in the binary co-adsorption system of Pb(II) and Sb(III). Mechanism studies indicated that Pb(II) removal primarily occurred through co-precipitation, complexation, ion exchange, and electrostatic adsorption, while Sb(III) was mainly adsorbed by FPBC via redox reactions and complexation. Therefore, this work not only provides a low-cost, high-performance adsorbent for the remediation of water contaminated with Pb(II) and Sb(III), but also opens up new avenues for the resource recovery of the leachate of spent LiFePO₄ batteries. Full article

Investigating the influence of landscape evolution on river eutrophication is critical for optimizing spatial patterns to improve water quality. Machine learning (ML) models can capture the complex relationship between landscape metrics and water quality, but their black-box property restricts the interpretability of the underlying mechanisms and makes it difficult to forecast future trends in water quality. To address this, we developed a novel framework that, for the first time, couples an interpretable ML model with the Patch-generating Land Use Simulation (PLUS) model for eutrophication index (EI) prediction. This approach elucidates the response of river eutrophication to landscape dynamics and forecasts future river EI trends. The random forest regression (RFR) model outperformed other algorithms in quantifying these relationships (R² = 0.934 for training, 0.711 for testing). SHAP analysis revealed that landscape metrics contributed 81.78% to the river EI, far exceeding climate factors (18.22%). Consequently, landscape evolution emerged as the dominant explanatory factor. Scenario simulations indicated that while the ecological protection (EP) scenario effectively mitigates river eutrophication, the urban development (UD) scenario significantly exacerbates it. Specifically, under the UD scenario, the average EI in urban sub-watersheds is projected to reach 60.78 by 2040, approaching heavy eutrophic levels. Our findings inform spatial optimization strategies for river eutrophication management and facilitate the design of targeted, localized water ecological protection policies in subtropical monsoonal basins. Full article

Eutrophication is a pervasive issue in Mediterranean reservoirs, where external nutrient inputs and internal sediment releases interact to impair water quality and ecological stability. This study assessed the trophic condition of the artificial lake Cuga in Sardinia (Italy), mainly used for irrigation and providing potable water, by integrating watershed nutrient load estimates, inter-lake transfers, and internal phosphorus release. Field campaigns between July 2022 and May 2023 provided bi-monthly measurements of physical, chemical, and biological parameters, complemented by GIS-based land cover analysis and export coefficient modeling to quantify spatial nutrient sources. Additional phosphorus inputs from water transfers with a nearby reservoir were calculated, while internal sediment release was estimated using a calibrated mass balance model. Results revealed high nutrient concentrations, with mean total phosphorus of 128 mg P m⁻³, chlorophyll a averaging 9.9 mg m⁻³, and Secchi depth below 1 m, classifying the reservoir as eutrophic to hypertrophic under OECD and Carlson indices. Spatial loads were dominated by agricultural areas, while inter-lake transfers and internal sediment release contributed substantially to the overall phosphorus budget. The predictive Vollenweider model closely matched the observed conditions, confirming the robustness of the combined approach. Maintaining good ecological status in Mediterranean reservoirs is essential for safeguarding human well-being, as eutrophication degrades drinking-water quality, increases treatment costs, and can promote toxin-producing algal blooms with direct implications for public health. These findings highlight the need for integrated management strategies addressing both external and internal nutrient sources to mitigate eutrophication in Mediterranean reservoirs, which affects the ecosystem functioning and the related human needs and well-being. Full article

High-density polyethylene (HDPE) geomembranes (GMs) in landfill liners experience UV exposure during installation. While tensile strength deterioration after UV aging is known, changes in interfacial shear properties are rarely reported. This study investigates the evolution of interfacial shear behavior at the GM/sand interface by subjecting GM specimens to varying durations of indoor UV aging followed by direct shear tests. Underlying mechanisms were explored through tensile strength, melt flow index, crystallinity, and oxidation induction time (OIT) measurements. Results show that displacement required to reach peak shear strength for smooth geomembrane (GMS)/sand interface decreased with aging time (49.0–70.1% reduction), while no clear trend emerged for textured geomembrane (GMX)/sand interface. Following 80 days of UV exposure, the GMS/sand interfacial shear strength declined, with the peak friction angle dropping 20.6% from 26.2° to 20.8°. For the GMX/sand interface, the peak friction angle dropped to its lowest value of 31.2° after 40 days of exposure (from 34.3°), and then exhibited an increase with further UV aging. The large displacement shear strength followed a trend similar to that of the peak strength. Among the other tested indicators, the variation pattern of OIT with UV exposure exhibited the best correlation with the GMS/sand interface shear strength. Full article

Surface water–groundwater interactions within oasis–desert ecotones of arid regions play a pivotal role in sustaining regional water security and ecological stability. Taking the Niya River Basin in Xinjiang, Northwest China, as a representative inland watershed, this study systematically elucidates the mechanisms and seasonal dynamics of surface water–groundwater coupling under the combined influences of natural processes and anthropogenic activities. A total of 68 surface water and groundwater samples were collected during the dry, normal, and wet hydrological periods. Integrated hydrochemical characterization, mineral saturation index analysis, and stable isotope (δ²H and δ¹⁸O) mass balance modeling were employed to quantify recharge contributions and unravel hydrogeochemical evolution pathways. Results indicate that the waters in the study area are predominantly brackish to saline, with consistent dominant ionic assemblages (SO₄²⁻ and Na⁺) across all hydrological periods, highlighting evaporite dissolution as the primary control on solute composition. Hydrochemical evolution is jointly regulated by evaporation concentration, water–rock interactions, and cation exchange processes. Surface water chemistry reflects the combined effects of silicate weathering and evaporite dissolution, whereas groundwater chemistry is mainly governed by evaporite dissolution coupled with pronounced cation exchange. Stable isotope signatures reveal substantial secondary evaporation of regional precipitation prior to recharge. Frequent bidirectional recharge between surface water and groundwater was observed, exhibiting distinct seasonal transitions. During the dry period, groundwater provides significant baseflow support to surface water (48.6% in the oasis zone and 54.3% in the desert zone). In the normal period, recharge direction reverses, with surface water becoming the dominant source of groundwater recharge (99.0% in the oasis zone and 76.6% in the desert zone). In the wet period, spatial heterogeneity becomes evident: surface water continues to dominate groundwater recharge in the oasis zone (92.7%), whereas groundwater recharge to surface water prevails in the desert zone (50.5%). This study identifies a seasonally dynamic “discharge–infiltration–zonal regulation” bidirectional recharge pattern in arid inland river systems. The findings advance the mechanistic understanding of hydrological connectivity reconstruction within oasis–desert ecotones and provide a scientific basis for optimized regional water resource allocation and groundwater salinization risk mitigation. Full article

Sediment yield remains a major challenge in erosion-prone watersheds because it affects reservoir capacity, water quality, hydraulic infrastructure, and ecological stability. Although numerous studies have examined sediment yield estimation and sediment control, these topics are often treated separately, limiting the development of integrated watershed management strategies. Unlike many existing sediment yield review papers that focus primarily on predictive models, erosion processes, or management measures in isolation, this study provides an integrated synthesis of sediment yield estimation methods and sediment control strategies within a single watershed management framework for erosion-prone environments. The review covers empirical models, traditional sampling, physically based models, and emerging data-driven tools such as artificial intelligence, machine learning, remote sensing, and sensor-based monitoring, alongside structural, vegetative, and adaptive sediment control measures. The reviewed literature indicates three major trends: increasing integration of GIS and remote sensing with conventional models, wider use of process-based models for scenario analysis, and rapid growth of AI-based methods for real-time and nonlinear prediction. The findings further show that no single estimation or control strategy is universally applicable; performance depends strongly on watershed scale, sediment connectivity, land use, climatic regime, and data availability. Overall, the review highlights the need for integrated, adaptive, and site-specific sediment management frameworks that combine predictive modeling, monitoring technologies, and practical control interventions to improve long-term watershed resilience. Full article

Many degraded streams in the Chesapeake Bay watershed have been structurally modified over the last two decades in an effort to reduce nutrient and sediment loads from urban catchments and contribute to the pollutant reduction goals of the Chesapeake Bay Total Maximum Daily Load (TMDL). The step-pool streamwater conveyance (SPSC) is a stream restoration design that has been extensively implemented in Maryland and the District of Columbia. In the summer of 2019, an SPSC was constructed in a degraded 800 m stream reach on the University of Maryland campus (i.e., Campus Creek). Precipitation, baseflow and stormflow runoff, and nutrient (nitrogen and phosphorus) and total suspended solid (TSS) concentrations were measured throughout pre- and post-restoration periods (~2 and 5 years, respectively) to determine the extent to which the SPSC structure reduced pollutant loads. A comparison of pre- (2018) versus post-restoration (2020) years with similar total annual rainfall volumes indicates that total annual runoff was 13% lower in the post-restoration period. Area yields of total nitrogen (TN), total phosphorus (TP) and TSS were 33, 39 and 59% lower, respectively, in the same pre- versus post-restoration comparison. Full article

The synergistic impacts of land use/land cover (LULC) transformations and weather pattern variabilities (WPV) represent a primary driver of hydro-geological instability, threatening agricultural productivity, soil conservation, and water quality. Disentangling the discrete contributions of these stressors to runoff and sediment yield (SY) remains a significant challenge, particularly in complex, confluence-proximal watersheds lacking major hydraulic regulations. This study investigates the Tirumakudalu Narasipura watershed in Karnataka, India, an agriculturally intensive system undergoing rapid peri-urbanization. Leveraging the process-based geospatial interface of the Water Erosion Prediction Project (GeoWEPP), we analyzed hydrological responses over a 24-year period (2000–2023) and projected future trajectories through 2030. To overcome the traditional constraints of GeoWEPP, which was developed for small-scale watersheds (<260 ha), we present a novel upscaling framework utilizing a multi-site multivariate temporal calibration of hydrological response variables to exploit its process-based precision in capturing distributed soil erosion and landscape heterogeneity. This approach is further reinforced by an ancillary data validation to minimize error propagation while model-upscaling. Our findings reveal projected increases in runoff and SY of 14.69% and 49.23%, respectively, between 2000 and 2030. Notably, the sub-decadal acceleration from 2023 to 2030 (17.32% for runoff and 18.51% for SY) underscores a shifting dominance where LULC-driven surface modifications now outweigh climatic variance in forcing hydrologic change. Furthermore, the study quantifies how anthropogenic interventions such as strategic crop selection, tillage intensity, and irrigation regimes act as critical determinants of topsoil preservation. These results provide a scalable, economically feasible framework for precision land stewardship and sustainable watershed management in rapidly developing tropical landscapes. Full article

Flood hazard mapping remains challenging in regions with limited hydrological and topographic data, despite increasing flood risk driven by climate change and land-use dynamics. This study aims to demonstrate that preliminary flood inundation maps can be developed under data-scarce conditions by integrating limited field observations with publicly available datasets and simplified hydrodynamic modeling. The Khlong Wat watershed in southern Thailand, where flood hazard maps had not previously existed despite recurrent flood events, was used as a case study. Flood simulations were conducted using the HEC-RAS model with a simplified terrain representation to approximate river bathymetry, acknowledging uncertainties in channel geometry. Hydrodynamic results show a systematic increase in flood extent and depth with increasing flood recurrence intervals, with inundated areas expanding from 1.43 km² for a 10-year flood to 4.02 km² and 5.97 km² for 100- and 500-year events, respectively. Agricultural land is consistently the most affected category, accounting for more than two-thirds of the flooded area across all scenarios, with rubber plantations being the dominant land use. Urban exposure increases with flood magnitude, although most buildings remain affected by shallow inundation below 0.5 m. The results confirm that meaningful flood hazard assessments can be achieved in data-limited regions and provide a transferable framework to support flood risk management and spatial planning in similar environments. Full article

Groundwater is a strategic resource for maintaining ecological balance and supporting human development in arid inland basins. However, under the dual pressures of climate change and human activities, it faces threats in both quantity and quality. This study selects the Chahan Usu River watershed in the eastern Qaidam Basin, a typical arid inland basin on the Tibetan Plateau, to assess the current quality of groundwater resources and reveal the formation mechanisms and material sources of its hydrochemistry. The results show that the groundwater in the watershed is generally weakly alkaline, with some areas exhibiting high salinity. The dominant cations and anions are Na⁺ and Cl⁻, respectively. The hydrochemical type is mainly Cl-Na, with a minority being mixed Cl-Mg·Ca. Overall, the groundwater in the watershed is suitable for domestic use. However, in the middle and lower reaches of the Chahan Usu River, nitrate and ammonia nitrogen contamination reduce its suitability. Meanwhile, although long-term use of this groundwater would not lead to soil degradation, its widespread high salinity and high sodium content make it unsuitable for irrigation. Water–rock interactions with evaporites and silicate rocks are the main mechanisms controlling groundwater chemistry in the watershed. Among them, halite minerals contribute most of the Na⁺ and Cl⁻, while sulfate minerals provide Ca²⁺ and SO₄²⁻. In addition, cation exchange is widespread. This study provides a reference for ensuring the security and sustainable development of groundwater resources on the plateau. Full article