Search Results (88)

The integration of water resources, water environment, and water ecology (hereinafter “three-water”) is essential not only for addressing the current water crisis but also for achieving sustainable development. Chaohu Lake is an important water resource and ecological barrier in the middle and lower reaches of the Yangtze River, undertaking such functions as agricultural irrigation, urban water supply, and flood control and storage. Studying the performance of “three-water” in the Chaohu Lake Basin will help to understand the pollution mechanism and governance dilemma in the lake basin. It also provides practical experience and policy references for the ecological protection and high-quality development of the Yangtze River Basin. We used the DPSIR-TOPSIS model to analyze the performance of the river–lake system in the Chaohu Lake Basin and employed an obstacle model to identify factors influencing “three-water.” The results indicated that overall governance and performance of the “three-water” in the Chaohu Lake Basin exhibited an upward trend from 2011 to 2022. Specifically, the obstacle degree of driving force decreased by 19.6%, suggesting that economic development enhanced governance efforts. Conversely, the obstacle degree of pressure increased by 34.4%, indicating continued environmental stress. The obstacle degree of state fluctuated, showing a decrease of 13.2% followed by an increase of 3.8%, demonstrating variability in the effectiveness of water resource, environmental, and ecological management. Additionally, the obstacle degree of impact declined by 12.8%, implying the reduced efficacy of governmental measures in later stages. Response barriers decreased by 5.8%. Variations in the obstacle degree of response reflected differences in response capacities. Spatially, counties and districts at the origins of major rivers and their lake outlets showed lower performance levels in “three-water” management compared to other regions in the basin. Notably, Wuwei City and Feidong County exhibited better governance performance, while Feixi County and Chaohu City showed lower performance levels. Despite significant progress in water resource management, environmental improvement, and ecological restoration, further policy support and targeted countermeasures remain necessary. Counties and districts should pursue coordinated development, leverage the radiative influence of high-performing areas, deepen regional collaboration, and optimize, governance strategies to promote sustainable development. Full article

Extracting drainage networks from a digital elevation model (DEM) with massive cells is time-consuming due to depressions and flats, where flow paths to the outlet cannot be extracted using downslope gradients. Algorithms based on a priority queue are an efficient solution for this task. However, the existing algorithms depend on the insertion order in a priority queue to determine flow directions for cells with equal elevation. This dependency increases the sorting time in the priority queue. Our study developed an improved algorithm (referred to as DZFlood), adopting a dual priority queue. The queue considers elevation and flow distance to outlets. Cells sharing equal elevation and flow distance can be randomly arranged to reduce time costs. A secondary correction is applied to select a more tortuous yet shortest flow path for each flat cell. The visual assessment results show that the flow paths derived by DZFlood are more accurate than five existing algorithms and consistent with the real rivers and lakes. The computation efficiency of DZFlood is 19.2% faster, on average, than that of another priority-queue-based algorithm named LCP. The relative difference between their runtimes is greater when a larger DEM is used. Over a DEM with 3 × 10⁸ cells, DZFlood performs at least 28% faster than LCP. Full article

Lake Hume, a critical reservoir within the Murray River system, Australia, has been identified as a potential source of cyanobacteria in downstream rivers during past mega-blooms. This study aims to evaluate the impact of lake-level fluctuations on cyanobacterial abundance at the dam outlets, with the goal of mitigating the risk of cyanobacteria intake from hydropower and irrigation outlets during periods of low dam levels. Utilising a one-dimensional vertical hydrodynamic model (LAKEoneD), the study simulated time series data on water temperature and stratification within Lake Hume. These outputs were then incorporated into a cyanobacteria growth model driven by water temperature, mixing dynamics and light. Despite inherent uncertainties in the models, the simulated cell counts effectively mirrored bloom occurrences. Consequently, a series of simulations across varying water levels in the lake revealed a consistent risk of significant cyanobacteria intake through both the hydropower and irrigation outlets when water levels dropped below specific thresholds. Notably, water levels below 20 m and 10 m posed heightened risks of releases of seed populations of cyanobacteria from the hydropower and irrigation outlets, respectively. Full article

Lakes are vital freshwater ecosystems that sustain biodiversity, support livelihoods, and drive socio-economic growth globally. However, they face escalating threats from anthropogenic activities, including urbanization, agricultural runoff, and pollution, which are exacerbated by climate change. Phewa Lake in Nepal was selected for this study due to its increasing rates of nutrient enrichment, sedimentation, and pollution. This study evaluated seasonal and spatial water quality variations within the lake by analyzing water samples from 30 sites during the pre-monsoon and post-monsoon seasons. Twenty physicochemical parameters, including the potential of hydrogen (pH), dissolved oxygen (DO), electrical conductivity (EC), and major ions, e.g., calcium (Ca²⁺), magnesium (Mg²⁺), sodium (Na⁺), potassium (K⁺), bicarbonate (HCO₃⁻), chloride (Cl⁻), sulfate (SO₄²⁻), nitrate (NO₃⁻), phosphate (PO₄³⁻), and ammonium (NH₄⁺), were measured. The average pH ranged from 8.06 (pre-monsoon) to 8.24 (post-monsoon), reflecting dilution from monsoon rains and increased carbonate runoff. Furthermore, the DO levels in Phewa Lake averaged 7.46 mg/L (pre-monsoon) and 8.62 mg/L (post-monsoon), with higher values observed post-monsoon due to rainfall-driven oxygenation. Nutrient concentrations were shown to be elevated, with the nitrate concentration reaching 2.31 mg/L during the pre-monsoon period, and the phosphate concentration peaking at 0.15 mg/L in the post-monsoon period, particularly near agricultural runoff zones. The dominant cations in the lake’s hydrochemistry were Ca²⁺ and Mg²⁺, while HCO₃⁻ was the primary anion, reflecting the influence of carbonate weathering. Cluster analysis identified the lake outlet as a high-pollution zone, with the total dissolved solids (TDS) reaching 108–135 mg/L. Additionally, Principal component analysis revealed agricultural runoff and sewage effluents as the main pollution sources. Seasonal dynamics highlighted monsoon-induced dilution and pre-monsoon pollution peaks. These findings underscore the need for targeted pollution control and eutrophication management. By aligning with the sustainable development goals (SDGs) relevant to clean water and climate action, this research provides a replicable framework for sustainable lake management that is applicable to freshwater ecosystems worldwide. Full article

Climate change exerts both direct and indirect influences on the eutrophication of surface water ecosystems in various ways. This study aimed to evaluate the impact of temperature fluctuations on trophic levels through various interdisciplinary coupling analysis methods after land use change, which including water and sediment sample analysis, hydraulic model, remote sensing, and historic data analysis. For the historical analysis, six satellite images of Lake Dianshan were examined to assess algal bloom occurrences and the coverage of Eichhornia crassipes from 2013 to 2023. The correlation between trophic indicators and temperature was analyzed using statistical methods. For the monthly analysis, a total of 27 sediment samples and 54 water samples collected from Lake Dianshan were assessed to determine how seasonal temperature variations influence eutrophication status. The trophic indicators have higher concentration at inlet sampling sites compared to outlet sites, which validated the potential external pollution source. The trophic level of Lake Dianshan is influenced not only by climate change but also significantly by urban human activities. The management of eutrophication has substantially improved the water quality of Lake Dianshan over the past few decades. Furthermore, increasing temperatures demonstrate a positive correlation with the proliferation of cyanobacteria, particularly in urban areas. Full article

The Great Salt Lake, located in Utah, USA, is a saltwater lake with no outlet and is surrounded by vast mountains and salt deserts. We aimed to use Great Salt Lake-derived processed mineral water (hereafter termed as GSL-MW) for maintaining oral health. Therefore, we examined its radical scavenging activity as an antioxidant and its cytoprotective effect on human gingival fibroblasts (hGFs). The scavenging activity against O₂^•− radicals was determined by an electron spin resonance (ESR)-spin trapping technique using two kinds of O₂^•− generation systems; however, we could not reach any concrete conclusion because of the interference caused by GSL-MW in both systems. Detection of ·OH radicals using the ESR-spin trapping technique and kinetic analyses using double-reciprocal plots (corresponding to Lineweaver–Burk plots that are used to represent enzyme kinetics) revealed that GSL-MW has the ability to scavenge ·OH radicals. GSL-MW also showed a weak 2,2-diphenyl-1-picrylhydrazyl (DPPH; a stable radical)-scavenging activity. Regarding the cytoprotective effects, subconfluent hGFs pretreated with 10× and 100× dilutions of GSL-MW for 3 min and then exposed to harsh environmental conditions, such as pure water or 100 μM H₂O₂ for 3 min, showed enhanced cell viability rate. Moreover, 10× and 100× dilutions of GSL-MW reduced oxidative damage in confluent hGFs exposed to 12.5 and 25 mM H₂O₂. Our findings show that GSL-MW has antioxidant potential and cytoprotective effects on hGFs, suggesting that GSL-MW can be used to maintain oral health. Full article

Despite more than 100 years of research, a number of questions concerning the evolution of the post-glacial connection between Lake Ladoga, the largest European lake, and the Baltic Sea remain unanswered. In particular, the location and chronological frames of the paleo-outlet from Lake Ladoga in the Holocene remain debatable. Paleolimnological studies were performed in small lakes in the northern part of the Karelian Isthmus (NW Russia), where the outlet from Lake Ladoga, the Heinjoki Strait, is thought to have existed until the lake drained to the south due to the tilting of its basin. The presence of the indicative “Ladoga species” (e.g., Aulacoseira islandica, Achnanthes joursacense, Cymbella sinuata, Ellerbeckia arenaria, Navicula aboensis, N. jaernefeltii, N. jentzschii, etc.) in the diatom assemblages is used as evidence for the influence of Lake Ladoga during the accumulation of coarse-grained sediments at the bottom of the ancient channel. It also confirms the functioning of the hypothetical northern local branch of the strait. Decreased abundances of the “Ladoga species” and the onset of the accumulation of fine-grained sediments suggest that the water discharge via this paleo-outlet rapidly reduced starting from ca. 4100 cal BP. The termination of the functioning of the Heinjoki Strait is recorded as an abrupt disappearance of the indicative taxa from the diatom record. This was dated to ca. 3500–3200 cal BP, which corresponds to the estimated ages of the birth of the River Neva, the present outlet from Lake Ladoga. Full article

A natural wetland receiving drainage from a 24-ha urbanized catchment in the Falls Lake Watershed of North Carolina was evaluated to determine if it was providing ecosystem services with regards to phosphate and Escherichia coli (E. coli) attenuation. Inflow and outflow characteristics including nutrient and bacteria concentrations along with physicochemical properties (discharge, pH, oxidation reduction potential, temperature, and specific conductance) were assessed approximately monthly for over 2 years. The median exports of phosphate (0.03 mg/s) and E. coli (5807 MPN/s) leaving the wetland were 85% and 57% lower, respectively, relative to inflow loadings, and the differences were statistically significant (p < 0.05). Hydraulic head readings from three piezometers installed at different depths revealed the wetland was a recharge area. Phosphate and E. coli concentrations were significantly greater in the shallowest piezometer relative to the deepest one, suggesting treatment occurred during infiltration. However, severe erosion of the outlets is threatening the stability of the wetland. Upstream drainageway modifications were implemented to slow runoff, and septic system repairs and maintenance activities were implemented to improve water quality reaching the wetland and Lick Creek. However, more work will be needed to conserve the ecosystem services provided by the wetland. Full article

Plain lakes play a crucial role in the hydrological cycle of a watershed, but their interactions with adjacent rivers and downstream water bodies can create complex river–lake relationships, often leading to frequent flooding disasters. Taking Poyang Lake as an example, this paper delves into its interaction with the Yangtze River, revealing the spatiotemporal patterns of flood propagation within the lake and its impact on surrounding flood control measures. The aim is to provide insights for flood management in similar environments worldwide. This study employs a comprehensive approach combining hydrological statistical analysis and two-dimensional hydrodynamic modeling, based on extensive hydrological, topographic, and socio-economic data. The results indicate that the annual maximum outflow from Poyang Lake is primarily controlled by floods within the watershed, while the highest annual lake water level is predominantly influenced by floods from the Yangtze River. The peak discharge typically reaches the lake outlet within 48 h, with the peak water level taking slightly longer at 54 h. However, water storage in the lake can shorten the time that it takes for the peak discharge to arrive. When converging with floods from the Yangtze River, the peak water level may be delayed by up to 10 days, due to the top-supporting interaction. Furthermore, floods from the “Five Rivers” propagate differently within the lake, affecting various lake regions to differing degrees. Notably, floods from the Fu River cause the most significant rise in the lake’s water level under the same flow rate. The top-supporting effect from the Yangtze River also significantly impacts the water surface slope of Poyang Lake. When the Yangtze River flood discharge significantly exceeds that of the “Five Rivers” (i.e., when the top-supporting intensity value, f, exceeds four), the lake surface becomes as flat as a reservoir. During major floods in the watershed, the water level difference in the lake can increase dramatically, potentially creating a “dynamic storage capacity” of up to 840 million cubic meters. Full article

Airborne sensing images harness the combined advantages of hyperspectral and high spatial resolution, offering precise monitoring methods for local-scale water quality parameters in small water bodies. This study employs airborne hyperspectral remote sensing image data to explore remote sensing estimation methods for total nitrogen (TN) and total phosphorus (TP) concentrations in Lake Dianshan, Yuandang, as well as its main inflow and outflow rivers. Our findings reveal the following: (1) Spectral bands between 700 and 750 nm show the highest correlation with TN and TP concentrations during the summer and autumn seasons. Spectral reflectance bands exhibit greater sensitivity to TN and TP concentrations compared to the winter and spring seasons. (2) Seasonal models developed using the Catboost method demonstrate significantly higher accuracy than other machine learning (ML) models. On the test set, the root mean square errors (RMSEs) are 0.6 mg/L for TN and 0.05 mg/L for TP concentrations, with average absolute percentage errors (MAPEs) of 23.77% and 25.14%, respectively. (3) Spatial distribution maps of the retrieved TN and TP concentrations indicate their dependence on exogenous inputs and close association with algal blooms. Higher TN and TP concentrations are observed near the inlet (Jishui Port), with reductions near the outlet (Lanlu Port), particularly for the TP concentration. Areas with intense algal blooms near shorelines generally exhibit higher TN and TP concentrations. This study offers valuable insights for processing small water bodies using airborne hyperspectral remote sensing images and provides reliable remote sensing techniques for lake water quality monitoring and management. Full article

The geomorphological impact of base-level lowering on ephemeral alluvial streams has been extensively investigated through fieldwork, experimentation, and modeling. Yet, the understanding of hydrological parameters governing the dynamics of the stream’s geometry during discrete flood events is lacking due to limited direct measurements of flood-scale erosion/deposition. The emergence of novel remote sensing methods allows for quantifying morphological modifications caused by floods in alluvial streams. This study utilizes drone surveys and hydrological data to quantitatively investigate the relation between channel evolution in alluvial tributaries draining to the receding Dead Sea and the hydrological characteristics of flash floods. Drone-based photogrammetric surveys were conducted before and after 25 floods, over a period of four years, to generate centimeter-scale Digital Elevation Models (DEM) and orthophoto maps of two major streams. The outcomes of these DEMs are maps of ground elevation changes (erosion/deposition), thalweg longitudinal profiles, and channel cross sections, revealing the incision/aggradation along and across the streams. Statistical comparison of results with flow hydrographs identified potential relations linking the hydrological characteristics of each flood and the corresponding geomorphological modifications. Peak discharge emerged as the primary factor influencing sediment removal, leading to more efficient sediment evacuation and a negative sediment budget with increased discharge. Water volumes of floods also exhibited a secondary effect on the sediment budget. The chronological order of floods, whether first or later in the season, was identified as the primary factor determining incision magnitude. Knickpoints formed at the streams’ outlets during the dry period, when lake-level drops, amplifying the impact of the first flood. These findings have potential implications for infrastructure planning and environmental management in the context of climate change and altered water runoff. The research highlights the efficiency of drone-based photogrammetry for cost-effective and timely data collection, providing invaluable flexibility for field research. Full article

The hydrological system of thebasin of Lake Urmia is complex, deriving its supply from a network comprising 13 perennial rivers, along withnumerous small springs and direct precipitation onto the lake’s surface. Among these contributors, approximately half of the inflow is attributed to the Zarrineh River and the Simineh River. Remarkably, Lake Urmia lacks a natural outlet, with its water loss occurring solely through evaporation processes. This study employed a comprehensive methodology integrating ground surveys, remote sensing analyses, and meticulous documentation of historical landslides within the basin as primary information sources. Through this investigative approach, we preciselyidentified and geolocated a total of 512 historical landslide occurrences across the Urmia Lake drainage basin, leveraging GPS technology for precision. Thisarticle introduces a suite of hybrid machine learning predictive models, such as support-vector machine (SVM), random forest (RF), decision trees (DT), logistic regression (LR), fuzzy logic (FL), and the technique for order of preference by similarity to the ideal solution (TOPSIS). These models were strategically deployed to assess landslide susceptibility within the region. The outcomes of the landslide susceptibility assessment reveal that the main high susceptible zones for landslide occurrence are concentrated in the northwestern, northern, northeastern, and some southern and southeastern areas of the region. Moreover, when considering the implementation of predictions using different algorithms, it became evident that SVM exhibited superior performance regardingboth accuracy (0.89) and precision (0.89), followed by RF, with and accuracy of 0.83 and a precision of 0.83. However, it is noteworthy that TOPSIS yielded the lowest accuracy value among the algorithms assessed. Full article

Understanding and modeling water quality in a lake/reservoir is important to the effective management of aquatic ecosystems. The advantages and disadvantages of different water quality models make it challenging to choose the most suitable model; however, direct comparison of 1-D and 3-D models for lake water quality modeling can reveal their relative performance and enable modelers and lake managers to make informed decisions. In this study, we compared the 1-D model MINLAKE and the 3-D model EFDC+ for water temperature, ice cover, and dissolved oxygen (DO) simulation in three Minnesota lakes (50-m Carlos Lake, 23.5-m Trout Lake, and 5.6-m Pearl Lake). EFDC+ performed well for water temperature and DO simulation in the open water seasons with an average root mean square error (RMSE) of 1.32 °C and 1.48 mg/L, respectively. After analyzing the ice thickness with relevant data, it was found that EFDC+ calculates a shorter ice cover period and smaller ice thickness. EFDC+ does not consider snowfall for ice thickness simulation. The results also revealed that EFDC+ considers spatial variance and allows the user to select inflow/outflow locations precisely. This is important for large lakes with complex bathymetry or lakes having multiple inlets and outlets. MINLAKE is computationally less intensive than EFDC+, allowing rapid simulation of water quality parameters over many years under a variety of climate scenarios. Full article

Predicting monthly streamflow is essential for hydrological analysis and water resource management. Recent advancements in deep learning, particularly long short-term memory (LSTM) and recurrent neural networks (RNN), exhibit extraordinary efficacy in streamflow forecasting. This study employs RNN and LSTM to construct data-driven streamflow forecasting models. Sensitivity analysis, utilizing the analysis of variance (ANOVA) method, also is crucial for model refinement and identification of critical variables. This study covers monthly streamflow data from 1979 to 2014, employing five distinct model structures to ascertain the most optimal configuration. Application of the models to the Zarrine River basin in northwest Iran, a major sub-basin of Lake Urmia, demonstrates the superior accuracy of the RNN algorithm over LSTM. At the outlet of the basin, quantitative evaluations demonstrate that the RNN model outperforms the LSTM model across all model structures. The S3 model, characterized by its inclusion of all input variable values and a four-month delay, exhibits notably exceptional performance in this aspect. The accuracy measures applicable in this particular context were RMSE (22.8), R² (0.84), and NSE (0.8). This study highlights the Zarrine River’s substantial impact on variations in Lake Urmia’s water level. Furthermore, the ANOVA method demonstrates exceptional performance in discerning the relevance of input factors. ANOVA underscores the key role of station streamflow, upstream station streamflow, and maximum temperature in influencing the model’s output. Notably, the RNN model, surpassing LSTM and traditional artificial neural network (ANN) models, excels in accurately mimicking rainfall–runoff processes. This emphasizes the potential of RNN networks to filter redundant information, distinguishing them as valuable tools in monthly streamflow forecasting. Full article

The extensive use of the parabens triclosan (TCS) and bisphenol A (BPA) has potential adverse effects on human health and aquatic organisms. However, their monitoring information in freshwater lakes is still limited. This study simultaneously summarized the concentrations, spatial distribution characteristics, and correlations of four types of parabens, TCS, and BPA in the surface water and sediment of Baiyang Lake. Finally, the potential risks of target pollutants were evaluated from two aspects: human health risks and ecological risks. The average contaminations of target compounds in surface water and sediment—BPA, TCS, and ∑₄ parabens—was 33.1, 26.1, 0.7 ng/L and 24.5, 32.5, 2.5 ng/g, respectively. The total concentration of target compounds at the inlet of the upstream Fu River and Baigouyin River is significantly higher than that near Hunan and the outlet. In addition, Spearman’s correlation analysis showed a significant positive correlation between compounds. The health hazards of target compounds in surface water were all within safe limits. However, the risk quotient results indicate that in some locations in surface water, TCS poses a high risk to algae and a moderate risk to invertebrates and fish, and appropriate attention should be paid to these areas. Full article