Water Level Changes Research Articles

Changing water levels and sandy barrier morphodynamics, eastern lake Ontario

Changing water levels and sandy barrier morphodynamics, eastern lake Ontario

Monitoring Lake Level Changes in Bosten Lake from 2003-2021 based on Multi-source Satellite Altimetry Data

The investigation of freshwater lake water resource changes in arid regions is crucial for understanding the evolution of regional lake dynamics under climate change, given their value and limited availability. This study aims to overcome the limitations of traditional water level monitoring methods and address the practical need for monitoring water level changes in Lake Bosten, located in the arid and semi-arid regions of China. To this end, we employed ICESat, ICESat-2, and CryoSat-2 altimetry data, as well as Landsat 8-OLI optical remote sensing data, to obtain the water level information for Bosten Lake from 2003 to 2022. We analyzed the temporal variation of the lake level and discussed the response of the lake level to climate and human activities in the context of temperature, precipitation data, and human water use. The water level of Lake Bosten exhibited a decreasing and then increasing trend, with three rising and three falling intervals, respectively. The intra-year variation of the lake water level exhibited bimodal characteristics, and the fluctuation range of water level during abundant water periods was greater than that during dry periods. Finally, we correlated the extracted lake water level with the measured water level at the hydrological station and found a significant positive linear correlation between the observed water level of Bosten Lake based on satellite altimetry and the measured water level at the hydrological station, with an overall correlation coefficient of 0.896 and 0.934 (P < 0.01), indicating high accuracy of the water level results obtained in this study. The dynamics of Lake Bosten are influenced by a combination of climate change, hydrological elements, and human activities, with a relatively weak relationship between climate change and lake volume and a strong influence of human activities. Multi-source altimetry satellites provide a powerful tool for monitoring lake water levels over a long time scale, which is critical for studying lake water level changes and their response to climate and the environment.

Synoptic results on the potential impacts of the Lake Maggiore water management strategy on freshwater littoral ecosystems and invertebrate biocoenosis (NW, Italy)

The first results of the application of the integrated multidisciplinary protocol to study the effects of water level management on the Lake Maggiore littoral habitats and biocoenosis are presented. The "Parchi Verbano Ticino" project (2019-2021, ID: 481668) was the driving force to fine-tune the monitoring and management system of multidisciplinary information (chemistry, hydro-morphology, macro- and meio-fauna monitoring). The study reveals that water level fluctuations in Lake Maggiore, sometimes characterized by measurable changes in water levels, have remarkable effects on littoral habitats and on the structure and function of macro- and meiofaunal assemblages living there. Overall, this study provides insights into the potential impacts of Lake Maggiore water management strategy on freshwater littoral ecosystems during late spring-early summer, and emphasizes the need for a comprehensive understanding of the lake ecosystem dynamics. Thanks to the results achieved, publicly endorsed water management rules will be stated, for the late spring-early summer period, considering frequency and amplitude of water level fluctuations as crucial factors in management plans to mitigate their impacts. The endorsed rules turn out to be a negotiated compromise between the maintenance of ecosystem services and the protection of littoral life below water.

Climate change variables modify microbial community structure and soil enzymes involved in nitrogen and phosphorus metabolism

Anthropogenic activities have threatened soil biodiversity which has a direct link with agricultural sustainability and ecosystem functionality. This study is aimed at investigating the changes in soil microbial biomass and enzyme activity in response to variations of primary climatic variables such as temperature and water regimes. Rhizosphere and non-rhizosphere soil samples were collected from an agricultural field of a rainfed area and transported to the laboratory for physicochemical analysis. These soil samples were preserved at 4 °C to be used for studying microbial biomass and enzymatic activities at varying soil temperatures (22, 33, and 44 °C) and water levels (30, 45, and 60% water holding capacity (WHC)). Urease and phosphatase activity showed a significant increase with increasing temperature. The urease and phosphatase values at a temperature of 44 °C after six weeks showed an increase of 19% and 67%, respectively, compared to the values before incubation. The microbial biomass carbon and the microbial biomass nitrogen decreased with increasing temperature and increasing time intervals. Under different temperatures, the diversity analyses of field samples showed maximum dominance of phylum proteobacteria with 70% relative abundance. With increasing water content, a relative decrease in the abundance of proteobacteria was observed. Water variability had non-significant effects on enzyme activity except at 30% WHC where a significant decrease (up to 14%) in urease activity was observed. The results showed a positive correlation between urease (r = 0.81) and phosphatase activity (r = 0.84) vs. an increase in temperature from 22 to 44 °C in soil. Based on these findings, it is concluded that changes in temperature and water levels modify microbial biomass, microbial community structure, and soil enzymatic activities involved in nitrogen and phosphorus metabolism.

Dam Surface Deformation Monitoring and Analysis Based on PS-InSAR Technology: A Case Study of Xiaolangdi Reservoir Dam in China

The Xiaolangdi Dam is a key project for the control and development of the Yellow River. It bears the functions of flood control, controlling water and sediment in the lower reaches, ice prevention, industrial and agricultural water supply, power generation, and so on. Its safety is related to people’s life and property safety and local economic and social development. It is of great significance to carry out comprehensive and regular deformation monitoring for dams since the deformation is an important evaluation index for dam safety. Interferometric Synthetic Aperture Radar (InSAR) technology has been a rapidly evolving technology in the field of space geodesy in recent years. It offers advantages such as high monitoring precision, extensive coverage, and high monitoring point density, making it a powerful tool for monitoring deformations in hydraulic engineering projects. Based on Sentinel-1 data covering the Xiaolangdi Dam from September 2020 to November 2022, the PS-InSAR technique was used to obtain the surface deformation of the Xiaolangdi Dam, and reservoir water level data on image acquisition dates were obtained for joint analysis. The results show that there is a large deformation in the center of the dam crest of the Xiaolangdi Dam, while both sides of the slope and downstream dam foot are relatively stable. The time series deformation of the dam body is closely related to the reservoir water level change. When the water level increases, the dam body tends to deform downstream; when the water level decreases, the dam body tends to deform upstream. The deformation and water level of the Xiaolangdi Dam exhibit a clear negative correlation. There is no significant cumulative deformation on the dam slopes or at the base of the dam. However, cumulative deformation occurs over time in the central area of the dam’s crest. The deformation process at the central area of the dam’s crest follows a continuous and non-disruptive pattern, which is consistent with the typical deformation behavior of the Xiaolangdi earth–rock dam structure. Therefore, it is judged that the current deformation of the Xiaolangdi Dam does not impact the safe operation of the dam. InSAR technology enables the rapid acquisition of high-precision, high-density deformation information on the surfaces of reservoir dams. With an increasing number of radar satellites in various frequency bands, such as Sentinel-1 and TerraSAR-X, there is now an ample supply of available data sources for InSAR applications. Consequently, InSAR technology can be extended to routine monitoring applications for reservoir dam deformations, especially for small and medium-sized reservoirs that may not be equipped with ground measurement tools like GNSS. This holds significant importance and potential for enhancing the safety monitoring of such reservoirs.

Inversion analysis of rock mass permeability coefficient of dam engineering based on particle swarm optimization and support vector machine: A case study

In order to efficiently and reasonably determine the permeability coefficient of engineering rock mass, the two key problems of complex seepage field simulation and objective function solution in permeability coefficient inversion are studied and improved. Firstly, a 3D refined seepage numerical model is established considering the main fault fracture zones and dam seepage control system. Secondly, combined with the support vector machine (SVM) algorithm, the complex mapping relationship between permeability coefficient of each rock layer and impervious structure and piezometer head is constructed. Finally, the particle swarm optimization (PSO) algorithm is introduced, and then the efficient optimization of permeability coefficient inversion of engineering rock mass and impervious structure is realized based on PSO-SVM. The case study of LJH arch dam shows that the inversion calculation framework based on PSO-SVM not only completes the rapid proxy calculation of the numerical model of complex seepage field, but also realizes the accurate optimization of the inversion objective function. The simulation results under the final inversion parameters reproduce the variation characteristics of the piezometric tube water level of each typical measuring point under the change of reservoir water level. In addition, with the correlation analysis between the permeability coefficient and the measured value of the corresponding piezometer, the parameter inversion method is endowed with new application value. This study is of great significance for clarifying the seepage characteristics of complex rock mass and improving the inversion efficiency of dam seepage monitoring data.

Factors affecting changes in water level and quality in a rural farmstead well

Factors affecting changes in water level and quality in a rural farmstead well

Relationship between pollination syndromes, pollen morphology and plant ecology in Quaternary deposits of the Cerrado

This study presents morphological descriptions and ecological information for 58 terrestrial pollen taxa and seven water-related pollen taxa from the Brazilian Cerrado, obtained from two sediment cores, Lake Feia (LFB1) and Getulio Swamp (VGE-17), encompassing the last 5000 and 15,000 cal yr BP, respectively. The relationships between the ecological and morphological traits (pollination syndrome, vegetation stratum and grain size) within each of the two depositional environments were investigated. In the LFB1 core, the pollen assemblages were dominated by arboreal pollen from closed physiognomies and lower storey trees (<10 m in height), while a combination of closed and open physiognomies was observed in the pollen assemblages from the VGE-17 core. The vast majority of the pollen taxa exhibited the entomophilous pollination syndrome, and a higher influx of entomophilous pollen was observed in both cores. Anemophilous and anemophilous/entomophilous syndromes were less well represented. Small and medium pollen grain classes were the most abundant, while the large pollen grain class was rare. The influx of small pollen grains was slightly more abundant in the lake record, while in the swamp record medium pollen grains were more abundant. Our results show that swamps and lakes differ in their representation of local versus regional pollen and in their sensitivity and responses to water-level changes. Landscape physiognomy also influences pollen dispersion: a closed physiognomy increases the local pollen signal, while a more open physiognomy results in better representation of local and regional signals.

Deformation warning index for reinforced concrete dam based on structural health monitoring data and numerical simulation

The material mechanical parameters of the dam body and foundation will change when a dam is reinforced during the aging process. This causes significant changes in the structural state of the project and makes it difficult to ensure its structural safety. In this study, a new deformation warning index for reinforced concrete dams was developed according to the prototype monitoring data, statistical models, three-dimensional finite element model (FEM) numerical simulation, and the critical conditions of the dam structure. A statistical model was established to separate the water pressure component. Then, a three-dimensional FEM of the reinforced concrete dam was constructed to simulate the water pressure component. Furthermore, the deformation components that affected the mechanical parameters of the dam under the same amount of reservoir water level change were separated and quantified accurately. In addition, the method for inversion of comprehensive mechanical parameters after dam reinforcement was used. The influence mechanisms of the deformation behavior of concrete dams under the reservoir water level and temperature changes were investigated. A new deformation warning index was developed by combining the forward-simulated critical water pressure component and temperature component in the period of extreme temperature decrease with the aging component separated by the statistical model. The new deformation warning index considers the structural state of the dam before and after reinforcement and links the structural strength criterion and the deformation evolution mechanisms. It provides a theoretical foundation and decision support for long-term service and operation management of reinforced dams.

The Interaction between Storm Surge and Concomitant Waves in Shandong Peninsula

Storm surge and concomitant waves induced by extreme weather systems can significantly modulate the marine dynamic environment. In this study, we used the Advanced Circulation-Simulating Waves Nearshore (ADCIRC-SWAN) coupled model to analyze spatiotemporal variation in dynamic processes during two types of weather systems, i.e., typhoons and extratropical storms, in the sea area near the Shandong Peninsula. The effects of waves on water level, water level change on wave height, and currents on wave height were investigated and quantified separately by performing sensitivity experiments. Our results showed that the interaction between water level change and waves occurred mainly in the nearshore zone. The wave-induced surge accounted for about 10–15% of the total storm surge. The water level change-induced significant wave height reached up to 0.9–1.3 m. Wave–current interaction occurred mainly in the offshore zone and was related to the relative angle between wave and current directions. The modulations of water level and wave height were strongly dependent on not only storm track and intensity but also topography and coastline shapes.

Combined Physical Process and Deep Learning for Daily Water Level Simulations across Multiple Sites in the Three Gorges Reservoir, China

Water level prediction in large dammed rivers is an important task for flood control, hydropower generation, and ecological protection. The variations of water levels in large rivers are traditionally simulated based on hydrological models. Recently, most studies have begun applying deep learning (DL) models as an alternative method for forecasting the dynamics of water levels. However, it is still challenging to directly apply DL to the simultaneous prediction of water levels across multiple sites. This study attempts to develop a hybrid framework by combining the Physical-based Hydrological model (PHM) and Long Short-Term Memory (LSTM). This study hypothesizes that our hybrid model can enhance the predictive accuracy of water levels in large rivers, because it considers the temporal-spatial information of mainstream-tributaries relationships. The effectiveness of the proposed model (PHM-BP-LSTM) is evaluated using the daily water levels from 2012 to 2018 in the Three Gorges Reservoir (TGR), China. Firstly, we use a hydrological model to produce a large amount of water level data to solve the limited training data set. Then, we use the Back Propagation (BP) neural network to capture the mainstream-tributaries relationship. The future changes in water levels in the different mainstream stations are simultaneously predicted by the LSTM model. We reveal that our hybrid model yields satisfactory accuracy for daily water level simulations at fourteen mainstream stations of the TGR. We further demonstrate the proposed model outperforms the traditional machine learning methods in different prediction scenarios (one-day-ahead, three-day-ahead, seven-day-ahead), with RMSE values ranging from 0.793 m to 1.918 m, MAE values ranging from 0.489 m to 1.321 m, and the average relative errors at each mainstream station are controlled below 4%. Overall, our PHM-BP-LSTM, combining physical process and deep learning, can be viewed as a potentially useful approach for water level prediction in the TGR, and possibly for the rapid forecast of changes in water levels in other large rivers.

Exploring the Effect of Meteorological Factors on Predicting Hourly Water Levels Based on CEEMDAN and LSTM

The magnitude of tidal energy depends on changes in ocean water levels, and by accurately predicting water level changes, tidal power plants can be effectively helped to plan and optimize the timing of power generation to maximize energy harvesting efficiency. The time-dependent nature of water level changes results in water level data being of the time-series type and is essential for both short- and long-term forecasting. Real-time water level information is essential for studying tidal power, and the National Oceanic and Atmospheric Administration (NOAA) has real-time water level information, making the NOAA data useful for such studies. In this paper, long short-term memory (LSTM) and its variants, stack long short-term memory (StackLSTM) and bi-directional long short-term memory (BiLSTM), are used to predict water levels at three sites and compared with classical machine learning algorithms, e.g., support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost), and light gradient boosting machine (LightGBM). This study aims to investigate the effects of wind speed (WS), wind direction (WD), gusts (WG), air temperature (AT), and atmospheric pressure (Baro) on predicting hourly water levels (WL). The results show that the highest coefficient of determination (R2) was obtained at all meteorological factors when used as inputs, except at the La Jolla site. (Burlington station (R2) = 0.721, Kahului station (R2) = 0.852). In the final part of this article, the complete ensemble empirical mode decomposition adaptive noise (CEEMDAN) algorithm was introduced into various models, and the results showed a significant improvement in predicting water levels at each site. Among them, the CEEMDAN-BiLSTM algorithm performed the best, with an average RMSE of 0.0759 mh−1 for the prediction of three sites. This indicates that applying the CEEMDAN algorithm to deep learning has a more stable predictive performance for water level forecasting in different regions.

Astronomical forcing in the coal-bearing Middle Jurassic Dameigou Formation, Qaidam Basin, northwestern China

Coal seams, as a terrestrial carbon sink, are not only important sedimentary and energy mineral resources but also excellent recorders of paleoclimate change. The study of coal-bearing strata is particularly significant in exploring the relationship between geological records and orbital forcing. However, the understanding of the relationship between coal seams of different sources of organic matter and astronomical cycles is incomplete. This study focuses on the Dameigou Formation, a typical Jurassic coal seam in the Qaidam Basin, Northwestern China. Organic petrology analysis, biomarker analysis, and whole-rock mineral analysis were combined to reconstruct the vegetation types and paleolake water level changes during coal seam deposition. In addition, using a time-series analysis method and high-precision gamma-scanning data from Well D1, we established a floating astronomical timescale and a time-depth model for cyclostratigraphical analysis. The results show that the Dameigou Formation, as coal-bearing strata, preserves well-developed Milankovitch cycles, and the climatic conditions and vegetation types during coal formation vary among different coal seams. Different patterns of variation in eccentricity, obliquity, and procession determine the thickness of the coal seam. This study is of great significance for understanding the astronomical factors that influenced climate evolution and coal deposition during the Middle Jurassic.

Typization of Lakes of the East Antarctica Oases

The urgency of creating a new complex typization of lakes of the East Antarctica oases is dictated not only by the desire to summarize accumulated Antarctic lakes’ data but also by the need to obtain the most informative characteristics of lake hydrological regime in the region for solving a wide applied problems’ range. Features of lake water level changes were used as a criterion in developing the complex typization of lakes of the East Antarctica oases for the first time, in contrast to existing classifications. The study was based on the analysis of literary and archive materials (the Larsemann Hills, the Schirmacher oasis, the Banger Hills, the Molodezhnyi oasis, the Vestfold Hills, and the McMurdo Dry Valleys), as well as our own expeditionary data (field seasons of 2017–2022, the Larsemann Hills). A group of indirect criteria (presence and type of natural dam, position in the cascade, flowage type, etc.) is proposed in addition to a group of direct criteria (duration of the lake filling phase, water level rise, etc. requiring organization of field observations) to obtain a holistic view of the water level regime of lakes. It is important that characteristics of the most indirect criteria can be obtained by visual reconnaissance surveys or by maps and remote sensing data. The identified 4 types (outbursting, tendentious, transit, and tidal) and 8 subtypes of lakes were illustrated by generalized graphs of water level changes, which objectively characterize the features of the lake hydrological regime. The openness of the typization suggests the opportunities for actualization with the accumulation of new scientific knowledge and data.

Beach rebuilding period buffers Indiana beach erosion in Lake Michigan

Recent high-water levels in the Laurentian Great Lakes caused widespread shoreline damage to beaches, homes, and coastal infrastructure. To quantify these shoreline changes and place them in historical context, shoreline imagery was analyzed to determine the magnitude, rates, and spatial variability of shoreline changes along the Indiana shoreline of Lake Michigan. The analysis shows that over the recent period of water level increase from 2013 to 2020, during which the water level rose nearly 2 m, the median shoreline recession along the Indiana coastline was 58 m and the median recession slope was 35:1 (shoreline recession : water level change). This magnitude of shoreline change is comparable to that experienced in other water level increase periods, 1965–1973 and 1990–1998. This recent shoreline recession was highly variable spatially, but not strongly correlated with shoreline type or position relative to littoral barriers. In spite of the widespread recent shoreline changes, the 2020 shoreline was generally more lakeward than previous high-water shorelines examined, with the exception of historical erosion zones downdrift of littoral barriers. Analysis of water level records and available wave hindcasts for the coastline suggest that while large, the erosion associated with the recent water level increase was tempered by a prolonged beach rebuilding period of low water levels and waves that resulted in an accreted shoreline that largely buffered the erosion associated with the water level increase. These results suggest that recent Indiana erosion could have been substantially worse had it not been preceded by the beach rebuilding period.

NON-STATIONARY PROBABILISTIC TSUNAMI HAZARD ASSESSMENTS INCORPORATING TIDES AND SEA LEVEL RISE

Tides and climate driven sea level rise (SLR) contribute significantly to water level changes in the short and long term, respectively. In terms of magnitude, they could be comparable to tsunamis of interest at certain coasts. New non-stationary probabilistic tsunami hazard assessment (nPTHA) methods that were developed to include the mean sea level changes due to a warming climate are now extended to incorporate the uncertainty of the tidal phase at the moment of tsunami occurrence. Here, a collocation-based model is used in the nPTHA method to render the calculation feasible and efficient.

CONTRIBUTION OF INFRAGRAVITY WAVES TO STORM WATER LEVEL ALONG A LARGE INLET: IMPLICATIONS FOR FLOODING AND OVERTOPPING HAZARDS

Tidal inlets are transitional area between the ocean and an estuary or a lagoon. They are characterised by very complex hydro-morphodynamics processes, resulting from the interaction between tidal currents and waves with large and rapid water level changes. The coastline around the inner part of the inlet and more generally the entire lagoon often host important economic and touristic activities. In these environments, the studies of hazards associated with energetic events are mainly based on modelling approaches. However, the phase-averaged numerical models typically used for large-scale coastal applications exclude infragravity waves (long waves ranging from several tens of seconds to several minutes, noted hereinafter IG) and phase-resolving model are too computationally expensive for such large domains. Therefore, the propagation of waves from the open sea to the lagoon and in particular the characterisation of IG waves are still poorly understood (Bertin et al., 2018). To study the amplitude and spatial variability of IG waves in the Arcachon lagoon during storms, the Xbeach model (Roelvink et al., 2009) was implemented in surfbeat mode (SB mode).

Decoding the hundred-year water level changes of the largest Saline Lake in China: A joint lake-basin modeling study based on a revised SWAT+

Study regionQinghai Lake Basin (QLB), the largest saline lake in China and its collecting basin Study focusClimate change has caused clear shrinkage or dramatic water level fluctuation of lakes in arid and semi-arid regions, while the underlain mechanisms remain unclear. The joint lake-basin investigations (spatial) and long-term studies (temporal) are urgently needed. This study developed SWAT+ to jointly simulate the water cycle of QLB and investigated how the hydrological regime of QLB changed at the hundred-year scale. New hydrological insights for the regionThe modeling framework consisted of the revised SWAT+ , reanalysis data, and reconstructed water level based on lake gravity core performed quite well (NSE > 0.9 for lake water level) in simulating the hydrological processes of QLB at the hundred-year scale (1910 – 2018). Temporally, decadal variations of hydrological components in QLB decreased in sequence of precipitation (46.33 mm), lateral flow (26.85 mm), evapotranspiration (16.03 mm), snowmelt (10.44 mm), groundwater flow (5.66 mm), and overland flow (1.18 mm). Spatially, precipitation, water yield, lateral flow, and groundwater flow in upstream regions of QLB, where the precipitation amount was small, were most sensitive to climate change. The long-term water level decrease of Qinghai Lake during 1928 – 2003 was mainly driven by variations of river runoff and lake surface evaporation; the clear water level increase since 2004 was dominated by river runoff changes.

Wind-modulated groundwater discharge along a microtidal Arctic coastline

Groundwater discharge transports dissolved constituents to the ocean, affecting coastal carbon budgets and water quality. However, the magnitude and mechanisms of groundwater exchange along rapidly transitioning Arctic coastlines are largely unknown due to limited observations. Here, using first-of-its-kind coastal Arctic groundwater timeseries data, we evaluate the magnitude and drivers of groundwater discharge to Alaska’s Beaufort Sea coast. Darcy flux calculations reveal temporally variable groundwater fluxes, ranging from −6.5 cm d−1 (recharge) to 14.1 cm d−1 (discharge), with fluctuations in groundwater discharge or aquifer recharge over diurnal and multiday timescales during the open-water season. The average flux during the monitoring period of 4.9 cm d−1 is in line with previous estimates, but the maximum discharge exceeds previous estimates by over an order-of-magnitude. While the diurnal fluctuations are small due to the microtidal conditions, multiday variability is large and drives sustained periods of aquifer recharge and groundwater discharge. Results show that wind-driven lagoon water level changes are the dominant mechanism of fluctuations in land–sea hydraulic head gradients and, in turn, groundwater discharge. Given the microtidal conditions, low topographic relief, and limited rainfall along the Beaufort Sea coast, we identify wind as an important forcing mechanism of coastal groundwater discharge and aquifer recharge with implications for nearshore biogeochemistry. This study provides insights into groundwater flux dynamics along this coastline over time and highlights an oft overlooked discharge and circulation mechanism with implications towards refining solute export estimates to coastal Arctic waters.

How should storm surge barrier maintenance strategies be changed in light of sea-level rise? A case study

Sea-level rise and changes in storminess, together with population growth and coastward migration, are increasing the risks of coastal flooding. The impacts are amplified in coastal cities due to the high concentration of inhabitants, infrastructure and services in low lying areas. Many coastal cities are located in estuaries, and storm surge barriers are often constructed to provide flood protection in these areas with long exposed coastlines. For these complex and unique structures, maintenance is vital to ensure they remain reliable and comply with legal protection standards. To ensure safe conditions for workers, storm surge barriers typically define water level thresholds, at which maintenance work must stop when these water levels are reached or exceeded. This paper evaluates the changes in past and future water levels exceeding the maintenance threshold to inform management, maintenance and operation strategies, and design, of storm surge barriers. The Maeslant barrier in Rotterdam, Netherlands is used as a case study to test this analysis. Water levels from measurements taken at the Hoek van Holland tide gauge are compared to the maintenance threshold level. The number of past threshold exceedances is determined and the sensitivity of exceedances to threshold level are assessed. Results show that the maintenance threshold has been exceeded 991 times of which 13% occurred during the maintenance season. Conversely, there were periods in the storm season when water levels were below the maintenance threshold and work could have been carried out safely. The effect of sea-level rise and natural inter-annual tidal cycles on future threshold exceedances is also assessed. Findings reveal that the maintenance window will shift earlier in the year and narrow until exceedances of the maintenance threshold occur regularly all year around. With 1 m sea-level rise maintenance threshold exceedances are likely to occur regularly all year around by 2048. This analysis highlights that maintenance strategies at the Maeslant barrier will need to be adapted for the barrier to remain operational until its design life of 2 100. This is due to the increase in maintenance threshold exceedances resulting from natural interannual tidal cycles combined with sea-level rise. This analysis framework is applicable to existing barriers worldwide to assess future intervention points and for barriers in the design phase to verify the implications of design decisions on planned maintenance.