Water Level Changes Research Articles

Characterizing the impact of reservoir storage and discharge on nitrogen dynamics in an upstream wetland using a δ15N and δ18O dual-isotope approach

The identification of nitrate sources in reservoir water is important for watershed-scale surface pollution management. Significant fluctuations in river water levels arising from reservoir storage and discharge influence nitrate sources and transport processes. The Sanmenxia Reservoir, in the middle reaches of the Yellow River in China, undergoes significant water level changes (290–316 m), altering the composition of the nitrogen sources. This study employed a δ15N and δ18O dual-isotope method and MixSIAR modeling to quantify the contributions of nitrate sources. This reveals the impact of reservoir water impoundment and discharge on nitrogen dynamics in the upstream region of the wetland and the model sensitivity for each nitrate source. The results showed that the average concentrations of nitrate‑nitrogen (NO- 3-N) were elevated during the impoundment period compared to the discharge period. Nitrogen sources exhibited varying proportions in surface water, groundwater, and soil water during both the impoundment and discharge periods. The predominant sources include manure and sewage (MS), with a maximum proportion of 57.4 % in surface water. Soil nitrogen (SN) accounted for 25.8 % of groundwater nitrogen and 32.1 % of soil water nitrogen during the impoundment period, whereas, during the discharge period, soil nitrogen made up 41.4 % of surface water nitrogen, manure and sewage contributed 44.8 % of groundwater nitrogen, and manure and sewage dominated with 56.7 % of soil water nitrogen. Sensitivity analysis of the MixSIAR model revealed that the isotopic composition of the manure and sewage primary source most significantly influenced the apportionment results of the riverine nitrate source. Reservoir discharge facilitates the dissimilatory nitrate reduction to ammonium (DNRA). The migration of NO- 3 from surface water to soil water and groundwater occurred from the impoundment period to the discharge period.

A study on the division and determination of characteristic indexes of underground reservoirs under inclined bottom plates

ABSTRACT In recent years, the slope of the bottom plate of the underground reservoir in the loose porous medium constructed in the middle and upper reaches of the river is relatively large, which makes the underground water surface incline to a certain slope as a whole, near-horizontal section will appear in front of the underground dam during continuous recharge. Given this situation, the definition and calculation of the characteristic index of the underground reservoir in line with the actual changes are carried out. The characteristic water level of the underground reservoir is defined based on the groundwater surface with a certain slope at the inclined level in the case of the lower dam (single dam) impoundment. The characteristic capacity is calculated through the water level at the typical section defined by the inclined surface. A new set of definition and calculation method based on the characteristic index of the underground reservoir with a dam on the inclined bottom plates is proposed and applied to the Rushan River underground reservoir, which more accurately reflects the water level change and the corresponding actual reservoir capacity during the operation of the underground reservoir.

Monitoring the Landscape Pattern Dynamics and Driving Forces in Dongting Lake Wetland in China Based on Landsat Images

Dongting Lake wetland is a typical lake wetland in the Middle and Lower Yangtze River Plain in China. Due to the influence of natural and human activities, the landscape pattern has changed significantly. This study used 12 Landsat images from 1991 to 2022 and applied three common classification methods (support vector machine, maximum likelihood, and CART decision tree) to extract and classify the landscape information, with the latter having a superior annual accuracy of over 90%. Based on the CART decision tree classification results, the dynamic characteristics of wetland spatial patterns were analyzed through the landscape pattern index, dynamic degree model, and transition matrix model. Redundancy and grey correlation analysis were employed to investigate the driving factors. The results showed increased landscape fragmentation, reduced heterogeneity, and increased complexity from 1991 to 2022. The water and mudflat areas exhibited three distinct stages: gradual decline until 2001 (−3.06 km2/a); sharp decrease until 2014 (−19.44 km2/a); and steady increase (22.93 km2/a). Vegetation conversion, particularly between sedge and reed, dominated the change in landscape pattern. Reed area initially increased (18.88 km2/a), then decreased (−35.89 km2/a), while sedge showed the opposite trend. Woodland area fluctuated, peaking in 2016 and declined by 2022. The construction of the Three Gorges Dam significantly altered landscape dynamics through water level changes, reflected by a 4.03% comprehensive dynamic degree during 2001–2004. Potential evaporation also emerged as a significant natural factor, exhibiting a negative correlation with the landscape index. During 1991–2001 and 2004–2022, the comprehensive explanatory rates of temperature, precipitation, potential evaporation, and water level on landscape pattern dynamics were 88.56% and 52.44%, respectively. Other factors like policies and socio-economic factors played a crucial role in wetland change. These findings offer valuable insights into the dynamic evolution and driving mechanisms of Dongting Lake wetland.

The role of phenotypic plasticity and corticosterone in coping with pond drying conditions in yellow-bellied toad (Bombina variegata, Linnaeus 1758) tadpoles.

Amphibian larvae inhabiting temporary ponds often exhibit the capacity to accelerate development and undergo metamorphosis in challenging conditions like desiccation. However, not all species exhibit this ability, the yellow-bellied toad (Bombina variegata) is one such example. The underlying mechanisms behind the inability to accelerate development under desiccation remain largely unexplored. The hypothalamic-pituitary-interrenal (HPI) axis and corticosterone (CORT), which act synergistically with thyroid hormone, are thought to facilitate metamorphosis in response to desiccation stress. In this study, we aimed to investigate whether modification in the HPI axis, particularly CORT levels, contributes to the absence of adaptive plasticity in B. variegata under desiccation stress. The study design included four treatments: high water level, high water level with exogenous CORT, low water level, and low water level with metyrapone (a CORT synthesis inhibitor). The main objective was to evaluate the effects of these treatments on whole-body corticosterone levels, life history, morphological traits, and oxidative stress parameters during the prometamorphic and metamorphic climax developmental stages. While low water level had no effect on total corticosterone levels, larval period, body condition index, and metamorphic body shape, it negatively affected metamorph size, mass, and growth rate. Our findings suggest that constant exposure to desiccation stress over generations may have led to modifications in the HPI axis activity in B. variegata, resulting in adaptation to changes in water level, evident through the absence of stress response. Consequently, CORT may not be a relevant stress indicator in desiccation conditions for this species.

Pemodelan 2D Daerah Rawan Banjir Sungai Lepo – Lepo Kota Kendari

Research was carried out to see the potential for flooding through Computational Fluid Dynamic simulations, namely a set of methodologies that allow computers to provide numerical simulations of fluid flow. The entire system is transformed into virtual form, and can be visualized via computer. Components in fluid dynamic computing include selection of mathematical models, discretization, numerical analysis schemes, numerical solutions and representation of processes numerically and graphically. Flood mapping can provide information about which areas need special attention so that it can be used as a reference in making policies related to flood management and can be used to increase wider public awareness regarding floods. The HEC-RAS permanent flow module is able to take into account the influence of various flow obstacles, such as bridges, culverts, bends, or obstacles on riverbanks. The permanent flow module is designed for use in riverbank management environments and the determination of flood risk insurance regarding the determination of riverbanks and floodplains. The permanent flow module can also be used to estimate changes in water level due to channel improvements or embankment construction. HEC-RAS permanent flow special module features include double plan analysis, double profile calculation, double culvert or gate analysis, flow optimization, and stable channel design and analysis. From the simulation results and depth classification, information on the area of inundation and areas prone to flood inundation on the Lepo-Lepo River is 29.34 Ha.

Hydrogeochemical changes with emphasis on trace elements in an artesian well before and after the September 8, 2018 Ms 5.9 Mojiang Earthquake in Yunnan, southwest China

Most groundwater geochemical studies associated with earthquakes have focused on changes in major ions and radon concentration. However, trace elements have also shown a dramatic response to earthquakes and attracted increasing attention. In this study, hydrochemical and water level changes were detected by an artesian well (DZ well) in Yunnan, China, during the 2018 Ms 5.9 Mojiang earthquake. The results show that the major and trace element concentrations changed considerably before and after the earthquake, which were attributed to the mixing of water from different aquifers due to the earthquake-induced alteration of permeability through wavelet analysis of continuous monitoring data and coseismic static strain. In addition, Self-Organizing Map (SOM) and K-means clustering algorithms were used to classify all water samples with 10 trace elements as variables, and the results showed that samples collected in pre- and post-earthquake can be categorized as two groups, showing a significant difference. We argue that the response of trace elements remains unaffected by their initial concentration levels. Notably, both high- and low-concentration trace elements (e.g., Cs, Rb, V, etc.) exhibit discernible changes in response to the Ms 5.9 Mojiang earthquake. These observations corroborate the efficacy of clustering methodologies in delineating seismic-induced concentration shifts and furnish fresh insights into the anomalous behavior of trace elements during the earthquake.

Leveraging Bayesian network to reveal the importance of water level in a shallow lake ecosystem: A study based on Paleo-diatom and fish community

Lake ecological processes and nutrient patterns are increasingly affected by water level variation around the world. Still, the long-term effects of water level change on lake ecosystems and their implications for suitable lake level management have rarely been studied. Here, we studied the ecosystem dynamics of a mesotrophic lake located in the cold and arid region of northern China based on long-term paleo-diatom and fishery records. Utilizing a novel Copula-Bayesian Network model, possible hydrological-driven ecosystem evolution was discussed. Results show that increased nutrient concentration caused by the first water level drop in the early 1980s incurred a transition of sedimental diatoms towards pollution-resistant species, and the following water level rise in the mid-1980s brought about considerable external loading, which attributed to eutrophication and caused the miniaturization of fishery structure. In the 21st century, a continuous water level plummet further reduced the sediment diatom biomass and the fish biomass by altering nutrient concentration. However, with the implementation of the water diversion project in 2011, oligotrophic species increased, and the ecosystem developed for the better. From the perspective of water quality protection requirements and the ecological well-being of Lake Hulun, the appropriate water level should be around 542.42–544.15 m. In summary, our study highlights the coupling effect of water level and water quality on Lake Hulun ecosystem and gives shed to lake water level operation and management under future climate change and human activities.

Responses of vegetation cover to hydro-climatic variations in Bosten Lake Watershed, NW China.

Amidst the backdrop of global climate change, it is imperative to comprehend the intricate connections among surface water, vegetation, and climatic shifts within watersheds, especially in fragile, arid ecosystems. However, these relationships across various timescales remain unclear. We employed the Ensemble Empirical Mode Decomposition (EEMD) method to analyze the multifaceted dynamics of surface water and vegetation in the Bosten Lake Watershed across multiple temporal scales. This analysis has shed light on how these elements interact with climate change, revealing significant insights. From March to October, approximately 14.9-16.8% of the areas with permanent water were susceptible to receding and drying up. Both the annual and monthly values of Bosten Lake's level and area exhibited a trend of initial decline followed by an increase, reaching their lowest point in 2013 (1,045.0 m and 906.6 km2, respectively). Approximately 7.7% of vegetated areas showed a significant increase in the Normalized Difference Vegetation Index (NDVI). NDVI volatility was observed in 23.4% of vegetated areas, primarily concentrated in the southern part of the study area and near Lake Bosten. Regarding the annual components (6 < T < 24 months), temperature, 3-month cumulative NDVI, and 3-month-leading precipitation exhibited the strongest correlation with changes in water level and surface area. For the interannual components (T≥ 24 months), NDVI, 3-month cumulative precipitation, and 3-month-leading temperature displayed the most robust correlation with alterations in water level and surface area. In both components, NDVI had a negative impact on Bosten Lake's water level and surface area, while temperature and precipitation exerted positive effects. Through comparative analysis, this study reveals the importance of temporal periodicity in developing adaptive strategies for achieving Sustainable Development Goals in dryland watersheds. This study introduces a robust methodology for dissecting trends within scale components of lake level and surface area and links these trends to climate variations and NDVI changes across different temporal scales. The inherent correlations uncovered in this research can serve as valuable guidance for future investigations into surface water dynamics in arid regions.

Comparative study on volume conservation among various SPH models for flows of different levels of violence

The weakly-compressible smoothed particle hydrodynamics (WCSPH) models offer distinct advantages in simulating free-surface flow. Within the rapidly evolving WCSPH field, Classical WCSPH model, based on the artificial viscous term, and its derived models, which additionally introduce numerical diffusive terms into the continuity equations - including the δ-SPH, δ-SPHC, δ-SPHC+, δ-LES-SPH, and δ-SPHF models have gained prominence recently. The numerical diffusive term is found to alter the particle distributions in the free-surface region, leading to a change in the mean water level that reflects the volume conservation, which might result in inaccuracies in some simulations. This study evaluates the volume conservations of the aforementioned WCSPH models for flows at quasi-hydrostatic states evolved from varying levels of flow violence under prolonged simulations, through a series of numerical tests involving hydrostatic, standing-wave, and dam-break cases. For the hydrostatic and standing-wave cases, the performance of different types of WCSPH models remains consistent overall. The Classical WCSPH and δ-LES-SPH models exhibit minimal changes in volume, with almost no decrease in the mean water level occurring. The δ-SPH, δ-SPHC, δ-SPHC + models demonstrate decreases in the mean water level converging to around 0.2 times the SPH particle diameter (Δx), indicating favorable volume conservation. Conversely, the δ-SPHF model consistently exhibits a decrease in the mean water level exceeding 1 Δx at t = 2000s in a linear fashion, resulting in a noticeable reduction in volume. Under the dam-break case, most of the mean water levels simulated by different models experience a small increase, which is close to the decrease observed under the hydrostatic and standing-wave cases with corresponding models. Only the δ-SPHF model continues to show a continuous decreasing tendency. In summary, considering volume conservation, the δ-LES-SPH model demonstrates the best performance (excluding the Classical WCSPH model as it cannot simulate violent flow), followed by the δ-SPHC, δ-SPHC+, δ-SPH and δ-SPHF models.

Demonstrating the Potential of Low-Cost GNSS Receiver for tidal monitoring, storms, and flood detecting: example of 2022 Noru Storm in Thua Thien Hue province, Vietnam

Extreme hydrological events such as tsunamis, high tides, or storm surges seriously threaten coastal communities. These events result in flooding, property damage, loss of life, and long-term economic and social impacts. Therefore, monitoring and detecting extreme hydrological events significantly affect coastal areas in disaster response efforts. However, the cost of installing and maintaining these stations can be a significant challenge for developing countries. The objective of this study is to use a low-cost GNSS receiver to monitor tides and detect extreme coastal hydrological phenomena by analyzing changes in water level, using analysis of the signal-to-noise ratio (SNR) data. Data used in this study were collected from a GNSS station located in the Tam Giang Lagoon area, Thua Thien Hue, Vietnam, from September to October 2022. The water level based on GNSS-R is compared with the sensor's measured water level, with the Pearson correlation coefficient reaching 0.96 and RMSE of 0.08m. Continuous Wavelet Transform analysis demonstrated the relationship between water levels and extreme hydrological events. The results show that distinct signatures in the data correspond to the Noru typhoon from September 27-29, 2022, and the inundation from October 14-19, 2022, in Thua Thien Hue. This information is the basis for forecasting and early warning of extreme events and informing disaster response and management efforts.

Regime shift in microalgal dynamics: Impact of water level changes on planktonic and benthic algal biomass

Whole-lake microalgal biomass surveys were carried out in Lake Balaton to investigate the seasonal, spatial, and temporal changes of benthic algae, as well as to identify the drivers of the phytobenthos. Phytobenthos was controlled mainly by light: the highest benthic algal biomass was in the shallow littoral region characterized by large grain size (sand) with good light availability but lower nutrient content in the sediment. During the investigated period, phytoplankton biomass showed a significant decrease in almost the entire lake. At the same time, the biomass of benthic algae increased significantly in the eastern areas, increasing the contribution of total lake microalgae biomass (from 20 % to 27 %). Benthic algal biomass increase can be explained by the better light supply, owing to the artificially maintained high water level which greatly mitigates water mixing. The decrease in planktonic algal biomass could be attributed to increased zooplankton grazing, which is otherwise negatively affected by mixing. As a result of the high water level, the trophic structure of the lake has been rearranged in recent decades with a shift from the planktonic life form to the benthic one while the nutrient supply has largely remained unchanged.

Effects of constant high water levels in winter on waterbird diversity in Caizi Lakes: A functional perspective

The middle and lower Yangtze River floodplain lakes are important stopover and wintering sites for migratory birds on the East Asian–Australasian Flyway. The periodic water level fluctuation of the lakes plays a critical role in the aggregation of waterbirds. However, the construction of a series of gates and dams has impeded the hydrological connectivity between rivers and lakes and disrupted the natural water level fluctuation patterns of lakes. The water level status of lakes influences habitat utilization by waterbirds. In recent years, Caizi Lakes, the gate-controlled lakes connected to the Yangtze River due to the need for water level regulation requirements, has experienced sustained high water levels in winter, which can reduce habitat quality and in turn influence waterbirds activity. In the present study, wintering waterbirds in Caizi Lakes were surveyed during the 2021–2022 (W1) and 2022–2023 (W2) wintering periods. Moreover, we explored the effects of constant high water levels in winter on waterbird assemblages by comparing species richness, abundance, and functional alpha and beta diversity. Correlation analyses were then performed to elucidate the relationship between habitat factors and water level changes during the wintering period of migratory waterbirds and between changes in various habitat factors and wintering waterbird assemblages under different hydrological conditions. The results showed that functional beta diversity was more sensitive to changes in waterbird assemblages in Caizi Lakes than functional alpha diversity. Moreover, constant high water levels in the mid-wintering period decreased suitable habitats for wintering waterbirds, increased functional turnover among waterbird assemblages, increased total dissimilarity among assemblages significantly, and decreased the level of functional nestedness significantly. Additionally, the areas of the three wetland habitats in Caizi Lakes were significantly correlated with water level changes during W1 and relatively less affected by water level changes under constant high water level conditions during W2. The changes in habitat area were influenced primarily by anthropogenic activities, with an increase in meadow area favorable for species richness and abundance, as well as functionally nested components. Water level regulation should take into consideration the natural hydrological rhythms of the declining water level to ensure that adequate and suitable habitats are provided for wintering waterbirds.

Development Characteristics and Reactivation Mechanism of a Large-Scale Ancient Landslide in Reservoir Area

The intricate geological conditions of reservoir banks render them highly susceptible to destabilization and damage from fluctuations in water levels. The study area, the Cheyipin section of the Huangdeng Hydroelectric Station, is characterized by numerous ancient landslides of varying scales and ages. In June 2019, during the reservoir filling process of the Huangdeng Hydroelectric Station, a large-scale reactivation of ancient landslides occurred in this area, posing severe threats to riverside infrastructure and human safety, including ground cracking, house cracking, foundation settlement, and road collapse. The reactivation mechanism of ancient landslides at reservoir banks is highly complex due to fluid dynamics. This study conducted field investigations in the Cheyipin landslide area, monitored surface and subsurface deformations using GNSS and inclinometers, and analyzed the distribution characteristics, destruction features, and reactivation mechanisms of the landslides through correlation analysis and numerical calculations. The results indicate that the instability pattern of the slopes manifests as traction-type sliding failure. The slopes do not slide along the ancient sliding surface but along a newly formed arcuate sliding surface, with the direct impact area mainly concentrated near the waterline. The stability of the slopes in this project is closely related to the reservoir water level. It can be assumed that the lowering of the reservoir water level triggered the reactivation of the ancient landslides in the Cheyipin section, while the influence of rainfall can be ignored. To prevent the reactivation of ancient landslides, attention should be focused on the changes in reservoir water level, avoiding rapid adjustments in water level during the initial lowering and final raising of the water level.

Analysis of the population genetics of the Yangtze finless porpoise population in the Poyang Lake Basin: Insight of conservation recommendations

Abstract The genomes of 32 Yangtze finless porpoises (YFPs) in the Poyang Lake Basin were sequenced, and the data were used for population genetic analysis. The population genetic structure of YFP in the Poyang Lake Basin is relatively simple, with a linkage disequilibrium decay distance of 705 bp. The correlation between genetic distance and geographic distance for YFP populations from different regions showed that the populations had a fixed range. Although Poyang Lake is connected during the rainy season, changes in water levels and human activities have hindered the exchange and migration of YFP populations between different areas. In particular, these changes may lead to differences in physiological metabolism and reproduction between populations in the main lake area and those in the sand pits, which are connected to the main lake area during the dry season. This study highlights the need for measures such as artificial translocation, dredging and habitat restoration to improve the exchange of YFP populations between different areas. We also suggest that the sand pits should be designated as protected areas, as their environment is conducive to the survival of the population.

Surface Water (SW) and Shallow Groundwater (SGW) Nutrient Concentrations in Riparian Wetlands of a Mixed Land-Use Catchment

Precipitation patterns, water flow direction, and local land-use practices affect surface water (SW) and shallow groundwater (SGW) nutrient concentrations in riparian wetlands. Given physical process complexities, spatiotemporal quantification of nutrients and physical factors influencing nutrient concentrations are needed to advance wetland water resource management. To address these needs, a study was conducted in riparian wetlands of a mixed land-use catchment in West Virginia (WV), USA. Observed data included SW–SGW levels and nutrient concentrations, including nitrate (NO3-N), nitrite (NO2-N), ammonium (NH4-N), orthophosphate (PO43-P), total nitrogen (total_N), and total phosphorus (total_P) from January 2020 to December 2021. Water samples were collected monthly from stream gauge sites (n = 4) and co-located piezometers (n = 13). Results showed that, on average, gaining stream conditions were observed in upstream sites, and losing stream conditions were observed in downstream sites. Observed nutrient profiles between SW and SGW included SW exhibiting a higher average NO3-N concentration (0.42 mg/L), while SGW displayed an elevated NH4-N concentration (1.55 mg/L) relative to other nitrogen species. Significantly high (p &lt; 0.05) SW NO3- concentrations in summer and fall were attributed to increased precipitation and corresponding water level and, therefore, pressure head and transport fluctuations. Principal Component Analysis (PCA) showed differences in nutrient concentrations based on the water source type and catchment land use, explaining 65% of data variability. Spearman correlation analysis illustrated the correlation among nutrient concentrations, land use, and water level changes in SW and SGW environments. This study provides needed baseline data on nutrient dynamics for a riparian wetland in a mixed land-use catchment, supplying science-based information to advance land and water management practices in the study watershed and similar physiographic watersheds globally.

Photogrammetric Investigation of Storm-Induced Erosion Process on Sandy Beach Profile in Medium-Scale Flume

In this study, laboratory experiments were conducted to investigate the influence of changes in storm wave height and water level on beach response in a medium-scale wave flume. A schematic storm was simulated (rising, apex, and waning phases). A non-intrusive photogrammetric method was used to collect high-resolution and synchronous data regarding the free surface water elevation and bed level, from which shoreline location, sandbar position, cross-shore sediment transport rates, and nonlinear wave parameters were derived. The cross-shore sediment transport was in agreement with previous laboratory measurements, including the monotonous exchange from foreshore erosion to shoaling zone accretion in most stages of the storm simulation. The surf zone was the main region supplying sediment for beach morphology modification and sandbar generation. The degree of storm erosion was not completely determined by the largest wave height and water level or the cumulative wave power of the apex phase. The largest gradients of the wave parameter sequence change occurred in the rising phase, and this was the main factor generating efficient beachface erosion. It induced an increase in sandbar size, accompanied by the cross-shore motion of maximum velocity amplitude, more violent disturbances of wave nonlinearity, and increased surf zone erosion, with these factors increasing beach instability and leading to more severe storm erosion. The large wave height and water level resulted in shoreline retreat, with a more significant swash zone erosion under a higher runup. The offshore sediment transport turned toward the onshore direction as the original large sandbar deteriorated under the decreasing wave parameter sequence in the waning phase.

Application of deep learning in predicting suspended sediment concentration: A case study in Jiaozhou Bay, China

Previous research methodologies for quantifying Suspended Sediment Concentration (SSC) have encompassed in-situ observations, numerical simulations, and analyses of remote sensing datasets, each with inherent constraints. In this study, we have harnessed Convolutional Neural Networks (CNNs) to create a deep learning model, which has been applied to the remote sensing data procured from the Geostationary Ocean Color Imager (GOCI) spanning April 2011 to March 2021. Our research indicates that on a small time scale, wind and hydrodynamic forces both have a significant impact on the prediction results of CNNs model. Considering both wind and hydrodynamic forces can effectively improve the model's prediction efficiency for SSC. Moreover, we have employed CNNs to interpolate absent values within the remote sensing datasets, yielding enhancements superior to those attained via linear or multivariate regression techniques. Finally, the correlation coefficient between CNN-derived SSC estimates for Jiaozhou Bay (JZB) and its corresponding remote sensing data is 0.72. Correlation coefficient and root mean square error differ in different regions. In the shallow water of JZB, due to water level changes, there is limited data, and the correlation coefficient in this area is about 0.5–0.6. In the central region of JZB with sufficient data, the correlation coefficient is generally higher than 0.75. Therefore, we believe that this CNNs model can be used to predict the hourly variation of SSC. When juxtaposed with alternative methodologies, the CNN approach is found to economize computational resources and enhance processing efficiency.

Comparison of water levels of the Angrapa river in the middle of the 20th and early 21st century

The results of a comparative analysis of the characteristic water levels in the Angrapa River (Berestovo gauging station, Kaliningrad region) in the middle of the 20th and at the beginning of the 21st century are presented. A number of average annual discharges of the Angrapa river (Berestovo gauging station) have been restored for analogue rivers. It has been established that the average long-term levels of the Angrapa river have decreased over the period under review. At the beginning of the 20th century, intra-annual changes in water levels with a spring flood peak, summer-autumn low water and rises during rain floods on the Angrape River were noted in less than half of the cases. In the 21st century, such a change occurs only in some years, in other years there are several rises in the water level, from December to March-April. The highest level in the Angrapa river (Berestovo gauging station) was recorded during a rain flood. The hydrological regime of a water body has a significant impact on the conditions for the existence of ecosystems, the level regime of a river significantly affects the floodplain ecosystem. The data obtained can be used in the development of environmental measures.

Early Flood Monitoring System Through AI, IOT and Thing Speak Cloud

One kind of natural disaster that can cause significant property damage and even fatalities is flooding. It's critical to diagnose floods early to reduce their effects. In this study, we describe a novel early flood detection technique utilizing the Thingspeak cloud platform, Artificial Intelligence (AI), and Internet Of Things (IOT) technologies. The system consists of a network of Internet Of Things (IOT) sensors positioned in flood-prone areas to detect water levels in real time. These sensors collect and transmit water level data to the Thingspeak cloud platform. The AI algorithms running on the cloud platform examine the data to look for changes in water levels that could indicate an impending flood. Keywords: Artificial Intelligence, Internet of Things, Thingspeak, esp32 microcontroller, water level sensor, Flood, Detection, alert.

Variable Natural Frequency Damper for Minimizing Response of Offshore Wind Turbine: Effect on Dynamic Response According to Inner Water Level

Offshore wind turbines (OWTs) are exposed to cyclic loads resulting from wind, waves, and rotor rotation. These loads can induce resonance, thereby significantly increasing the amplitude of the structure and accelerating the accumulation of fatigue damage. Particularly, wave loads can induce the first mode of large turbines. While many studies have been conducted to suppress OWT vibrations due to external loads, research on variable natural frequency damper (VNFD), which control vibrations through changes in the natural frequency by adjusting the inner water level of the structure, is still in its infancy. Herein, the performance of a VNFD in controlling the vibration of monopile-type OWTs is analyzed by focusing on cyclic environmental loads. To analyze the amplitude minimization achieved using a VNFD, wave loads with the same period as that of the structure’s natural frequency were generated, and the structural response resulting from changes in the inner water level were analyzed. As a result, the peak displacement at the top of the tower decreased by 5.8% and 34% at the water depths of 20 m and 50 m, respectively. In terms of the peak intensity determined through Fast Fourier Transform of the displacement response, reductions of 33% and 65% were confirmed at the depths of 20 m and 50 m, respectively.