scholarly journals How historical information can improve estimation and prediction of extreme coastal water levels: application to the Xynthia event at La Rochelle (France)

2015 ◽  
Vol 15 (6) ◽  
pp. 1135-1147 ◽  
Author(s):  
T. Bulteau ◽  
D. Idier ◽  
J. Lambert ◽  
M. Garcin
Keyword(s):  
Water Level ◽  
Coastal Water ◽  
Extreme Values ◽  
Tide Gauge ◽  
Heterogeneous Data ◽  
Water Levels ◽  
Exceedance Probability ◽  
Historical Information ◽  
Order Of Magnitude ◽  
Tide Gauge Measurements

Abstract. The knowledge of extreme coastal water levels is useful for coastal flooding studies or the design of coastal defences. While deriving such extremes with standard analyses using tide-gauge measurements, one often needs to deal with limited effective duration of observation which can result in large statistical uncertainties. This is even truer when one faces the issue of outliers, those particularly extreme values distant from the others which increase the uncertainty on the results. In this study, we investigate how historical information, even partial, of past events reported in archives can reduce statistical uncertainties and relativise such outlying observations. A Bayesian Markov chain Monte Carlo method is developed to tackle this issue. We apply this method to the site of La Rochelle (France), where the storm Xynthia in 2010 generated a water level considered so far as an outlier. Based on 30 years of tide-gauge measurements and 8 historical events, the analysis shows that (1) integrating historical information in the analysis greatly reduces statistical uncertainties on return levels (2) Xynthia's water level no longer appears as an outlier, (3) we could have reasonably predicted the annual exceedance probability of that level beforehand (predictive probability for 2010 based on data until the end of 2009 of the same order of magnitude as the standard estimative probability using data until the end of 2010). Such results illustrate the usefulness of historical information in extreme value analyses of coastal water levels, as well as the relevance of the proposed method to integrate heterogeneous data in such analyses.

scholarly journals How historical information can improve extreme coastal water levels probability prediction: application to the Xynthia event at La Rochelle (France)

2014 ◽  
Vol 2 (11) ◽  
pp. 7061-7088 ◽  
Author(s):  
T. Bulteau ◽  
D. Idier ◽  
J. Lambert ◽  
M. Garcin
Keyword(s):  
Water Level ◽  
Coastal Water ◽  
Extreme Values ◽  
Tide Gauge ◽  
Heterogeneous Data ◽  
Water Levels ◽  
Exceedance Probability ◽  
Historical Information ◽  
Order Of Magnitude ◽  
Tide Gauge Measurements

Abstract. The knowledge of extreme coastal water levels is useful for coastal flooding studies or the design of coastal defences. While deriving such extremes with standard analyses using tide gauge measurements, one often needs to deal with limited effective duration of observation which can result in large statistical uncertainties. This is even truer when one faces the issue of outliers, those particularly extreme values distant from the others which increase the uncertainty on the results. In this study, we investigate how historical information, even partial, of past events reported in archives can reduce statistical uncertainties and relativize such outlying observations. A Bayesian Markov Chain Monte Carlo method is developed to tackle this issue. We apply this method to the site of La Rochelle (France), where the storm Xynthia in 2010 generated a water level considered so far as an outlier. Based on 30 years of tide gauge measurements and 8 historical events, the analysis shows that: (1) integrating historical information in the analysis greatly reduces statistical uncertainties on return levels (2) Xynthia's water level no longer appears as an outlier, (3) we could have reasonably predicted the annual exceedance probability of that level beforehand (predictive probability for 2010 based on data till end of 2009 of the same order of magnitude as the standard estimative probability using data till end of 2010). Such results illustrate the usefulness of historical information in extreme value analyses of coastal water levels, as well as the relevance of the proposed method to integrate heterogeneous data in such analyses.

scholarly journals Determining Extreme Still Water Levels for Design and Planning Purposes Incorporating Sea Level Rise: Sydney, Australia

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Phil J. Watson
Keyword(s):  
Sea Level Rise ◽  
Water Level ◽  
Sea Level ◽  
Tide Gauge ◽  
Water Levels ◽  
Extreme Value Analysis ◽  
Tide Gauge Record ◽  
Value Analysis ◽  
Mean Sea Level ◽  
The Impact

This paper provides an Extreme Value Analysis (EVA) of the hourly water level record at Fort Denison dating back to 1915 to understand the statistical likelihood of the combination of high predicted tides and the more dynamic influences that can drive ocean water levels higher at the coast. The analysis is based on the Peaks-Over-Threshold (POT) method using a fitted Generalised Pareto Distribution (GPD) function to estimate extreme hourly heights above mean sea level. The analysis highlights the impact of the 1974 East Coast Low event and rarity of the associated measured water level above mean sea level at Sydney, with an estimated return period exceeding 1000 years. Extreme hourly predictions are integrated with future projections of sea level rise to provide estimates of relevant still water levels at 2050, 2070 and 2100 for a range of return periods (1 to 1000 years) for use in coastal zone management, design, and sea level rise adaptation planning along the NSW coastline. The analytical procedures described provide a step-by-step guide for practitioners on how to develop similar baseline information from any long tide gauge record and the associated limitations and key sensitivities that must be understood and appreciated in applying EVA.

scholarly journals Evolution of extreme Total Water Levels along the northern coast of the Iberian Peninsula

2011 ◽  
Vol 11 (2) ◽  
pp. 613-625 ◽  
Author(s):  
D. F. Rasilla Álvarez ◽  
J. C. García Codron
Keyword(s):  
Iberian Peninsula ◽  
Water Level ◽  
Sea Level ◽  
Tide Gauge ◽  
Water Levels ◽  
Northern Coast ◽  
Atmospheric Conditions ◽  
Total Water ◽  
Total Water Level

Abstract. This paper assesses the evolution of storminess along the northern coast of the Iberian Peninsula through the calculation of extreme (1%) Total Water Levels (eTWL) on both observed (tide gauge and buoy data) and hindcasted (SIMAR-44) data. Those events were first identified and then characterized in terms of oceanographic parameters and atmospheric circulation features. Additionally, an analysis of the long-term trends in both types of data was performed. Most of the events correspond to a rough wave climate and moderate storm surges, linked to extratropical disturbances following a northern track. While local atmospheric conditions seem to be evolving towards lesser storminess, their impact has been balanced by the favorable exposure of the northern coast of the Iberian Peninsula to the increasing frequency and strength of distant disturbances crossing the North Atlantic. This evolution is also correctly reproduced by the simulated long-term evolution of the forcing component (meteorological sea level residuals and wave run up) of the Total Water Level values calculated from the SIMAR 44 database, since sea level residuals have been experiencing a reduction while waves are arriving with longer periods. Finally, the addition of the rate of relative sea level trend to the temporal evolution of the atmospheric forcing component of the Total Water Level values is enough to simulate more frequent and persistent eTWL.

scholarly journals The effect of changing sea ice on the vulnerability of Arctic coasts

2014 ◽  
Vol 8 (3) ◽  
pp. 2277-2329 ◽  
Author(s):  
K. R. Barnhart ◽  
I. Overeem ◽  
R. S. Anderson
Keyword(s):  
Sea Ice ◽  
Water Level ◽  
Coastal Erosion ◽  
Extreme Values ◽  
Open Water ◽  
Water Levels ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Ice Edge ◽  
Sea Ice Edge

Abstract. Shorefast sea ice prevents the interaction of the land and the ocean in the Arctic winter and influences this interaction in the summer by governing the fetch. In many parts of the Arctic the sea-ice-free season is increasing in duration, and the summertime sea ice extents are decreasing. Sea ice provides a first order control on the vulnerability of Arctic coasts to erosion, inundation, and damage to settlements and infrastructure. We ask how the changing sea ice cover has influenced coastal erosion over the satellite record. First, we present a pan-Arctic analysis of satellite-based sea ice concentration specifically along the Arctic coasts. The median length of the 2012 open water season in comparison to 1979 expanded by between 1.5 and 3-fold by Arctic sea sector which allows for open water during the stormy Arctic fall. Second, we present a case study of Drew Point, Alaska, a site on the Beaufort Sea characterized by ice-rich permafrost and rapid coastal erosion rates where both the duration of the sea ice free season and distance to the sea ice edge, particularly towards the northwest, has increased. At Drew Point, winds from the northwest result in increased water levels at the coast and control the process of submarine notch incision, the rate-limiting step of coastal retreat. When open water conditions exist, the distance to the sea ice edge exerts control on the water level and wave field through its control on fetch. We find that the extreme values of water level set-up have increased, consistent with increasing fetch.

Modelling waves and surges during the 1953 storm

2005 ◽  
Vol 363 (1831) ◽  
pp. 1359-1375 ◽  
Author(s):  
J Wolf ◽  
R.A Flather
Keyword(s):  
Water Level ◽  
Sea Level ◽  
North Sea ◽  
Tide Gauge ◽  
High Water ◽  
Water Levels ◽  
Wind Fields ◽  
Sea Levels ◽  
Southern North Sea ◽  
Wave Models

Waves and sea levels have been modelled for the storm of 31 January–1 February 1953. Problems in modelling this event are associated with the difficulty of reconstructing wind fields and validating the model results with the limited data available from 50 years ago. The reconstruction of appropriate wind fields for surge and wave models is examined. The surges and waves are reproduced reasonably well on the basis of tide-gauge observations and the sparse observational information on wave heights. The maximum surge coincided closely in time with tidal high water, producing very high water levels along the coasts of the southern North Sea. The statistics of the 1953 event and the likelihood of recurrence are also discussed. Both surge and wave components were estimated to be approximately 1 in 50 year events. The maximum water level also occurred when the offshore waves were close to their maximum. The estimation of return period for the total water level is more problematic and is dependent on location. A scenario with the 1953 storm occurring in 2075, accounting for the effects of sea level rise and land movements, is also constructed, suggesting that sea level relative to the land could be 0.4–0.5 m higher than in 1953 in the southern North Sea, assuming a rise in mean sea level of 0.4 m.

scholarly journals What's streamflow got to do with it? A probabilistic simulation of the competing oceanographic and fluvial processes driving extreme along-river water levels

2019 ◽  
Author(s):  
Katherine A. Serafin ◽  
Peter Ruggiero ◽  
Kai A. Parker ◽  
David F. Hill
Keyword(s):  
Water Level ◽  
River Water ◽  
Extreme Event ◽  
Tide Gauge ◽  
High Water ◽  
Water Levels ◽  
Tribal Community ◽  
Indian Reservation ◽  
Environmental Forcing ◽  
Extreme Water Levels

Abstract. Extreme water levels driving flooding in estuarine and coastal environments are often compound events, generated by many individual processes like waves, storm surge, streamflow, and tides. Despite this, extreme water levels are typically modeled in isolated open coast or estuarine environments, potentially mischaracterizing the true risk to flooding facing coastal communities. We explore the variability of extreme water levels near the tribal community of La Push, within the Quileute Indian Reservation on the Washington state coast where a river signal is apparent in tide gauge measurements during high discharge events. To estimate the influence of multivariate forcing on high water levels, we first develop a methodology for statistically simulating discharge and river-influenced water levels in the tide gauge. Next, we merge probabilistic simulations of joint still water level and discharge occurrences with a hydraulic model that simulates along-river water levels. This methodology produces water levels from thousands of combinations of events not necessarily captured in the observational record. We show that the 100-yr ocean or 100-yr streamflow event does not always produce the 100-yr along-river water level. Along specific sections of river, both still water level and streamflow are necessary for producing the 100-yr water level. Understanding the relative forcing of extreme water levels along an ocean-to-river gradient will better prepare communities within inlets and estuaries for the compounding impacts of various environmental forcing, especially when a combination of extreme or non-extreme forcing can result in an extreme event with significant impacts.

Enhanced tide model: Improving tidal predictions with integration of wind data

Shore & Beach ◽  
2020 ◽  
pp. 40-45
Author(s):  
Thomas Huff ◽  
Rusty Feagin ◽  
Jens Figlus
Keyword(s):  
Water Level ◽  
Empirical Model ◽  
Prediction Error ◽  
Tide Gauge ◽  
Water Levels ◽  
Wind Data ◽  
Flood Prediction ◽  
Tidal Model ◽  
The Public ◽  
Coastal Flood

Publicly available tidal predictions for coastlines are predominantly based on astronomical predictions. In shallow water basins, however, water levels can deviate from these predictions by a factor of two or more due to wind-induced fluctuations from non-regional storms. To model and correct these wind-induced tidal deviations, a two-stage empirical model was created: the Enhanced Tidal Model (ETM). For any given NOAA tide gauge location, this model first measured the wind-induced deviation based on a compiled dataset, and then adjusted the astronomical predictions into the future to create a 144-hour forecast. The ETM, when incorporating wind data, had only 76% of the error of NOAA astronomical tidal predictions (e.g. if NOAA had 1.0 ft. of error, ETM had only 0.76 ft. error from the observed water level). Certain ETM locations had approximately half (49%) as much prediction error as NOAA. With the improvement in tidal accuracy prediction, the ETM has the ability to significantly aid in navigation along with coastal flood prediction. We envision the ETM as a resource for industry and the public to make informed decisions that impact their livelihood.

Development of an Atlantic Canadian Coastal Water Level Neural Network Model

2008 ◽  
Vol 25 (11) ◽  
pp. 2117-2132 ◽  
Author(s):  
Guoqi Han ◽  
Yu Shi
Keyword(s):  
Neural Network ◽  
Water Level ◽  
Sea Level ◽  
Coastal Water ◽  
Water Levels ◽  
Atlantic Canada ◽  
Level Data ◽  
Coastal Water Level ◽  
Term Data

Abstract Coastal water-level information is essential for coastal zone management, navigation, and oceanographic research. However, long-term water-level observations are usually only available at a limited number of locations. This study discusses a complementary and simple neural network (NN) approach, to predict water levels at a specified coastal site from the data gathered at other nearby or remote permanent stations. A simple three-layer, feed-forward, back-propagation network and a neural network ensemble, named Atlantic Canadian Coastal Water Level Neural Network (ACCSLENNT) models, was developed to correlate the nonlinear relationship of sea level data among stations by learning from their historical characteristics. Instantaneous hourly observations of water level from five stations along the coast of Atlantic Canada—Argentia, Belledune, Halifax, North Sydney, and St. John’s—are used to formulate and validate the ACCSLENNT models. Qualitative and quantitative comparisons of the network output with target observations showed that despite significant changes in sea level amplitudes and phases in the study area, appropriately trained NN models could provide accurate and robust long-term predictions of both tidal and nontidal (tide subtracted) water levels when only short-term data are available. The robust results indicate that the NN models in conjunction with limited permanent stations are able to supplement long-term historical water-level data along the Atlantic Canadian coast. Because field data collection is usually expensive, the ACCSLENNT models provide a cost-effective alternative to obtain long-term data along Atlantic Canada.

scholarly journals PUMMA (Perangkat Ukur Murah untuk Muka Air) performance for water level monitoring of mangrove ecosystem in Pangandaran

2021 ◽  
Vol 925 (1) ◽  
pp. 012060
Author(s):  
N R Prasetiawan ◽  
D Novianto ◽  
A Setiawan ◽  
S Husrin ◽  
R Bramawanto ◽  
...  
Keyword(s):  
Water Level ◽  
Real Time ◽  
Tide Gauge ◽  
Mangrove Ecosystem ◽  
Water Levels ◽  
Tidal Range ◽  
Technical Problems ◽  
Mangrove Area ◽  
Data Gap ◽  
Water Level Measurements

Abstract PUMMA is a real-time tide gauge that has been operating in several locations in Indonesia. One of them was installed in a mangrove area of Pangandaran that supports both the fisheries and tourism sectors. Tidal dynamics is one of the factors that can affect fish abundance in the mangrove ecosystem. PUMMA Pangandaran monitors the water levels of the mangrove ecosystem in real-time 24/7 and produces CCTV images. This paper aims to analyze the performance of the PUMMA in Pangandaran based on data from water level measurements and image quality from CCTV. The results show that the tidal range in the waters of the mangrove ecosystem in Pangandaran is 1.3 m, with the maximum and minimum high tides being 0.79 m and -0.53 m. The tidal type in the mangrove ecosystem in Pangandaran is semidiurnal and affected by geometry of the estuary. The water level in the mangrove area was influenced by sediments that form a sandbar at the mouth of the Ciputrapinggan River, which controls the fluxes of seawater. There is a data gap of 368 hours during the operation period of PUMMA, and mostly due to technical problems that often occurred at the beginning of the installation. However, after March and April, its performance was improved with only three hours data gap. For the quality of CCTV images, good quality contributed to about 76.67% and only 5.06% on bad quality. Overall, PUMMA’s performance showed excellent reliability in monitoring the water levels and the conditions of the mangrove ecosystem.

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