scholarly journals Modeling the Nonlinearity of Sea Level Oscillations in the Malaysian Coastal Areas Using Machine Learning Algorithms

2019 ◽  
Vol 11 (17) ◽  
pp. 4643
Author(s):  
Vivien Lai ◽  
Ali Najah Ahmed ◽  
M.A. Malek ◽  
Haitham Abdulmohsin Afan ◽  
Rusul Khaleel Ibrahim ◽  
...  
Keyword(s):  
Sea Level ◽  
Peninsular Malaysia ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Mean Sea Level ◽  
Sea Levels ◽  
Tuning Parameters ◽  
Level Data ◽  
Input Dataset ◽  
Sea Level Oscillations

The estimation of an increase in sea level with sufficient warning time is important in low-lying regions, especially in the east coast of Peninsular Malaysia (ECPM). This study primarily aims to investigate the validity and effectiveness of the support vector machine (SVM) and genetic programming (GP) models for predicting the monthly mean sea level variations and comparing their prediction accuracies in terms of the model performances. The input dataset was obtained from Kerteh, Tioman Island, and Tanjung Sedili in Malaysia from January 2007 to December 2017 to predict the sea levels for five different time periods (1, 5, 10, 20, and 40 years). Further, the SVM and GP models are subjected to preprocessing to obtain optimal performance. The tuning parameters are generalized for the optimal input designs (SVM2 and GP2), and the results denote that SVM2 outperforms GP with R of 0.81 and 0.86 during the training and testing periods, respectively, at the study locations. However, GP can provide values of 0.71 and 0.79 for training and testing, respectively, at the study locations. The results show precise predictions of the monthly mean sea level, denoting the promising potential of the used models for performing sea level data analysis.

scholarly journals Flooding Conditions at Aveiro Port (Portugal) within the Framework of Projected Climate Change

2021 ◽  
Vol 9 (6) ◽  
pp. 595
Author(s):  
Américo Soares Ribeiro ◽  
Carina Lurdes Lopes ◽  
Magda Catarina Sousa ◽  
Moncho Gomez-Gesteira ◽  
João Miguel Dias
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Climate Change Impacts ◽  
Storm Surges ◽  
Historical Period ◽  
Return Periods ◽  
Wave Regime ◽  
Mean Sea Level ◽  
Sea Levels ◽  
Far Future

Ports constitute a significant influence in the economic activity in coastal areas through operations and infrastructures to facilitate land and maritime transport of cargo. Ports are located in a multi-dimensional environment facing ocean and river hazards. Higher warming scenarios indicate Europe’s ports will be exposed to higher risk due to the increase in extreme sea levels (ESL), a combination of the mean sea level, tide, and storm surge. Located on the west Iberia Peninsula, the Aveiro Port is located in a coastal lagoon exposed to ocean and river flows, contributing to higher flood risk. This study aims to assess the flood extent for Aveiro Port for historical (1979–2005), near future (2026–2045), and far future (2081–2099) periods scenarios considering different return periods (10, 25, and 100-year) for the flood drivers, through numerical simulations of the ESL, wave regime, and riverine flows simultaneously. Spatial maps considering the flood extent and calculated area show that most of the port infrastructures' resilience to flooding is found under the historical period, with some marginal floods. Under climate change impacts, the port flood extent gradually increases for higher return periods, where most of the terminals are at high risk of being flooded for the far-future period, whose contribution is primarily due to mean sea-level rise and storm surges.

Mean Sea Level as a Reference for Geodetic Leveling

1974 ◽  
Vol 28 (5) ◽  
pp. 524-530 ◽  
Author(s):  
G. W. Lennon
Keyword(s):  
Sea Level ◽  
World Ocean ◽  
Equipotential Surface ◽  
Scientific Discipline ◽  
Mean Sea Level ◽  
Sea Levels ◽  
Coastal Sea ◽  
Long Time ◽  
Marine System

The use of mean sea level as a surface of reference that might provide an independent control for geodetic leveling has been a long term goal arising from the classical analogy between the geoid as an equipotential surface and the surface assumed by a hypothetical undisturbed world ocean. The problems associated with this aim are now known to be vast, and are associated with the dynamics of the marine system, notably its response to meteorological forces, to variations in density and to the effects of basic circulation patterns. In consequence the mean sea level surface varies rapidly in both time and space. This identifies in fact a distinctive scientific discipline, coastal geodesy, in which contributions are required by both geodesists and oceanographers. It has come to be recognized that the coastal zone is a hazardous environment for all observational techniques concerned. On the one hand, the difficulties of measurement of coastal sea levels have only recently been understood; on the other hand, precise leveling procedures are now known to be influenced by the attraction of marine tides and by crustal deformation of tidal loading. Much of the data available for study are therefore inadequate and, moreover, it should be noted that long-time series are required. It is now possible to lay plans for both geodetic and oceanographic procedures to remedy these deficiencies in the long-term interests of the study.

Estimating contribution of high-frequency sea-level oscillations to the extreme sea levels in the Adriatic Sea

2021 ◽  
Author(s):  
Krešimir Ruić ◽  
Jadranka Šepić ◽  
Maja Karlović ◽  
Iva Međugorac
Keyword(s):  
Time Series ◽  
Sea Level ◽  
High Frequency ◽  
Adriatic Sea ◽  
Tide Gauge ◽  
Data Series ◽  
Sea Levels ◽  
Short Period ◽  
Extreme Sea Levels ◽  
Sea Level Oscillations

<p>Extreme sea levels are known to hit the Adriatic Sea and to occasionally cause floods that produce severe material damage. Whereas the contribution of longer-period (T > 2 h) sea-level oscillations to the phenomena has been well researched, the contribution of the shorter period (T < 2 h) oscillations is yet to be determined. With this aim, data of 1-min sampling resolution were collected for 20 tide gauges, 10 located at the Italian (north and west) and 10 at the Croatian (east) Adriatic coast. Analyses were done on time series of 3 to 15 years length, with the latest data coming from 2020, and with longer data series available for the Croatian coast. Sea level data were thoroughly checked, and spurious data were removed. </p><p>For each station, extreme sea levels were defined as events during which sea level surpasses its 99.9 percentile value. The contribution of short-period oscillations to extremes was then estimated from corresponding high-frequency (T < 2 h) series. Additionally, for four Croatian tide gauge stations (Rovinj, Bakar, Split, and Dubrovnik), for period of 1956-2004, extreme sea levels were also determined from the hourly sea level time series, with the contribution of short-period oscillations visually estimated from the original tide gauge charts.  </p><p>Spatial and temporal distribution of contribution of short-period sea-level oscillations to the extreme sea level in the Adriatic were estimated. It was shown that short-period sea-level oscillation can significantly contribute to the overall extremes and should be considered when estimating flooding levels. </p>

scholarly journals ANALYSIS OF MAXIMUM SEA LEVELS IN SOUTHERN ENGLAND

1978 ◽  
Vol 1 (16) ◽  
pp. 53
Author(s):  
J. Graff ◽  
D.L. Blackman
Keyword(s):  
Sample Size ◽  
Sea Level ◽  
Linear Trend ◽  
South Coast ◽  
Annual Maximum ◽  
Return Periods ◽  
The South ◽  
Mean Sea Level ◽  
Sea Levels ◽  
Southern England

Along the south coast of England, series of observed annual maximum sea levels, ranging from 16 years to 125 years have been analysed for each of 10 ports. The Jenkinson method of analysis was used to compute the frequency of recurrence of extreme levels. For a number of these ports the series of annual maxima are shown to have significant trends of the same order as those for mean sea level. The Jenkinson method can be simply adjusted to cope with maxima having a component linear trend, making it possible to allow for such trends in computing the frequency of recurrence of extreme levels. If a trend in the annual maxima varies throughout the sample of observations it is shown that difficulties arise in using the Jenkinson method to compute acceptable statistics. It is also shown that for certain ports having long series of observed annual maxima it may be necessary to restrict the sample size of observations in order to compute estimates of the recurrence of extreme levels within reasonable return periods.

Water circulation and shelf waves in the northern Great Barrier Reef lagoon

1981 ◽  
Vol 32 (5) ◽  
pp. 721 ◽  
Author(s):  
E Wolanski ◽  
B Ruddick
Keyword(s):  
Great Barrier Reef ◽  
Sea Level ◽  
Low Frequency ◽  
Current Data ◽  
Barrier Reef ◽  
Sea Levels ◽  
The North ◽  
Level Data ◽  
Shelf Wave ◽  
Salinity Water

Currents and sea levels were measured at a number of locations in the Great Barrier Reef (GBR) lagoon from about 10 to 13� S., during the period October-December 1979. A strong non-tidal, low-frequency modulation of all sea-level and current data was found. The currents nearshore were driven northward by the wind, and then at least partially blocked by the dense network of reefs to the north of 10� s. The water then flowed southward in deeper water adjacent to the reef, driven by a longshore pressure gradient. The low- frequency sea-level data, though not the current records, showed northward phase propagation at speeds characteristic of a first-mode shelf wave trapped in the lagoon between the shore and the reef. Data are presented revealing the intrusion of low-salinity water, through Bligh Entrance, in the GBR lagoon, as a result of river discharges in the Gulf of Papua. It is suggested that low-frequency longshore currents may periodically flush these river plumes from the GBR lagoon and enhance interaction between reefs. In the Coral Sea in front of reef passages, the large horizontal velocities may result in forces upwelling by selective withdrawal and jet entrainment.

Sea level in the Global Geodetic Observing System

2020 ◽  
Author(s):  
Elizabeth Bradshaw ◽  
Andy Matthews ◽  
Kathy Gordon ◽  
Angela Hibbert ◽  
Sveta Jevrejeva ◽  
...  
Keyword(s):  
Sea Level ◽  
Working Group ◽  
Sea Level Change ◽  
Tide Gauges ◽  
Controlled Vocabularies ◽  
Mean Sea Level ◽  
Level Change ◽  
Level Data ◽  
Metadata Standards

<p>The Permanent Service for Mean Sea Level (PSMSL) is the global databank for long-term mean sea level data and is a member of the Global Geodetic Observing System (GGOS) Bureau of Networks and Observations. As well as curating long-term sea level change information from tide gauges, PSMSL is also involved in developing other products and services including the automatic quality control of near real-time sea level data, distributing Global Navigation Satellite System (GNSS) sea level data and advising on sea level metadata development.<br>At the GGOS Days meeting in November 2019, the GGOS Focus Area 3 on Sea Level Change, Variability and Forecasting was wrapped up, but there is still a requirement in 2020 for GGOS to integrate and support tide gauges and we will discuss how we will interact in the future. A recent paper (Ponte et al., 2019) identified that only “29% of the GLOSS [Global Sea Level Observing System] GNSS-co-located tide gauges have a geodetic tie available at SONEL [Système d'Observation du Niveau des Eaux Littorales]” and we as a community still need to improve the ties between the GNSS sensor and tide gauges. This may progress as new GNSS Interferometric Reflectometry (GNSS-IR) sensors are installed to provide an alternative method to observe sea level. As well as recording the sea level, these sensors will also provide vertical land movement information from one location. PSMSL are currently developing an online portal of uplift/subsidence land data and GNSS-IR sea level observation data. To distribute the data, we are creating/populating controlled vocabularies and generating discovery metadata.<br>We are working towards FAIR data management principles (data are findable, accessible, interoperable and reusable) which will improve the flow of quality controlled sea level data and in 2020 we will issue the PSMSL dataset with a Digital Object Identifier. We have been working on improving our discovery and descriptive metadata including creating a use case for the Research Data Alliance Persistent (RDA) Identification of Instruments Working Group to help improve the description of a time series where the sensor and platform may change and move many times. Representatives from PSMSL will sit on the GGOS DOIs for Data Working Group and would like to contribute help with controlled vocabularies, identifying metadata standards etc. We will also contribute to the next GGOS implementation plan.<br>Ponte, Rui M., et al. (2019) "Towards comprehensive observing and modeling systems for monitoring and predicting regional to coastal sea level." <em>Frontiers in Marine Science</em> 6(437).</p>

scholarly journals A century of sea level data and the UK's 2013/14 storm surges: an assessment of extremes and clustering using the Newlyn tide gauge record

2014 ◽  
Vol 11 (4) ◽  
pp. 1995-2028 ◽  
Author(s):  
M. P. Wadey ◽  
I. D. Haigh ◽  
J. M. Brown
Keyword(s):  
Sea Level ◽  
Return Period ◽  
Tide Gauge ◽  
Storm Surges ◽  
High Water ◽  
Lower Probability ◽  
Tide Gauge Record ◽  
Storm Activity ◽  
Sea Levels ◽  
Level Data

Abstract. For the UK's longest and most complete sea level record (Newlyn), we assess extreme high water events and their temporal clustering; prompted by the 2013/2014 winter of flooding and storms. These are set into context against this almost 100 yr record. We define annual periods for which storm activity, tides and sea levels can be compared on a year-by-year basis. Amongst the storms and high tides which affected Newlyn the recent winter produced the largest recorded high water (3 February 2014) and five others above a 1 in 1 yr return period. The large magnitude of tide and mean sea level, and the close inter-event spacings (of large return period high waters), suggests that the 2013/2014 high water "season" may be considered the most extreme on record. However, storm and sea level events may be classified in different ways. For example in the context of sea level rise (which we calculate linearly as 1.81 ± 0.1 mm yr−1 from 1915 to 2014), a lower probability combination of surge and tide occurred on 29 January 1948, whilst 1995/1996 storm surge season saw the most high waters of ≥ 1 in 1 yr return period. We provide a basic categorisation of five types of high water cluster, ranging from consecutive tidal cycles to multiple years. The assessment is extended to other UK sites (with shorter sea level records and different tide-surge characteristics), which suggests 2013/2014 was extreme, although further work should assess clustering mechanisms and flood system "memory".

scholarly journals Coastal Floods Induced by Mean Sea Level Rise—Ecological and Socioeconomic Impacts on a Mesotidal Lagoon

2021 ◽  
Vol 9 (12) ◽  
pp. 1430
Author(s):  
Francisco Silveira ◽  
Carina Lurdes Lopes ◽  
João Pedro Pinheiro ◽  
Humberto Pereira ◽  
João Miguel Dias
Keyword(s):  
Sea Level ◽  
Storm Surge ◽  
Storm Surges ◽  
Socioeconomic Impacts ◽  
Mean Sea Level ◽  
Sea Levels ◽  
Ria De Aveiro ◽  
The Future ◽  
Coastal Floods ◽  
Agricultural Areas

Coastal floods are currently a strong threat to socioeconomic activities established on the margins of lagoons and estuaries, as well as to their ecological equilibrium, a situation that is expected to become even more worrying in the future in a climate change context. The Ria de Aveiro lagoon, located on the northwest coast of Portugal, is not an exception to these threats, especially considering the low topography of its margins which has led to several flood events in the past. The growing concerns with these regions stem from the mean sea level (MSL) rise induced by climate changes as well as the amplification of the impacts of storm surge events, which are predicted to increase in the future due to higher mean sea levels. Therefore, this study aims to evaluate the influence of MSL rise on the inundation of Ria de Aveiro habitats and to assess the changes in inundation patterns resulting from frequent storm surges (2-year return period) from the present to the future, assessing their ecological and socioeconomic impacts. For this, a numerical model (Delft3D), previously calibrated and validated, was used to simulate the lagoon hydrodynamics under different scenarios combining MSL rise and frequent storm surge events. The numerical results demonstrated that MSL rise can change the vertical zonation and threaten the local habitats. Many areas of the lagoon may change from supratidal/intertidal to intertidal/subtidal, with relevant consequences for local species. The increase in MSL expected for the end of the century could make the lagoon more vulnerable to the effect of frequent storm surges, harming mostly agricultural areas, causing great losses for this sector and for many communities who depend on it. These extreme events can also affect artificialized areas and, in some cases, endanger lives.

scholarly journals CROP CLASSIFICATION ON SINGLE DATE SENTINEL-2 IMAGERY USING RANDOM FOREST AND SUPPOR VECTOR MACHINE

2018 ◽  
Vol XLII-5 ◽  
pp. 683-688 ◽  
Author(s):  
R. Saini ◽  
S. K. Ghosh
Keyword(s):  
Random Forest ◽  
Near Infrared ◽  
Vegetation Mapping ◽  
Good Choice ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Tuning Parameters ◽  
Spectral Bands ◽  
Fodder Crops ◽  
Sentinel 2

<p><strong>Abstract.</strong> Mapping of the crop using satellite images is a challenging task due to complexities within field, and having the similar spectral properties with other crops in the region. Recently launched Sentinel-2 satellite has thirteen spectral bands, fast revisit time and resolution at three different level (10<span class="thinspace"></span>m, 20<span class="thinspace"></span>m, 60<span class="thinspace"></span>m), as well as the free availability of data, makes it a good choice for vegetation mapping. This study aims to classify crop using single date Sentinel-2 imagery in the Roorkee, district Haridwar, Uttarakhand, India. Classification is performed by using two most popular and efficient machine learning algorithms: Random Forest (RF) and Support Vector Machine (SVM). In this study, four spectral bands, i.e., Near Infrared, Red, Green, and Blue of Sentinel-2 satellite are stacked for the classification. Results show that overall accuracy of the classification achieved by RF and SVM using Sentinel-2 imagery are 84.22% and 81.85% respectively. This study demonstrates that both classifiers performed well by setting an optimal value of tuning parameters, but RF achieved 2.37% higher overall accuracy over SVM. Analysis of the results states that the class specific accuracies of High-Density Forest attain the highest accuracy whereas Fodder class reports the lowest accuracy. Fodder achieve lowest accuracy because there is an intermixing of pixels among Wheat and Fodder crops. In this study, it is found that RF shows better potential in classifying crops more accurately in comparison to SVM and Sentinel-2 has great potential in vegetation mapping domain in remote sensing.</p>

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