scholarly journals Predicting typhoon-induced storm surge tide with a two-dimensional hydrodynamic model and artificial neural network model

2012 ◽  
Vol 12 (12) ◽  
pp. 3799-3809 ◽  
Author(s):  
W.-B. Chen ◽  
W.-C. Liu ◽  
M.-H. Hsu
Keyword(s):  
Neural Network ◽  
Storm Surge ◽  
Hydrodynamic Model ◽  
East Coast ◽  
Storm Surges ◽  
Two Dimensional ◽  
Astronomical Tide ◽  
Tide Level ◽  
Surge Height ◽  
Bpnn Model

Abstract. Precise predictions of storm surges during typhoon events have the necessity for disaster prevention in coastal seas. This paper explores an artificial neural network (ANN) model, including the back propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS) algorithms used to correct poor calculations with a two-dimensional hydrodynamic model in predicting storm surge height during typhoon events. The two-dimensional model has a fine horizontal resolution and considers the interaction between storm surges and astronomical tides, which can be applied for describing the complicated physical properties of storm surges along the east coast of Taiwan. The model is driven by the tidal elevation at the open boundaries using a global ocean tidal model and is forced by the meteorological conditions using a cyclone model. The simulated results of the hydrodynamic model indicate that this model fails to predict storm surge height during the model calibration and verification phases as typhoons approached the east coast of Taiwan. The BPNN model can reproduce the astronomical tide level but fails to modify the prediction of the storm surge tide level. The ANFIS model satisfactorily predicts both the astronomical tide level and the storm surge height during the training and verification phases and exhibits the lowest values of mean absolute error and root-mean-square error compared to the simulated results at the different stations using the hydrodynamic model and the BPNN model. Comparison results showed that the ANFIS techniques could be successfully applied in predicting water levels along the east coastal of Taiwan during typhoon events.

scholarly journals Maximum Storm Tide Response to the Intensity of Typhoons and Bathymetric Changes along the East Coast of Taiwan

2017 ◽  
Author(s):  
Wen-Cheng Liu ◽  
Wei-Bo Chen ◽  
Lee-Yaw Lin
Keyword(s):  
Storm Surge ◽  
Return Period ◽  
East Coast ◽  
Storm Surges ◽  
Measured Data ◽  
Water Levels ◽  
Storm Tide ◽  
Astronomical Tide ◽  
Extreme Flooding ◽  
Bathymetric Changes

A typhoon-induced storm surge is considered one of the most severe coastal disasters in Taiwan. However, the combination of the storm surge and the astronomical tide called the storm tide can actually cause extreme flooding in coastal areas. This study implemented a two-dimensional hydrodynamic model to account for the interaction between tides and storm surges on the coast of Taiwan. The model was validated with observed water levels at Sauo Fish Port, Hualien Port, and Chenggong Fish Port under different historical typhoon events. The model results are in reasonable agreement with the measured data. The validated model was then used to evaluate the effects of the typhoon's intensity, bathymetric change, and the combination of the typhoon’s intensity and bathymetric change on the maximum storm tide and its distribution along the east coast of Taiwan. The results indicated that the maximum storm tide rises to 1.92 m under a typhoon with an intensity of a 100-year return period. The maximum storm tide increased from a baseline of 1.26 m to 2.63 m for a 90% bathymetric rise at Sauo Fish Port under the conditions of Typhoon Jangmi (2008). The combination of the intensity of a typhoon with a 100-year return period and a 90% bathymetric rise will result in a maximum storm tide exceeding 4 m, 2 m, and 3 m at Sauo Fish Port, Hualien Port, and Chenggong Fish Port, respectively. We also found that the distribution of the maximum storm tide on the east coast of Taiwan can expand significantly subject to the bathymetric rise.

scholarly journals Advancing global storm surge modelling using the new ERA5 climate reanalysis

2019 ◽  
Vol 54 (1-2) ◽  
pp. 1007-1021 ◽  
Author(s):  
Job C. M. Dullaart ◽  
Sanne Muis ◽  
Nadia Bloemendaal ◽  
Jeroen C. J. H. Aerts
Keyword(s):  
Tropical Cyclones ◽  
Storm Surge ◽  
Global Climate ◽  
Storm Surges ◽  
Early Warning Systems ◽  
Climate Modelling ◽  
Wind Fields ◽  
Recent Advances ◽  
Global Climate Modelling ◽  
Surge Height

Abstract This study examines the implications of recent advances in global climate modelling for simulating storm surges. Following the ERA-Interim (0.75° × 0.75°) global climate reanalysis, in 2018 the European Centre for Medium-range Weather Forecasts released its successor, the ERA5 (0.25° × 0.25°) reanalysis. Using the Global Tide and Surge Model, we analyse eight historical storm surge events driven by tropical—and extra-tropical cyclones. For these events we extract wind fields from the two reanalysis datasets and compare these against satellite-based wind field observations from the Advanced SCATterometer. The root mean squared errors in tropical cyclone wind speed reduce by 58% in ERA5, compared to ERA-Interim, indicating that the mean sea-level pressure and corresponding strong 10-m winds in tropical cyclones greatly improved from ERA-Interim to ERA5. For four of the eight historical events we validate the modelled storm surge heights with tide gauge observations. For Hurricane Irma, the modelled surge height increases from 0.88 m with ERA-Interim to 2.68 m with ERA5, compared to an observed surge height of 2.64 m. We also examine how future advances in climate modelling can potentially further improve global storm surge modelling by comparing the results for ERA-Interim and ERA5 against the operational Integrated Forecasting System (0.125° × 0.125°). We find that a further increase in model resolution results in a better representation of the wind fields and associated storm surges, especially for small size tropical cyclones. Overall, our results show that recent advances in global climate modelling have the potential to increase the accuracy of early-warning systems and coastal flood hazard assessments at the global scale.

scholarly journals Modeling Storm Surge Attenuation by an Integrated Nature-Based and Engineered Flood Defense System in the Scheldt Estuary (Belgium)

2020 ◽  
Vol 8 (1) ◽  
pp. 27
Author(s):  
Sven Smolders ◽  
Maria João Teles ◽  
Agnès Leroy ◽  
Tatiana Maximova ◽  
Patrick Meire ◽  
...  
Keyword(s):  
Storm Surge ◽  
Flood Control ◽  
Storm Surges ◽  
Scheldt Estuary ◽  
Scale Model ◽  
Defense System ◽  
Height Reduction ◽  
Flood Defense ◽  
Physical Scale ◽  
Surge Height

There is increasing interest in the use of nature-based approaches for mitigation of storm surges along coasts, deltas, and estuaries. However, very few studies have quantified the effectiveness of storm surge height reduction by a real-existing, estuarine-scale, nature-based, and engineered flood defense system, under specific storm surge conditions. Here, we present data and modelling results from a specific storm surge in the Scheldt estuary (Belgium), where a hybrid flood defense system is implemented, consisting of flood control areas, of which some are restored into tidal marsh ecosystems, by use of culvert constructions that allow daily reduced tidal in- and outflow. We present a hindcast simulation of the storm surge of 6 December 2013, using a TELEMAC-3D model of the Scheldt estuary, and model scenarios showing that the hybrid flood defense system resulted in a storm surge height reduction of up to half a meter in the estuary. An important aspect of the work was the implementation of model formulations for calculating flow through culverts of restored marshes. The latter was validated comparing simulated and measured discharges through a physical scale model of a culvert, and through a real-scale culvert of an existing restored marsh during the storm surge.

scholarly journals Simulation of storm surge inundation under different typhoon intensity scenarios: case study of Pingyang County, China

2020 ◽  
Vol 20 (10) ◽  
pp. 2777-2790
Author(s):  
Xianwu Shi ◽  
Pubing Yu ◽  
Zhixing Guo ◽  
Zhilin Sun ◽  
Fuyuan Chen ◽  
...  
Keyword(s):  
Storm Surge ◽  
Water Depth ◽  
Storm Surges ◽  
Economic Losses ◽  
Astronomical Tide ◽  
Evacuation Plans ◽  
Typhoon Intensity ◽  
Typhoon Tracks ◽  
The Impact

Abstract. China is one of the countries that is most seriously affected by storm surges. In recent years, storm surges in coastal areas of China have caused huge economic losses and a large number of human casualties. Knowledge of the inundation range and water depth of storm surges under different typhoon intensities could assist predisaster risk assessment and making evacuation plans, as well as provide decision support for responding to storm surges. Taking Pingyang County in Zhejiang Province as a case study area, parameters including typhoon tracks, radius of maximum wind speed, astronomical tide, and upstream flood runoff were determined for different typhoon intensities. Numerical simulations were conducted using these parameters to investigate the inundation range and water depth distribution of storm surges in Pingyang County considering the impact of seawall collapse under five different intensity scenarios (corresponding to minimum central pressure values equal to 915, 925, 935, 945, and 965 hPa). The inundated area ranged from 103.51 to 233.16 km2 for the most intense typhoon. The proposed method could be easily adopted in various coastal counties and serves as an effective tool for decision-making in storm surge disaster risk reduction practices.

scholarly journals Accurate Storm Surge Prediction with a Parametric Cyclone and Neural Network Hybrid Model

Water ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 96
Author(s):  
Wei-Ting Chao ◽  
Chih-Chieh Young
Keyword(s):  
Neural Network ◽  
Storm Surge ◽  
Hybrid Model ◽  
Lead Time ◽  
Hybrid Approach ◽  
Coastal Region ◽  
Storm Surges ◽  
Search Space ◽  
Observation Data ◽  
Local Pressure

Storm surges are one of the most devastating coastal disasters. Numerous efforts have continuously been made to achieve better prediction of storm surge variation. In this paper, we propose a parametric cyclone and neural network hybrid model for accurate, long lead-time storm surge prediction. The model was applied to the northeastern coastal region of Taiwan, i.e., Longdong station. A total of 14 historical typhoon events were used for model training and validation, and the results and questions associated with this hybrid approach carefully discussed. Overall, the proposed method reduced the complexity of network structure while retaining the important typhoon indicators. In particular, local pressure and winds estimated from the storm parameters through physically-based parametric cyclone models allow for inferring the possible future influence of a typhoon, unlike the simple collection and direct usage of observation data from local stations in earlier works. Meanwhile, the error-tolerance capability of the neural network alleviated some discrepancy in the model inputs and enabled good surge prediction. Further, the proposed method showed better and faster convergence thanks to the retention of storm information and the reduced dimensions of the search space. The hybrid model presented excellent performance or maintained reasonable capability for short lead-time and long lead-time storm surge prediction. Compared with the pure neural network model under the same network dimensions, the present model demonstrated great improvement in accuracy as the prediction lead time increased to 8 h, e.g., 33–40% (13–21%) and 32–37% (18–29%) RMSE and CE, respectively, in the training/validation phase.

scholarly journals EXAMPLES OF STORM SURGE PREDICTION MODELS

1982 ◽  
Vol 1 (18) ◽  
pp. 52
Author(s):  
P. Lencioni ◽  
J.P. Benque ◽  
Y. Coeffe
Keyword(s):  
Storm Surge ◽  
Autoregressive Model ◽  
Good Accuracy ◽  
Prediction Models ◽  
Storm Surges ◽  
Local Data ◽  
Deterministic Models ◽  
Tide Level ◽  
Storm Condition

For a given site, deterministic models may be applied to predict the tide level with a rather good accuracy. However, a difference is observed between the observed and predicted tide level under storm condition. This difference is called storm surge. Two different storm surges prediction models are presented for the site of Le Havre ; an autoregressive model ; a model using wind and pressure local data. The autoregressive model can be used for a prediction 5 hours in advance. The availability of accurate wind and pressure predictions by the Meteorological Service of Le Havre within 36 hours in advance makes the use of the second model of great interest because it provides the possibility of predictions within 39 hours in advance.

Using Neural Networks Forecast the Economic Losses Caused by Storm Surge

2013 ◽  
Vol 798-799 ◽  
pp. 987-991
Author(s):  
Ling Di Zhao ◽  
Ming Ye Yang ◽  
Chun Peng Bian ◽  
Qing Hao
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Storm Surge ◽  
Bp Neural Network ◽  
Storm Surges ◽  
Economic Loss ◽  
Entropy Method ◽  
Economic Conditions ◽  
Economic Losses ◽  
Grade Prediction

In order to make up for the lack of natural grade warning, we sought a new method for judging the losses of storm surges. Firstly apply entropy method etc to grade storm surges into 4 levels (mild, moderate, heavy and extra heavy) according to economic loss indices in Zhejiang Province. Then develop BP neural network to forecast losses with the selected indicators of natural, social and economic conditions. Comparing forecast grades with the actual value, we found the accuracy of grade prediction is 80%. It shown the grading results and predicting method are reliable and could be used for the grades of economic losses forecast of storm surges in future.

scholarly journals A PRELIMINARY STUDY OF STORM SURGES IN HUDSON BAY

1972 ◽  
Vol 1 (13) ◽  
pp. 9
Author(s):  
K.B. Yuen ◽  
T.S. Murty
Keyword(s):  
Electric Power ◽  
Storm Surge ◽  
Storm Surges ◽  
Hudson Bay ◽  
Two Dimensional ◽  
James Bay ◽  
Power Development ◽  
The Past ◽  
Resource Exploration ◽  
Preliminary Study

In view of resource exploration, hydro-electric power development and other activities, there is a clear need for a better understanding of the hydrodynamics of Hudson Bay. One particular area that has received little attention in the past is storm surges. It is likely that a storm surge prediction will be very useful in the future and towards this goal a two-dimensional homogenous model has been constructed. A hindcast of the storm of October 15, 1969 is presented here. The calculated surge for Churchill, Manitoba compares favourably with observed residues. The overall response of the basin and the types of oscillations that are produced are also described here. In addition, the differences in behavior between James Bay and Hudson Bay proper are demonstrated. Finally the results also indicate the steady circulation which the storm has produced.

scholarly journals STUDY ON INTERACTION BETWEEN THE ESTUARY DYNAMIC AND STORM SURGE INDUCED BY TROPICAL CYCLONE WINNIE(1997) IN YANGTZE RIVER ESTUARY

2011 ◽  
Vol 1 (32) ◽  
pp. 22
Author(s):  
Jinshan Zhang ◽  
Jun Kong ◽  
Zhiyi Lei ◽  
Weisheng Zhang
Keyword(s):  
Tropical Cyclone ◽  
Water Level ◽  
Storm Surge ◽  
Yangtze River ◽  
River Estuary ◽  
Storm Surges ◽  
Yangtze River Estuary ◽  
Meteorological Model ◽  
Astronomical Tide ◽  
Level Increase

ABSTRACT This paper studied the interaction between the Estuary dynamic and storm surge induced by super tropical cyclone Winnie(1997) in Yangtze River Estuary with nested numerical model, which is driven by meso-scale meteorological model established. And the results indicate that, storm surges have significant influences on the Yangtze River Estuary. The maximum water level increase caused by storm surge can be monitored between Jiangyin and Xuliujing, whose exact position fluctuates owing to effects of the upstream runoff and estuarine tide. Furthermore the general laws about the relationships among astronomical tide, storm surge, and flood are revealed in this paper, and flood water level under storm surge events is predicted also.

Sign in / Sign up

Export Citation Format

Share Document