Maximum Water Level Research Articles

The hydraulic investigation of harmonic plan weirs

Existing dams and reservoirs need to be revised to meet safety standards. For the existing reservoirs where flood control is important and the maximum water level is limited, the best method to increase reservoir capacity is to build a labyrinth weir on the dam. In labyrinth weirs, the collision of two nappe flows produces nappe interference, and this reduces the weir performance. In this study, the semi-circle weirs are placed in an open channel harmonically to increase the efficiency of the labyrinth weirs to make the areas more efficient and increase the flow capacity because of the nappe interference and to ensure the flow moving perpendicular to the weir as possible. In the experimental study of the asymmetrically placed circular weirs, 3 different weir heights (P = 20 cm, 30 cm and 40 cm) and 3 different labyrinth cycle numbers (N = 2, N = 3 and N = 4) were used. As a result of the experiments, although there was a 13 % decrease in the discharge coefficients (Cd) compared to the linear weirs, it provided a 57 % increase in the net crest length (Lnet). Discharge coefficient (Cd) is decreased 3.4 %, as the number of cycles (N) increases. As the weir height (P) decreases, Cd increases 7.5 % due to the vacuum effect.

UAV AERIAL SURVEY IN MONITORING OF COASTAL GEOSYSTEMS IN THE SOUTHERN IRKUTSK AMPHITHEATRE

Estimating the dynamics of exogenous geological processes and understanding their controlling factors is an urgent task faced by many regions of the world. One of the methods of its solution is monitoring. The paper presents the UAV monitoring results for short-term dynamics of complex exogenous processes at five key sites in the coastal zone south of the Bratsk reservoir. The study area is a part of the platform structure in the south of the Irkutsk amphitheater, which is considered to be relatively stable in terms of geodynamics. There has been developed a methodical scheme for obtaining data series on the dynamics of complex exogenous geological processes in the coastal geosystem. A flight altitude of 50–60 m is optimal to obtain orthophotos with a resolution of 1.1–2.2 cm/px, sufficient to estimate the areal dynamics of the processes, and a DEM with a resolution of 2.6–5.4 cm/px to estimate the volumetric dynamics.The eroded coastal area at the Rassvet site was measured to be 6900 m2, which corresponds to an average erosion width of 3.45 m per linear meter of coastal length with maximum values of up to 6.51 m. A high rate of coastal erosion in the period 2021–2022 is related to the maximum water level in the Bratsk reservoir, close to the normal headwater level. The assessment of the volumetric dynamics of the coastal gullies yielded negative values, as most of the gully mouths were eroded. The secondary valley-bottom gullies (Mamontov and Barany sites) and coastal gullies (Khadakhan site) are characterized by positive dynamics both in area and volume growth (12–20 m2 and 1.3–35.0 m3, respectively). At the Khadakhan site, the volumetric growth of new and previously observed suffusion sinkholes was 0.45 m3.The obtained areal and volumetric rates of the exogenous processes can serve as a basis for their modern assessment and prediction of their development in order to prevent and reduce socio-economic risks.

Assessment of the impact of the rise in Lake Victoria water levels on urban flooding using a GIS-based spatial flood modelling approach

ABSTRACT During the period 2018–2021, Lake Victoria experienced a rapid rise in water levels that caused significant urban flooding consequences. However, there are no studies that have extensively investigated the effect of the rising lake water levels on urban flooding. This research responds to this by developing and applying a GIS-based spatial flood modelling approach to simulate the resulting flooding impacts in Entebbe City, Uganda, corresponding to the May 2021 observed maximum lake water level of 13.49 m. Using the validated GIS-based flood model, the simulated flooded area and average flood depth were determined as 9.1 km2 and 1.52 m, respectively. Furthermore, through application of GIS overlay analysis, the total number of affected buildings and length of urban roads were quantified. The proposed methodology provides a robust and computationally efficient approach for identification of at-risk buildings along the lake shoreline and for testing the effectiveness of potential adaptation strategies.

Uncertainties and discrepancies in the representation of recent storm surges in a non-tidal semi-enclosed basin: a hindcast ensemble for the Baltic Sea

Abstract. Extreme sea level events, such as storm surges, pose a threat to coastlines around the globe. Many tide gauges have been measuring the sea level and recording these extreme events for decades, some for over a century. The data from these gauges often serve as the basis for evaluating the extreme sea level statistics, which are used to extrapolate sea levels that serve as design values for coastal protection. Hydrodynamic models often have difficulty in correctly reproducing extreme sea levels and, consequently, extreme sea level statistics and trends. In this study, we generate a 13-member hindcast ensemble for the non-tidal Baltic Sea from 1979 to 2018 using the coastal ocean model GETM (General Estuarine Transport Model). In order to cope with mean biases in maximum water levels in the simulations, we include both simulations with and those without wind-speed adjustments in the ensemble. We evaluate the uncertainties in the extreme value statistics and recent trends of annual maximum sea levels. Although the ensemble mean shows good agreement with observations regarding return levels and trends, we still find large variability and uncertainty within the ensemble (95 % confidence levels up to 60 cm for the 30-year return level). We argue that biases and uncertainties in the atmospheric reanalyses, e.g. variability in the representation of storms, translate directly into uncertainty within the ensemble. The translation of the variability of the 99th percentile wind speeds into the sea level elevation is in the order of the variability of the ensemble spread of the modelled maximum sea levels. Our results emphasise that 13 members are insufficient and that regionally large ensembles should be created to minimise uncertainties. This should improve the ability of the models to correctly reproduce the underlying extreme value statistics and thus provide robust estimates of climate change-induced changes in the future.

Chronic flooding events due to sea-level rise in French Guiana

As sea levels are rising, the number of chronic flooding events at high tide is increasing across the world coastlines. Yet, many events reported so far either lack observational evidence of flooding, or relate to coastal areas where ground subsidence or oceanic processes often enhance climate change-induced sea-level rise (SLR). Here we present observational and modelling evidence of high-tide flooding events that are unlikely to occur without SLR in French Guiana, where sea-level rise rates are close to the global average and where there is no significant ground subsidence. In particular, on 16 October 2020, a well-documented flooding event happened in Cayenne under calm weather conditions. Our probabilistic assessment of daily maximum water levels superimposed on SLR shows that this event can be modelled and is a consequence of SLR. As sea levels will continue to rise, we show that the number, severity and extent of such high-tide flooding events will increase across several urban areas of French Guiana, with an evolution depending on the topography. As concerns are growing regarding the economic impacts and adaptation challenges of high-tide chronic events across the world, our study provides new evidence that this early impact of SLR is emerging now.

Model of Storm Surge Maximum Water Level Increase in a Coastal Area Using Ensemble Machine Learning and Explicable Algorithm

AbstractThis study proposes a novel, new ensemble model (NEM) designed to simulate the maximum water level increases caused by storm surges in a frequently cyclone‐affected coastal water of Hong Kong, China. The model relies on storm and water level data spanning 1978–2022. The NEM amalgamates three machine learning algorithms: Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and XGBoost (XGB), employing a stacking technique for integration. Six parameters, determined using the Random Forest and Recursive Feature Elimination algorithms (RF‐RFE), are used as input features for the NEM. These parameters are the nearest wind speed, gale distance, nearest air pressure, minimum distance, maximum pressure drop within 24 hr, and large wind radius. Model assessment results suggest that the NEM exhibits superior performance over RF, GBDT, and XGB, delivering high stability and precision. It reaches a coefficient of determination (R2) up to 0.95 and a mean absolute error (MAE) that fluctuates between 0.08 and 0.20 m for the test data set. An interpretability analysis conducted using the SHapley Additive exPlanations (SHAP) method shows that gale distance and nearest wind speed are the most significant features for predicting peak water level increases during storm surges. The results of this study could provide practical implications for predictive models concerning storm surges. These findings present essential tools for the mitigation of coastal disasters and the improvement of marine disaster warning systems.

Effect of Daily Regulation on Navigation Conditions in Deep Reservoirs

The daily regulation and anti-regulation of upstream and downstream power stations, respectively, frequently alter the river flow regime, velocity, and surface gradient, thus resulting in unsteady flow characteristics of the river and hindering shipping, waterway maintenance, and wharf operations. This study investigated the influence of daily regulation on the navigation conditions in the deep reservoir by taking the rivers between the Three Gorges Dam and the Gezhouba Dam as the research object. Prototype observations and a depth-averaged 2-D model were used to determine the main factors affecting the propagation law of unsteady flow. The propagation pattern of unsteady flow and channel navigational conditions and measures of the power station were analyzed systematically. The results showed that the water level amplitude was affected primarily by the peak amplitude and duration of the peak shaving. Additionally, the base flow significantly influenced time spatial distributions of the water level amplitude. Impacted by the reservoir storage capacity, a threshold for the duration of peak shaving was noted; this may result in maximum water level variation. As the peak shaving duration increased, the amplitude of the water level decreased. The research results can provide theoretical support for the optimization of hub shipping.

Seepage Model of Heterogeneous Municipal Solid Waste Landfill and Application under Process of Waste Accumulation

The distribution of leachate directly impacts the safety and stability of the landfill, so it is important to research the distribution of seepage characteristics and migration patterns of leachate. The study aims to investigate the impact of heterogeneous permeability distribution and clogging of the drainage layer on leachate transportation in landfills. To achieve this, a heterogeneous transient seepage model was developed. Results showed that when considering the heterogeneous permeability of the waste in the buried depth direction, the maximum perched water level was higher, which is not conducive to the safety and stability of the landfill. Taking Xi’an Jiangcungou Landfill as a research object, the maximum perched water level of each waste layer was higher compared to the homogeneous condition when considering the landfill process and heterogeneous permeability. The differential value ranged from 0.08 m to 1.88 m. Furthermore, the calculation results obtained from the heterogeneous seepage model were found to be in good agreement with both actual field data and referenced survey data, thus confirming the reliability of the model. These research findings not only offer technical support but also provide a solid theoretical foundation for leachate level control and safety and stability assessments.

Estimation of the Water Level in the Ili River from Sentinel-2 Optical Data Using Ensemble Machine Learning

Monitoring of the water level and river discharge is an important task, necessary both for assessment of water supply in the current season and for forecasting water consumption and possible prevention of catastrophic events. A network of ground hydrometric stations is used to measure the water level and consumption in rivers. Rivers located in sparsely populated areas in developing countries of Central Asia have a very limited hydrometric network. In addition to the sparse network of stations, in some cases remote probing data (virtual hydrometric stations) are used, which can improve the reliability of water level and discharge estimates, especially for large mountain rivers with large volumes of suspended sediment load and significant channel instability. The aim of this study is to develop a machine learning model for remote monitoring of water levels in the large transboundary (Kazakhstan-People’s Republic of China) Ili River. The optical data from the Sentinel-2 satellite are used as input data. The in situ (ground-based) data collected at the Ili-Dobyn gauging station are used as target values. Application of feature engineering and ensemble machine learning techniques has achieved good accuracy of water level estimation (Nash–Sutcliffe model efficiency coefficient (NSE) >0.8). The coefficient of determination of the model results obtained using cross-validation of random permutations is NSE = 0.89. The method demonstrates good stability under different variations of input data and ranges of water levels (NSE > 0.8). The average absolute error of the method ranges from 0.12 to 0.18 meters against the background of the maximum river water level spread of more than 4 meters. The obtained result is the best current result of water level prediction in the Ili River using the remote probing data and can be recommended for practical use for increasing the reliability of water level estimation and reverse engineering of data in the process of river discharge monitoring.

Predicting the Overflowing of Urban Personholes Based on Machine Learning Techniques

Urban stormwater drainage systems, which include many personholes to collect and discharge precipitation within a city, are extensively constructed to prevent streets and buildings from flooding. This research intends to build a machine learning model to predict whether a personhole will overflow soon, which is crucial to alleviate the damage caused by floods. To address the challenges posed by many diverse personholes, we proposed segmenting the personholes into several groups and have designed two methods employing different personhole features. The first, the geography-based method, uses the geographical locations of the personholes for the grouping. The second, the hydrology-based method, uses the characteristics that are directly related to the overflowing situation, such as the depth of the personhole, and the average and the maximum water level of the personholes. We also investigated several machine learning techniques, such as the multilayer perceptron (MLP) model and a fine-tuning architecture. The study area was located in the new Taipei city and the experimental results have shown the impressive predictive ability of the proposed approaches. Particularly, by applying the hydrology-based grouping method, and using a hybrid model combining the machine learning model prediction results with heuristic rules, we can obtain the best prediction result, and the accuracy is over 99%. We have also noticed the influence of the activation function used in the neural network and the number of frozen layers in the fine-tuning architecture. Particularly, using the tanh function with one frozen layer is good in some cases. However, since it is not general enough, we suggest the readers perform empirical studies before choosing the best setting in their own environment.

Statistical and hydrodynamic numerical modeling to quantify storm surge hazard: Comparison of approaches applied to U.S. North Atlantic coast

Estimating the storm surge magnitude and annual exceedance probability is a key element in the siting and design of coastal nuclear power plants in both the U.S. and France. However, differences in storm climatology, specifically the relative importance of tropical cyclones (TCs) versus extratropical storms (XTCs), have driven differences in estimation method development. This work compares purely statistical modeling with combined statistical and numerical simulation modeling approaches for extreme storm surge applied to the U.S. North Atlantic coast which is subject to both tropical and extratropical storms. Two frequency analysis methods are applied to observed water levels and compared to a copula-based joint probability analysis of TCs and automated frequency analysis of XTCs that is enriched with numerically simulated storms. One frequency analysis method is applied using (1) hourly at-site data and (2) hourly at-site data enriched with additional data from a homogeneous region. The other frequency analysis method is applied using (1) hourly at-site data and (2) hourly at-site data enriched with monthly water level maxima. Variables of interest used in the comparison are skew storm surge, maximum instantaneous storm surge, non-tidal residual and maximum seal level. The performance of the methods (mean surge and water level estimates and confidence intervals) depend on the variable of interest and, to some extent, on return period. Inclusion of additional information (e.g., regional water levels, and monthly maxima) in the frequency analysis methods does not have a large impact on estimated mean surge and water levels, but significantly reduces resulting confidence intervals (over 40% reduction in some cases). However, the confidence intervals still grow with increasing return period. Inclusion of simulated storms in the joint probability analysis results in significantly different mean surge and water level estimates (up to 25% higher than the frequency analysis in some cases). The joint probability analysis confidence intervals are wider than those for the frequency analysis methods lower return periods (e.g., 60%–80% wider at 100 years), but they grow much more slowly and are significantly narrower for higher return periods (e.g., 40%–60% narrower at 1 000 years). Although there are appreciable differences between the results documented in this paper, these are reasonable due to differences in the data and methods used in this comparison.

How Sea Level Rise May Hit You Through the Backdoor: Changing Extreme Water Levels in Shallow Coastal Lagoons

AbstractDue to their choked geometry, coastal lagoons can attenuate extreme water levels compared to the open sea. However, this protective property is expected to decrease due to sea‐level rise. By studying idealized lagoons in a non‐dimensional parameter space, this study describes non‐linear interactions between tides, storm surges, freshwater fluxes into the lagoon, and sea‐level rise. The non‐dimensional numbers include lagoon geometry and forcing scales. The main objective is to provide an overview of potentially affected lagoons and to highlight the importance of attenuation changes due to sea‐level rise. Tidal and storm surge induced maximum water levels inside lagoons rise faster than sea‐level rise for most of the parameter space. Maximum water levels due to freshwater fluxes rise slower than sea‐level rise for strongly choked lagoons. For compound events, the response between rising faster or slower than sea‐level rise depends strongly on the lagoon geometry.

Assessment of groundwater reservoir and the influence of its characteristics on water dynamic control.

Groundwater reservoirs play an important role in regional water volume balance. In order to ensure the efficiency of a groundwater reservoir and obtain its maximum value, it is necessary to figure out its characteristics, such as minimum water level, normal water level, and maximum water level. The characteristics not only determined the storage capacity but also influenced the water allocation and utilization. Therefore, this paper took a groundwater reservoir built in an alluvial fan as an example to assess its storage capacity and the influence on water dynamic control. The alluvial fan was located in the front of Lao River, where there were an alluvial-diluvial fan, groundwater storage space, and natural impervious boundary. Therefore, it was an ideal place for constructing a groundwater reservoir. Through theoretical analysis and numerical simulation, the storage capacity was determined, and the influence of groundwater reservoir characteristics on water dynamic control was analyzed. On this basis, the water-supply method in the research area was confirmed. This paper will present a new method for repairing the groundwater system and protecting the ecological environment.

Influence of maximum water level and coastal inundation on the east coast of India based on future tropical cyclones

Influence of maximum water level and coastal inundation on the east coast of India based on future tropical cyclones

AUTOMATIC FISHPOND IRRIGATION DOOR CONTROL SYSTEM BASED ON ATMEGA16 MICROCONTROLLER AND SMS GATEWAY

The process of controlling irrigation doors in fishponds is still mostly done manually, this results in the performance of farmers being less effective and efficient. Current technological developments, especially in the field of IoT, can be used to design a simulation that is able to control irrigation gates automatically. Based on the results of the tests that have been carried out, it can be concluded that the ATmega16-based automatic irrigation gate simulation tool can work well according to the designed working principle. If the condition of fishpond water is less than the ideal height of the fishpond and the condition of river water is more than the height of the fishpond, the motor will move to "open" the irrigation door to fill fishpond water. If the fishpond water condition is more than the ideal height and the river water condition is less than the fishpond height, the motor will move to "open" the irrigation door to discharge fishpond water and if the river water condition is the same as the fishpond water condition, the motor will move "close” the irrigation door so that the ideal height of the fishpond can be achieved. There are certain conditions to control the door manually using the SMS Gateway. Information about the maximum or minimum fishpond water level will be displayed on the LCD to determine the maximum or minimum fishpond height using Keypad.

Изменчивость сроков прохождения максимальных уровней воды на реках Северного Кавказа

The intra-annual distribution of the timing of maximum water levels in the rivers of the North Caucasus has been studied. Observation data from 54 hydrological gauges for the period from 1961 to 2017 were used. The intra-annual distribution of these dates was typified, according to which for each season of the year their frequency may exceed 80%, be in the range from 50 to 80% or not exceed 50%. On this basis, the zoning of river sections in the North Caucasus is proposed according to the type of variability in the timing of maximum water levels. The geographical validity of the proposed zoning is confirmed by its good enough correspondence to the existing ideas about the peculiarities of flow formation and water regime of the studied rivers. The obtained results can be used to estimate the probability of dangerous floods in the rivers of the North Caucasus in different seasons of the year. Keywords: the rivers of the North Caucasus, maximum water levels, timing of water level peaks, types of seasonal distribution, zoning

Estimation of Equivalent Rainfall for Ungauged Reservoir Using Satellite-Based High-Resolution Terrain Data

Equivalent rainfall refers to the amount of precipitation required to reach a specific water level from the current water level in a reservoir. It serves as a flood forecasting and warning system that allows for the rapid assessment of the reservoir’s maximum water level at the moment of rainfall forecast. In reservoirs where terrain and survey data can be obtained, deriving equivalent rainfall is not difficult. However, without terrain data, satellite imagery and global topographic data are the only available options. In this study, high-resolution topographic data based on satellites were utilized to estimate the equivalent rainfall in the ungauged reservoir, Hwanggang Dam, located in the upper stream of the Imjin River in North Korea. To calculate the inflow into the reservoir, the Natural Resources Conservation Service-Curve Number method was used to determine the effective rainfall, taking into account the antecedent conditions, as the inflow into the reservoir can be changed for the same amount of rainfall depending on the soil moisture content of the watershed.

Investigating the reduction of rainfall intensity beneath an urban deciduous tree canopy

Trees have an indispensable role to play in the hydrological cycle. The process of interception by tree canopies alters the magnitude, pathway, and intensity of rainfall reaching the ground. This study investigates the rainfall intensity-attenuating effects of canopy interception by open-grown birch trees (Betula pendula Roth.) in an urban environment and the influence of atmospheric variables. Rainfall partitioning was measured in a research plot in the city of Ljubljana, Slovenia, from August 2021 to August 2022. Simultaneously, optical disdrometers above and below the birch tree canopy measured microstructures of rainfall and throughfall, from which the intensities were calculated. During the measurement period, the birch tree intercepted on average 25.6 % of gross rainfall, with the interception being twice as high during the leafed season than in the leafless season. Consequently, the total number and volume of drops under the canopy were reduced on average by 16.4 % and 48.7 %, respectively, indicating the interception and fragmentation of raindrops by the canopy. Owing to these processes, the leafed and leafless states of the birch tree canopy attenuate the average intensities of rainfall by 50.2 % and 41.6 %, respectively. Canopy interception also moderates the maximum 10-minute rainfall intensities by 11.6–83.8 % and 13.1–74.2 % during the leafed and leafless periods, respectively. This percentage of reduction in the rainfall intensities below the canopy decreases with rainfall amount and in the absence of foliage. Aside from phenoseasons, we also found that vapor pressure deficit and air temperature were among the atmospheric variables that exert the highest influence on the intensities of throughfall. Furthermore, the regression analysis between the maximum throughfall intensity and peak water level for each rainfall event indicates that the reduction of rainfall intensity by the canopy has a significant effect on runoff peak water level (R2 = 0.76, p < 0.001).

Declines in the Mekong’s Megadiverse Larval Fish Assemblages: Implications for Sustainable Development

Migratory fishes of the Mekong Basin are facing challenges from human-induced stressors. Quantifying the patterns of fish’s early life stages provides important information on spawning seasons, spawning and nursery habitats, reproductive strategies, migration and dispersal patterns, and stock status. However, the ecology of the Mekong larval fishes, including patterns and drivers of larval fish dispersal, is not well understood. Here, we investigate the temporal variability of drifting larval and juvenile fish assemblages in the Cambodian Mekong River and identify their environmental drivers using long-term (10 year) daily fish larval/juvenile data collections. We found that, in the Mekong main channel, the larval and juvenile assemblages were dominated by longitudinal migrants from the families Cyprinidae and Pangasiidae. Peak abundance and richness were found to occur in July and August, respectively. We detected a significant decline in larval and juvenile abundance and richness over the study period. Cross-wavelet analysis revealed that water levels always lead larval abundance, but lag richness. In addition, cross-correlation analysis observed that peak abundance and richness occurred eight weeks and one week, respectively, before the peak water level. We also discovered that species abundance and richness had a strongly positive relationship with maximum water levels. Variation in fish larval and juvenile abundance and richness was also related to total phosphorus, nitrate, alkalinity, and conductivity. Maximum water levels and the key water quality parameters (e.g., phosphorus, nitrate, alkalinity, and conductivity) significantly influence larval and juvenile fish abundance and richness patterns. Therefore, safeguarding natural seasonal flows, especially maximum flows associated with the peak flood pulse, as well as maintaining good water quality, are key to the reproductive success of many migratory fishes and effective dispersal of offspring to the lower floodplain for nursing, rearing, and growth. Clean and unregulated rivers support productive and diverse fisheries.

Emergency intervention modes for ice jam events in large-scale water diversion projects

Abstract The formation of ice jams is sudden, and they will cause abnormal water level fluctuations in water diversion projects, affecting the water supply and even causing severe flood disasters. Based on the characteristics of the Middle Route of the South-to-North Water Diversion Project, this paper uses the numerical simulation method to establish an emergency intervention effect simulation model for ice jam events. The hydraulic response characteristics of the project under gate group scheduling and taking different emergency measures are analyzed with the water level deviation and stabilization time consumption of the pool as indicators. Moreover, this paper proposes an emergency intervention mode for ice jam events. The results show that using the gate group scheduling after ice jam events will cause a sharp rise in the upstream water level of the pool where the ice jams are located. Also, compared with other emergency measures, the electric heating ice melting measure has less influence on water level, and the de-icing effect is better. Finally, the emergency intervention mode can significantly reduce the maximum water level deviation and shorten the time required to stabilize the water level.