Determining the recharge sources of adjacent old-working water outlets and their hydraulic connections is essential for zoned pollution control in closed coal mines. This study examined two outlets, S1 and S2, 174 m apart in the Chunjingwa closed coal mine area, Shanxi Province, China. Discharge dynamics, hydrochemistry, hydrogen–oxygen stable isotopes, and a goaf pumping test were combined. During natural monitoring, discharges at S1 and S2 ranged from 1.172–1.958 and 1.012–8.630 m3/h, respectively, with the variation at S2 (7.618 m3/h) being 9.7 times that at S1 (0.786 m3/h). Most contamination indicators had higher median exceedance levels at S2; for SO42−, the median was 14.6 at S2 versus 8.4 at S1. Isotopically, S1 overlapped with ZK2 and ZK3, whereas S2 was distinct. During the 27-day pumping test, S1 discharge fell by about 91%, whereas S2 showed no clear response. The evidence identifies two distinct recharge–discharge systems on opposite sides of F2 at the tested scale. F2 is interpreted as a structural divide, not a uniformly impermeable fault. S1 is regulated mainly by goaf-water storage to the south, whereas S2 is dominated by shallow-catchment, rapid-infiltration recharge to the north. The framework provides a practical alternative to artificial tracer tests for outlet-scale source identification and zoned remediation.
Community irrigation systems integrate water, infrastructure, governance, environmental, and market conditions, yet comparative evidence on their multidimensional sustainability remains limited in the Andes. This cross-sectional secondary analysis developed a bounded 10-indicator formative territorial sustainability index for 241 community irrigation systems in Azuay Province, Ecuador, and used multivariable models to examine conditional associations with system characteristics. Physical infrastructure condition and organizational activity planning showed the clearest positive coefficient patterns in the global model under nominal inference, but neither remained below 0.05 after Benjamini–Hochberg adjustment; the global model explained 12.1% of between-system variation. In the original water-domain model, reported source-area contamination was associated with a lower score (B = −14.23, 95% CI: −22.00 to −6.47; BH-adjusted p = 0.016). When perceived water quality was removed from the domain outcome, the contamination coefficient remained negative, although multiplicity-adjusted support was attenuated. The aggregate–domain contrast illustrates how a multidimensional composite score can obscure a domain-specific environmental constraint. The framework extends descriptive inventory information into a comparative, sensitivity-tested territorial assessment, but the non-probability, questionnaire-based design does not support causal or population-wide inference. Direct hydrological and water-quality monitoring should complement future applications.
The occurrence of microplastics in groundwater remains insufficiently documented, particularly across contrasting hydrogeological settings. This study provides the first baseline assessment of microplastic contamination in Slovenian groundwater by comparing its occurrence in urban alluvial and karst aquifers, which represent important drinking-water resources in Slovenia. Groundwater was sampled at 19 sites (8 alluvial, 11 karst) using a large-volume in situ filtration system, with three 1 m3 replicates collected at each site. Polymer composition was confirmed using attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR). Microplastics were detected at nearly all sampling sites, with concentrations ranging from 0 to 13.33 particles/m3 (mean: 4.65 particles/m3). Although no statistically significant differences in microplastic occurrence were observed between aquifer types at the available sample size, average concentrations were slightly higher in alluvial aquifers, whereas karst systems showed greater site-level variability. Differences in particle characteristics were observed between aquifer types, with fragments predominating in alluvial aquifers, and fibres and larger particles proportionally more abundant in karst springs. These patterns are consistent with differences in groundwater flow and filtration processes between karst and alluvial aquifers. Polyethylene and polyethylene terephthalate were the most frequently identified polymers across all samples. Correlations between microplastic concentrations and selected water-quality parameters, particularly temperature and nitrate, were identified. Overall, the results emphasise the relevance of hydrogeological context for interpreting microplastic occurrence in groundwater and provide baseline information to support future monitoring efforts.
Karst groundwater systems are characterized by highly heterogeneous flow networks, resulting in complex responses of groundwater levels to precipitation variability. The Jinan Spring Basin, one of the most representative karst spring systems in northern China, has experienced substantial changes in spring discharge due to variations in precipitation, groundwater exploitation, and hydrogeological conditions. However, the temporal scales at which precipitation signals control groundwater-level fluctuations and the mechanisms governing their transmission within the karst aquifer remain poorly understood. In this study, daily precipitation data from 30 meteorological stations and groundwater-level records at Baotu Spring during 2016–2018 were analyzed using global wavelet spectrum (GWS) and wavelet transform coherence (WTC) approaches. The dominant precipitation cycles, scale-dependent precipitation–groundwater relationships, and phase-derived groundwater response lags were quantified to reveal the hydrological response characteristics of the Jinan karst system. Three prominent precipitation periods were identified at 17.37, 29.22, and 330.57 days. Groundwater responses presented clear temporal-scale dependence, with short-period signals showing rapid but localized responses, while intermediate and long-period signals demonstrated stronger and more persistent coherence. The percentage of significant coherence area (PASC) increased from 23.50% at the 0–17.37 day scale to 64.28% at the 29.22–330.57 day scale, indicating that accumulated precipitation rather than individual rainfall events exerts the dominant control on groundwater-level variations. The spatial distribution of response lags revealed that rapid responses (17.37 days) mainly occurred in the southern recharge areas, reflecting preferential recharge through well-developed karst conduits. Intermediate responses (29.22 days) showed a progressive increase in lag time from south to north, indicating the influence of regional groundwater flow and aquifer storage. Long-period responses (330.57 days) were locally enhanced near major faults, suggesting structural controls on deeper groundwater circulation. This study reveals that precipitation signals in the Jinan Spring Basin are transmitted through multiple groundwater circulation pathways with distinct temporal characteristics. The identified multi-scale response patterns provide new insights into the internal structure and hydrological functioning of karst aquifers and offer scientific support for sustainable management of spring water resources.
Aquatic and semiaquatic beetles are important components of wetland ecosystems serving as bioindicators, predators, and vital prey resources. Numerous studies examined how their dispersal flights are influenced by biotic and abiotic factors, but the wavelength-specific attraction of different artificial light sources remains understudied. This study evaluated the attractiveness of three portable light traps equipped with different light sources emitting light with different wavelength ranges: a compact light tube, an LED light source, and a UV lamp. A total of 6568 individuals representing 54 species were captured. Total nightly abundance correlated positively with mean nocturnal temperature. Light source type significantly affected both species richness and abundance, with the broad-spectrum compact light tube outperforming the other tested light sources both in abundance and species richness. For Dytiscidae and Hydrophilidae, the compact light tube was significantly more attractive only than the blue LED source, while its attractiveness did not differ significantly from that of the UV lamp, demonstrating family-level differences in attraction. The light source-dependent attraction remained stable across phenological periods. Our findings suggest that while broad-spectrum lights improve the efficiency of faunistic surveys and support conservation-oriented monitoring of aquatic beetle assemblages, their integration into public lighting networks near vulnerable wetlands must be strictly avoided to prevent severe ecological trapping.
Reservoir impoundment can reactivate pre-existing landslides and reorganize slope topography, thereby changing seepage conditions and subsequent deformation. However, crack mapping, geomorphic interpretation, and hydrodynamic diagnosis are still often treated as separate tasks. This study investigates the Hemenkou (HMK) landslide in the Wudongde Reservoir area, China, using multi-scale space–air–ground observations, including multi-temporal optical satellite images, unmanned aerial vehicle (UAV) photogrammetry, pyramid scene parsing network (PSPNet)-based crack segmentation, global navigation satellite system (GNSS) monitoring, and convergent cross mapping (CCM). The remote sensing record shows a progressive damage sequence: cracks were mainly restricted to the upper source area in 2012, crown cracking intensified and propagated downslope by December 2020, and the UAV survey of 10 June 2024 revealed a mature tension-crack network concentrated in Zone II. ResNet-50-PSPNet achieved the best crack-extraction performance among the tested models, with Precision = 0.9120, Recall = 0.9041, F1 = 0.9081, and IoU = 0.8316. The mapped cracks are dominated by short, narrow, northeast–southwest-oriented tension cracks. GNSS monitoring reveals strong spatial heterogeneity, with stepwise deformation concentrated in Zone II. CCM provides strong directional evidence for the influence of reservoir water-level fluctuation on Zone II deformation, whereas the weaker rainfall signal is consistent with a secondary reinforcing role. The apparent increase in the rainfall-related CCM signal from 2021 to 2023 is consistent with progressive crack expansion and potentially enhanced hydraulic connectivity in Zone II. Taken together, these observations support the interpretation that post-deformation topography, particularly the tension-crack network and disturbed toe, may organise preferential seepage pathways and increase the sensitivity of the landslide to reservoir drawdown. The study provides an integrated remote sensing and monitoring framework for process-based interpretation of reservoir landslides.
Streamflow estimation at ungauged sections is essential for flood warning, reservoir operation, water allocation, and basin management. Conventional regionalization approaches typically require the construction, calibration, and parameter transfer of conceptual or process-based hydrological models, resulting in high application costs when data are scarce, gauge networks are frequently adjusted, or management sections do not coincide with existing gauging stations. In recent years, regional Long Short-Term Memory (LSTM) networks have provided a data-driven alternative for ungauged streamflow estimation. However, existing studies have focused mainly on spatial generalization across independent catchments, with limited attention to hydrological information transfer among sections with different upstream and downstream relationships within the same nested basin. This study used five nested hydrological stations in the Fujiang River Basin to develop a Hydrological-Efficiency-Guided Long Short-Term Memory framework (HEG-LSTM) and compared it with a baseline LSTM. The model incorporated local meteorological forcing, antecedent precipitation, static basin attributes, and scenario-permitted donor-station discharge as inputs, and leave-one-station-out validation was adopted to assess cross-section applicability. To investigate the effects of different upstream and downstream relationships on streamflow estimation, three gauge-network scenarios were designed: S1 estimated downstream streamflow using upstream stations; S2 was downstream-to-upstream synchronous estimation; and S3 jointly estimated streamflow at an intermediate ungauged section using upstream and downstream stations. HEG-LSTM achieved a mean Nash–Sutcliffe efficiency (NSE) of 0.703, exceeding the 0.603 obtained by the baseline LSTM. The mean NSE values of HEG-LSTM under S1, S2, and S3 were 0.692, 0.695, and 0.730, respectively, with the best performance obtained under S3. Compared with the baseline LSTM, HEG-LSTM increased the coefficient of determination for high flow from 0.617 to 0.737 and that for annual peak flow from 0.731 to 0.770, whereas improvement in low flow correlation remained limited. Shapley Additive Explanations (SHAP) showed that donor-station discharge, drainage area, elevation, slope, and antecedent precipitation jointly influenced cross-section transferability. The proposed HEG-LSTM framework provides a methodological reference for streamflow estimation, historical streamflow estimation, and gauge-network optimization at ungauged sections in nested basins.
River-connected lakes are characterized by complex hydrological regimes, where hydrodynamic conditions serve as key physical drivers of aquatic ecosystem evolution and eutrophication. However, traditional water-balance methods struggle to accurately quantify water exchange under strong seasonal water-level fluctuations and the backwater effect of the Yangtze River, resulting in significant gaps in understanding lake hydrodynamic features and their seasonal eutrophication response patterns. Taking Dongting Lake as an example, this study employed a two-dimensional hydrodynamic model coupled with the advection–dispersion equation of a conservative tracer to simulate the spatiotemporal patterns of flow velocity and water turnover time during the dry season, rising-water season, wet season, and receding-water season using observed hydrological data from 2017 to 2025. Field sampling data and structural equation modeling were further used to identify the pathways through which hydrodynamic conditions affect lake trophic status. Flow velocity and water turnover time exhibited significant spatiotemporal heterogeneity: water turnover time was generally within 10 d in main flood channels but exceeded 60 d in stagnant floodplain areas and local topographic depressions. Seasonally, it was shortest in the wet season due to enhanced hydrological connectivity, yet longest in the dry season because of weakened hydraulic connection. The effects of hydrodynamics on trophic status were strongly season-dependent: during the rising-water season, hydrodynamics inhibited nutrient accumulation through dilution and flushing; during the wet season, strong runoff promoted external nutrient input; and during the dry season, hydrodynamics mainly affected trophic status by modifying physical habitat conditions for algal growth. These findings reveal the hydrological and hydrodynamic mechanisms regulating eutrophication in typical river-connected lakes, providing direct scientific support for hydrological regulation optimization, zonal eutrophication prevention and control, and water environmental carrying capacity assessment in Dongting Lake and similar systems, enabling lake managers to formulate differentiated pollution control strategies based on the hydrodynamic–trophic status response relationships across different hydrological seasons.
Existing DNAPL groundwater source inversion approaches are confronted with prominent bottlenecks: shallow surrogate models often fail to capture strong nonlinear multiphase flow relationships, traditional heuristic optimizers suffer from premature convergence, and ill-posed equifinality further degrades inversion reliability, together with prohibitive computational costs from repeated multiphase numerical simulation. Taking a typical chemical-contaminated site in Northeast China as the research object, this study establishes a multiphase flow numerical model that fully reproduces the migration and transformation mechanisms of chlorobenzene-based DNAPLs after systematic generalization of the site’s geological and hydrogeological conditions. To drastically cut the computational burden incurred during iterative inversion, high-quality datasets are generated via parameter sensitivity analysis and Latin hypercube sampling, based on which a deep convolutional neural network (DCNN)-driven high-fidelity surrogate model is constructed and embedded into the optimization framework as an equality constraint. A separated nonlinear programming model is formulated to independently quantify pollution source characteristics and hydrogeological parameters, with the objective of minimizing the residual error between field-measured and numerically simulated contaminant concentrations. A hybrid homotopy-particle swarm optimization (HH-PSO) algorithm is further proposed to address the limitations of conventional optimizers, including strong dependence on initial guesses and susceptibility to local optima. On this basis, a closed-loop feedback iteration scheme is developed, where source identification and parameter calibration are implemented alternately with bidirectional constraints and progressive correction to continuously refine and stabilize inversion outputs. This work presents distinct innovations in the methodology, algorithm, and practical application of DNAPL groundwater source inversion. Results from synthetic benchmark cases and on-site field applications demonstrate that the DCNN surrogate model achieves far higher fitting accuracy than shallow learning approaches (e.g., Kriging and support vector regression), with the coefficient of determination R2 exceeding 0.99. After the feedback correction iteration procedure, the average relative error for retrieved source locations, release histories, and hydrogeological parameters drops to 3.72%, and the overall computational efficiency is elevated by approximately 99.84%. The integrated simulation–optimization inversion framework proposed in this work integrates monitoring signal denoising, multiphase numerical simulation, deep learning surrogate modeling, hybrid intelligent optimization, and feedback iterative correction. This integrated system effectively resolves core technical bottlenecks in DNAPL groundwater source inversion, such as nonlinear ill-posedness, equifinality induced by mutual interference between source terms and aquifer parameters, prohibitive computational costs of multiphase simulations, and premature convergence of traditional optimization algorithms. The established framework can serve as a robust theoretical foundation and technical tool for rapid, precise source tracing, pollution liability confirmation, and remediation design at complex contaminated sites.
Improving water resource use efficiency (WRUE) is essential for achieving sustainable water management under increasing socioeconomic and environmental pressures. This study investigates the spatiotemporal evolution, associated factors, and spatial transition characteristics of WRUE across 11 provincial-level administrative regions in the Yangtze River Basin during 2010–2024. An integrated framework combining the super-efficiency SBM-window DEA model, Malmquist–Luenberger index, GeoDetector, and conventional and spatial Markov chain models was developed to characterize efficiency dynamics, productivity changes, explanatory factors, and state-transition pathways. The results showed that WRUE exhibited an overall fluctuating upward trend with a clear spatial gradient of lower reaches > middle reaches > upper reaches. The mean ML index was 1.004, indicating that technological change (TC) was the main contributor to productivity improvement. Urbanization rate, water use per CNY 10,000 of GDP, industrial water-use share, and primary-industry share exhibited relatively high explanatory power, and their interactions enhanced explanatory power. Markov analysis revealed strong persistence in WRUE states, while transition probabilities differed across spatial neighborhood conditions. Assuming stable transition probabilities, the high-efficiency state would reach a steady-state probability of 0.8155. These findings provide insights for differentiated water resource management and coordinated regional development.
Dissolved organic carbon (DOC) is a climate-sensitive component of carbon cycling in inland waters, but consistent regional comparisons of its seasonal and interannual patterns remain limited across China. Here, we conducted a secondary analysis of a published monthly DOC dataset for 60 selected lake and reservoir series (15 per climate region) spanning China’s subtropical monsoon, temperate monsoon, temperate continental, and plateau mountainous regions during 2000–2023. The source dataset was generated using random forest models constrained by 1326 DOC observations from 83 lake and reservoir stations, and with watershed-scale climate, soil, and anthropogenic variables used as predictors. Across the four regions, the long-term mean DOC concentrations were 9.78, 14.10, 16.12, and 15.14 mg L−1, respectively. Seasonal medians showed spring–summer enrichment in the two monsoon regions, nearly equal spring and summer values in the temperate continental region, and an autumn maximum in the plateau mountainous region. Interannual variability was greatest in the subtropical monsoon region (CV = 3.18%), whereas the plateau mountainous region had the lowest variability (CV = 0.95%). Mann–Kendall analysis identified a significant decline only in the temperate continental region (Z = −2.51, p = 0.012). These results provide a climate–region synthesis of model-derived DOC patterns in Chinese inland waters. Because climate variables contributed to the original random forest predictions, the present study interprets regional contrasts descriptively rather than as independent causal evidence of climatic controls.
This study provides a systematic review of mathematical programming models applied to agricultural water management, with a focus on their relevance for policy design addressing water scarcity and agricultural pollution. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, 42 peer-reviewed studies were selected from an initial sample of 438 records and analysed using a multi-dimensional framework covering research context, economic objectives and policy orientation, and model features. The analysis reveals a pronounced geographical and thematic segmentation: water scarcity studies are concentrated in Asia, while water quality studies are predominantly European and regulatory-driven, with limited mutual influence. While deterministic optimisation approaches remain prevalent, models increasingly integrate biophysical processes through coupling with agro-hydrological components. However, policy applicability is often constrained by the limited representation of farmers’ behavioural responses, trade-offs between model complexity and usability, and difficulties in transferring results across institutional contexts. Emerging policy instruments remain limited in the sample. Progress in this field depends less on technical elaboration within existing frameworks and more on integration across disciplinary approaches. A suitable pathway would be the development of models that treat water availability and quality as jointly determined outcomes and embed institutional design within the optimisation framework.
Human activities such as intensive groundwater abstraction and mine dewatering can profoundly disrupt the natural hydrological functioning of karst aquifers. The Transdanubian karst aquifer in Hungary represents one of Central Europe’s most prominent examples, where decades of coal-mine dewatering lowered groundwater levels by more than 40 m and fundamentally altered the natural recharge–discharge regime. Understanding and forecasting recovery in such complex karst systems remain challenging because of heterogeneous conduit–fracture networks, strong climate sensitivity, incomplete monitoring records, and uncertainty in long-term predictions. This study presents an integrated end-to-end machine learning framework for groundwater characterization and climate-constrained probabilistic forecasting. Monthly groundwater-level records (1970–2026) from five monitoring wells were first reconstructed using a hybrid Moving Average–Random Forest gap-filling approach, achieving high reconstruction accuracy (R2 = 0.87–0.98). Self-Organizing Maps subsequently identified four hydrogeological states representing the dewatering, transition, recovery, and near-equilibrium phases, while inter-well weight-plane correlations (>0.95) confirmed strong basin-scale hydraulic connectivity. A Bootstrapped Random Forest model forced by bias-corrected COSMO-CLM precipitation projections under the SSP2-4.5 climate scenario generated probabilistic groundwater forecasts through 2030, achieving high predictive performance (NSE > 0.80; RMSE = 0.10–0.35 m). Forecast results indicate that the basin as a whole is approaching hydraulic equilibrium by 2030, with distinct well-specific trajectories including mild steady decline and near-stable water level. The proposed framework provides a robust and transferable methodology for groundwater characterization and long-term forecasting in complex karst and fractured aquifer systems under changing climatic conditions.
Halogenated ketones (HKs) and aldehydes (HAs) are prevalent emerging disinfection by-products (DBPs) threatening drinking water safety. Although pre-oxidation and coagulation are widely applied in drinking water treatment, critical knowledge gaps remain regarding the precursor-specific effects of KMnO4 and O3 pre-oxidation on chlorinated ketone/aldehyde formation potential, as well as the interaction between coagulation optimization and DBP yields. This study systematically investigates the effects of KMnO4/O3 pre-oxidation and optimized coagulation on the formation potential (FP) of 1,1-dichloroacetone (1,1-DCP), 1,1,1-trichloroacetone (1,1,1-TCP), and chloral hydrate (CH) from four typical precursors (fulvic acid, citric acid, L-threonine, L-asparagine). Batch pre-oxidation and chlorination experiments were performed; three-dimensional excitation–emission matrix (3D-EEM) fluorescence spectroscopy was used to characterize organic-precursor structural changes, while gas chromatography–mass spectrometry (GC-MS) was adopted to quantify target DBPs. Results show that KMnO4 and O3 pre-oxidation significantly promote (p < 0.05) DBP formation from fulvic acid but exert precursor-specific effects on small-molecule precursors: KMnO4 enhances CKs while inhibiting CH from amino acids, and O3 suppresses all three DBPs from small-molecule precursors. Coagulation pretreatment weakly inhibits DBP formation (reduction rate < 20%) by removing partial precursors. This study clarifies the mechanism of process-driven DBP modulation and provides a theoretical basis for optimizing water treatment processes to control chlorinated ketone/aldehyde DBPs.
Water governance in the Colombian Amazon is shaped by institutional fragmentation, the marginalization of local and ancestral knowledge, and a disconnect between water conservation and territorial development. This article applies a social multi-criteria evaluation (NAIADE) and a territorially situated prospective analysis to two contrasting Amazonian municipalities, Puerto Caicedo (Putumayo) and Puerto Nariño (Amazonas), to examine how strategic actors evaluate alternative water governance scenarios. Working from participatory workshops, documentary analysis, and an actor characterization, we elicited actor judgments on five governance scenarios across 10 criteria and analyzed them with this method, reporting the two preorders and their intersection rather than a single synthetic index. Contrary to the expectation that the more socially cohesive, predominantly indigenous municipality would converge on a distinct preferred scenario, both municipalities exhibit weak to absent discrimination among scenarios: Puerto Caicedo shows complete indifference across all five alternatives, and Puerto Nariño does not distinguish among continuity, active community participation, and interinstitutional coordination, while clearly rejecting external dependence and purely technological solutions. Coalition structures are similar in both sites, reaching complete fusion at comparable similarity levels. We interpret this shared non-differentiation as an expression of generalized institutional fragility under post-normal conditions. The article contributes a transparent and reproducible NAIADE-to-prospective workflow, comparative evidence that contrasting structural social capital endowments do not by themselves produce divergent deliberative outcomes here, and a diagnosis-to-instrument design logic for fragile contexts.
As the largest inland river basin in China’s extremely arid region, the stability of the groundwater–vegetatifon system in the Tarim River Basin is crucial for the consolidation of the ecological security barrier in the northwest. To reveal the evolution law of groundwater storage in the watershed from 2003 to 2024 and its response mechanism to vegetation dynamics, this study is based on GRACE gravity satellite, GLDAS land surface assimilation and MODIS remote sensing data. The Theil Sen trend analysis, Hurst index, spatiotemporal Granger causality test, and standardized multiple linear regression model are integrated to systematically analyze the spatiotemporal heterogeneity, future evolution trend, and multi-driving factor contribution pattern of groundwater storage (GWSA) in the watershed. The results showed that: (1) During the study period, the GWSA of the watershed showed a significant downward trend, with a rate of −3.5 mm/a, and experienced a spatial redistribution process of “comprehensive loss local recovery southern compensation northern loss”. The northern and peripheral regions faced new depletion risks. (2) The vegetation condition continues to improve, and the VCI gradually rises from the low to medium range, but the spatial heterogeneity increases synchronously; there is a significant spatial positive correlation between VCI and GWSA, with only a strong lag driving effect in the southwestern region (F > 40). The explanatory power of vegetation factors for groundwater in other regions is limited. (3) Future trend predictions show that over 70% of the region will continue in the direction of historical changes, and the continuous loss trend in the north is difficult to reverse. (4) There is significant spatial differentiation in the contribution rate of driving factors: vegetation conditions (VCI) are the dominant factor, controlling 57.53% of the watershed edge and eastern region; precipitation and temperature dominate the central region (24.94%) and southwestern desert areas (17.53%), respectively. The research results can provide scientific basis for differentiated ecological water delivery and refined management of water resources in the Tarim River Basin.
A membrane brine concentrator (MBC) can reduce the concentrate volume entering thermal processes for zero liquid discharge (ZLD). Previous LSRRO-based studies have largely focused on high-salinity brines using modified or specifically selected low-salt-rejection membranes. This study examined the extent to which water recovery could be increased in wastewater reclamation using conventional nanofiltration (NF) modules in MBC processes. Two brackish water reverse osmosis (BWRO) modules and two NF modules were tested in 2000–40,000 mg/L NaCl. NE4040-90 provided the best balance between salt-concentrating performance and required pressure. An NF module model was developed using experimentally estimated water permeability, salt permeability, and mass-transfer coefficient. It reproduced permeate concentration and feed pressure with normalized root-mean-square errors of 5.73% and 1.20%, respectively. The developed NF module model was then iteratively coupled with the upstream BWRO simulation to evaluate an integrated two-stage BWRO and three-stage MBC process. Compared with conventional BWRO, the integrated system increased overall recovery from 81.0% to 95.9%, reduced concentrate flow from 32 to 7 m3/h, predicted a final concentrate concentration of 51,396 mg/L, and maintained permeate concentration at 34 mg/L while remaining below the 41.4 bar pressure limit. The reduced concentrate load lowered total specific energy consumption from 4.5 to 1.6 kWh/m3 of wastewater feed under the adopted ZLD assumptions. Conventional NF modules therefore provide a practical option for high-recovery wastewater reclamation toward ZLD.
Torrential flows, a broad category of rapid hydrogeomorphic processes that in the Colombian Andes includes debris flows, mudflows, and hyperconcentrated flows, pose a major hazard in tropical mountain regions. This study used two complementary binary classification models to examine geomorphometric conditioning and antecedent rainfall triggering of torrential flow occurrence. A 12.5 m ALOS PALSAR DEM and 42 years of daily rainfall data (1981–2023) from IDEAM rain gauges and CHIRPS v2 were analyzed in a GIS-based regional framework. Antecedent rainfall variables were aggregated at watershed scale using zonal statistics. The conditioning dataset comprised 642 watersheds (321 with documented events and 321 controls). Gradient boosting ranked first in the preliminary grouped holdout comparison, whereas the uncalibrated random forest achieved the highest mean score under spatial leave-one-province-out validation and was selected as the final conditioning model (mean ROC-AUC = 0.747 ± 0.052). Basin scale and relief were the leading morphometric associations. In the rainfall trigger model, previous day IDEAM mean rainfall and previous day IDEAM maximum rainfall were the two leading permutation importance predictors, followed by monthly CHIRPS rainfall; the 90-day IDEAM maximum accumulation ranked fourth. This ordering indicates that immediate rainfall dominated the fitted model, while longer antecedent wetness retained a secondary contribution. The results support watershed prioritization and regional hazard assessment; because operational rainfall thresholds were not derived, they should not be treated as a ready-to-use early-warning model.
Alpine streams are increasingly exposed to multiple disturbances, including extreme flood events, expected to become more frequent under climate change, and the expansion of small hydropower plants (SHPs). Understanding the resilience of aquatic communities and the ability of biomonitoring tools to detect disturbance-driven changes is essential for ecological assessment. We conducted an eleven-year monitoring programme (2014–2024) in the Corsaglia Stream (Northwestern Italy), comprising 16 sampling campaigns before, during, and after two flood events and SHP construction. Macroinvertebrate and fish communities were analysed using taxonomic, functional, and temporal beta-diversity metrics. Macroinvertebrates were assessed using the nationally standardised STAR_ICMi biomonitoring index and the recently developed Flow-T index. Macroinvertebrate assemblages showed high resilience, recovering taxonomic richness while maintaining “Good ecological status” despite severe flood-induced collapse. Recovery followed a nestedness-to-turnover trajectory, indicating recolonization from refugia rather than community replacement. Flow-T detected transient functional changes not captured by STAR_ICMi. In contrast, fish communities exhibited persistent structural changes, with reduced abundance, marked shifts in species composition, and slower recovery of native salmonids and European bullhead (Cottus gobio) under combined flood and hydropower impacts. These findings show that integrating taxonomic, functional, and temporal approaches improves ecological assessment beyond single-index biomonitoring approaches such as STAR_ICMi alone.
Slope stability in vegetated hillslopes depends on groundwater, geometry, external loading, soil properties, and root reinforcement. This study evaluated a low-plasticity clayey silt (CL–ML) from Loja, Ecuador, under bare soil, Eucalyptus, Pine, Vetiver, and Kikuyu covers. Direct shear tests on root-containing specimens provided equivalent Mohr–Coulomb parameters for limit-equilibrium and PLAXIS 2D strength-reduction analyses considering three slope geometries and three loading conditions: elevated groundwater, groundwater plus an 8 kN m−2 surcharge, and groundwater, surcharge, and pseudo-static loading. The resulting 90 factor-of-safety values were assessed using scenario-based factorial ANOVA and MANOVA. Geometry and loading explained 41.4% and 35.0% of total variance, respectively, whereas numerical method explained 1.1%. Limit-equilibrium factors of safety were 5.4% higher on average than PLAXIS 2D values. The vegetation-cover main effect was small and marginal (η2 = 1.5%, p = 0.051), while significant cover–loading and cover–method interactions indicated a scenario- and method-dependent response. Under pseudo-static loading, Vetiver and Kikuyu showed the highest PLAXIS 2D factors of safety, whereas LEM results remained narrowly grouped, precluding a general ranking of vegetation effectiveness. These findings support scenario-specific evaluation of equivalent root reinforcement in slope-stabilization design.
