Search Results (1,523)

Quantifying groundwater storage in karst aquifers remains challenging because of their heterogeneous structure and the scarcity of direct observations. This study proposes a pragmatic approach for characterizing storage and water availability in karst systems at the regional scale using long-term hydrographs from 16 Swiss karst springs and rivers. We distinguish between seasonal storage, associated with recharge events, and low-water storage, which sustains discharge during periods without significant recharge. Seasonal storage was estimated at approximately 30–70 mm for most investigated systems, while total storage reached up to about 140 to 180 mm at some sites, based on recharge–discharge modelling. Low-water storage was estimated to be on the order of 200 mm across most investigated systems, despite differences in hydrogeological settings. Analysis of low-water recession curves showed that most natural springs analyzed in this study followed a similar master recession curve, with low-water conditions defined as beginning at a specific transition discharge of 11.25 L s⁻¹ km⁻². This similarity provides the basis for a regional drought index that estimates the volume of remaining groundwater storage and forecasts discharge several weeks in advance. The results also support a conceptual model in which epikarstic, epiphreatic, and deeper storage compartments attenuate short-term discharge variability while sustaining low-water discharge over prolonged periods. Comparison with non-karst catchments shows that karst hydrogeological systems dampen peak flows but sustain baseflow through distinct storage reservoirs. This approach delivers quantitative indicators to assess drought, manage groundwater, and foresee water shortages in karst regions. Future work will test its validity outside the Swiss dataset. Despite discussed uncertainties in discharge measurements and catchment delineation, results demonstrate that dedicated hydrograph-based analyses can yield robust and transferable insights into karst groundwater storage at regional scales. Full article

Meteorological, soil, and hydrological droughts are among the most important phenomena affecting the natural environment and water management. Prolonged precipitation deficits often result in low river flows, reducing water resources and degrading aquatic ecosystems. This study evaluates the potential of meteorological drought indices as predictors of observed low flows. Long-term meteorological and hydrological data, including precipitation and river discharge records, were analyzed for the Biała Lądecka River catchment in Lower Silesia, southwestern Poland. Meteorological drought was characterized using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) calculated for 1-, 3-, and 6-month timescales, together with corresponding one- and two-week indices. Relationships between drought index values and observed low flows were analyzed while accounting for the time lag of the catchment response. The predictive performance of individual indices was evaluated to determine their suitability for water resource monitoring and management. The results show that meteorological drought indices can effectively indicate the occurrence of low flows, although the strength of the relationships depends on the adopted timescale. Both classical and short-term indices proved useful for analyzing the development of hydrological drought and have potential applications in low-flow monitoring and early warning systems. Full article

Neosalanx taihuensis is a fish species endemic to China, primarily distributed in the middle and lower reaches of the Yangtze and Huaihe rivers and their affiliated lakes. To assess its resource status and facilitate targeted conservation of genetic diversity, we analyzed genetic differences among populations in the lower Yangtze River. Samples were collected from four natural river populations (JJ, AQ, NJ, and TZ) and one lacustrine population (THL). Whole genome resequencing was performed to characterize genetic diversity, population structure, and selection signatures across the five populations. The results showed no obvious genetic divergence among the natural river populations, whereas all natural river populations were distinctly separated from the THL population. The natural river populations harbored higher genetic diversity than the THL population. Gene flow analysis suggested that historical gene exchange might have occurred between TZ and THL, as well as between TZ and NJ. Selective sweep analysis identified Chr01, Chr04, Chr09, and Chr15 as candidate genomic regions potentially carrying adaptive selection signatures. In summary, conservation efforts should prioritize the genetic diversity of both natural river populations and the THL population, facilitate gene flow among populations, and adopt differentiated management strategies for each group. Full article

One of the most common dynamic phenomena occurring in surface waters is the transport of soluble and insoluble contaminants from various sources, such as industry and agriculture. A key concern associated with this transport is the rate at which contaminants migrate downstream to a point of interest, as well as their overall impact. In order to characterize the transport of contaminants in a body of surface water (in this case, a river), this study applied a one-dimensional advection–dispersion model that incorporated transient storage effects. This enabled the characterization of nutrient transport considering varying flow velocities along the river’s course. Adopting a more comprehensive, systemic approach enables a more holistic environmental application and facilitates parameterization of a considerably larger river than in previous case studies. The model’s innovation lies in using routinely monitored water quality constituents to evaluate their ability to inform the characterization of mixing conditions and solute transport in surface water streams. Its dynamic nature provides a reasonable approximation of the real system’s behavior over time. Finally, for management purposes, the proposed model can be replicated without extensive changes to its fundamental structure. Full article

Piezoelectric energy harvesters, characterised by design simplicity, robustness, high energy density and conversion efficiency, as well as scalability, are a viable choice for transducing ubiquitous kinetic energy in a reliable and stable electrical energy source aimed at powering IoT and other prospective applications of autonomous sensors. The performances of this class of harvesting devices can be considerably enhanced by optimising their design configurations. An overview of several optimised piezoelectric harvesters’ designs, with the respective modelling and experimental validation procedures, is provided in this work. In this regard, special attention is dedicated to innovative topologies of the considered devices, as well as to excitation mechanisms leading to considerably ameliorated output power levels. Possible applications in wearables for biomedical applications, structural health monitoring in aircraft, open-field applications (either for environmental monitoring of river flows or rainfall-actuated devices), as well as in automobile tyre pressure monitoring, are given as elaborated examples of conceivable sensing nodes. A basic overview of the aspects related to the conforming power management electronics and an outlook on future research directions are also given. Full article

Changes in river channel morphology under the influence of natural and anthropogenic factors pose a serious threat to the stability of aquatic ecosystems and water resource use, especially in regions with limited hydrological information. This study presents, for the first time, a three-dimensional numerical investigation of channel processes in the Talas River (Kazakhstan), employing the Volume of Fluid (VOF) method for free-surface flow simulation and a non-Newtonian model for sediment transport and riverbed morphodynamics. To verify the developed mathematical model, experimental data on the flow in the L-shaped channel and Earthfill dam break were used, which provided high reliability of the calculated results. The calculations showed a significant increase in the channel area in the studied section of the Talas River (from 41,334.92 m² to 56,890.17 m²) for the period from 2019 to 2024, mainly due to the intensification of the dynamics of currents and the formation of additional vortex zones with a diameter of 50 to 200 m. It was found that in places of local flow acceleration, water velocity increased up to 4.5 m/s, leading to bank erosion and channel widening, whereas after redistribution of channel flows, the maximum velocity decreased to 2.8 m/s, ensuring stabilisation of morphological changes. The results of the study underline the need for an integrated approach to river morphodynamics management using numerical modelling to predict channel changes, minimise flood risks and optimise the use of water resources. The presented computational approach can be adapted to analyse hydrodynamic processes in other poorly studied river systems, which significantly expands its scientific and practical value. Full article

This study investigates the impacts of human activities and climate variability on hydrologic alterations in the Mobile River and Perdido River Basins of Alabama. The research uses a machine learning approach, specifically cubist models, to quantify and predict changes in flow duration curves (FDCs) under both historical (1980–2009) and future climate scenarios. Future climate projections include the Representative Concentration Pathways (RCP 4.5 and RCP 8.5) and the Shared Socioeconomic Pathways (SSP2 4.5 and SSP5 8.5), evaluated for two future periods: 1980–2069 and 1980–2099. The models incorporate a wide range of covariates, including basin geomorphology, aquifer characteristics, land cover, water storage, environmental factors, solar radiation, census data, and water use data. Under the baseline period (1980–2009), most level 12 hydrologic unit codes (HUC12s) in both basins showed alterations, with substantial differences observed between pre- and post-alteration FDCs. The model performance varied, with a Nash–Sutcliffe Efficiency between 0.91 and 0.95 for testing and between 0.98 and 0.99 for training during the baseline period. Future projections under the RCP 4.5 and RCP 8.5 scenarios generally differed significantly from baseline conditions across all flow regimes (p < 0.05). In contrast, SSP2 4.5 showed comparatively limited statistical significance, while SSP5 8.5 exhibited significant departures from baseline conditions across all flow regimes, reflecting the greater influence of high-emissions climate forcing on projected hydrologic alterations. Overall, the RCP scenarios projected more widespread statistically significant changes than the corresponding SSP scenarios at the same forcing level, particularly when comparing RCP4.5 with SSP2-4.5, while both RCP8.5 and SSP5-8.5 consistently indicated greater hydrologic alterations than their moderate-emissions counterparts. These findings highlight the importance of considering different flow regimes when assessing the impacts of climate variability on streamflow. This study contributes to the understanding of hydrologic alterations in the Mobile River and Perdido River Basins, providing insights for water resource management and ecological conservation efforts in the region. Full article

Rainfall–runoff modeling is a key challenge in hydrological research. Despite the extensive application of long short-term memory (LSTM) networks in rainfall–runoff modeling, our understanding of the influence of different hyperparameter configurations on various hydrograph components, as well as the linkages between hydrological concepts and LSTM architectures, remains elusive. Here, we integrated Multi-Objective Particle Swarm Optimization (MOPSO) with LSTM hyperparameter optimization by targeting the root mean square error of the overall hydrograph (RMSE_all), high-flow (RMSE_high) and low-flow (RMSE_low) dynamics, and water volume deviation (Dv). The MOPSO-LSTM framework was applied to the upstream catchments of the Miyun Reservoir in Beijing, China. At a lead time of 1d, the optimal solution achieved an NSE of 0.920 in the Chaohe River Basin, with a minimum RMSE_all of 0.848 m³/s, RMSE_high of 2.081 m³/s, RMSE_low of 0.382 m³/s, and Dv of 0.002%. However, as the lead time increased to 3 and 7 days, the maximum NSE declined to 0.747 and 0.560, respectively, with process-related metrics deteriorating more substantially than water balance-related metrics. The Baihe River Basin performed better, with maximum NSE and KGE values of 0.949 and 0.970 at a lead time of 1d. Clear trade-offs among different evaluation objectives were further identified, particularly the competitive relationship between RMSE_high and RMSE_low, as well as the coupling between RMSE_low and Dv. SHAP (Shapley additive explanation) and partial dependence plots (PDPs) were used to quantify and interpret the effects of hyperparameters on model performance, and the results showed that learning rate, number of units, and lookback window served as the most influential hyperparameters. Moreover, optimization preferences resulted in distinct hyperparameter configurations, where Dv-oriented solutions favored smaller learning rates, longer lookback windows, and larger batch sizes than RMSE-oriented solutions. Compared with the Chaohe River Basin, the larger Baihe River Basin favored LSTM configurations with longer lookback windows, more hidden units, higher learning rates, and lower dropout rates, which was associated with the hydrological memory of the catchment. Overall, this study provides a novel multi-objective LSTM optimization framework, improving the understanding of LSTM hyperparameters and offering practical guidance for hydrological prediction and water resource management. Full article

The Upper Yellow River (UYR) basin is the predominant runoff-yielding area of the entire watershed. Accurately simulating annual runoff is crucial for water resources management. While the Budyko framework effectively captures long-term hydro-thermal equilibrium, it struggles to represent nonlinear dynamics, flow channel routing, and spatial interconnections. Here, we propose a hybrid physics- and data-driven approach by coupling the Budyko framework (Fu’s equation) with an eXtreme Gradient Boosting (XGBoost) model, integrating upstream channel routing and antecedent storage-lag features using long-term hydrologic observations for nonlinear runoff simulation and driver attribution. To resolve the feature multicollinearity on machine learning attributions, input variables were consolidated into three groups: precipitation driven, evaporation limitation, and flow storage lag. The results demonstrate that the Budyko–XGBoost coupled model enhances annual runoff prediction accuracy compared to the standalone Fu equation and pure XGBoost, raising the coefficient of determination (R²) to 0.63–0.86 (mean R² = 0.75) and capturing both nonlinear dynamics and turning points, alongside reductions of 6.2% in the mean RMSE (18.77 mm) and 11.0% in the MAE (13.66 mm) compared to the pure XGBoost model (mean R² = 0.70, RMSE = 20.01 mm, and MAE = 15.35 mm). Group-level SHAP attributions reveal that flow storage-lag drivers (R_lag and $R_{\mathit{lag}}^{\prime }$) exert a primary control on runoff evolution across all the stations. Spatially, secondary drivers exhibit heterogeneity: in relatively humid, energy-limited regions (Maqu), high precipitation promotes positive runoff deviations, whereas in arid/semi-arid, water-limited reaches (e.g., Guide, Xunhua, Xiaochuan, and Lanzhou stations), high precipitation is absorbed by severe soil moisture deficits and reservoir interception, exerting a negative effect on runoff deviation. Full article

At Yuehai Lake, China, managed Yellow River diversion maintains open water while imposing a persistent hydraulic boundary on the shallow aquifer. We combined water balance, zonal Darcy estimation, a calibrated regulated-stage groundwater model, particle tracking, major ions, and stable isotopes. Yellow River diversion supplied 93.7% of quantified external inflows. Zonal Darcy and model leakage were 2.39 and 2.47 × 10⁶ m³ a⁻¹. Across the monitored stage range (1105.96–1106.42 m), modeled leakage was 2.41–2.53 × 10⁶ m³ a⁻¹; alternative upper-aquifer structures produced 1.91–3.02 × 10⁶ m³ a⁻¹ without reversing exchange or eliminating the mound. Particles from 441 lakebed cells moved a median 24.5 m over 1065 d, indicating slow near-shore advection. Selected-screen isotopes were consistent with evaporatively enriched lake-water influence, whereas major ions showed a distinct west–east shift from Ca–Mg–HCO₃ toward Na–SO₄ and Na–Cl facies. Yuehai Lake therefore functions as a regulated losing lake. Its salinity pattern likely reflects lake leakage, agricultural return flow, soil-salt mobilization, background saline groundwater, and restricted drainage. Management should integrate lake-stage, groundwater-flow, and salinity monitoring. Full article

Urban agglomerations rely on both direct physical water intake and substantial virtual water embedded in cross-regional traded commodities and services to meet water demand. It is important to analyze the complex virtual water flows in urban agglomerations to advance sustainable water utilization and coordinated regional sustainable development. In this study, we constructed a multi-scale hierarchical analysis framework covering industrial sectors, internal cities and external hinterland regions by coupling multi-regional input–output (MRIO), ecological network analysis (ENA), and structural decomposition analysis (SDA). The framework was adopted to quantify consumption-driven virtual water flows across the Pearl River Delta (PRD) urban agglomeration in 2012, 2017 and 2022. Furthermore, we quantified the economic value of virtual water flows by considering water rights trading prices, which mainly reflect the scarcity value of regional water resources, aiming to provide new perspectives for water resources compensation and sustainable water management decision making. The results showed that the virtual water flows mainly satisfied food-related water requirements in the PRD. Declining water use intensity in external supply regions was the dominant factor reducing the water footprint in the PRD. The virtual water flows had greater economic value in the water-scarce northern provinces. On this basis, we put forward targeted financial subsidy recommendations for water-supplying external regions; the above economic quantification serves as the core evidence supporting this subsidy proposal. This work provides decision support for formulating sustainability-oriented water policies, balancing interregional water ecological benefits, and realizing long-term sustainable utilization of water resources. Full article

Periphytic algae and extracellular polymeric substances (EPS) shape river biofilms, but hydrodynamic relationships remain poorly resolved in mountain rivers. We surveyed 32 points in the Nanxi River, Zhejiang, China, in August and October 2025. Gaussian, linear, and Spearman analyses assessed velocity responses and algal–EPS relationships. Algal-group densities showed significant unimodal responses (p < 0.05), peaking at 0.62–0.63 m/s for diatoms, 0.14–0.20 m/s for cyanobacteria, and 0.23 m/s for green algae. Total EPS was unrelated to velocity; soluble EPS decreased, whereas bound fractions increased (p < 0.05). Total algae correlated with total EPS (ρ = 0.65–0.73, p < 0.01), and diatoms with bound fractions (ρ = 0.52–0.68, p < 0.05). These patterns suggest that flow may affect biofilms through linked pathways: direct scouring and EPS redistribution, and differential algal detachment and retention that alter community composition and, in turn, EPS production and partitioning. Group-specific density peaks provide a quantitative basis for determining site-specific near-bed velocity ranges for sustainable flow management. The findings provide field observational evidence for aquatic habitat conservation and sustainable water-resource management. However, sampling covered only two periods, and hydrodynamics were represented solely by near-bed velocity; long-term multiparameter monitoring is needed. Full article

This study investigated nitrate contamination, potential nitrate sources, and transformation processes in shallow and deep groundwater of a steep coastal agricultural catchment in western Japan. Hydrochemistry and Endmember Mixing Analysis (EMMA) were applied to shallow and deep groundwater samples collected along a groundwater flow path. A spring and a river sample were used for comparative purposes. The results suggested that the groundwater hydrochemistry comprised mixed, Ca-HCO₃, Ca-Cl, and Na-Cl water types. Nitrate concentrations exceeded 10 mg L⁻¹ in 51.1% (23 out of 45) of the groundwater samples, higher in upstream groundwater than downstream groundwater, especially in deep wells. EMMA suggested agricultural recharge water as potentially the main nitrate source contributor to groundwater. Sewage contributions were greater in shallow wells, and deep natural groundwater in deep wells. The transformation processes were associated with nitrate addition via fertilizers and nitrification, water mixing, and nitrate removal potential by denitrification in shallow downstream wells. Sewage contributions were associated with the shallow downstream groundwater in areas with a greater residential area. Groundwater mixing was suggested to influence hydrochemical variability, especially in DD groundwater, which showed stronger coastal influences. These findings improve understanding of nitrate contamination and support sustainable groundwater management in steep coastal agricultural areas. Full article

Winter imposes severe ecological constraints on Eurasian otters (Lutra lutra), yet the environmental characteristics of their winter marking sites remain poorly understood. We characterized winter sprainting sites along a human disturbance gradient in Changbai Mountain, northeastern China. In January 2025, 55 sites were recorded along three rivers and assigned to urban or wild river-reach contexts based on the broader spatial and management context of each reach. We measured topographic, hydrological, riparian, fish-diversity, and anthropogenic variables. Broad environmental gradients were summarized using Factor Analysis of Mixed Data (FAMD), and five local variables were compared between river-reach contexts using exploratory tests with Holm adjustment. Of the 55 sites, 54 were beside flowing, unfrozen water. Intermediate-to-deep water, natural banks and forested riparian backgrounds were common. The first two FAMD dimensions explained 52.5% of environmental variation, representing a spatially coupled gradient involving anthropogenic remoteness and river-section fish resource background, and a topographic and channel-structure contrast. Urban and wild sites differed in water depth, bank type, and vegetation cover, while sprainting sites occurred in both. These findings show that winter marking activity was concentrated within accessible river sections embedded in contrasting landscape contexts. Full article

River networks influenced by tides represent dynamic, hydrologically complex systems where fluvial inflows interact with oceanic tidal forcing. Conventional flow-based indica-tors of hydrologic alteration (IHA) inadequately capture tidal-driven dynamics, including diurnal water level fluctuations, flow reversals, and tidal asymmetry. This study develops an augmented IHA (AIHA) framework comprising 96 indicators derived from hourly-resolution hydrodynamic simulations (1960–2019) in the Pearl River Delta (PRD), China. The AIHA extracts four daily series—ebb-peak flow and residual, highest, and lowest water levels—supplemented by tidal characteristic metrics. A moving t-test identified 1991 as the significant regime shift, enabling comparison of reference (1960–1991) and altered (1992–2019) periods. Three-dimensional alteration was assessed as follows: deviation from the range of variability (RVA), shift in central tendency (RCM), and change in dispersion (RCD). Indicator importance was integrated via CRITIC weighting and multi-site Borda scoring. Results show that range shifts and central-tendency shifts were generally dominated by low-intensity alteration, accounting for 58.3–71.9% and more than 85% of the indicators, respectively, whereas dispersion shifts were more pronounced, with medium- and high-alteration indicators accounting for an average of 42.4%. Water level indicators exhibited substantially greater alteration sensitivity than flow indicators, particularly in estuarine zones where the alteration degrees of some indicators exceeded 90%. Among hydrological elements, ebb-peak flow indicators responded more strongly in range shifts, with an average comprehensive alteration degree of 29.6%, while water level indicators showed more pronounced changes in central tendency and dispersion; the lowest water level indicators were especially sensitive, with average comprehensive alteration degrees of 19.6% and 77.3%, respectively. Spatially, center-of-distribution shifts (RCM) diverged: positive in western/northern tributaries (increased flows) versus negative in the eastern PRD (decreased flows). Integrated Borda scoring identified low-flow extremes during dry seasons, event timing, and tidal modulation as the most sensitive responses to hydrological stress. The AIHA framework demonstrates that tidal river alteration is characterized by intensified low-flow volatility and amplified tidal influence, with water level metrics providing a superior detection capacity than achieved by discharge alone. This process-integrated approach offers robust quantitative support for ecological flow management and estuarine restoration in tidal environments globally. Full article