High Water Levels Research Articles

Trophic niche variation driven by water level fluctuations facilitates the co-occurrence of invasive tilapia species in a subtropical reservoir in China.

Investigating how multiple invasive fish species with similar ecological traits respond to different environmental conditions is crucial to understanding their successful invasion and coexistence. Here, we used stomach content analysis and stable isotope analysis to analyse the effects of water level fluctuation on the trophic niche plasticity of three dominant co-occurring invasive tilapia species (Coptodon zillii, Sarotherodon galilaeus, and Oreochromis niloticus) in the Shanmei Reservoir, southern China. We found that the tilapia species exhibited an iliophagous habit with dietary variations between the high-water (HW) and low-water (LW) level periods. During the LW period, tilapia fishes primarily fed on periphytic algae, whereas during the HW period, they reduced their consumption of epiphytic algae and increased their intake of plant remains. Biofilms were the most assimilated resource by the species during the LW period, whereas riparian plants dominated during the HW period. The niche width and niche overlap of the three tilapia species were significantly greater in the HW period than in the LW period. However, their trophic positions were not significantly affected by water level fluctuations. Our findings indicate that temporal variation in diet composition and trophic niche, driven by water level fluctuations, may favor food resource partitioning and facilitate the coexistence of these invasive tilapia species.

Exploring Optimal Complexity for Water Stress Representation in Terrestrial Carbon Models: A Hybrid‐Machine Learning Model Approach

AbstractTerrestrial biosphere models offer a comprehensive view of the global carbon cycle by integrating ecological processes across scales, yet they introduce significant uncertainties in climate and biogeochemical projections due to diverse process representations and parameter variations. For instance, different soil water limitation functions lead to wide productivity ranges across models. To address this, we propose the Differentiable Land Model (DifferLand), a novel hybrid machine learning approach replacing unknown water limitation functions in models with neural networks (NNs) to learn from data. Using automatic differentiation, we calibrated the embedded NN and the physical model parameters against daily observations of evapotranspiration, gross primary productivity, ecosystem respiration, and leaf area index across 16 FLUXNET sites. We evaluated six model configurations where NNs simulate increasingly complex soil water and photosynthesis interactions against test data sets to find the optimal structure‐performance tradeoff. Our findings show that a simple hybrid model with a univariate NN effectively captures site‐level water and carbon fluxes on a monthly timescale. Across a global aridity gradient, the magnitude of water stress limitation varies, but its functional form consistently converges to a piecewise linear relationship with saturation at high water levels. While models incorporating more interactions between soil water and meteorological drivers better fit observations at finer time scales, they risk overfitting and equifinality issues. Our study demonstrates that hybrid models have great potential in learning unknown parameterizations and testing ecological hypotheses. Nevertheless, careful structure‐performance tradeoffs are warranted in light of observational constraints to translate the retrieved relationships into robust process understanding.

The properties of potato starch with different moisture content treated by cold plasma:Structure, physicochemical and digestive properties

To investigate the effect and mechanism of water on the structure, physicochemical properties, and in vitro digestibility of starch treated with CP, different moisture content (16.7 %, 28.6 %, 37.5 %, 44.4 %, and 50 %, w/w) were used, followed by treatment with CP (40 V, 1 A, 3 mins). Results show that CP treatment preserves the Maltese cross pattern, crystal morphology, and Fourier transform infrared spectroscopy spectra of potato starch. However, significant changes were observed in molecular weight, chain length distribution, average particle size, ordered structure, and relative crystallinity. As moisture content increased, the etching effect on the particle surface intensified, leading to further reductions in molecular weight and ordered structure. Concurrently, amylose content, solubility, relative crystallinity, and resistant starch content increased. At higher water levels, water molecules exhibited protective effects, mitigating CP-induced structural damage by reducing etching and loss of molecular weight. These findings suggest that the role of water in CP treatment is complex and provide insights into the interaction between CP and water in starch properties, highlighting its potential applications in starch-based foods.

Untangling the coupling effect of water quality and quantity on lake algal blooms in Lake Hulun from a dual perspective of remote sensing and sediment cores

Algal blooms and sediment diatoms are crucial indicators of lake water ecology, influenced by water quantity and quality. However, the coupled effects of water quality and quantity changes on algal blooms are still unclear, especially for lakes in cold and arid regions. This study assessed the long-term variations in algal blooms in Hulun Lake using a novel approach combining remote sensing and sediment core samples for diatom analysis. Two mutation points from the structural change test were identified in approximately 2000 and 2010 for algal bloom area (MBE) and sediment diatom richness, indicating asynchronous algal blooms. A structural equation model (SEM) demonstrated that water level (WL) changes were the dominant influencing factor, co-driving the variations in algal blooms and sediment diatoms in conjunction with total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD). The results revealed nonlinear relationships between the lake WL, TN, Chla, and COD. The water level of 543 m emerged as a critical threshold affecting the relationship between water quality and quantity. Distinct differences in this relationship were observed when water levels were above or below this threshold. These variations became particularly pronounced during periods of high and low water levels. The results provide novel insights into the dynamics of algal blooms and can further support lake ecosystem conservation and management.

Dissipation Scaled Internal Wave Drag in a Global Heterogeneously Coupled Internal/External Mode Total Water Level Model

AbstractThis study showcases a global, heterogeneously coupled total water level system wherein salinity and temperature outputs from a coarser‐resolution (12 km) ocean general circulation model are used to calculate density‐driven terms within a global, higher‐resolution (2.5 km) depth‐averaged total water level model. We demonstrate that the inclusion of baroclinic forcing in the barotropic model requires modification of the internal wave drag term to prevent excess degradation of tidal results compared to the barotropic model. By scaling the internal tide dissipation by an easy to calculate dissipation ratio, the resulting heterogeneously coupled model has complex root mean square errors (RMSE) of 2.27 cm in the deep ocean and 12.16 cm in shallow waters for the tidal constituent. While this represents a 10%–20% deterioration as compared to the barotropic model, the improvements in total water level prediction more than offset this degradation. Global median RMSE compared to observations of total water levels, 30‐day sea levels, and non‐tidal residuals improve by 1.86 (18.5%), 2.55 (42.5%), and 0.36 (5.3%) cm respectively. The drastic improvement in model performance highlights the importance of including density‐driven effects within global hydrodynamic models and will help to improve the results of both hindcasts and forecasts in modeling extreme and nuisance flooding. With only an 11% increase in model run time compared to the fully barotropic total water level model, this approach paves the way for high resolution coastal water level and flood models to be used alongside climate models, improving operational forecasting of total water levels.

Flooding and elevated prenatal depression in a climate-sensitive community in rural Bangladesh: a mixed methods study.

Prenatal depression can have lasting adverse impacts on child health. Little is known about the impact of floods on prenatal depression in low- and middle-income countries. We conducted a cross-sectional survey of 881 pregnant women from September 24, 2023 to July 19, 2024 in riverine communities in rural Bangladesh. We recorded participant-reported flooding in the past 6 months, administered the Edinburgh Postnatal Depression Scale (EPDS), and obtained water level data and remote sensing data on distance to surface water. We fit generalized linear and log-linear models adjusting for month, wealth, education, age, and gestational age. We conducted 2 focus group discussions with 20 adult women. 3.6% of compounds were flooded in the past 6 months. Compound flooding was associated with elevated depression (adjusted prevalence ratio (aPR) = 2.08, 95% CI 1.14, 3.51) and thoughts of self-harm (aPR=8.40, 95% CI 4.19, 16.10). Latrine flooding was associated with higher depression (aPR=3.58, 95% CI 1.49, 7.29)). Higher water levels and shorter distance to permanent surface water were significantly associated with mean EPDS scores. Focus groups revealed that domestic violence, inadequate sanitation, gendered vulnerabilities in accessing latrines, childcare difficulties, and food insecurity were key drivers of depression due to floods. Flood preparedness strategies included relocation, storing food, and home modifications. Flooding, higher water levels, and proximity to water bodies were associated with prenatal depression in a rural, low-income setting. Inadequate sanitation and hygiene infrastructure were particularly strong drivers of depression. Eunice Kennedy Shriver National Institute of Child Health and Human Development. Evidence before this study: We searched SCOPUS titles, abstracts, and keywords as follows: (antenatal OR prenatal OR perinatal OR prepartum OR pregnan* OR antepartum OR maternal) AND (depress* OR "mental health") AND (flood*). After filtering to include research articles focused on humans, we identified 35 articles, including 3 protocols, 4 reviews, 22 research articles in high-income settings, and 7 research articles in low- or middle-income countries (LMICs).In high-income settings, two studies have found that flooding is associated with prenatal depression. A review of the influence of extreme weather events on maternal health in LMICs only found one study that investigated the relationship between flooding and mental health (specifically coping) in pregnancy, but it did not measure depression. The search did not yield any studies that have investigated the relationship between flooding and prenatal depression in LMICs.Added value of this study: To our knowledge, this is the first study estimating the association between flooding and prenatal depression in an LMIC. In a cross-sectional survey in a flood-prone region of rural Bangladesh, we found that flooding of the household compound and latrine was associated with higher prenatal depression prevalence. Proximity to surface water and higher water levels were associated with higher Edinburgh Postnatal Depression Scale scores. Our study describes flood preparedness strategies used by pregnant women and their households to inform climate adaptation in rural, riverine communities. We observed that these strategies largely focused on short-term mitigation rather than long-term resilience as more than half of all strategies involved temporary relocation.Additionally, we qualitatively examined gender-specific vulnerabilities related to flooding to understand mechanisms through which flooding may contribute to prenatal depression, with the aim of informing targeted flood resilience interventions for pregnant women. Women reported increased domestic violence during floods, gendered vulnerabilities in accessing latrines, and childcare difficulties, and food insecurity during floods.Implications of all the available evidence: Our findings underscore the need to integrate maternal mental health care into climate resilience policy in flood-prone regions to prevent adverse downstream effects on child development and birth outcomes. Though pregnant women described multiple adaptation approaches, strong associations between flooding and depression indicate that existing adaptation methods fall short of supporting climate-related resilience. Climate-resilient water, sanitation, and hygiene (WASH) infrastructure may be particularly important to prenatal mental health during floods. Interventions may be most effective if targeted to women residing in areas closest to surface water.

Methane and carbon dioxide evasion from a mosaic of Amazon lakes, river channels, and inundated forests

Seasonally inundated forests are the largest type of wetland in the Amazon basin. Here we provide new data from inundated forests, a lake, and river channels during high water in the forested Anavilhanas archipelago (Negro River, Brazil). Evasion pathways of CH4 in flooded forests include tree trunks, diffusion from the water, and ebullition. Within flooded forest sites, diffusive CH4 fluxes were lowest (mean, 6.2 µmol m-2 h-1), ebullitive fluxes averaged 50 µmol m-2 h-1, and fluxes from the trees had the highest fluxes when expressed per inundated surface area (83 µmol m-2 h-1). The lake and river channels usually had higher CH4 and CO2 fluxes than inundated forests. Overall, mean CH4 fluxes from inundated forests in our study were lower than fluxes measured in nutrient-rich inundated forests. Our results contribute to understanding the heterogeneity of C fluxes from inundated forests. Water levels, currents and extent of inundated habitats contribute to variability in gas fluxes. Outgassing rates are expected to become more variable with projected periods of especially high and low water levels as the climate changes.

The Impact of Heterogeneous Market Sentiments on Corporate Risk-Taking and Governance

This research focuses on how market sentiment affects corporate governance in the Chinese market. The sample covers the years from 2014 to 2023. Market sentiment is estimated using a cross-sectional absolute deviation (CSAD) model, and earnings quality is used as an indicator of the consequences of corporate governance. Both mutual fund shareholding and the number of firm visits by mutual fund analysts are verified as effective corporate governance instruments that work well in a regular market but become ineffective when the market sentiment is high. The reason for this is that managers’ expectations change, and they may believe that disclosing good news during high-sentiment market periods significantly increases the share prices and helps them meet their performance requirements. In a high-sentiment market, an incentive contract encourages managers to take on projects with inappropriate risk or even manipulate earnings. One potential solution is to adopt venture capital firms’ high-water mark and clawback clauses to prevent managers from focusing on short-term goals rather than seeking long-term business sustainability.

Geotechnical characteristics of levees subjected to sand boil due to high-water levels

The investigation of river levees holds significant implications for mitigating flood damage. Sand boiling, backward erosion piping, and phenomena manifesting along the riverside of levees directly imperil the integrity of these structures. It is imperative to address these phenomena comprehensively to safeguard both lives and property amidst flood events. The principal aim of this research is to delineate the variances in geotechnical conditions between sand boils observed at slope toes on the landside and those occurring at a distance from this region along the levee. Therefore, this study conducted extensive boring investigations at sites where sand boils occurred. The soil samples sampled from the boring investigations were analysed for grain size. The results of a series of geotechnical investigations showed that in the cases where sand boils occurred near the toe of the slope, a series of sandy soils with grain size characteristics similar to those of the sand boils were deposited in the foundation of the levee. On the other hand, in the case where the sand boil occurred far from the toe of the slope, sandy soil with grain size characteristics similar to that of the sand boil was deposited only on the landside.

High Water Level Forecast Under the Effect of the Northeast Monsoon During Spring Tides

One of the manifests of air-sea interactions is the change in sea level due to meteorological forcing through wind stress and atmospheric pressure. When meteorological conditions conducive to water level increase coincide with high tides during spring tides, the sea level may rise higher than expected and pose a flood risk to coastal low-lying areas. In Hong Kong, specifically when the northeast monsoon coincides with the higher spring tides in late autumn and winter, and sometimes even compounded by the storm surge brought by late-season tropical cyclones (TCs), the result may be coastal flooding or sea inundation. Aiming at forecasting such sea level anomalies on the scale of hours and days with local tide gauges using a flexible and computationally efficient method, this study adapts a data-driven method based on empirical orthogonal functions (EOF) regression of non-uniformly lagged regional wind field from ECMWF Reanalysis v5 (ERA5) to capture the effects from synoptic weather evolution patterns, excluding the effect of TCs. Local atmospheric pressure and winds are also included in the predictors of the regression model. Verification results show good performance in general. Hindcast using ECMWF forecasts as input reveals that the reduction of mean absolute error (MAE) by adding the anomaly forecast to the existing predicted astronomical tide was as high as 30% in February on average over the whole range of water levels, as well as that compared against the Delft3D forecast in a strong northeast monsoon case. The EOF method generally outperformed the persistence method in forecasting water level anomaly for a lead time of more than 6 h. The performance was even better particularly for high water levels, making it suitable to serve as a forecast reference tool for providing high water level alerts to relevant emergency response agencies to tackle the risk of coastal inundation in non-TC situations and an estimate of the anomaly contribution from the northeast monsoon under its combined effect with TC. The model is capable of improving water level forecasts up to a week ahead, despite the general decreasing model performance with increasing lead time due to less accurate input from model forecasts at a longer range. Some cases show that the model successfully predicted both positive and negative anomalies with a magnitude similar to observations up to 5 to 7 days in advance.

Prediction of impulse waves generated by the potential failure of large deposits in the Rumei Reservoir, Lancang River, China

The impulse wave generated by the reservoir landslide seriously endangers the surrounding safety. In this paper, the failure mode of a large deposit in Rumei Reservoir, China was first explored by centrifuge test. Thereafter, a physical model based on Froude similarity (scale 1:200) and a numerical model based on fluid‒solid coupling were constructed. The failure motion process and the generated impulse waves of the deposits at high (2895 m) and low (2750 m) water levels are studied in detail. The results of the two models are similar. The velocity and wave height of the deposits at the 2750 m water level are greater than those at the 2895 m water level. The maximum wave heights generated in the river under both conditions exceed 46 m and 22 m, respectively, and the maximum run-ups formed on the opposite bank are 71 m and 30 m, respectively. This also suggests that landslides in the near field area are dangerous. Waves at both water levels will not overtop the dam, but attention should be given to the effect of the first wave at the 2895 m water level on the dynamic water pressure in the key area of the dam.

High Capacity and Reversible Fragile Watermarking Method for Medical Image Authentication and Patient Data Hiding.

The exchange of medical images and patient data over the internet has attracted considerable attention in the past decade, driven by advancements in communication and health services. However, transferring confidential data through insecure channels, such as the internet, exposes it to potential manipulations and attacks. To ensure the authenticity of medical images while concealing patient data within them, this paper introduces a high-capacity and reversible fragile watermarking model in which an authentication watermark is initially generated from the cover image and merged with the patient's information, photo, and medical report to form the global watermark. This watermark is subsequently encrypted using the chaotic Chen system technique, enhancing the model's security and ensuring patient data confidentiality. The cover image then undergoes a Discrete Fourier Transform (DFT) and the encrypted watermark is inserted into the frequency coefficients using a new embedding technique. The experimental results demonstrate that the proposed method achieves great watermarked image quality, with a PSNR exceeding 113dB and an SSIM close to 1, while maintaining a high embedding capacity of 3 BPP (Bits Per Pixel) and offering perfect reversibility. Furthermore, the proposed model demonstrates high sensitivity to attacks, successfully detecting tampering in all 18 tested attacks, and achieves nearly perfect watermark extraction accuracy, with a Bit Error Rate (BER) of 0.0004%. This high watermark extraction accuracy is crucial in our situation where patient data need to be retrieved from the watermarked images with almost no alteration.

Context dependence of grassland plant response to arbuscular mycorrhizal fungi: The influence of plant successional status and soil resources

Abstract Many of the disturbance‐sensitive, late successional plant species in grasslands respond to arbuscular mycorrhizal (AM) fungi more positively via growth and establishment than plants that readily establish in disturbed areas (i.e. early successional species). Inoculation with AM fungi can therefore aid the establishment of late successional species in disturbed areas. If the differential benefit of AM fungi to late versus early successional plants is context‐dependent, however, this advantage could be diminished in high phosphorus (P) post‐agricultural soils or in future climates with altered precipitation. In this greenhouse experiment, we tested if late successional plant species are less plastic in their reliance on AM fungi than early successional plants by growing 17 plant species of different successional status (9 early and 8 late successional) in full factorial combinations of inoculated or uninoculated with AM fungi, with ambient or high P levels, and with low or high levels of water. AM fungi positively affected the biomass of the 17 grassland plant species, but across all environments, late successional plant species generally responded more positively to AM fungi than early successional plants species. AM fungal growth promotion and change in below‐ground biomass allocation was generally diminished with P fertilizer across all plant species, and while there was significant variation among plant species in the sensitivity of AM fungal responsiveness to P fertilization, this differential sensitivity was not predicted by plant successional status. The role of AM fungi in plant growth promotion was not generally altered by variation in watering, however late successional plant species allocated a greater proportion of their biomass below‐ground in response to AM fungi in low versus high water conditions. Synthesis. Overall greater responsiveness to arbuscular mycorrhizal (AM) fungi by late successional species is consistent with an important role of AM fungi in plant succession, even while AM fungi are less impactful overall in high P soils. However, the increase in responsiveness of below‐ground allocation of late successional species to AM fungi in low water conditions suggests that successional dynamics may be more dependent on AM fungi in future climates that feature greater propensity for drought.

Hydrological-driven changes in the phytoplankton community structure under nutrient stress in island river ecosystems

While the spatiotemporal dynamics of phytoplankton community structures in river ecosystems have been extensively studied, their primary driving factors remain elusive, particularly at the watershed scale. This research examined the phytoplankton community structure across three watersheds of an island and concurrently analyzed its response to water level fluctuations (WLFs). The phytoplankton density was notably higher at elevated water levels, registering an increase of 1.29 times in Nandu River, 1.34 times in Changhua River, and 1.28 times in Wanquan River. Notably, the middle reaches of the Changhua River recorded the highest phytoplankton density (4.46 × 108 cells/L). Broadly speaking, Cyanophyta, Chlorophyta, and Bacillariophyta remained the predominant phytoplankton across varied water levels. Dominant phytoplankton species varied with water levels; however, the most prevalent species consistently belonged to the Cyanophyta group, primarily Microcystis or Merismopedia, with dominance ranging between 0.17 to 0.38 (low water level) and 0.18 to 0.32 (high water level). Enhanced phytoplankton diversity and richness were observed at higher water levels, correlating with increased concentrations of NH4+-N, NO3−-N, and PO43− in the river water. Consequently, nutrient fluctuations driven by hydrodynamics significantly influence the phytoplankton community structure in island river ecosystems.

Spatial and Temporal Variability in the Bottom Sediment Characteristics of a Shallow Lake under Backwater Separation and Application of Effective Microorganisms

Lake Konin is a small and shallow lake under the influence of highly eutrophic riverine waters. Feeding the lake as a backwater during high water level periods, the River Obra had exerted a decisive impact on lake water quality, and thus a new dike with a closing device was created. Protective measures were followed by the application of Effective Microorganisms (EM), aiming at a reduction in nutrient concentrations and CyanoHABs. Positive changes in the ecosystem were initiated (increased phytoplankton diversity), but cyanobacteria blooms were still present due to high nutrient content. Some changes were observed in the lake sediments (phosphorus (P) and its fractions, P in pore waters, organic matter and experimental assessment of internal P loading) studied before and during treatment. A slight increase in P content in sediments was noted, as a result of an increase in the Res-P fraction. Simultaneously, a decrease in the most mobile fractions was observed. Summer internal P load was reduced from 5.4 kgP d−1 before the treatment to less than 1 kgP d−1 in the first year, but increased again in the second year to 4.5 kgP d−1. Similarly to lake water quality, positive changes were induced in the lake sediments; nevertheless, they still acted as an important source of nutrients for primary producers. Additional restoration methods shall be considered, as combined treatments used simultaneously are reported to be the most effective for water quality improvement.

Dual-Column Stopped-Flow GC Method for Quantification of Permanent Gases, Water, and Organic Acids from a Single Injection.

Analysis of permanent gases and organic acids is typically performed with separate methods due to challenges in achieving sufficient resolution when using GC columns that are chemically compatible with acids. We developed a method to analyze samples containing high levels of water, organic acids, oxygenates, and permanent gases (CO, CO2, and C2H4) using a single injection. Resolution is achieved using two columns: (1) an HP-FFAP column resistant to water and acids, which separates compounds based on hydrogen-bonding affinity, and (2) a GS-CarbonPLOT column capable of separating permanent gases. We employed a column isolation methodology using rotary valves to allow a heart cut of permanent gases, which coelute off the HP-FFAP column, to be trapped on the CarbonPLOT column. After separation and analysis of water, organic acids, and oxygenates via the HP-FFAP column, flow is resumed on the CarbonPLOT column, and the permanent gases are separated independently. By utilizing the unique combination of columns and the stopped-flow sequence, we achieved separation and quantification of the wide array of compounds occurring during lactic acid dehydration to acrylic acid from a single injection without the need for a sophisticated flow modulator or multiple GCs or detector arrays. This GC apparatus serves as an economical in-line analysis method for our catalytic studies and is applicable to a wide array of samples relevant to biobased fuels and chemicals.

Study on flood level forecasting of tidal reach in Puyang River basin

Abstract The downstream section of the Puyang River is a tidal river reach subject to both upstream floods and downstream tides. This combined impact results in an unstable relationship between water level and discharge at the forecast station, making flood level forecasting challenging. This paper took the Linpu station on the Puyang River in Zhejiang Province as the research object. Based on the historical flood data, the cause of high water levels at Linpu station was analyzed. The flood levels at Linpu station were decomposed into flood increments and basic tidal levels. Using the multiple regression method, the prediction formula for upstream flood-induced water level increments was obtained. A flood level forecasting method based on the flood increment was developed. The result of the scheme accuracy evaluation indicates that this method has good forecasting performance. The flood level forecasting method for the tidal channel proposed in this paper has a simple structure and high accuracy, which provides a scientific basis for the prevention and control of flood and drought hazards and the decision-making of project scheduling in the tidal river.

Road and Bridge Blocking System in Flood Situation

Abstract: The system uses hydraulic or mechanical barriers that can be quickly opened in response to rising water levels, preventing access to barriers and bridges. Up to date data from weather forecasters and water gauges provide effective protection to ensure closure times before flooding reaches critical levels. In addition, the central control centre provides timely updates to the public via mobile and digital signage applications, encouraging collaboration with emergency services and local authorities. The purpose of this document is to provide guidance to highway authorities and other relevant organisations on road drainage. One problem that arises during floods is the closure of roads due to flooding, especially on roads located near rivers and canals. Most brides give the height above the highest water level, but the approach to the bridges often does not give the required height. As a result, the road was flooded while the bridge was standing

Genotoxicity in the goldfish of TiO2 nanoparticles combined with high CO2 levels

TiO2 nanoparticles are photocatalytic, generate reactive oxygen, and can be harmful to aquatic biota. We have studied the toxic effects of nTiO2 combined with high CO2 levels in water. We exposed goldfish to environmentally relevant concentrations of nTiO2 and CO2 levels. Comet assay results showed that DNA breaks increased at high CO2 concentration, but no effect of nTiO2 concentrations was seen. Micronucleus assays showed no significant micronucleus formation. Histopathological alterations were seen in the gills but not in the liver.

Using ARIMA and ETS models for forecasting water level changes for sustainable environmental management

It is vital to provide useful hydrological forecasts for urban and agricultural water management, hydropower generation, flood protection and management, drought mitigation and alleviation, and river basin planning and management, among other things. This paper introduces a simple and flexible hydrological time series forecasting framework. Predicting water levels is crucial, given the need for sustainable environmental management. The prognosis should be reasonable to persuade individuals to take proper precautions. While many methods have been developed to predict water levels, here the effectiveness of two approaches to predicting river water levels was assessed. For this purpose, nine years of data were used, which were divided into input data (2014–2021) and validation data (2022), on water levels in the Morava e Binçës river for the Vitia station, in the form of monthly time series records, to identify the best model among those used and to identify the information necessary for water resource management and hazard control. Models Autoregressive Integrated Moving Average(ARIMA) and Error Trend and Seasonality, or Exponential Smoothing (ETS), were examined using the R package to determine the most accurate. The results indicate the applicability of both models, as evidenced by the Root Mean Square Error (RMSE) and the Mean Absolute Error (MAE). The predictive analysis based on historical water levels allowed the identification of distinct periods characterized by high and low water levels between 2022 and 2024, which is important for the area in question due to the numerous flood events occurring here.